Journal of Mechanical Engineering 2014 6

http://www.sv-jme.eu

60 (2014) 6

Strojniški vestnik Journal of Mechanical Engineering

Since 1955

Papers

375

Enrico Troiani, Lorenzo Donati, Gianluca Molinari, Raffaella Di Sante: Influence of Plying Strategies and Trigger Type on Crashworthiness Properties of Carbon Fiber Laminates Cured through Autoclave Processing

382

Marjan Leber, Majda Bastič, Borut Buchmeister: The Trends in Usage and Barriers of Innovation Management Techniques in New Product Development

389

Sergey Nikolaevich Grigoriev, Tatyana Vasilievna Tarasova, Galina Olegovna Gvozdeva, Steffen Nowotny: Structure Formation of Hypereutectic Al-Si-Alloys Produced by Laser Surface Treatment

395

Qihui Yu, Maolin Cai, Yan Shi, Zichuan Fan: Optimization of the Energy Efficiency of a Piston Compressed Air Engine

407

Ana Bižal, Jernej Klemenc, Matija Fajdiga: Evaluating the Statistical Significance of a Fatigue-Life Reduction Due to Macro-Porosity

417

Yesid Asaff, Victor J. De Negri, Heinrich Theissen, Hubertus Murrenhoff: Analysis of the Influence of Contaminants on the Biodegradability Characteristics and Ageing of Biodegradable Hydraulic Fluids

425

Miha Praznik, Vincenc Butala, Martina Zbašnik-Senegačnik: A Simple Method for Evaluating the Sustainable Design of Energy Efficient Family Houses

437

Shengli Song, Xinglong Zhang, Zhitao Tan: RBF Neural Network Based Sliding Mode Control of a Lower Limb Exoskeleton Suit

Journal of Mechanical Engineering - Strojniški vestnik

Contents

6 year 2014 volume 60 no.

Strojniški vestnik – Journal of Mechanical Engineering (SV-JME) Aim and Scope The international journal publishes original and (mini)review articles covering the concepts of materials science, mechanics, kinematics, thermodynamics, energy and environment, mechatronics and robotics, fluid mechanics, tribology, cybernetics, industrial engineering and structural analysis.

The journal follows new trends and progress proven practice in the mechanical engineering and also in the closely related sciences as are electrical, civil and process engineering, medicine, microbiology, ecology, agriculture, transport systems, aviation, and others, thus creating a unique forum for interdisciplinary or multidisciplinary dialogue.

The international conferences selected papers are welcome for publishing as a special issue of SV-JME with invited co-editor(s).

Editor in Chief Vincenc Butala University of Ljubljana, Faculty of Mechanical Engineering, Slovenia

Technical Editor Pika Škraba University of Ljubljana, Faculty of Mechanical Engineering, Slovenia

Founding Editor Bojan Kraut University of Ljubljana, Faculty of Mechanical Engineering, Slovenia

Editorial Office University of Ljubljana, Faculty of Mechanical Engineering SV-JME, Aškerčeva 6, SI-1000 Ljubljana, Slovenia Phone: 386 (0)1 4771 137 Fax: 386 (0)1 2518 567 info@sv-jme.eu, http://www.sv-jme.eu Print: Littera Picta, printed in 400 copies Founders and Publishers University of Ljubljana, Faculty of Mechanical Engineering, Slovenia University of Maribor, Faculty of Mechanical Engineering, Slovenia Association of Mechanical Engineers of Slovenia Chamber of Commerce and Industry of Slovenia, Metal Processing Industry Association President of Publishing Council Branko Širok

International Editorial Board Koshi Adachi, Graduate School of Engineering,Tohoku University, Japan Bikramjit Basu, Indian Institute of Technology, Kanpur, India Anton Bergant, Litostroj Power, Slovenia Franci Čuš, UM, Faculty of Mechanical Engineering, Slovenia Narendra B. Dahotre, University of Tennessee, Knoxville, USA Matija Fajdiga, UL, Faculty of Mechanical Engineering, Slovenia Imre Felde, Obuda University, Faculty of Informatics, Hungary Jože Flašker, UM, Faculty of Mechanical Engineering, Slovenia Bernard Franković, Faculty of Engineering Rijeka, Croatia Janez Grum, UL, Faculty of Mechanical Engineering, Slovenia Imre Horvath, Delft University of Technology, Netherlands Julius Kaplunov, Brunel University, West London, UK Milan Kljajin, J.J. Strossmayer University of Osijek, Croatia Janez Kopač, UL, Faculty of Mechanical Engineering, Slovenia Franc Kosel, UL, Faculty of Mechanical Engineering, Slovenia Thomas Lübben, University of Bremen, Germany Janez Možina, UL, Faculty of Mechanical Engineering, Slovenia Miroslav Plančak, University of Novi Sad, Serbia Brian Prasad, California Institute of Technology, Pasadena, USA Bernd Sauer, University of Kaiserlautern, Germany Brane Širok, UL, Faculty of Mechanical Engineering, Slovenia Leopold Škerget, UM, Faculty of Mechanical Engineering, Slovenia George E. Totten, Portland State University, USA Nikos C. Tsourveloudis, Technical University of Crete, Greece Toma Udiljak, University of Zagreb, Croatia Arkady Voloshin, Lehigh University, Bethlehem, USA General information Strojniški vestnik – Journal of Mechanical Engineering is published in 11 issues per year (July and August is a double issue).

University of Ljubljana, Faculty of Mechanical Engineering, Slovenia

Vice-President of Publishing Council Jože Balič University of Maribor, Faculty of Mechanical Engineering, Slovenia

Cover: The energy-absorption devices, particular in the case of aircraft, allow a controlled collapse of the structure during which they absorb energy involving extensive plastic deformation. A small-scale experimental test is able to characterize the energy absorption of a material under compression by innovatively introducing self-supporting sinusoidal shape specimens (upper picture).

Lower pictures show typical broken specimens for both unidirectional and plain weave configurations.

Courtesy: MasterLab, University of Bologna, Italy

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Strojniški vestnik - Journal of Mechanical Engineering 60(2014)6 Contents

Contents Strojniški vestnik - Journal of Mechanical Engineering volume 60, (2014), number 6 Ljubljana, June 2014 ISSN 0039-2480 Published monthly

Papers Enrico Troiani, Lorenzo Donati, Gianluca Molinari, Raffaella Di Sante: Influence of Plying Strategies and Trigger Type on Crashworthiness Properties of Carbon Fiber Laminates Cured through Autoclave Processing 375 Marjan Leber, Majda Bastič, Borut Buchmeister: The Trends in Usage and Barriers of Innovation Management Techniques in New Product Development 382 Sergey Nikolaevich Grigoriev, Tatyana Vasilievna Tarasova, Galina Olegovna Gvozdeva, Steffen Nowotny: Structure Formation of Hypereutectic Al-Si-Alloys Produced by Laser Surface Treatment 389 Qihui Yu, Maolin Cai, Yan Shi, Zichuan Fan: Optimization of the Energy Efficiency of a Piston Compressed Air Engine 395 Ana Bižal, Jernej Klemenc, Matija Fajdiga: Evaluating the Statistical Significance of a Fatigue-Life Reduction Due to Macro-Porosity 407 Yesid Asaff, Victor J. De Negri, Heinrich Theissen, Hubertus Murrenhoff: Analysis of the Influence of Contaminants on the Biodegradability Characteristics and Ageing of Biodegradable Hydraulic Fluids 417 Miha Praznik, Vincenc Butala, Martina Zbašnik-Senegačnik: A Simple Method for Evaluating the Sustainable Design of Energy Efficient Family Houses 425 Shengli Song, Xinglong Zhang, Zhitao Tan: RBF Neural Network Based Sliding Mode Control of a Lower Limb Exoskeleton Suit 437

Strojniški vestnik - Journal of Mechanical Engineering 60(2014)6, 375-381 © 2014 Journal of Mechanical Engineering. All rights reserved.

DOI:10.5545/sv-jme.2013.1506

Received for review: 2013-10-14 Received revised form: 2014-02-10 Accepted for publication: 2014-02-28

Original Scientific Paper

Influence of Plying Strategies and Trigger Type on Crashworthiness Properties of Carbon Fiber Laminates Cured through Autoclave Processing Troiani, E. – Donati, L. – Molinari, G. – Di Sante, R. Enrico Troiani* – Lorenzo Donati – Gianluca Molinari – Raffaella Di Sante University of Bologna, MasterLab, Italy A small-scale experimental test able to characterize the energy absorption of a material under compression was developed by innovatively introducing self-supporting sinusoidal shape specimens, thus avoiding the complex anti-buckling devices of classical flat specimen tests.

Two carbon-fiber-reinforced polymer (CFRP) pre-preg types were tested: 12 plies of unidirectional tape or 8 plies of plain weave fabric for a laminate approximately 1.8 mm thick in both cases. Three stacking sequences were analysed, in order to identify the configuration able to maximize the specific energy absorption (SEA), i.e. the energy absorbed per unit mass of crushed structure is expressed in J/g, with the unidirectional specimen providing the best results.

In order to have a controlled crush, the specimens were produced with different auto-triggering configurations. Indeed, the fibers’ continuity was interrupted in selected position and to different degrees in order to investigate the SEA of the weakened laminates. For unidirectional specimens, the SEA maximum value and behaviour over the stroke were unaffected by the trigger position. Therefore, the auto-triggering configuration was able to control the position of the initial failure of the specimen without any decrease in safety performance.

Keywords: composites, compression test, crashworthiness, specific energy absorption (SEA)

0 INTRODUCTION The overall objective of designing for crashworthiness is to use the energy-absorption characteristics of structures in order to reduce injuries and fatalities in mild impacts, which are mostly due to the accelerations and load histories experienced by passengers. The energy-absorption effect can be attained either by modifying the structural geometry of the assembly or by introducing specific load-limiting devices into the structure, e.g. the controlled collapse of a vehicle ensures a safe dissipation of a given amount of kinetic energy.

Therefore, an important aspect of crashworthiness is the progressive failure of the structure, which is a controlled and predictable failure that progresses through the body at the loading speed. The progressive failure mechanism allows a larger amount of energy to be absorbed, compared to a catastrophic failure. The typical behaviour of a progressive failure in a crushed structure is shown in Fig. 1. The key parameters are the energy absorption (EA), which is the total energy absorbed and is represented by the area below the load-deformation curve, and the specific energy absorption (SEA), the energy absorbed per unit mass of the crushed sample.

Traditionally, in the particular case of aircraft, the energy-absorption devices are steel or aluminum structural elements; these materials allow a controlled collapse of the structure during which they absorb energy by folding or hinging, involving extensive

plastic deformation. The current trend of substituting metals with composites, mostly carbon fibers-epoxy resins, can improve the energy absorption performance of the devices [2] and [3], but it introduces several problems due to the complexity of failure mechanisms that can occur within the material [4] to [7].

Fig. 1. Typical force-stroke history [1]

Moreover, many studies indicate that the energy absorption characteristics in composite structures are strictly dependant on the crushing triggers [8] to [10], i.e. weakened areas at appropriate locations [11] and [12], which are useful in initiating a stable and controlled progressive failure. Bevels and chamfers are very effective in the preventing catastrophic failures [13], thus providing a stable propagation of the collapse, while at the same time reducing the peak load at the initial failure. More advanced and effective

*Corr. Author’s Address: University of Bologna, MasterLab, via Fontanelle 40, 47121 Forlì, Italy, enrico.troiani@unibo.it

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Strojniški vestnik - Journal of Mechanical Engineering 60(2014)6, 375-381

technical solutions using shape memory alloys [14] have been introduced, at the expense of a more complex manufacturing.

However, there is a lack of information about the behaviour of these structures under operative loads, because the introduction of composite materials makes the data obtained from the incidents and accidents of existing metallic aircrafts no longer representative. The behaviour of composite structures can be described through extensive substructure testing within a building block approach to the design of crashworthy structures. Numerical models of both structural and material behaviour, supported by tests of coupons or small structures, are the preferred choice for understanding the behaviour of these structures In the literature, the available coupon size test methods for the energy absorption determination of composite materials can be divided into two main categories based on the kind of specimen used: flat specimen and self-supporting specimen, usually thin walled tubes. The flat specimen test method, which is easier and less expensive, consists of crushing a rectangular specimen constrained in a dedicated antibuckling fixture [15] and [16]. However, the overall procedure is influenced by many external parameters like the complex fixture or the test operator’s skills.

The self-supporting specimen test method eliminates the need for an anti-buckling fixture and all its related issues, like the phenomenon of fronds tearing or the arbitrary closing force of the specimen.

The different shapes for the self-supporting specimens found in the literature range from a simple tube, round or square, to sinusoidal webs [17] to complex C-shaped tube-segments like the ones developed by DLR [18]. The manufacture of tubes is more complex than that of flat specimens, requiring an internal mandrel around which the plies have to be wrapped.

as shown in Fig. 2, which is easier to produce than the ones proposed in the literature.

The main goal of this research has been therefore the better understanding of SEA behaviour in a corrugated specimen, together with optimization of the crush initiator.

Crush tests of two pre-preg systems were performed to evaluate the SEA behaviour. After observation of the failure modes, a new trigger geometry was tested in the same materials.

1 EXPERIMENTAL PROCEDURE The specimens’ material is a carbon fiber reinforced epoxy matrix. Two pre-preg systems were tested: 12 plies of unidirectional (UD) tape (ACG T700 24k/MTM57) or 8 plies of plain weave (PW) fabric (GG200P/IMP530R), for the production of a laminate of around 1.8 mm thickness in both cases. Both materials were cured in an autoclave, according to the supplier indications at 120 °C for 1 h for unidirectional tape and 0.5 h at 120 °C then 0.5 h at 150 °C for plain weave, both under 6.2 bar compacting pressure.

Three stacking sequence (UD [0/90]3s, PW0/90° and PW±45°) were tested in order to identify the configuration able to maximize the SEA. Once machined, each plate is about 210×180 mm and 1.8 mm thick. Six specimens per plate can be cut, four with three repetitions of the half-circular modulus (60×80 mm, called 3HC) and two with five repetitions (80×, called 5HC).

At first, all the specimens were triggered with a simple 45° single side chamfer trigger, as shown in Fig. 3, due to its ease of use.

Fig. 3. Trigger chamfer configuration

Fig. 2. Example of self-supporting specimen, 3HC shape

In order to define a simple and useful tool for the design of crashworthiness in composite materials, an innovative test method for the energy absorption determination has been developed [19] to [21]. The study led to a new concept for a corrugated specimen, 376

Each specimen was tested in a vertical configuration, as shown in Fig. 4, compressed between two steel plates that slide along four steel shafts with self-aligning ball bearings at a quasi-static speed rate of 50 mm/min. A displacement of half the height of the specimen is imposed. Performing the tests at a quasi-static rate does not influence the test results: even if there is a lack of consensus about the

Troiani, E. – Donati, L. – Molinari, G. – Di Sante, R.

Strojniški vestnik - Journal of Mechanical Engineering 60(2014)6, 375-381

influence of test speed on the energy absorption in the literature, a side test campaign confirmed that it does not affect the SEA [21]. The load and displacements were recorded.

Fig. 4. Testing configuration

2 RESULTS AND DISCUSSION From the SEA point of view, the chamfer trigger works perfectly, initiating the crushing smoothly up to an almost steady level of sustained load, as shown in Fig. 5, where the SEA stroke behaviour for the tested specimens is reported.

The EA can be calculated as the total area under the force-stroke diagram. The SEA is the energy absorbed per unit mass, where stroke l, cross-sectional area A, and density ρ [21] thus:

SEA = EA / (ρAl) .

(1)

As might be expected, the maximum energy is absorbed by the UD [0/90]3s specimens due to the material having better mechanical properties, thus providing a maximum value of 100 J/g for SEA, which was stable all along the compression stroke. The UD specimen collapse is mostly due to a mechanism combining lamina bending and fragmentation.

A chamfer trigger is therefore an excellent solution for the experimental tests, as it is both simple and quick to execute. However, as an effective practical application (for example, as energy absorbers situated behind the bumper of a vehicle), a small drawback consists in the difficulty of adequately supporting and fixing the chamfered end of the component. More generally, post curing mechanical machining constitutes an additional operation, which is not negligible in terms of time and resources in the production phase of the test, and which can generate local defects and micro-cracks, that, in turn, influence the test results.

Fig. 5. SEA Stroke behaviour; a) UD, b) PW 0/90° and c) PW ±45°

A very promising way to solve the aforementioned problems of the chamfer trigger consists in creating a localized weakening of the specimen directly in the lamination phase. One of the simplest solutions is to insert in the stacking sequence some shorter layers, in order to obtain a specimen which presents a reduced number of layers at one end (called an ATF configuration), as shown in Fig. 6. This is a pre-curing process with no supporting problems in the test phase.

A testing campaign on this auto-trigger configuration was carried out on the same [0/90]3s stacking sequence of UD tape (ACG T700 24k/ MTM57). The SEA-stroke behaviour is shown in

Influence of Plying Strategies and Trigger Type on Crashworthiness Properties of Carbon Fiber Laminates Cured through Autoclave Processing

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Strojniški vestnik - Journal of Mechanical Engineering 60(2014)6, 375-381

Fig. 7. The achieved levels of SEA are close to those obtained with the 45° single side chamfer trigger.

Fig. 8. New trigger configuration Fig. 6. ATF-trigger specimen

This simple solution avoids the problem of a lack of resin on the trigger because the small thickness “d” of the gap is easily filled by an excess of resin in the prepreg. Moreover, unlike the ATF configuration, this new idea involves the use of a very narrow trigger (only 5 mm strips compared with 20 mm of the ATF), in order to increase the level of SEA.

Fig. 7. SEA comparison between UD 45° chamfer and UD ATF trigger specimen

Unfortunately, the SEA trend is not optimal: the SEA value begins to climb (rather slowly) to significant levels only after rupture of the entire trigger. This is due to the large weakening area, which prevents a rapid rise in specific energy. Furthermore, there is a substantial lack of resin in the trigger area, as shown in Fig. 6, thereby generating lower and nonuniform mechanical properties.

In order to overcome the drawbacks of the ATF configuration, avoiding the lack of fibers in specific areas and getting a trigger that is as small as possible (in order to maximize the SEA), a new type of trigger configuration has been conceived: on each weakened lamina, a strip is cut (as in the ATF configuration) but not discarded, and is therefore laminated in the mold together with the remaining part of the sheet. Fig. 8 shows an example of the standard and weakened laminae with the new auto-trigger for the 0 and 90° layers. If the cut is on the 90° laminae, the weakening is achieved through a reduction of fiber content in the zone (resin properties dominated zone), while when the weakening is realized on the 0° laminae, a discontinuity in the fibers is deliberately introduced.

In a similar way the configurations PW 45* and PW 0/90* were realized.

378

Fig. 9. Comparison of SEA values for 3HC and 5HC specimens

A new test campaign on this auto-trigger configuration was carried out on the same materials and stacking sequences of previous UD and PW specimens. The stacking sequences are reported in detail in Table 1, where the symbol * is used to identify the weakened laminae. The measured values of loads and SEA are not dependent on the number of semi-circular repetitions: the 3HC and 5HC specimen results are comparable, as shown in Fig. 9 for the SEA. As can be seen from Table 1, Set 1 has four weakened layers in the inner 90° laminae where d = 0 mm, i.e. without any interrupted fiber. Moreover, during the curing process the matrix becomes partially fluid and fills the voids, recreating the material continuity. As a result, these specimens are considered not to be triggered, and can also be a benchmark for comparison with data from Fig. 5a. Their SEA behaviour is shown in Fig. 10.

Troiani, E. – Donati, L. – Molinari, G. – Di Sante, R.

Strojniški vestnik - Journal of Mechanical Engineering 60(2014)6, 375-381

Table 1. New trigger configurations stacking sequences Set no.

1 2 3 4 5 6 7 8

Features UD [0 ; 90*]3s; d = 0 mm UD [0 ; 90*]3s; d = 2 mm UD [0* ; 90]3s; d = 0 mm UD [0* ; 90]3s; d = 0 mm UD [0 ; 90*]3s; d = 2 mm PW [0/90; 45*]2s; d = 0 mm PW [0/90]4s; d = 0 mm PW [0/90]4s; d = 0 mm

Fig. 10. SEA behaviour in Set 1 - 6 specimens

layup 0 – 90 – 0 – 90* – 0 – 90* – 90* – 0 – 90* – 0 – 90 – 0 0 – 90 – 0 – 90* – 0 – 90* – 90* – 0 – 90* – 0 – 90 – 0 0 – 90 – 0* – 90 – 0* – 90 – 90 – 0* – 90 – 0* – 90 – 0 0 – 90 – 0 – 90 – 0* – 90 – 90 – 0* – 90 – 0 – 90 – 0 0 – 90 – 0 – 90 – 0* – 90 – 90 – 0* – 90 – 0 – 90 – 0 0/90 – 45* – 0/90 – 45 – 45 – 0/90 – 45* – 0/90 0/90 – 0/90* – 0/90 – 0/90 – 0/90 – 0/90 – 0/90* – 0/90 0/90 – 0/90 – 0/90 – 0/90* – 0/90* – 0/90 – 0/90 – 0/90

0 to 2 mm (on four layers) makes the specimens more sensitive to the presence of the trigger, as shown by the decrease in SEA values immediately after the initial peak. This transient phenomenon in the SEAstroke behaviour is mostly due to the wide strip of resin, which results in too weak a trigger. A 10% lower average SEA and higher dispersion of results are related to the higher sensitivity to the trigger.

Conversely, cutting the 0° fibers brings about a greater degree of weakening: the fibers, in fact, are irreversibly broken in relation to the trigger, and the empty spaces are again filled by the resin with lower mechanical properties. As a consequence, the Set 3 results in Fig. 12 show high SEA peaks and immediate collapse loads. In these specimens, four of the 0°-layers were weakened, thus generating the drastic reduction in SEA performance.

Fig. 11. SEA behaviour in Set 2 - 6 specimens

Fig. 13. SEA behaviour in Set 4 - 6 specimens

Fig. 12. SEA behaviour in Set 3 - 6 specimens

Analyzing the test results of Sets 1 and 2 (Fig. 11), it is noticeable that increasing the d values from

By reducing the number of split layers (Set 4, Fig. 13), the magnitude of the weakening is clearly lower than in Set 3, which reduces the sensitivity to the trigger and decreases the SEA. Thanks to the high values of SEA and the very short transition, Set 4 is an optimum configuration from the point of view of the absorption energy, although there is still an excessive variability in behaviour in the initial transient.

Similarly, in Set 5, where d is increased to 2 mm and it is more difficult to fill in the voids in the matrix, the values of SEA (Fig. 14) are fairly stable

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and, on average, comparable to Set 4. As seen in the previous set, very high SEA values were found and were comparable to the reference condition (Set 1), on average about 100 J/g, after a very short transient.

shows typical broken specimens for both UD and PW configurations.

a)

Fig. 14. SEA behaviour in Set 5 - 6 specimens

b) Fig. 16. Failure modes; a) UD, and b) PW

A direct comparison between the UD and PW specimen SEA behaviour is shown in Fig. 17. The behaviour of UD Set 2 specimens, a sharp peak followed by a drop, shows a different initial transient when compared to the reference set, although there is a similar mean value of SEA (differences less than 10%). Conversely, the weaker mechanical properties of the PW greatly reduce the energy absorption, with a collapse at very low levels (20 J/g) and SEA mean values more than 30% lower than those of UD. Fig. 15. SEA behaviour in PW specimens (set n.6)

The performance of PW specimens is obviously worse than the UD, due to the lower mechanical properties of the material. Another interesting difference is a noticeable “softening” of the SEA curves, as shown in Fig. 15. The range of stroke required to reach the equilibrium is much larger than in previous sets, which indicates an unstable crush and the presence of local unpredictable phenomena.

Another important issue is the failure mode of the specimens: the UD prepreg failures are due to the mixed contribution of transverse shearing and plate bending. For the PW fabric specimens, the intertwining of fibers at 0 and 90° interferes with the respective free deformation, thus generating a very large number of breaks extremely close together. This effect produces a very large number of tiny shards, which accumulate as debris at the base of the specimen. This kind of failure is considerably more stable and therefore very favorable for crashworthiness applications. However, the limited mechanical properties of PW fabric significantly reduced the absorption capacity. Fig. 16 380

Fig. 17. SEA mean values comparison

3 CONCLUSIONS The main achievement of the present paper is the definition of a reliable and affordable experimental procedure for the quantification of the energy absorption capability of composite materials. This work also constitutes the first step of a building block approach program that, starting from experimental tests on small specimens and numerical analysis, helps the designer to build up knowledge to better focus the study of more complex structures.

Troiani, E. – Donati, L. – Molinari, G. – Di Sante, R.

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The results obtained from the experimental campaign showed that the test method using selfsupporting specimens is reliable and, most important, is not affected by external factors introduced by the anti-buckling fixture, which is necessary in the flat specimens test procedure. Moreover, the sine wave specimens are easier to manufacture than the widely used tubes.

Regarding the other important feature for a crashworthy structure, namely the ability to control the position of the initial damage and its propagation, the auto-triggering configurations, with fiber continuity interrupted in selected positions and to various extents, proved to be a viable alternative to external triggers. The achieved levels of SEA for Sets 1, 4 and 5 are close to those obtained with the traditional chamfer configuration in UD, while eliminating timeconsuming, post-curing, mechanical machining.

4 REFERENCES [1] VV.AA. (2012). Chapter 14 – Crashworthiness and Energy Management. Composite Materials Handbook CMH-17-3G, vol. 3. SAE International, Washington D.C. USA, p. 1-9.

[2] Jacob, G.C., Fellers, J.F., Simunovic, S., Starbuck, J.M. (2002). Energy absorption in polymer composites for automotive crashworthiness. Journal of Composite Materials, vol. 36, no. 7, p. 813-850, DOI:10.1177/002 1998302036007164.

[3] Carruthers, J.J., Kettle, A.P., Robinson, A.M. (1998).

Energy absorption capability and crashworthiness of a composite material - a review. Applied Mechanics Review, vol. 51, no. 10, p. 635-649, DOI:10.1115/1.3100758.

[4] Hull, D. (1991). A unified approach to progressive crushing of fibre-reinforced composite tubes.

Composites Science and Technology, vol. 40, no 4, p.

377-421, DOI:10.1016/0266-3538(91)90031-J. [5] Farley, G.L., Jones, R.M. (1992). Crushing characteristics of continuous fiber-reinforced composite tubes. Journal of Composite Materials, vol. 26, no. 1, p. 37-50, DOI:10.1177/002199839202600103.

[6] Mamalis, A.G., Robinson, M., Manolakos, D.E., Demosthenous, D.A., Ioannidis, M.B., Carruthers, J. (1997). Crashworthy capability of composite material structures. Composite Structures, vol. 37, no. 2, p. 109134, DOI:10.1016/S0263-8223(97)80005-0.

[7] Bolukbasi, A.O., Laananen, D.H. (1995). Analytical and experimental studies of crushing behavior in composite laminates. Journal of Composite Materials, vol. 29, no.

8, p. 1117-1139, DOI:10.1177/002199839502900806.

[8] Thornton, P.H. (1979). Energy absorption in composite structures. Journal of Composite Materials, vol. 13, no.

3, p. 247-262, DOI:10.1177/002199837901300308.

[9] Thornton, P.H. (1982). Energy absorption in composite tubes. Journal of Composite Materials, vol. 16, no. 6, p. 521-545, DOI:10.1177/002199838201600606.

[10] Farley, G.L. (1983). Energy absorption of composite materials. Journal of Composite Materials, vol. 17, p.

267-279, DOI:10.1177/002199838301700307.

[11] Sigalas, I., Kumosa, M., Hull, D. (1991). Trigger mechanisms in energy-absorbing glass cloth/epoxy tubes. Composites Science and Technology, vol. 40, no.

3, p. 265-287, DOI:10.1016/0266-3538(91)90085-4.

[12] Thuis, H.G.S.J., Metz, V.H. (1994). The influence of trigger configuration and laminate lay-up on the failure mode of composite crush cylinders.

Composite Structures, vol. 28, no. 2, p. 131-137, DOI:10.1016/0263-8223(94)90043-4.

[13] Song, H.W., Du, X.W., Zhao, G.F. (2002). Energy absorption behavior of double-chamfer triggered glass/epoxy circular tubes. Journal of Composite Materials, vol. 36, no. 18, p. 2183-2198, DOI:10.1177/0021998302036018515.

[14] Huang, J.C., Wang, X.W. (2010). Effect of the SMA trigger on the energy absorption characteristics of cfrp circular tubes. Journal of Composite Materials, vol. 44, no. 5, p. 639-651, DOI:10.1177/0021998309347572.

[15] Lavoie, J.A., Kellas, S. (1996). Dynamic crush tests of energy-absorbing laminated composite plates. Composites: Part A Applied Science and Manufacturing, vol. 27, no. 6, p. 467-475, DOI:10.1016/1359-835X(95)00058-A. [16] Cauchi Savona, S., Hogg, P.J. (2005). Investigation of plate geometry on the crushing of at composite plates. Composites Science and Technology, vol.

66, no. 11-12, p. 1639-1650, DOI:10.1016/j. compscitech.2005.11.011.

[17] Farley, G.L., Jones, R.M. (1989). Energy-absorption capability of composite tube and beams. NASA Technical Publications TM 101634:1-248, Hampton.

[18] Kohlgruber, D., Kamoulakos, A. (1998). Validation of numerical simulation of composite helicopter subfloor structures under crush loading. Proceedings of the 54th AHS Annual Forum, Washington, D.C. [19] Garattoni, F., Molinari, G., Troiani, E. (2010).

Development of a reliable test to support and validate a numerical model of progressive damage for composite materials. Proceedings of the Royal Aeronautical Society 2nd Aircraft Structural Design Conference, London.

[20] Garattoni, F., Troiani, E. (2010). An experimental method and numerical simulation for composite materials energy absorption determination. Proceedings of the 27th International Congress of the Aeronautical Sciences. Nice.

[21] Feraboli, P. (2008). Development of a corrugated test specimen for composite materials energy absorption.

Journal of Composite Materials, vol. 42, no. 3, p. 229256., DOI:10.1177/0021998307086202.

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DOI:10.5545/sv-jme.2013.1611

Received for review: 2013-12-16 Received revised form: 2014-02-05 Accepted for publication: 2014-02-18

Original Scientific Paper

The Trends in Usage and Barriers of Innovation Management Techniques in New Product Development Leber, M. – Bastič, M. – Buchmeister, B. Marjan Leber1 – Majda Bastič2 – Borut Buchmeister1,*

1 University

2 University

of Maribor, Faculty of Mechanical Engineering, Slovenia of Maribor, Faculty of Economics and Business, Slovenia

This paper reports the results of a survey on the use of innovation management techniques (IMTs) with the potential to improve effectiveness of new product development (NPD), and customer satisfaction as well as about those barriers preventing their introduction in Slovene firms in the period from 2003 to 2011. The results show that small percentage of Slovene firms used IMTs. Failure mode and effects analysis (FMEA) was found as the most applied IMT in Slovene firms with the highest perceived utility potential to reduce development costs and improve customer satisfaction. Results also indicate a trend towards the increasing use of fault tree analysis (FTA), value analysis, target costing, and TRIZ especially during the period of 2008 to 2011 which coincides with the period of economic and financial crisis. IMT complexity, a needed coaching and training and the lack of input data for IMT usage were recognized as the main barriers to implementing IMTs in Slovene firms.

Keywords: innovation management techniques, new product development, longitudinal study

0 INTRODUCTION Satisfying new customers’ requirements regarding product quality and price presents an opportunity to firms to develop new products as well as the challenge for operational innovation and knowledge management. Innovative approaches are essential in successful product design (for new and modified existing products).

Innovations defined as the successful exploitation of new ideas are seen as “powerful engine” for firms’ development that also influence social and global challenges [1] to [5]. Even in the years of economic instability it was often heard how innovations were important for the success of companies [6] to [9].

New product development (NPD) defined as the transformation of a new idea or a new market opportunity into a new product available for sale is risky and not easy [10]. With short time-tomarket, fierce competition in an already crowded market place, and ever-more demanding consumers, organizations must continually make trade-offs when identifying project priorities and allocating resources [11]. Cooper estimated that 46% of the resources that companies devote to the designing, developing, and launching of new products go into projects that fail in the market place or perhaps never even make it to market [12]. Barczak et al. found that only 14% of initial ideas actually become commercially successful.

Therefore, it is vital that less promising ideas are filtered out as early as possible, but that promising ideas are not dissipated [13].

The effectiveness of NPD measured by time-tomarket, product and development cost, and product 382

quality can be improved by usage of innovation management techniques (IMTs) [14] to [17]. Barczak et al. [13] found a significant difference in the use of these techniques in the best firms, and the rest. The best firms used large numbers of techniques more frequently, which suggests that they may be more open to experimenting with new tools and methodologies and to leveraging existing tools and methodologies for improving the efficiency and effectiveness of their innovation projects. Rihar et al. [18] presented the strengths of simultaneous product development and complete realisation from the initial idea to market presence.

Considering the impact of IMT usage on the NPD effectiveness and firms’ success as well as the current situation of Slovene firms which are facing with consequences of economic and financial crisis the objective of this study was to analyse the usage and trends in IMT usage in Slovene firms, the IMT perceived utility in improving NPD effectiveness and the most important barriers which prevented the Slovene firms to use IMTs. 1 INNOVATION MANAGEMENT TECHNIQUES IMTs can be seen as a range of tools, techniques and methodologies that help companies to adapt to circumstances and meet market challenges in a systematic way [19]. Numerous new IMTs, as well as appropriate software, have been developed for improving the NPD process and reducing the uncertainty of NPD outcomes [20]. The growth of IMTs results from a new way of thinking. It is not necessarily due to technology, but more to the

*Corr. Author’s Address: University of Maribor, Faculty of Mechanical Engineering, Smetanova 17, Maribor, Slovenia, borut.buchmeister@um.si

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capacity of firms to apply their knowledge to improve businesses internally and their relationships with external actors [21].

Palacios & Gonzáles classified the IMTs into five generic categories [22]: • Design techniques: quick product specification, quality function deployment, conjoint analysis, design for excellence, robust design modular design, incremental innovation, rapid design transfer, group technology, rapid prototyping and tooling, failure mode effect analysis; • Organizational techniques (concurrent activities management, stage-gate process, multifunctional design teams); • Manufacturing techniques, (manufacturing resource planning, just in time, optimal product technology, statistical process control); • Information techniques (computer aided design, computer aided manufacturing, computer aided engineering, computer integrated manufacturing, internet and intranets, electronic data interchange, expert systems, groupware, and product data management); and • Supplier involvement.

These techniques can be applied to timely experiment a number of product and process options that are available or feasible [14]. They must empower teams at all levels of organizations by giving them timely information for making timely decisions, before tasks become critical [23] to [25].

Successful implementation and utilization of IMTs calls for a holistic view of all aspects of the NPD process, the specific tasks or techniques, the types of information and knowledge to be processed and the people who are supposed to use them [20]. In addition, it is essential to carefully select and match the right IMT with the right task and phase of the NPD process.

A lack of qualified personnel with experience in IMTs has been the reason for non-use of IMT. Most SMEs do not have the necessary in-house knowledge of IMTs and their implementation [21].

Our study deals with two major questions: • Does innovation management technique usage contribute (support) the NPD in Slovene firms?

• Can Slovene firms improve innovation processes using innovation management techniques?

2 METHODOLOGY The study carried out in 2011 was part of longitudinal survey started in 2003. The questionnaire applied

during the 2011 survey was 16 pages in length and covered the following issues: • background information on the respondents; • the main reasons which initiated NPD; • competences and frequency of IMT usage; • the perceived utility potential of IMTs to NPD effectiveness; • barriers to IMT usage in NPD. The questions about percentages of firms using IMTs and the IMT utility potential were worded identically as in the 2003 survey. The sections: the importance of reasons influencing the start of an NPD, percentage of Slovene firms with IMT competence and the frequency of IMTs use, were completely new. The informants were top managers or product development managers as it was assumed that they best know the innovation processes in their firms.

The 2003 survey was an exploratory study based on a sample of 19 firms. Either personally or by e-mail all 15 still operating firms participating in the 2003 survey were contacted in 2011. In addition, we invited also similar firms to participate in the survey in order to increase sample size and improve the reliability of the obtained results. The invitation for participating in this study was provided by The Chamber of Commerce and Industry of Slovenia website home page. The questionnaires were completed between March and April 2011. As the financial and economic crisis started in the year 2008 had changed the business environment, changes in IMT usage were of interest in the period from 2008 to 2011. Therefore, the respondents were asked to provide data on IMT use in the years 2008 and 2011.

Completed questionnaires were received from 40 firms, three questionnaires were unusable. 15 usable questionnaires were from firms participating in the 2003 survey. The potential reasons for the low response rate could be the length of the questionnaire and the numerous questionnaires Slovene firms obtain almost every day. The same problems have also been noticed in the similar studies [22] and [26].

The majority of the firms in sample operated in the metal processing industry (45.9%) followed by service firms (18.9%), and the electro industry (13.5%). The remainder of the firms belonged to the chemical, textile, and other industries. Regarding firms’ size 31.4% were small firms, 34.3% mediumsized, and 34.3% were large firms. 75% of the firms were profitable. The firms were also asked about their most important strategic objective. 15.2% of the firms reported cost reduction, 27.2% quality improvement of existing products or services, and 57.6% the development of new products or services.

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The following IMTs that were often cited in the literature and were known to respondents in the 2003 survey were included in 2011 survey. They were classified into three groups: • Idea generation and screening: delphi method (DM), theory of inventing problem solving (TRIZ); • Design techniques: conjoint analysis (CA), fault tree analysis (FTA), failure mode and effects analysis (FMEA), design of experiment (DoE), quality function deployment (QFD), value analysis (VA), target costing (TC); • Manufacturing techniques: statistical process control (SPC).

CA, QFD, DoE, DM are known as IMTs that contribute to a reduction in time-to-market.

Development costs could be successfully planned and controlled using TC, VA, and TRIZ. Customer satisfaction could be improved using CA, FMEA, QFD and VA. FMEA and FTA are known as the best tools to foster expert teams to perpetuate the voice of the customer and engineer throughout the product development cycle so that QFD is the guardian to the voice of customer while FMEA is the guardian to the voice of the engineer [27].

Although we attempted to overcome some of the methodological problems, some caveats also apply to this research. Firstly, the results must be considered exploratory by nature because of the sources employed in our research. A second concern about the study was that all the data were collected from a single respondent from each firm. While the respondents were shown to possess high degrees of relevant knowledge, they were still subject to respondent bias.

Due to the small sample, it was impossible to draw any representative conclusions for this subset of firms using IMTs in innovation processes. However, an initial impression of the methodology used can be obtained. Further studies with larger samples would clarify the picture.

3 RESULTS 3.1 Reasons Triggering the NPD In the first step of the survey, we analysed the importance of reasons which initiated an innovation process in Slovene firms. The questionnaire included the following reasons: creating a competitive advantage, the development of new package, an improvement of product quality by incremental changes, an improvement of product quality by radical changes, the development of a new product 384

in the word, the development of a new product in the firm, better meeting customers’ requirements.

The respondents estimated the importance of these reasons on a 10-point scale ranging from 1 – ‘not at all important’ to 10 – ‘very important’.

Table 1. The importance of reasons influencing the start–up of innovation process The reason Competitive advantage Development of new package Incremental changes of a product Radical changes of a product New-to-the world product New-to-the firm product Customers’ requirements

2008 6.04 2.90 7.04 6.54 5.81 5.39 7.59

2011 7.17 3.10 7.24 7.33 5.89 6.50 7.92

Customers’ requirements were found as the most important reason which triggered NPD processes in Slovene firms. They were followed by the improvement of product quality by incremental changes in 2008 and the improvement of product quality by radical changes in 2011 (see Table 1). The trend of increasing importance of all reasons was also noticed.

3.2 Firms’ Competences Regarding Innovation Management Techniques More than half of the sampled Slovene firms chose the development of new products as their main strategic goal. To efficiently achieve this goal a high effectiveness and efficiency of NPD processes have been requested. They can be improved by a methodological know-how within the firm. For this reason, we inquired about the IMT competences in Slovene firms.

Table 2. The percentages of Slovene firms with competences in IMTs (multiple answers were possible) Innovation management techniques CA FTA FMEA DoE QFD VA TC SPC TRIZ DM

Leber, M. – Bastič, M. – Buchmeister, B.

2008 5.0 25.0 37.5 10.0 17.5 25.0 12.5 27.5 7.5 7.5

2011 2.5 35.0 40.0 12.5 22.5 30.0 25.0 25.0 25.0 10.0

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The figures in Table 2 indicate that the competences in Slovene firms were different across the IMT spectrum. The majority of Slovene firms (37.5%) had competences in FMEA followed by SPC (27.5%) and FTA (25%) in 2008. In 2011, the most popular was again FMEA (40%) followed by FTA (35%) and QFD (22.5%). The share of firms with competence in CA was very low. In 2011, the increase in the percentage of Slovene firms with competence in FMEA and FTA was noticed on one hand and a decrease in SPC and CA on the other hand. In addition, an enormous increase in the percentages of firms with competences in TRIZ and target costing in 2011 was found.

3.3 The Implementation of IMTs In addition to competences, we investigated the use of IMTs during the period from 2003 to 2011.

Table 3. The percentages of firms using IMTs (multiple answers were possible) Innovation management techniques CA FTA FMEA DoE QFD VA TC SPC TRIZ DM

2003 0.5 13.0 38.0 4.0 12.0 18.0 8.5 34.0 0 0

2008 2.7 21.2 35.1 8.1 13.5 24.3 10.8 27.0 5.4 0

2011 0 29.7 37.8 8.1 13.5 27.0 16.2 27.0 8.1 2.7

The figures in Table 3 show that more than 60% of Slovene firms did not use individual IMTs. In 2003, the most applied IMT was FMEA followed by SPC and VA. The rank order of the most applied IMTs did not change in the year 2008. In 2011, the majority of firms (37.8%) used FMEA followed by FTA (29.7%), VA (27%), and TC (27%). The very small percentage of Slovene sampled firms used AC and DM. A comparison of the data about IMTs usage between 2003 and 2011 showed stability in the percentages of firms using FMEA and QFD, a decline in the use of SPC and CA, and an increase in the use of other IMTs as presented in Table 3. The highest increase in the IMT usage was found for FTA (16.7%), followed by VA (9%), TRIZ (8.1%), and TC (7.7%).

We also analysed the difference in the frequency of IMT usage between profitable and non-profitable Slovene firms in 2008 and 2011 (See Table 4). The frequency of IMT usage was measured on a 10-point

scale ranging from 1 – ‘never used’ to 10 – ‘always used’. In 2008 and 2011 the profitable firms used all IMTs except TC in 2011 more frequently than the non-profitable firms. The most frequently used IMT in profitable firms was FMEA while non-profitable firms preferred SPC in 2008 and target costing in 2011.

Table 4. The frequency of IMT usage with respect to firms’ profits Innovation management techniques CA FTA FMEA DoE QFD VA TC SPC TRIZ DM

Firm’s profit 2008

2011

Yes

No

Yes

No

1.50 4.00 7.00 2.67 4.29 5.30 4.43 5.38 3.17 1.00

1.00 2.00 3.40 1.67 2.00 2.33 1.33 5.20 1.00 1.00

5.00 6.92 2.86 3.67 6.50 4.33 6.82 2.78 1.67

1.67 4.00 1.00 3.67 4.25 4.50 1.00 1.50 1.00

3.4 Utility Potential of IMT and Barriers to Their Usage Table 5 gathers information on the perceived utility potential of IMTs for the years 2008 and 2011. In the 2003 analysis, the respondents were asked to choose one out of four areas where their experience shows the highest utility potential of IMTs: shorter development time (SDT) 13%, failure cost reduction (FCR) 39%, improvement of customer satisfaction (ICS) 40%, knowledge management (KM) 8%. The IMT utility potential in 2008 and 2011 were measured on a 10-point scale ranging from 1 – ‘no utility potential’ to 10 – ‘very high utility potential’.

Table 5. Utility potential of innovation management techniques Utility potential SDT FCR ICS KM

2008 4.85 6.15 7.76 5.65

2011 6.20 7.35 9.00 6.95

As can be seen in Table 5, respondents did not perceive low utility potential of IMTs. Therefore, this finding does not explain the low percentage of Slovene firms using IMTs. In all three analysed years, they assigned the highest IMT potential to ICS followed by FCR. The perceived utilities were higher in 2011 than in 2008 and the differences in the perceived utility potentials between 2008 and 2011 were statistically significant for all areas, except for

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KM at p < 0.01. It is quite possible that during the economic crisis Slovene top managers and product development managers have become aware of the IMT potential to the NPD effectiveness and especially to meeting customers’ needs.

After having discovered that the utility potential of IMTs was an insignificant barrier to IMT usage, our research was directed towards the respondents’ experience about the utility potential of those IMTs which mean frequency of usage was higher than 3.0 (a selection from Table 4). The results are presented in Table 6. They assigned the highest utility potential to FMEA with a mean utility of 6.21. Regarding their experience, FMEA provided the most useful information about FCR and ICS amongst all in the survey included IMTs. FMEA was followed by QFD with mean utility of 6.05. This technique had the greatest potential for SDT. VA had the highest potential to KM. The usage of IMTs has mostly contributed to an ICS (mean = 6.08), and a RFC (mean = 5.49).

The next step analysed the importance of other potential barriers to IMT usage in Slovene firms.

Table 6. Utility potential of selected IMTs (10-point scale ranging) IMT FTA FMEA QFD VA TC SPC Mean

SDT 3.43 4.90 5.60 3.78 4.20 3.75 4.28

FCR 5.86 7.22 5.60 3.89 3.00 7.38 5.49

ICS 5.14 7.10 6.80 5.67 5.50 6.25 6.08

KM 4.14 5.60 6.20 6.71 3.80 4.86 5.22

Mean 4.64 6.21 6.05 5.01 4.13 5.56

We investigated the following barriers: the availability of information needed (ANI) in IMT implementation, IMT complexity (TEC), needed coaching and training of employees (CTN) due to the lack of IMT competences, and problems in implementing the IMT results (ITR). In the 2003 analysis, the respondents were asked to choose one out of four offered barriers that represented the most important barrier to IMT usage in their firms: ANI 26%, TEC 33%, CTN 11%, and ITR 30 %. In 2008 and 2011, the importance of barriers was measured on a 10-point scale ranging from 1 – ‘not at all important’ to 10 – ‘very important’. Results for 2008 and 2011 are presented in Table 7.

Technique complexity has been reported as the most important barrier to IMT usage as 33% of respondents found it to be the greatest obstacle to using IMTs in innovation process in 2003, and the highest mean importance also belonged to this barrier in 2008 and 2011. The importance of other barriers 386

differed in 2003 or 2008 and 2011. The problems with an implementation of IMT results were recognized as the second most important barrier in 2003, the needed coaching and training for IMT usage was the second most important barrier in 2008, but in 2011 the lack of available information needed for the IMT usage was found as the second most important barrier.

Table 7. Barriers to IMT usage Barriers ANI TEC CTN ITR

2008 5.00 5.56 5.22 4.61

2011 6.10 6.27 5.94 5.50

4 DISCUSSION The customers’ requirements have played very important role as they found as the most important trigger of NPD in Slovene firms. In 2008, the customers’ requirements were mainly met by incremental changes of products. However, the shift to radical product changes was noticed in 2011. The economic crisis and keener competition have probably forced Slovene firms to adapt to new economic circumstances by development of more radically new products. It confirms the finding of the Organisation for economic co-operation and development (OECD) (2010) that innovations are essential for countries and firms that are to recover from the economic downturn and thrive in today’s highly competitive global economy.

FMEA was the most used IMT in Slovene firms.

Less than one third of Slovene firms used other IMTs. The percentage of Slovene firms using IMTs was lower than was the percentage of firms included in the study of Barczak et al. [13].

The highest percentage of Slovene firms using FMEA and FTA shows that the IMT usage has been closely connected with their main objective NPD – to better meet customers’ needs. The comparison of data about the IMT usage in 2003 and 2011 shows the stability in the usage of FMEA and QFD as well as the substantial increase in FTA and TRIZ usage.

The finding that substantially more Slovene firms used FMEA than QFD shows the higher popularity of FMEA which is the guardian to the voice of the engineer. The increasing number of Slovene firms with competences and usage of TRIZ could be a signal that Slovene firms are becoming aware of the importance that systematic way of managing idea generation has on new product success. The shift

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from the most frequently usage of SPC in 2008 to TC in 2011 in non-profitable firms could be a sign that innovations and the effectiveness of NPD become more and more important objectives also in the nonprofitable firms.

Profitable Slovene firms have used IMTs more frequently than non-profitable firms. Barczak et al.

[13] stated the similar finding also for firms included in their study thus forming the conclusion that IMT usage contributes to the effectiveness and efficiency of innovation processes, and consequently to the new product success. Therefore, the IMT competences and usage can be taken as an opportunity especially for non-profitable Slovene firms to improve the effectiveness and efficiency of their innovation processes.

The data comparison between 2008 and 2011 shows the increasing trend in IMT competence in Slovene firms which could be a consequence of increasing trend of perceived IMT utility as well as the consequences of economic crisis which forces Slovene firms to introduce more radical innovations in the shorter time.

The perceived utility potential of IMTs cannot be taken as the reason for current state of competences and IMT use in Slovene firms. Technique complexity was the most important barrier to IMT use in the period from 2003 to 2011 in Slovene firms. Technique complexity represents a serious barrier to IMT use especially in small firms. This finding is similar to finding of Libutti [28] who revealed that an IMT, to be usable by a small company, must be simple to explain to the personnel and must quickly produce visible effects. A similar conclusion was made by Barczak et al. [13]. The rank order of other reasons fluctuated during the investigated period. The second most important barrier was the implementation of technique results in 2003; in 2008 it was needed coaching and training of employees to be able to use IMTs; and in 2011 it was the lack of needed data for IMT usage.

The rank order of these barriers can be also explained

by Dermol and Drev who found that the problem in Slovene industry is not the number of highly-educated people but rather their skills and knowledge about IMTs obtained during their education [29]. It is very important that management insists on introducing and perfecting individual methods and techniques, and provides continuous on-job training for their staff.

Using training of employees responsible for NPD will probably remove major barriers to use IMTs in Slovene firms. Universities can help to remove these barriers by adding IMT competence in their curriculum.

5 REFERENCES [1] Adams, R., Bessant, J., Phelps, R. (2006). Innovation management measurement: A review. International Journal of Management Reviews, vol. 8, no. 1, p. 2147, DOI:10.1111/j.1468-2370.2006.00119.x.

[2] Trott, P. (2008). Innovation Management and New Product Development (4th ed.). Pearson Education Limited, Essex.

[3] Benedicic, J., Zavbi, R., Duhovnik, J. (2012).

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[4] Fagerberg, J., Mowery, D.C., Nelson, R.R. (2006). The Oxford Handbook of Innovation.

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[5] Novak, M. (2012). Computer aided decision support in product design engineering. Tehnički vjesnik - Technical Gazette, vol. 19, no. 4, p. 743-752.

[6] Christensen, C.M. (1997). The Innovator’s Dilemma: When New Technologies Cause Great Firms to Fail.

Harvard Business School Press, Boston.

[7] Christensen, C.M., Raynor, M.E. (2003). The Innovator’s Solution: Creating and Sustaining Successful Growth. Harvard Business School Press, Boston.

[8] Bessant, J., Tidd, J. (2007). Innovation and Entrepreneurship. John Wiley & Sons, Chichester.

[9] OECD. Key Findings, Ministerial report on the OECD Innovation Strategy – Innovation to strengthen growth and address global and social challenges, from http:// www.oecd.org/site/innovationstrategy, accessed on 2010-10-05.

[10] Krishnan, V., Ulrich, K.T. (2001). Product Development Decisions: A Review of the Literature. Management Science, vol. 47, no. 1, p. 1-21, DOI:10.1287/ mnsc.47.1.1.10668.

[11] Chao, L.P., Ishii, K. (2004). Design process errorproofing: project quality function deployment.

Proceedings of DETC’04. ASME Design Engineering Technical Conferences, Salt Lake City.

[12] Cooper, R.G. (2000). Doing it right winning with new products. Ivey Business Journal, vol. 64, no. 6, p. 5463.

[13] Barczak, G., Griffin, A., Kahn, K.B. (2009).

Perspective: Trends and drivers of success in NPD practices: Results of the 2003 PDMA best practices study. Product Innovation Management, vol. 26, no. 1, p. 3-23, DOI:10.1111/j.1540-5885.2009.00331.x.

[14] Büyüközkan, G., Dereli, T., Baykasoğlu, A. (2003).

A survey on the methods and tools of concurrent new product development and agile manufacturing. Journal of Intelligent Manufacturing, vol. 15, no. 6, p. 731-751, DOI:10.1023/B:JIMS.0000042660.77571.81.

[15] Shepherd, C., Ahmed, P.K. (2000). NPD frameworks: a holistic examination. European Journal of

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Innovation Management, vol. 3, no. 3, p. 160-173, DOI:10.1108/14601060010341166.

[16] Milosavljevic, B.B., Congradac, V.D., Velickovic, V.M., Prebiracevic, B.V. (2012). Business process management in sustainable property/asset management by using the TotalObserver. Thermal Science, vol.

16, Supplement 1, p. S269-S279, DOI:10.2298/ TSCI120223077M. [17] Ayadi, M., Costa Affonso, R., Cheutet, V., Masmoudi, F., Riviere, A., Haddar, M. (2013). Conceptual model for management of digital factory simulation information. International Journal of Simulation Modelling, vol. 12, no. 2, p. 107-119, DOI:10.2507/ IJSIMM12(2)4.233.

[18] Rihar, L., Kusar, J., Gorenc, S., Starbek, M. (2012).

Teamwork in the simultaneous product realisation.

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[19] Phaal, R., Farrukh, C.J.P., Probert, D.R. (2006).

Technology management tools: concept, development and application. Technovation, vol. 26, no. 3, p. 336344, DOI:10.1016/j.technovation.2005.02.001.

[20] Kohn, S., Hüsig, S. (2006). Potential benefits, current supply, utilization and barriers to adoption: An exploratory study on German SMEs and innovation software. Technovation, vol. 26, no. 8, p. 988-998, DOI:10.1016/j.technovation.2005.08.003.

[21] Hidalgo, A., Albors, J. (2008). Innovation management techniques and tools: a review from theory and practice. R&D Management, vol. 38, no. 2, p. 113-127, DOI:10.1111/j.1467-9310.2008.00503.x.

T.M.B., González, F.J.M. (2002).

[22] Palacios, Assessing the validity of new product development techniques in Spanish firms. European Journal of Innovation Management, vol. 5, no. 2, p. 98-106, DOI:10.1108/14601060210428195.

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[23] Prasad, B. (2000). Converting computer-integrated manufacturing into an intelligent information system by combining CIM with concurrent engineering and knowledge management. Industrial Management and Data Systems, vol. 100, no. 7, p. 301-316, DOI:10.1108/02635570010349104.

[24] Bozickovic, R., Radosevic, M., Cosic, I., Sokovic, M., Rikalovic, A. (2012). Integration of simulation and lean tools in effective production systems – Case study. Strojniški vestnik – Journal of Mechanical Engineering, vol. 58, no. 11, p. 642-652, DOI:10.5545/ sv-jme.2012.387.

[25] Smew, W., Young, P., Geraghty, J. (2013). Supply chain analysis using simulation, Gaussian process modelling and optimisation. International Journal of Simulation Modelling, vol. 12, no. 3, p. 178-189, DOI:10.2507/ IJSIMM12(3)4.239.

[26] Scozzi, B., Garavelli, C. (2005). Methods for modelling and supporting innovation processes in SMEs. European Journal of Innovation Management, vol. 8, no. 1, p. 120-137, DOI:10.1108/14601060510578619.

[27] Liu, H.-C., Liu, L., Liu, N. (2013). Risk evaluation approaches in failure mode and effects analysis: A literature review. Expert systems with applications, vol.

40, no. 2, p. 828-838, DOI:10.1016/j.eswa.2012.08.010.

[28] Libutti, L. (2000). Building competitive skills in small and medium-sized enterprises through innovation management techniques: overview of an Italian experience. Journal of Information Science, vol. 26, no.

6, p. 413-419.

[29] Dermol, V., Drev, D. (2011). Inženirstvo in z njim povezani dejavniki tehnološkega razvoja (Engineering and Associated Factors of Technological Development).

Naše gospodarstvo (Our Economy), vol. 57, no. 5-6, p.

63-75.

Leber, M. – Bastič, M. – Buchmeister, B.

Strojniški vestnik - Journal of Mechanical Engineering 60(2014)6, 389-394 © 2014 Journal of Mechanical Engineering. All rights reserved.

DOI:10.5545/sv-jme.2013.1211

Received for review: 2013-05-16 Received revised form: 2013-10-04 Accepted for publication: 2013-11-29

Original Scientific Paper

Structure Formation of Hypereutectic Al-Si-Alloys Produced by Laser Surface Treatment Grigoriev, S.N. – Tarasova, T.V. – Gvozdeva, G.O. – Nowotny, S. Sergey Nikolaevich Grigoriev1 – Tatyana Vasilievna Tarasova1,* – – Galina Olegovna Gvozdeva1 – Steffen Nowotny2

1 Moscow

State University of Technology “STANKIN”, Russian Federation 2 Fraunhofer IWS, Germany

Using a coaxial laser cladding process AlSix (X=30, 40, 60) clad tracks were produced. The mechanisms of structure formation in Al-Si alloys during laser cladding were studied. Particle size distribution, surface morphology and microstructure of the initial powders were investigated.

The influence of the chemical composition of the powder material on the structure and the microhardness of the coating has been shown, as well as the influence of processing parameters on the microstructure and the geometry of the resulting tracks. Conclusions about the technological possibility of manufacturing single tracks with widths of < 500 µm based on an Al metallic matrix bearing a Si content ranging from 30 to 60 wt.% Si have been made.

Keywords: laser processing, Al-Si-alloys, laser cladding, powder metallurgy

0 INTRODUCTION Technologies used in modern industry must be flexible, energy efficient and, in particular, materialsaving. Additive manufacturing processes, such as selective laser melting [1] and [2] or directed material deposition [3] and [4], build up parts by adding materials layer-by-layer, using a CAD model [5]. These technologies use less material than conventional techniques; therefore, they are superior to alternative processes particularly for the generative manufacturing and the repair of the components on a micro-scale.

Laser surface cladding (LSC) is a material deposition process that uses a high-powered laser beam to melt the added material (usually in the form of a powder) and a thin layer of the substrate to form a coating on the surface. LSC via coaxial powder injection has found broad industry applications for wear protection materials [6]. New laser beam sources (disk laser) provide beam parameters that offer considerable potential for high precision cladding (weld track width < 1 mm).

Hypereutectic Al-Si alloys have found application in the manufacture of tools [7] and automotive engine components [8]. The wear resistance of these alloys increases with increasing of the Si content. However, the Si content is limited to 20 wt.% in conventional casting processes because of the formation of large primary Si particles (about 30 μm), which reduce the mechanical properties of these alloys. The LSC of AlSi alloys has attracted considerable interest in recent decades, because it leads to structure refining by rapid solidification [9]. However, all the experiments were based on specimens with a single track width about 3

to 5 mm. In the present work, the authors investigate the possibility of single track manufacturing with widths of < 500 µm, based on an Al metallic matrix bearing a Si content ranging from 30 to 60 wt.% Si. 1 EXPERIMENTAL METHODS AlSi-alloys powders with silicon content of 30, 40 and 60% (AlSi30, AlSi40 and AlSi60 respectively) obtained by gas-atomization were used as coating materials for the following reasons. Firstly, the primary Si particles may serve as hard reinforcements to metal matrix composites (MMC) and their size can be controlled by process treatment parameters.

Secondly, metal powders obtained via gas-atomization offer a perfectly spherical shape combined with a high cleanliness level. As will be shown below, these factors are essential for providing the desired level of technological properties. Substrates were cut from a rolled plate of commercial alloy (AA6060) with a nominal composition (wt.%): 0.35 to 0.6 Mg, 0.3 to 0.6 Si, 0.1 to 0.3 Fe, and Al in balance; their size is 50×30×10 mm³. To increase the absorption of the laser beam, the substrates were ground with 60-grit SiC paper and cleaned in acetone in an ultrasonic bath prior to cladding.

A continuous Yb:YAG 1kW disc laser was used for the coating deposition. The spot size of the laser beam on the surface of the substrate for cladding was 50 μm. Powders were injected through a coaxial nozzle. A coaxial jet of argon gas was used to protect the melt pool from contamination and oxidation.

The optimal shielding gas feed rate was determined experimentally and set at 5 l/min. Argon (Ar) was used as a carrier gas. The feed rate varied in from 2 to 10

*Corr. Author’s Address: Moscow State University of Technology, Lenin Hills, 1, GSP-1, Moscow, Russian Federation, science@stankin.ru

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l/min. The processing parameters varied from 150 to 250 W laser power, 800 to 900 mm/min beam speed, and 4 to 10 g/min powder feed rate. The symbols used for the study of the geometrical characteristics of the cladding track are shown in Fig. 1.

to the normal (or Gaussian) law distribution around a mean particle sized m = 45 to 55 μm.

Fig. 1. Cladding track diagram: b – clad track width; h - clad track height; s – clad track thickness; F1 –clad area; F2 – molten area (dilution γ= (F2 /(F1 +F2)) · 100%)

The particle size distribution of the investigated powders was determined with an OCCHIO 500nano microscope with integrated “Callisto” software used for statistical data processing. Phases of the initial powders were identified by X-ray diffraction analysis using an ALR X’TRA diffractometer equipped with “WinXRD 2.0-8с” software and the “ICDD PDF2” database of reference radiographs (2010). The radiation of copper anode (Cu Kα) was used for the conduction of measurements (capture mode: 30 mA, 40 kW).

The transverse sections of the clad tracks (in the plane perpendicular to the laser tracks) were cut for microstructural examinations. Powder samples for metallographic observation were cold-mounted and mechanically polished; a cross section was etched with Keller’s reagent. A Leica MEF4M standard optical microscope was employed for studying the microstructure of the powders and clad tracks. A VEGA 3 LM scanning electron microscope (SEM) equipped with energy dispersive X-ray analysis was used to investigate the chemical composition of the powders and clad tracks, as well powder surface morphology.

2 RESEARCH RESULTS AND DISCUSSION 2.1 The Research of Powder Materials AlSi30, AlSi40 and AlSi60 Fig. 2 presents the cumulative frequency distribution of the AlSi30 powder particle size. It was determined that, for the powders of all studied compositions, particle size distribution was similar and corresponded 390

Fig. 2. Cumulative frequency distribution of AlSi30 powder particle size Table 1. Chemical composition (at. %) of AlSix powders Chemical element AlSi30 AlSi40 AlSi60

Al 66.5 to 67.0 55.5 to 56.0 32.5 to 33.0

Si 33.5 to 33.0 44.5 to 44.0 67.5 to 67.0

The AlSix (X = 30, 40, 60) powder particles have a high index of circularity (average values are 69.6; 59.3; 71.8% respectively) and low values of roughness (mean values were 3.3; 4.6; 1.7%, respectively). The average chemical composition of the investigated powders is presented in Table 1.

Fig. 3 shows a typical surface of gas-atomized powders. The powder particles have a globular shape with a dendritic surface. The dendritic morphology corresponds to eutectic silicon [10]. The primary and eutectic Si are fine and homogeneously distributed in the Al matrix (Fig. 4). The size and shape of primary Si particles change as the silicon content in the initial powders increases, from the regular polygon (size about 1 to 5 µm) to a branched structure with high aspect ratio (size 10×30 µm). The comparison of X-ray diffraction patterns of AlSi30, AlSi40 and AlSi60 (Fig. 5, for example, for AlSi30) and reference

Grigoriev, S.N. – Tarasova, T.V. – Gvozdeva, G.O. – Nowotny, S.

Strojniški vestnik - Journal of Mechanical Engineering 60(2014)6, 389-394

diffraction patterns from the “Pdf-2” database (2010) showed that samples AlSi30, AlSi40 and AlSi60 are two-phase and contain 33, 44 and 67% wt. Si, respectively, which is consistent with the results of the chemical analysis.

Fig. 3. Morphology of the AlSi30 powder particle

AlSi30

AlSi40

AlSi60

Fig. 4. Microstructure of powders with different silicon content

Fig. 5. Diffraction pattern of AlSi30 powder

2.2 The influence of the chemical composition of the powder material on the structure and microhardness of the coating Fig. 6 presents the microstructure of laser clad tracks as a function of silicon content. A large amount of primary silicon particles is observed over the entire

cross sections of the clad tracks. It is noteworthy that the primary Si particles significantly increase in size with increasing silicon content. All clad tracks consist of primary Si crystals surrounded by α-Al halos and Al/Si eutectic mixing. This non-equilibrium structure was observed in other studies [11]. The Si particles nucleate from the liquid via a heterogeneous mechanism and grow in the undercooled melt. When local concentration of the melt is sufficient, the α-Al phase nucleates. The growth of the α-Al halos results in an increasing Si content of the remaining liquid phase that leads to the eutectic phase formation. The size of the Si particles is a consequence of their local nucleation and growth conditions. Previous studies [12] and [13] have shown that the molten hypereutectic Al-Si alloys are inhomogeneous at the temperature well above the liquidus. The high cooling rates (typical for the laser cladding) lead to a significant suppression of the diffusion processes. Therefore, large Si particles in the Al-Si alloys with a high Sicontent can increase the inhomogeneity of the molten alloy. It can be expected that this inhomogeneity influences the solidification structure of hypereutectic Al-Si alloys, i.e. the size of the primary Si particle increases with silicon content in alloy from value < 1 µm when using an AlSi30 alloy to 30 µm when using an AlSi60 alloy.

Microstructural examination showed that with the silicon content of 30% the primary Si particles are extremely fine, and it is impossible to distinguish primary Si and eutectic Si in the coating (Fig. 6a).

With a silicon content of 60% in the alloy structure, the interlayer of aluminum matrix becomes so much thinner that it is accompanied by a degradation of the mechanical properties [14].

A change in the primary silicon particles shape is also observed with increasing Si content in the initial powders: from a regular polygon for the AlSi30 alloy to a branched structure with a high aspect ratio for the AlSi60 alloy (Fig. 6).

In order to examine technological properties of the AlSix powders, single tracks were produced with a high laser power (P = 400 W), which resulted in an increase in size of the tracks and in dilution with the substrate. Fig. 7 shows the change in the surface morphology of single tracks with increasing silicon content. That many adherent particles can be observed on the coarser track surface in case of the AlSix (X = 40, 60) powders was shown. It was found that the smooth surface of a single track can be fabricated only with the AlSi30 powder.

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alloy: from HV0.05 190 down to HV0.05 80. The hardness of the AlSi40 and AlSi60 coating alloys is constant in the coating region and equal to about HV0.05 180. Some fluctuations on the AlSi40 and AlSi60 hardness profiles are caused by the presence of the larger Si particles than that of AlSi30 alloy, where the hardness curve is gradual. Hardness distribution in the lateral direction of the laser clad tracks is nearly constant. The insignificant difference in the hardness level on the AlSix coatings is explained by presence of the supersaturated solid solution of silicon in aluminum in the case of AlSi30, which takes place at high cooling rates [15] and is consistent with the other studies results [11], [16] and [17].

Due to its superior technological property and sufficient hardness, AlSi30 powder was selected for the further investigations.

a)

b)

Fig. 8. Microhardness distribution of laser cladding produced from alloys with different Si-content (P=400 W, v=800 mm/min, Pm=1 g/min)

c) Fig. 6. Microstructure of alloys with increasing silicon content [%]: а 30; b 40; c 60 (P=200 W, v=800 mm/min, Pm=10 g/min)

Fig. 7. Change in the surface morphology of single track with silicon content in initial powders (P = 400 W, v = 800 mm/min, Pm = 1 g/min)

A hardness profile of the AlSix tracks is presented in Fig. 8. It is interesting to note that the Si content in the initial powders does not influence the maximal hardness level. A gradual hardness distribution from the surface to their substrate is observed for AlSi30 392

2.3 The Influence of Processing Parameters on the Structure of the Cladding Tracks The main parameters of laser cladding that have a significant impact on the structure and properties of the resulting tracks are laser power, beam-scanning speed, and powder feed rate.

The influence of laser power and powder feed rate on the cladding structure is expressed in dilution change. Dilution with the substrate decreases with increases in the powder feed rate and decreases in the laser power. This leads to the larger amount of Si in the alloy structure. Finally, this results in the formation of the larger primary Si particles. The beam speed influences the distribution of Si particles. The difference in Si particle size between the top and the bottom of the clad tracks increases with increases of beam speed. The combination of laser power decreasing and beam speed increasing results in larger primary silicon particles in the clad bottom, which can lead to the formation of a sharp interface between the

Grigoriev, S.N. – Tarasova, T.V. – Gvozdeva, G.O. – Nowotny, S.

Strojniški vestnik - Journal of Mechanical Engineering 60(2014)6, 389-394

coating and the substrate, which is often a potential source of weakness (Fig. 8).

the powder feed rate in the range of 4 to 10 g/min at laser power P = 200 W and scanning speed v = 800 mm/min, while the width of the track varies slightly.

This is due to the increase of particle flow density and the decrease of direct substrate exposure to the laser beam.

Table 4. Clad track geometry variation vs. powder feed rate (P = 200 W, v = 800 mm/min) Pm [g/min] 4 7 10

Fig. 8. Optical micrographs of AlSi30 clad track at 150 W laser power, 900 mm/min beam speed and 10 g/min powder feed rate

2.4. The Influence of Processing Parameters on the Geometric Characteristics of the Cladding Tracks The influence of the process parameters on the geometric characteristics of the cladding tracks was investigated (the data are given in Tables 2 to 4). It was found that laser power is the main parameter of the laser cladding process that influences the formation of single tracks. The width of the clad track and dilution with the substrate are continuously increasing with the increase of the laser power (Table 2). The change of tracks height caused by the change of the laser power is insignificant.

Table 2. Clad track geometry variation vs. laser power (v = 800 mm/min, Pm = 10 g/min) P [W] 150 200 250

b [μm] 132 156 213

h [μm] 77 59 61.5

γ [%] 37.6 42.9 59

Beam speed variation in the range of 800 to 900 mm/min does not exert an obvious influence on the clad track geometry (Table 3). However, dilution with the substrate decreases with increasing of the beam speed.

Table 3. Clad track geometry variation vs. beam speed (P = 150 W, Pm = 10 g/min) v [mm/min] 800 850 900

b [μm] 132 120 118

h [μm] 77 81 64

γ [%] 37.6 27.1 22.7

The clad tracks’ height increases and dilution with the substrate continuously decreases with increases of

b [μm] 128 130 156

h [μm] 9.4 20.8 59

γ [%] 89 64.5 42.9

3 CONCLUSIONS 1. Powders AlSi30, AlSi40 and AlSi60 meet the requirements for materials for coaxial laser cladding because they have a good flowability (mean sphericity is equal to 66.9%; mean roughness ranges from 1.7 to 4.6%) and provide the ability to obtain a single track on a microscale (particle size varies from 22.5 mm to 67 mm; the mean diameter is 45.6 mm).

2. Using a coaxial laser cladding process, AlSix clad tracks with lateral resolution of < 500 μm were produced. The coatings consist of silicon primary particles surrounded by α-Al halos and Al/Si eutectic mixing.

3. Si content in the initial powders does not influence on the maximal hardness level in the coating, which is equal to 190 HV0.05 for the powders of all investigated chemical compositions.

4. The larger primary Si-particles were formed in the coating structure with increases of the powder feed rate and decreasing the laser power. The difference in Si-particle size between the top and the bottom of the AlSix (X = 40, 60%) clad tracks increases with increasing beam speed.

The primary Si particles in the case AlSi30 are extremely fine, and it is impossible to distinguish primary Si and eutectic Si in the coating.

5. The width of the clad track and dilution with the substrate continuously increase with the increase of the laser power. The change of tracks height caused by the change of the laser power is insignificant.

6. The clad tracks height increases and dilution with the substrate continuously decreases with increasing of the powder feed rate in the range of 4 to 10 g/min at a radiation power P = 200 W and a scanning speed of v = 800 mm/min, while the width of the track varies slightly.

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4 ACKNOWLEDGEMENT This work was supported by the Ministry of Education and Science of the Russian Federation within the state task in the sphere of scientific activity. Experiments on the laser cladding were conducted at the Fraunhofer Institute for Material and Beam Technology.

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Grigoriev, S.N. – Tarasova, T.V. – Gvozdeva, G.O. – Nowotny, S.

Strojniški vestnik - Journal of Mechanical Engineering 60(2014)6, 395-406 © 2014 Journal of Mechanical Engineering. All rights reserved.

DOI:10.5545/sv-jme.2013.1383

Original Scientific Paper

Received for review: 2013-08-16 Received revised form: 2013-12-13 Accepted for publication: 2014-01-17

Optimization of the Energy Efficiency of a Piston Compressed Air Engine Yu, Q. – Cai, M. – Shi, Y. – Fan, Z. Qihui Yu – Maolin Cai – Yan Shi* – Zichuan Fan

Beihang University, School of Automation Science and Electrical Engineering, China To improve the energy efficiency and output power of the piston compressed air engine (CAE), a mathematical model of its working process was set up. With the use of the MATLAB/Simulink software for simulation, the influences of the bore-to-stroke ratio, intake pressure and valve lift on the performance of the engine were obtained for the analysis of the energy efficiency and the output power. Moreover, to optimize the energy efficiency of the engine with the given output power, an improved NSGA-II was introduced, and a series of optimization intake pressures and valve lifts was obtained. When the output power value is about 2 kW, the intake pressure and the intake valve lift can be set to 1.99 MPa and 9.99 mm, the energy efficiency is highest: 31.17%. Finally, that the improved NSGA-II is superior to NSGA-II in proximity and diversity has been proved. This research can be referred in the optimization of the piston CAE and provides a method for the energy efficiency optimization study.

Keywords: compressed air engine, optimization, energy efficiency, improved NSGA-II algorithm

0 INTRODUCTION The burning of fossil fuels has been recognized as the main cause of serious environmental issues, including the greenhouse effect, ozone layer depletion and acid rain [1]. Renewable fuels, such as wind, solar, compressed air, etc., are used as obvious solutions [2]. With respect to environmental protection, Shafiee and Topal believe that oil and gas reserves may be diminished in 2042; this enhances the competition in the field of renewable energy vehicles [3]. Because of its low cost, safe maintenance, easy access, recyclability, higher energy storage density and long lifespan, compressed air energy storage will be an advanced and rapidly developing field in the future. The flow characteristics of compressed air in equipment have been studied [4] to [6].

As important equipment in the compressed air energy storage system, the compressed air engine (CAE) is utilized to convert the energy stored as compressed air into mechanical energy. Furthermore, the CAE has been used in many fields, e.g. pneumatic systems, vehicles, cryogenic engineering, and vacuum machinery. At the beginning of the 20th century, the CAE began to be used to power mining locomotives in the United States and Europe [7]. However, the energy efficiency and output power of the CAE are limited, which restricts its application and popularization [8].

To improve energy the efficiency and output power of CAE, Motor Development International (MDI), a banner company in the field of CAE, has developed a set of novel CAEs over the previous ten years [9]. Ahmed proposed that steam be replaced by double-acting steam, and the reciprocating motion of the piston be governed through flywheel using

a solenoid valve [10]. Maghoub and Craighead developed the idea of controlling the gas inlet and outlet of the piston-type pneumatic motor to meet the requirements of driven components by either a PID or H-bridge control method [11]. Huang et al. put forward a hybrid pneumatic-power system that was able to ensure that the internal-combustion engine could work at its optimal condition [12]. Pirc et al. presented a universal model to analyses the energy system in full detail [13]. Dovjak et al. analysed energy use for the cooling environment [14]. Hammadi et al. used a sequentially coupled approach to optimize power modules [15]. In order to investigate the design method of the CAE, multi-objective optimization was used to obtain the relation of maximum specific work with engine power and engine structure parameters [16].

However, thus far, all the studies on the CAE have been based on the analysis of certain parameters, so it is difficult to maintain the CAE working at optimized conditions with load variation.

In this paper, firstly, based on the working principles of the piston CAE, a mathematical model was established. Next, through the simulation analysis, the influences of the bore-to-stroke ratio, intake pressure and valve lift on the performance of the engine were obtained. Finally, an improved NSGA-II algorithm was introduced to the optimization study on the piston CAE. This research can be referred to in the design optimization of the piston CAE and provided a method for the optimization study.

*Corr. Author’s Address: Beihang University, School of Automation Science and Electrical Engineering XueYuan Road No.37, Beijing, China, yesoyou@gmail.com

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1 WORKING PRINCIPLES OF THE PISTON CAE

Flywheel

As shown in Fig. 1, the piston CAE consists of an intake valve, an exhaust valve, a piston, a cylinder, a link, and a crank. It is obvious that working process of the piston CAE is a thermodynamic process composed of the intake and the exhaust processes.

1. The intake process: when piston reaches its top dead centre (TDC), the intake valve opens at the beginning of the engine cycle, the compressed air flows into the cylinder, and the intake valve closes entirely at the crank angle of 100°, leaving 80° for isentropic expansion. During this process, the exhaust valve stays closed, and the piston is pushed from the top dead centre (TDC) toward the bottom dead centre (BDC) by the charged compressed air, producing the power stroke.

The downward movement of piston produces work while the compressed air flows into the cylinder during the intake process, and even after the intake valve closes during the isentropic expansion process [17].

2. The exhaust process: The exhaust valve opens when the piston reaches the BDC. During the process, the intake valve remains closed. The piston moves from the BDC toward the TDC to discharge the compressed air from the cylinder.

The cylinder pressure during the exhaust process is always greater than the ambient pressure to facilitate discharging.

Piston Link Crank shaft

a)

396

+

h1G1 dV uG ]. − pc − dϕ ω ω

(1)

Q

p,θ ,V , G , u

cylinder

W

β link ω

ϕ

crank

b) Fig. 1. The thermodynamic analysis diagram of the compressed air engine; a) structure of the piston CAE, b) configuration of the piston CAE

2.1 Mathematical Modelling of the Piston CAE

exhaust valve G2 , p2 ,θ 2 , h2

intake valve G1 , p1 ,θ1 , h1

piston

2 MODELLING AND SIMULATION OF THE PISTON CAE

The engine cylinder can be considered to be a thermodynamic system that is composed of a cylinder cover, piston head and cylinder wall; to facilitate this research, the following assumptions were made: 1. The working fluid (air) of the system follows all ideal gas laws.

2. There is no leakage in the working process.

3. The flow of air moving into and out of the cylinder is a stable one-dimensional flow.

4. The viscous friction force on the piston of the compressed air engine is neglected.

The energy equation can be illustrated by the following equation: 1 α S (ϕ )(θ a − θ ) hG2 dθ = [ − + dϕ mCv ω ω

Exhaust valve

Intake valve

The full mathematical process about Eq. (1) can be obtained in Appendix A. Assuming that the compressed air velocity is proportional to the average piston speed UP, and heat transfer coefficient a can be expressed by the following equation [18]:

 4V p RDS  a = 0.1129    π 

− 0.2 3

p 0.8U 0p.8θ −0.594 , (2)

1/ 3

 4V p RDS  Up =   π 

⋅ n / 30. (3)

From the law of mass conservation, air mass can be given as:

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dm = G. (4) dt

The flow equation for the air flow through a restriction can be written as follows [19] and [20]: k   when, pL ≤  2  k −1    pH  k + 1   k +1  k  2  k −1  Ap  H Rθ  k + 1  H  . (5) G= k  p 2  k −1  when, L >   pH  k + 1    k +1   p 2  p 2k ( L ) k − ( L ) k   ApH pH (k − 1) Rθ H  pH   

Where the subscripts H and L stand for the upstream and downstream of the compressed air, respectively. The adiabatic exponent κ was set to 1.4.

The intake valve and exhaust effective areas are dependent on the cam profile, which can be expressed by the following equation:    hv πhv cos γ d f + sin 2γ  hv ≤ 0.31 d f   2 A =  . (6)  π 2 2  d f -d v hv > 0.31 d f  4

(

)

π V p [1 − cos ϕ + 2

   1  + (1 − 1 − λ 2 sin 2 (ϕ ))]  λ   dV (ϕ ) π λ sin ϕ cos ϕ     = V p sin ϕ + 2 2 dϕ 2    . (7) λ sin ( ϕ ) 1 −   2/3 2 1/ 3   4 V R 16 V π  p DS  π p    S (ϕ ) =  + ×   2 π 2  π 2 RDS    1   2 2 × 1 − cos ϕ + 1 − 1 − λ sin (ϕ )   λ  

V (ϕ ) = Vc +

(

)

The structure equation and motion equation can be given by the following equations: The full mathematical process of Eq. (7) can be obtained in Appendix B. The state equation can be illustrated by the following equation:

pcVc = mc Rθ c . (8)

Thereafter, the objectives and comparisons are made with energy efficiency and output power, whose definitions are summarized as following equations:

η=

W , (9) psVs ln ps pa

Pe =

Te ⋅ n ⋅ 30 , (10) 9550 ⋅ π

where

Te =

∫ pdV . (11) 2π

2.2 Simulation Research of the Piston CAE From the discussion above, it can be found that working characteristics of the engine are determined by 13 parameters as mentioned above. The initial values of the 13 parameters are shown in Table 1, bore-to-stroke ratio, valve lift, intake pressure are variables. Simulation were performed using the software MATLAB. Table 1. Engine specifications Parameter Intake pressure (single-cylinder) Atmosphere pressure The clearance volume Intake valve open Intake valve close Intake valve lift Exhaust valve lift Exhaust valve open Exhaust valve close Bore-to-stroke Displaced volume Cylinder wall temperature Engine speed

Value 1,000,000 Pa 100,000 Pa 3e–5 m³ 0° 100° 6 mm 8 mm 180° 300° 1 100 ml 293 K 800 rpm

2.3 Gas state Variations of the Cylinder The main dynamic characteristics of the CAE were obtained by analysing the mathematical model using MATLAB/Simulink. The pressure, mass flow and temperature curves of compressed air in the cylinder can be shown in Figs. 2a to c, respectively.

As shown in Fig. 2, the characteristics of the piston compressed air engine change periodically.

When the piston reaches its TDC and the intake valve open is set to a 0° crank angle, compressed air rapidly flows into the cylinder, after the top of air mass flow, there is a substantial decrease, and a

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slight increase follows. Meanwhile, the pressure of the cylinder rapidly increases to the intake pressure, after a slight decrease, the pressure of the cylinder drops dramatically. At this time, because of expansion of the compressed air in the cylinder, the temperature of the cylinder drops from its peak.

a)

expansion, the compressed air in the cylinder keeps driving the piston until the piston arrives to its BDC. Meanwhile, the pressure and temperature of the cylinder drops dramatically.

When the piston reaches its BDC and the outtake valve opens at a 180° crank angle, the compressed air is discharged from the cylinder, and the mass flow decreases from its top. Meanwhile, the pressure and temperature of the cylinder drops to their lowest levels.

When the piston leaves its BDC and the outtake valve is closed at a 300° crank angle, compressed air stops being discharged from the cylinder, so the mass flow of compressed air drops to zero. Depending on the inertia of the flywheel, the piston compresses the air in the cylinder, then the pressure and temperature of the cylinder increase slowly.

The engine revolves and repeats the process discussed above; mechanical power can be output continuously.

From Fig. 2c, it is obvious that the temperature of the cylinder can reach 231 K, which may ice up in cool, moist climates, so a heat exchanger must be used.

2.3.1 Influences of the Bore-to-Stroke Ratio

b)

c) Fig. 2. Simulation curves of the cylinder; a) pressure; b) mass flow; and c) temperature

When the piston leaves its TDC and the intake valve is closed at a 100° crank angle, compressed air stops flowing into the cylinder, so the mass flow of compressed air drops to zero. Depending on its 398

The bore-to-stroke ratio, as one of the main geometrical parameter, plays the most prominent role on performance of the piston CAE. The output power and the energy efficiency of the compressed air engine were obtained at various bore-to-strokes ratios.

The relationship of the performance (i.e. output torque power, Pe, and energy efficiency, η) and the bore-to-stroke ratio of the engine are shown in Fig. 3.

When the bore-to-stroke ratio is smaller than 1, the output power and the energy efficiency increase sharply to 0.8761 kW and 40.25%, respectively, with an increase in the bore-to-stroke ratio. When the boreto-stroke ratio is greater than 1, the output power and the energy efficiency increase slowly with an increase in the bore-to-stroke ratio.

This is because the output power and the energy efficiency are determined by the volume of the cylinder. Therefore, under the given operating conditions, the larger bore-to-stroke ratio can increase the power output and energy efficiency of the piston CAE.

Yu, Q. – Cai, M. – Shi, Y. – Fan, Z.

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2.3.2 Influences of the Intake Pressure Intake pressure is an critical parameter, which determines the air mass flow of the engine, and is vital for improving the performance of the engine.

For the CAE, the intake pressure can be adjusted according to the loading system. The influence of the intake pressure on the performance of the engine can be obtained through simulation and analysis, and the influence of the intake pressure on the energy efficiency and the output power can be described in Fig. 4.

As shown in Fig. 4, with an increase in the intake pressure, the output power increases; however, the energy efficiency decreases. Thus, a higher intake pressure can increase the output power of the piston CAE, but decrease the energy efficiency of the piston CAE. That is because the compressed air in the cylinder cannot expand sufficiently.

a)

2.3.2 Influences of the Valve Lift b) Fig. 3. a) Output power and b) energy efficiency of the CAE at different bore-to-stroke ratio

a)

The valve lift is another important parameter that greatly affects the air mass flow. The influence of the valve lift on the energy efficiency and the output power can be illustrated in Fig. 5.

a)

b) Fig. 4. The output power and the energy efficiency of the CAE at different intake pressure

b)

Fig. 5. The output power and the energy efficiency of the CAE at different intake valve lift

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As shown in Fig. 5, with an increase in the valve lift, the output power increases; however, the energy efficiency decreases. So, a bigger valve lift can increase the output power of the piston CAE, but decrease the energy efficiency of the piston CAE. That is also because the compressed air in the cylinder cannot expand sufficiently.

3 MULTI-OBJECTIVE OPTIMIZATION BY IMPROVED NSGA-II In real operations, the performance of the engine needs to be adjusted to cope with demands of the loading system. To achieve a given output power and high energy efficiency, the intake pressure and the valve lift can be optimized, which is a typical multiobjective engineering optimization.

In this paper, two optimization objectives, higher output power and higher energy efficiency, have been considered. As discussed above, it is obvious that the energy efficiency decreases with the increase of the output power. The objectives in this paper is to maximize the output power and the energy efficiency, so a single optimization solution will not serve this purpose, as these objectives are conflicted in nature.

Furthermore, the output power of the engine depends on its speeds and road conditions. As a conclusion, the performance optimization of the engine requires a multi-objective optimization.

where, P[i]dis is the crowding distance of individual i, P[i]·f is the function value of the individual i with the sub-goal f ; The calculation method above fails to maintain good diversity from Eq. (12). Some poor diversity individuals may be kept. The problem can be expressed by Fig. 6.

As shown in Fig. 6, the crowding distance of individual b and c is small, but both b and c are relatively far away from the other individuals. If the crowding distance of individual b and c is calculated with NSGA-II method, both individual b and c will be reserved, or both are eliminated. However, in the improved NSGA-II method, either individual b or c is reserved. In the same case, individual e, f and g are eliminated with NSGA-II method. However, these individuals are useful in diversity. Therefore, the NSGA-II plays a significant role in calculating the crowding distance. f2

a b

d

3.1 The Improved NSGA-II

P[i ]dis = ( P[i + 1] ⋅ f 1 − P[i − 1] ⋅ f 1) + 400

e f

The genetic algorithm (GA) is a powerful, general-purpose optimization tool, widely used to solve optimizing problems in the mathematics, engineering, etc. GA works with a range of feasible solutions; therefore, it can be used in multi-objective optimization problems to obtain a number of solutions simultaneously. NSGA-II, proposed by Kalyanmoy, is a fast and state-of-the-art multi-objective GA [21].

The crossover and mutation operators remain as usual, but selection operator works differently from that of a simple GA. Selection is done with the help of a crowded-comparison operator, based on ranking (according to non-domination level), and crowding distance. The crowding distance is briefly explained below [22].

The crowding distance is crucial to population selection. The individuals are selected based on the rank and the crowding distance. The crowding distance can be calculated by following equations:

c

+( P[i + 1] ⋅ f 2 − P[i − 1] ⋅ f 2), (12)

g

h

f1 Fig. 6. The deficiency of NSGA

To guarantee a good diversity of the individual point, the following questions must be solved.

1. What is the definition of the threshold value about adjacent individuals?.

2. Which individual is selected when the adjacent individual distance is less than the threshold value?

Firstly, the minimum and the maximum extreme endpoints are found in current elitist sorting. Then the distance of the two extreme end points are calculated which indicated by dmax. The threshold value can be written by:

δ=

d max , (13) 2 × num

where, num is the number of individual.

The threshold individual selection can be shown in Fig. 7.

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Strojniški vestnik - Journal of Mechanical Engineering 60(2014)6, 395-406

f2

3.2 Optimization of the Piston CAE Performance Using the Improved NSGA-II

0

c a

b

e d n

f1 Fig. 7. The crowding distance calculation and individual selection

As shown in Fig. 7, if the Euclidian distance between the individual a or b is less than or equal to the threshold value, adjacent individual c and d are found, and the centre point e, between c and d, can be obtained. If the distance between a and e is less than e and b, the individual b is deleted.

3.3 Results and Analysis In this paper, the objectives are to maximize the output power and the energy efficiency. However, the NSGA-II algorithm is used to calculate the minimization of the inverse of the output power and the energy efficiency. Thus, in order to convert the two objectives to minimization, the functions should be modified, which are given below.

Initialize population intake pressure and intake valve lift

Generation=1

Fitness value by simulation model

Sorting based on crowding distance comparison operator Selection, Crossover and Mutation create offspring

Combined Population

Simulation model

Chose Population based on crowded comparison operator

Generation>Max Generation

To optimize the piston CAE with the improved NSGA-II, the fitness value and the objective function values should first be provided.

Therefore, there is a need for a function or equation, which relates the decision variable with the objective. In the present study, objectives are maximization of the output power and energy efficiency. Because the bore-to-stroke ratio and the valve timing are constant values in the CAE-operated piston, the decision variables are the intake pressure and the intake valve lift. Based on the improved NSGA-II algorithm, the relationship of the objectives and the decision variables can be obtained through analysis and simulation of the mathematical model using MATLAB/Simulink.

The flow chart of the improved NSGA-II is shown in Fig. 8.

No

Yes

End

Fig. 8. Flow chart of parameters optimization process based on NSGA-II

Objective 1 = –Pe . (14)

Objective 2 = –η . (15)

The range and the step length of the two decision variables (i.e. the intake pressure and the intake valve) are different.

In this paper, the range of the intake pressure is between 1 and 3 MPa; the range of the intake valve lift is between 3 and 10mm.

Initially, the individuals are created randomly in the certain range. An initial size of 50 populations is chosen. Two-point crossover and bitwise mutation have been used with a crossover probability (pc = 0.9) and mutation probability (pm = 0.08). Objective values are calculated from the simulation model as described in Section 2. Rank and sorting of solutions have been done as it is mentioned in the NSGA-II algorithm [23].

The crowding distance of solutions has been done with the improve NSGA-II algorithm. The corresponding objective function values and the decision variables of these non-dominated solution set are given in Table 3.

From Table 3, when the output power value is about

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Table 3. Optimal combination of parameters Solution No. 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50

402

Intake valve Intake Energy Output lift [mm] pressure [MPa] efficiency [%] power [kW] 10 3 27.74751 3.211623 8.5478802 1 38.96734 0.946822 9.9431132 1.917673 31.52734 1.993636 10 2.863532 28.10521 3.058173 9.9997962 2.991168 27.77281 3.201505 10 2.985675 27.78668 3.195049 9.9078591 2.714702 28.52115 2.888402 9.699271 1.306782 35.56081 1.303572 9.9297642 1.911494 31.55969 1.986411 10 2.17895 30.3583 2.288059 9.4499517 2.266745 30.02908 2.374782 9.9772842 2.49371 29.20234 2.641665 9.4925149 1.239833 36.19001 1.225848 9.7349878 1.776188 32.27323 1.830979 9.8016439 2.43028 29.42342 2.5665 9.9911639 2.530873 29.0855 2.684099 9.2789913 2.41843 29.48782 2.540333 9.456174 2.309249 29.87085 2.423005 9.99097 2.580417 28.92445 2.739475 9.8930414 1.608644 33.26752 1.645136 9.9905225 1.99207 31.16623 2.078036 9.9074163 1.665011 32.91191 1.708604 9.9896744 1.990353 31.17363 2.076008 9.6340991 1.411081 34.70321 1.419902 9.6020143 1.187974 36.70408 1.168968 9.6486727 1.582179 33.44675 1.611695 9.4970056 1.30351 35.60395 1.297214 9.2848868 1.13589 37.27776 1.106954 9.9956906 2.824939 28.20759 3.014164 9.6848885 1.362328 35.09101 1.365723 9.9765874 2.059843 30.86507 2.154141 10 2.057104 30.87317 2.151364 9.6258029 1.445649 34.42779 1.458293 9.2465682 2.409115 29.51477 2.529041 9.9956833 2.82229 28.21644 3.011611 9.9033288 1.6554 32.96986 1.697816 9.6850463 1.361491 35.09697 1.364616 9.9889066 2.610964 28.82987 2.773785 9.9953157 2.763197 28.38462 2.945189 9.306671 1.545281 33.71495 1.565099 9.3060582 1.541313 33.74159 1.560635 9.9678352 2.1387 30.52148 2.242348 9.2916736 1.085916 37.84915 1.051128 9.2880712 1.207297 36.51947 1.186901 9.5769537 1.121414 37.42706 1.093994 9.9905176 2.577939 28.93141 2.736659 9.4137469 2.349895 29.72476 2.46748 9.4588273 2.307429 29.87327 2.420431 9.4950968 1.01296 38.75124 0.971522 9.6465629 1.482105 34.14948 1.499429

2 kW, the intake pressure and the intake valve lift can be set 1.99 MPa and 9.99 mm respectively, the energy efficiency is highest at 31.17%.

The non-dominated solution set, obtained over the entire optimization procedure, is shown in Fig. 9.

It is obvious that the formation of the Pareto-optimal front determines the final set of solutions. Since none of the solutions in the Pareto-optimal front is absolutely better than any others, anyone of them is an acceptable solution. The best choice of one solution is determined by the requirement output. From optimal combination of parameters in Table 3, the intake valve lifts value distribute from 9 to 10 mm, while the intake pressure value varies between the maximum value and minimum value. Therefore, regulating intake pressure is a major method to meet variable speeds and road conditions. Appropriate adjustment of the intake valve lift can improve energy efficiency.

Fig. 9. Improved NSGA-II Pareto-optimal set

To validate the performance of the improved NSGA-II, Generational Distance (GD) is introduced to estimate the algorithm convergence performance [23]:

GD =

1 popsize

popsize

∑ i=1

di2 , (16)

where, popsize is the number of vectors in the set of non-dominated solutions found thus far, di is the Euclidean distance (measured in objective space) between each of the nearest member of the Paretooptimal set. It is clear that when the value of GD is 0, all the elements generated are in the Pareto-optimal set. Therefore, any other values will indicate how “far” we are from the global Pareto front of our problem.

Schott [24] proposed a metric to measure the range variance of neighbouring vectors in the nondominated vectors. The metric is defined as:

Yu, Q. – Cai, M. – Shi, Y. – Fan, Z.

SP =

1 popsize d − di ∑ i popsize − 1 =1

(

)

2

, (17)

Strojniški vestnik - Journal of Mechanical Engineering 60(2014)6, 395-406

where,  f1i ( x) − f1 j ( x)   , (i, j = 1, 2,..., n), (18) di = min j   + f i ( x) − f j ( x)  2  2  d is the mean of the crowding distance.

In the same situation, the performance of the improved NSGA-II had been compared with the NSGA-II by the use of evaluating indicators above.

The result is shown in Table 4.

1.99 MPa and 9.99 mm respectively, the energy efficiency is highest, 31.17%.

This research can be referred in the optimization of the piston CAE and provided a method for the optimization study.

5 ACKNOWLEDGMENT The research work presented in this paper is financially supported by a Grant (51205008) of the National Natural Science Foundation of China.

6 APPENDIX A

Table 4. Performance compared NSGA-II Improved NSGA-II

GD 0.029876 0.022276

SP 0.31241 0.17367

It is obvious that the improved NSGA-II is superior to NSGA-II in proximity and diversity.

4 CONCLUSIONS In this paper, a mathematical model of the working process of the piston CAE was proposed. The working characteristics of the piston compressed air engine were obtained. To achieve the given output power and optimization energy efficiency of the CAE, the improved NSGA-II method was introduced, and the influences of the bore-to-stroke ratio, intake pressure and valve lift on the performance of the engine were obtained. The conclusions are summarized as follows: 1. The improved NSGA-II can be used in the optimization of the piston engine, and it is superior to NSGA-II in proximity and diversity.

2. When the bore-to-stroke ratio is smaller than 1, the output power and the energy efficiency increase sharply to 0.8761 kW and 40.25% respectively, with an increase in the bore-tostroke ratio. When the bore-to-stroke ratio is greater than 1, the output power and the energy efficiency increase slowly with an increase in the bore-to-stroke ratio.

3. With an increase in the intake pressure or the valve lift, the output power increases, however the energy efficiency decreases. However, regulating intake pressure is a major method to meet variable speeds and road conditions, appropriate adjustment of the intake valve lift can improve energy efficiency.

4. When the output power value is about 2 kW, the intake pressure and the intake valve lift can be set

According to the first law of thermodynamics, the energy equation can be expressed as:

δ m2 δ m δW dU δ Q + h1 1 − . (A1) = − h2 dt dt dt dt dt

The heat capacity of the engine body made of metal is much greater than that of the air, so the temperature of the internal walls can be considered to be constant. The heat transfer is:

δ Q dt = α S (ϕ )∆θ = α S (ϕ )(θ a − θ )). (A2)

The internal energy of gas can be expressed as:

dU = d (mu ) = mdu + udm. (A3) For ideal air, it can be yielded as: du = Cv dθ . (A4)

Substituting Eq. (A4) to Eq. (A3) yields:

by:

dU = mCv dθ + udm. (A5) The work done by the compressed air is described dW = pc dV . (A6)

Substituting Eq. (A2) to (A6) into Eq. (A1) yields: 1 dθ = [aS (ϕ )(θ a − θ ) − hG2 + dt mCv

+ h1G1 − pc

dV − uG ], dt

(A7)

where, δ m1 δ m2 dm = G1 , = G2 , h2 = h, G = . dt dt dt

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by:

The relationship time and angle can be described

ω = dϕ dt . (A8) Substituting Eq. (A.8) into Eq. (A.7) yields: 1 α S (ϕ )(θ a − θ ) hG2 dθ = [ − + dϕ mCv ω ω +

h1G1 dV uG ]. − pc − dϕ ω ω

Substituting Eq. (B3) and (B6) into Eq. (B5) yields: V (ϕ ) = Vc +

where

(A9)

The total heat transfer area, S(φ) , is described by: S (ϕ ) = Ah + Ap + π Dy, (B9)

where, Ah is the heat transfer area of cylinder head, Ap is the heat transfer area of the piston.

In there,

7 APPENDIX B Fig. 10 shows the piston-crank mechanism.

piston

L

TDC

S (ϕ ) =

The bore-to-stroke ratio is expressed as:

From the piston-crank geometry, the piston displacement, y, is given by:

Substituting equations (B12) and (B8) into equation (B11) yields: π  4V p RDS  S (ϕ ) =   2 π 

y = r + L − L cos β − r cos ϕ , (B1)

where β can be expressed as r sin ϕ β = sin −1 . (B2)

L Substituting Eq. (B2) into Eq. (B1) yields: 1   y = r 1 − cos ϕ + 1 − 1 − λ 2 sin 2 ϕ  , (B3) λ  

)

where,

λ = r L. (B4) The volume can be described by: V (ϕ ) = Vc + π D 2 y 4 . (B5)

The relationship between crank radius r and stroke S is expressed as:

404

RDS = D Sr . (B12)

Fig. 10. The piston-crank mechanism

)

(

ϕ

π 2 π DSr D + [1 − cos ϕ + 2 2 1 + 1 − 1 − λ 2 sin 2 ϕ . (B11) λ

β

(

π 2 D . (B10) 4

Substituting Eq. (B10) and (B3) into Eq. (B9) yields:

r

Ah = Ap =

D y

π 2 D Sr . (B8) 4

Vp =

x

)

(

π  1  V p 1 − cos ϕ + 1 − 1 − λ 2 sin 2 ϕ  , (B7) λ 2  

Sr = 2r. (B6)

2/3

2 π  16V p +  2 2  π RDS

(

1/ 3

   

×

1  × 1 − cos ϕ + 1 − 1 − λ 2 sin 2 (ϕ ) λ 

) . (B13)

8 NOMENCLATURE A Ah Ap Cv df dv G h hv k L m

Effective area [m²] The area of cylinder head [m²] The heat transfer area of piston [m²] Specific heat at constant volume [718 J/kg·K] The diameter of the flow channel [m] The diameter of the valve stem [m] Air mass flow [kg/s] Specific enthalpy [J/kg] The valve lift [m] Specific heat ratio Connecting rod length [m] Mass [kg]

Yu, Q. – Cai, M. – Shi, Y. – Fan, Z.

Strojniški vestnik - Journal of Mechanical Engineering 60(2014)6, 395-406

n p Pe r R RDS S Sr Te u Up V Vc Vp

Crank speed [rad/s] Pressure [Pa] Output power [kW] Crank radius [m] Gas constant=287 J/[kg·K] Bore-to-stroke ratio Heat transfer area [m²] The stroke of cylinder [m] The effective output torque [N·m] Specific thermodynamic energy [J/kg] The average speed of piston [m/s] Volume [m³] The clearance of cylinder [m³] Engine displacement [m³] W Work done per cycle [J] y Piston displacement [m] α Heat transfer coefficient [W/m²·K] β The angle of link and crank [rad] θ Temperature [K] ω Crank speed [rad/s] φ Crank angle [rad] η Efficiency δ The threshold value γ The cone angle of the valve sealing [°] λ The ratio of crank and link Subscripts a Atmosphere c Inside cylinder H Upstream L Downstream s Supply 1 Intake 2 Exhaust 9 REFERENCES [1] [1] Veziroglu, T. N., Sahin, S. (2008). 21st century’s energy: hydrogen energy system. Energy Conversion and Management, vol. 49, no. 7, p. 1820-1831, DOI:10.1016/j.enconman.2007.08.015.

[2] Li, Y., Chen, H., Zhang, X., Tan, C., Ding, Y. (2010). Renewable energy carriers: Hydrogen or liquid air/nitrogen?. Applied Thermal Engineering, vol. 30, no. 14-15, p. 1985-1990, DOI:10.1016/j. applthermaleng.2010.04.033.

[3] Shafiee, S., Topal, E. (2009). When will fossil fuel reserves be diminished? Energy Policy, vol. 37, no.1, p.181-189, DOI:10.1016/j.enpol.2008.08.016.

[4] Bergant, A., Kruisbrink, A., Arregui, F. (2012).

Dynamic behavior of air valves in a large-scale pipeline apparatus. Strojniški vestnik - Journal of Mechanical Engineering, vol. 58, no. 4. p. 225-237, DOI:10.5545/ sv-jme.2011.032.

[5] Vukčević, V., Werner, A., Degiuli, N. (2012).

Application of smoothed particle hydrodynamics

method for simulating incompressible laminar flow.

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[6] Dudić, S.P., Ignjatović, I.M., Šešlija, D.D., Blogojević, V.A., Stojiljković, M.M. (2012). Leakage quantification of compressed air on pipes using thermovision. Thermal Science, vol. 16, Suppl. 2, p. 555-565, DOI:10.2298/ TSCI120503191D. [7] Gairns J.F. (1904). Industrial locomotives for mining, factory, and allied uses. Part II.-Compressed air and internal combustion locomo-tives. Cassier’s Magazine, vol. 16, p. 363-377.

[8] Creutzig, F., Papson A., Schipper, L.K., Kammen, D.M. (2009). Economic and environment evaluation of compressed air cars. Environmental Research Letters, vol. 4, no. 4, p. 044011, DOI:10.1088/17489326/4/4/04011.

[9] MDI Enterprises S.A. (2013). from http://www.mdi.lu/ english/, accessed on 2013-08-13.

[10] Afzal, A. (2011). A pilot compressed air engine.

Energy & Environment, vol. 22, no. 8, p. 1105-1113, DOI:10.1260/0958-305X.22.8.1105.

[11] Mahgoub, H.M., Craighead, I.A. (1995). Development of a microprocessor-based control system for a pneumatic rotary actuator. Mechatronics, vol. 5, no. 5, p. 541-560, DOI:10.1016/0957-4158(95)00025-Z. [12] Huang K.D., Tzeng S.C., Ma, W.P. et al., (2005).

Hybrid pneumatic-power system which recycles exhaust gas of an internal-combustion engine. Applied Energy, vol. 82, no. 2, p. 117-132, DOI:10.1016/j. apenergy. 2004.10.006.

[13] Pirc, A., Sekavčnik, M., Mori, M. (2012) . Universal model of a biomass gasifier for different syngas compositions. Strojniški vestnik - Journal of Mechanical Engineering, vol. 58, no. 5. p. 291-299, DOI:10.5545/sv-jme.2011.101.

[14] Dovjak, M., Shukuya, M., Krainer, A. (2012). Exergy analysis of conventional and low exergy systems for heating and cooling of near zero energy buildings.

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2011.158.

[15] Hammadi, M., Choley, J.Y., Penas, O., Louati, J., Rivière, A., Haddar, M. (2011). Layout optimization of power modules using a sequentially coupled approach.

International Journal of Simulation Modelling, vol. 10, no. 3, p. 122-132, DOI:10.2507/IJSIMM10(3)2.183.

[16] Liu, L., Yu, X.L., Hu, J.Q. (2009). Air powered engine design based on Pareto Frontier. Journal of Zhejiang University (Engineering Science), vol. 43, no. 1, p.123127, DOI:10.3785/j.issn.1008-973X.2009.01.24. (in Chinese) [17] Huang, C.Y., Hu, C. K., Yu, C.J., Sung, C.K. (2013).

Experimental investigation on the performance of a compressed-air driven piston engine. Energies, vol. 6, no. 3, p.1731-1745, DOI:10.3390/en6031731.

[18] He, W., Wu, Y.T., Peng, Y.H., Zhang, Y.Q., Ma, C.F., Ma, G.Y. (2013). Influence of intake pressure on the performance of single screw expander working

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with compressed air. Applied Thermal Engineering, vol. 51, no. 1-2, p. 662-669, DOI:10.1016/j. applthermaleng.2012.10.013.

[19] Cai, M.L. (2007). The flow characteristics of pneumatic components. Hydraulic Pneumatic and Sealing, vol.

27, no. 2, p. 44-48. (In Chinese).

[20] Shi, Y., Cai, M.L. (2011).Working characteristics of two kinds of air-driven boosters. Energy Conversion and Management, vol. 52, p. 3399-3407, DOI:10.1016/j. enconman.2011.07.008.

[21] Kalyanmoy, D. (2002). A fast and elitist multiobjective genetic algorithm: NSGA-II. Transactions on Evolutionary Computation, vol. 6, no. 2, p. 182-197, DOI:10.1007/3-540-45356-3_83.

[22] Atashkari, K., Nariman-Zadeh, N. Gölcü, M., Khalkhalia, A., Jamalia, A. (2007). Modeling and

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multi-objective optimization of a variable valvetiming spark-ignition engine using polynomial neural networks and evolutionary algorithms. Energy Conversion and Management, vol. 48, no. 3, p. 10291041, DOI:10.1016/j.enconman.2006.07.007.

[23] Van Veldhuizen, D.A., Lamont, G.B. (1998).

Evolutionary computation and convergence to a Pareto front. Late Breaking Papers at the Genetic Programming 1998 Conference, University of Wisconsin, Madison, p.

221-228.

[24] Schott, J.R, (1995). Fault Tolerant Design Using Single and Multicriteria Genetic Algorithm Optimization.

Master’s thesis, Massachusetts Institute of Technology, Cambridge.

Yu, Q. – Cai, M. – Shi, Y. – Fan, Z.

Strojniški vestnik - Journal of Mechanical Engineering 60(2014)6, 407-416 © 2014 Journal of Mechanical Engineering. All rights reserved.

DOI:10.5545/sv-jme.2013.1453

Original Scientific Paper

Received for review: 2013-09-23 Received revised form: 2013-11-06 Accepted for publication: 2013-11-13

Evaluating the Statistical Significance of a Fatigue-Life Reduction Due to Macro-Porosity Bižal, A. – Klemenc, J. – Fajdiga, M. Ana Bižal*,1 – Jernej Klemenc2 – Matija Fajdiga2

2University

1Hella Saturnus Slovenija d.o.o., Slovenia of Ljubljana, Faculty of Mechanical Engineering, Slovenia

This study focuses on an evaluation of the significance of the fatigue-life reduction due to macro-porosity present in pressure-die-casted aluminium specimens. Three statistical models, i.e., univariate analysis of variance, multivariate analysis of variance and linear regression with dummy variables, were applied to test the statistical significance of the fatigue-life reduction. The three statistical models were applied for the case of experimentally determined fatigue-life data for an AlSi9Cu3 alloy with different levels of macro-porosity. Cylindrical specimens according to ASTM E606 were manufactured by pressure die casting using different manufacturing parameters (die pressure, die temperature) to artificially introduce detectable macro-pores into the specimens. The manufactured specimens were classified into three groups, representing their levels of porosity, which were identified based on x-ray images of the specimens. For each group, strain-controlled fatigue tests were performed at different strain levels. Of these approaches, linear regression with dummy variables proved to be the most appropriate, due to its ability to robustly identify the differences between the fatigue lives for different porosity levels.

Keywords: AlSi9Cu3 alloy, porosity, fatigue life, ANOVA, MANOVA, linear regression with dummy variables

0 INTRODUCTION Engineering applications usually require a homogeneous material; however, this is sometimes impossible to achieve. Alloys and castings, for example, are very susceptible to inhomogeneities.

And while some inhomogeneities can be avoided completely, others, like porosity, can only be reduced.

Despite many studies that have shown the detrimental effect of such inhomogeneities on fatigue life [1, 2], castings are still widely used in the automotive industry due to their favourable strength-to-weight ratio.

By knowing that inhomogeneities cannot be completely avoided, the question arises: when does the level of the inhomogeneities start to significantly influence the fatigue behaviour of the structures?

In our study we have focused on the AlSi9Cu3 aluminium alloy, since it is often used in the automotive industry for complex cast parts such as engine supports. We narrowed our study to macroporosity inhomogeneities for a few reasons: a) it can be relatively easily introduced into specimens by varying the casting parameters, b) it can be detected using non-destructive inspections and c) it can be estimated with numerical simulations [3].

In the production process, when macro-porosity is discovered within a cast part, the part is normally discarded. This leads to a decreased throughput of good products as well as increased production costs.

However, the size and location of the observed macro-porosity could not be such that it significantly diminishes the load capacity or the fatigue life of the cast part. Discarding such a part is economically

unjustified. Our study focuses on the effect of different levels of porosity on the fatigue life and answering the question: when does the reduction in fatigue-life become statistically significant?

The effects of porosity on aluminium alloys have been researched before. Linder et al. [4] recorded a 15% drop in the material’s strength when increasing the porosity from an initial 0.7 to 4.1%. Wang [5] discovered that it is not only the percentage of porosity within the material, but also the size of the pores, that defines the effect on the fatigue-life.

When designing parts that experience dynamic loads, the fatigue strength of a material has to be known. It is usually determined by loading the specimens with dynamic loads at two different amplitude-load levels. Based on the scatter of the fatigue-life N the durability curve representing a certain probability of rupture can be identified. When the materials’ structure is not homogenous, the fatiguelife scatter is expected to increase. Fatigue-life tests can be stress or strain controlled. Loading a material containing inhomogeneities causes a localized increase in the stress and strain. Often, plastic deformation occurs around the inhomogeneities. Therefore, in cases where inhomogeneities are expected within the material, strain-controlled tests are preferred to ensure better control of a stress-strain state in the specimen.

Considering that macro-pores were expected within the specimens, as well as a large scatter of the fatiguelife data, it was decided to perform the experiments at many different amplitude-strain levels. The results from this testing form a cloud of points in the ε–N diagram. The results also indicated that despite the tests being strain-controlled the plastic component of

*Corr. Author’s Address: Hella Saturnus Slovenija d.o.o., Letališka c. 17, 1001 Ljubljana, Slovenia, ana.bizal@hella.com

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Strojniški vestnik - Journal of Mechanical Engineering 60(2014)6, 407-416

the strain-life curve was not captured. Therefore, when performing statistical analyses, the same methods were applied as are used in stress-life fatigue-data analyses (see also Eq. (1)).

Since the literature is very scarce on this topic (no systematic survey of the statistical methods that could be applied for testing statistical differences between the fatigue-life curves was found) our goal was to find statistical methods that would first enable an identification of the fatigue-life reduction due to the level of porosity and, second, evaluate the statistical significance of the observed reduction. Three approaches were researched and compared to find the most suitable one for comparing different fatigue-life curves. The statistical significance was first estimated using a simple transformation of the fatigue-life data points (ε, N) into a one-dimensional parameter combined with an analysis of the variance analysis (ANOVA). This parameter requires the assumption of equal slopes for all the fatigue-life curves. However, as it is shown later in the paper, that is not always the case. With the intent to avoid the assumption of equal slopes as well as the assumption of a linear relation between log ε and log N - a multivariate analysis of variance (MANOVA) for sets of non-transformed data points was employed. Finally, the estimation of a joint regression model with dummy variables for different groups of fatigue-life data combined with a significance test for the sets’ dummy variables was carried out.

The theoretical background of the applied statistical methods is presented in Section 2. The experimental work is presented in Section 3, together with the used samples, the sample manufacturing and the testing plan. Three levels of porosity are defined, together with a non-destructive method for the detection of this porosity. The fatigue curves are presented at the end of this section. The results are presented in Section 4 and the concluding remarks are given in Section 5.

1 THEORETICAL BACKGROUND 1.1 One-Dimensional Fatigue-Life Parameter Combined with the Univariate Analysis of Variance (ANOVA) ε-N curves are usually characterized by the CoffinManson relationship [6] and [7]. However, due to the small amount of experimental data in our case it turned out that the plastic part of the Coffin-Manson curve was not well expressed. That is why we decided to apply only a linear ε–N fatigue-life curve equation that should approximate a high-cycle fatigue regime.

408

By doing so we adopted a fatigue-life curve that is steeper than the elastic part, and more gradual than the plastic part, given by the Coffin-Manson relation.

The relationship between the number-of-cycles-tofailure N and amplitude strain level ε can be written as follows: −k

N1  ε1  =   . (1) N2  ε 2  From this equation it follows that: N1ε 2− k = N 2ε1− k = const. (2)

Therefore, a point with two coordinates (N and ε) can be transformed into a one-dimensional parameter using Ni∙εj-k. This means that each of the measured data points should be reduced to a single value of this parameter if there was no scatter between the individual fatigue-life data points (ε, N). Of course, because of the scattered fatigue-life data, the values of the one-dimensional parameter are also scattered.

If two fatigue-life curves are not identical, this parameter would be different for each of the two curves. As a result, the identity of two or more fatiguelife curves can be checked by testing the equality of the one-dimensional parameters from Eq. (2) for different data sets. However, this approach assumes the equality of the fatigue-life curve slopes k for different groups of fatigue-life data. Therefore, when the slopes of the fatigue-life curves are not identical, the reduction to a one-dimensional parameter is made for the average parameter k . Since the s fatigue-life data are reduced to a one-dimensional parameter, the significance between the different data sets is then tested using the one-way ANOVA test [8].

1.2 Multivariate Analysis of Variance (MANOVA) MANOVA [9] is a multivariate extension of ANOVA. Its objective is to determine whether different groups of data are significantly different with respect to a given set of variables. The null and alternative hypotheses for multivariate statistical significance testing in MANOVA are for two groups of the bivariate variable x = (x1, x2):

 µ11   µ12   µ11   µ12  H0 :  =  ; Ha :  ≠  , (3)  µ 21   µ 22   µ 21   µ 22 

where μij is the mean of the ith variable for the jth group.

The statistical distance between the mean vectors of the two groups is measured with the Mahalanobis distance (MD). The MD is given by [10]: MDik = ( x i − x k ) ' S −1 ( x i − x k ) , (4)

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Strojniški vestnik - Journal of Mechanical Engineering 60(2014)6, 407-416

where x is a p×1 vector of the coordinates and S is a p×p covariance matrix. The MD2 between the mean vectors is directly proportional to the differences between the two groups. The MD2 can then be transformed into various test statistics to determine whether it is large enough to claim that the difference between the groups is statistically significant. For multiple dependent variables the multivariate analogue for the differences between the groups is a function of the eigenvalue(s) λi of the SSCPb∙SSCPw-1 matrix.

Where SSCPb is between groups sum of squares and cross products matrix and SSCPw is within group sum of squares and cross products matrix. To test the null hypothesis against its alternative, eigenvalues λi of the SSCPb∙SSCPw-1 matrix are combined together using, e.g., Pillai’s trace (V), Hotelling’s trace (T2) or Wilks’s lambda (Λ), Eq.(5) to (7), respectively.

K λ V = ∑ i , (5)

i =1 1 + λi

K

T = ∑ λi ,

(6)

i =1

K

Λ=∏ i =1

1 , (7) 1 + λi

where λi is the eigenvalue for the ith discriminant variate and K is the number of variates. In our case we have two dependent variables and two groups for the independent variable and therefore K = 1. Because the MD is used to measure the distance between the group mean values and the MD is based on an elliptical distribution of the sample points around the group mean vector, the vectors (ε, N) cannot be used directly, but must be transformed into their logarithms (log(ε), log(N)).

Although the MANOVA reduces to a onedimensional parameter, it does have a significant advantage over the one-dimensional parameter introduced in Section 1.1, i.e., no transformation is carried out considering the slope of a regression line.

1.3 Linear Regression with Dummy Variables Linear regression models the relationship between one dependent and one or more independent variables by fitting a linear equation to the observed data. The equation of the ε–N fatigue-life curve, as defined in Section 1.1 (see Eq. (1)), becomes linear on a logarithmic scale. When generalized by N1 = N and ε1 = ε Eq. (1) can be written as follows:

1 1  log ( ε ) = − log ( N ) +  log ( N 2 ) + log ( ε 2 )  . (8) k k  

If b0 = k–1 log(N2) + log(ε2) and b1 = –k–1 then Eq. (8) can be written as: log ( ε ) = b0 + b1 ⋅ log ( N ) . (9)

Different specimen groups can be considered by introducing dummy variables (DV) into Eq. (9). When analyzing the differences between two groups of data, one DV is needed and Eq. (9) becomes: log ( ε )i = b0 + b1 ⋅ log ( N )i + b2 ⋅ DVi + +b3 ⋅ log ( N )i ⋅ DVi ,

0; if reference group DV =  . 1; if other group

(10)

The regression coefficients b0 and b1 are the intercept and the slope, respectively, of a reference group. To account for the effect of the group, b2∙DVi is used to model the variation of the intercept between the groups and b3∙DVi is used to model the variation of the slope between the groups.

When analyzing three groups of data, two DVs are needed and Eq. (9) becomes: log ( ε )i = b0 + b1 ⋅ log ( N )i + b2 ⋅ DVi1 + b3 ⋅ DVi 2 +

+b4 ⋅ log ( N )i ⋅ DVi1 + b5 ⋅ log ( N )i ⋅ DVi 2 ,

1; DV1 =  0; 1; DV2 =  0;

if group 1 , if other group if group 2 . if other group

(11)

The regression coefficients b0 and b1 are the intercept and the slope, respectively, of a reference group. To account for the effect of the second group, b2∙DVi1 is used to model the variation of the intercept and b4∙DVi1 is used to model the variation of the slope between the second group and the reference group.

Similarly, b3∙DVi2 is used to model the variation of the intercept and b5∙DVi2 is used to model the variation of the slope between the third group and the reference group.

2 EXPERIMENTAL DATA Standard specimens according to the ASTM E606 [11] standard were manufactured from the AlSi9Cu3 alloy using pressure die casting – see Fig. 1.

Evaluating the Statistical Significance of a Fatigue-Life Reduction Due to Macro-Porosity

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Strojniški vestnik - Journal of Mechanical Engineering 60(2014)6, 407-416

Fig. 1. Shape and dimensions of standard specimen

In order to study the effect of different porosity levels on the fatigue life the porosity had to be introduced into the specimens. This was achieved by not applying the usual pressure of 710 bar in the third phase of casting, used to condense the aluminium.

A total of 33 specimens were manufactured. The condition of the specimen’s interior was unknown after the manufacturing process. To determine the level of porosity induced in each specimen, the samples were X-rayed in two perpendicular planes.

Based on the acquired x-ray images, three levels of porosity were defined: • level A: no macro-pores are visible in the narrow part of the specimen, Fig. 2a, • level B: in the narrow part of the specimen a small number of macro-pores (usually only one) are detected, Fig. 2b, • level C: in the narrow part of the specimen a large number of macro-pores are detected, Fig. 2c.

These data correspond to homogenous specimens and represent the reference data from another production series of the specimens. These data were marked with MJ, after the first author of the previous research. To define the amplitude-strain levels for the fatigue-life experiments, destructive tensile tests were performed for one specimen of each porosity level. The tensiletest results were compared to the results of the homogenous specimens of AlSi9Cu3 from [12]. The results are listed in Table 1 and shown in Fig. 3.

Table 1. Material parameters of porous and homogenous AlSi9Cu3 Por. level A B C MJ #1 MJ #2 MJ #3

E [MPa] 79631 70777 69143 80212 74761 78649

Rp02 [MPa] 178 154 152 164 137 136

Rm [MPa] 323 271 248 304 312 303

εrup [%] 4.35 2.31 2.48 4.93 5.21 4.85

Fig. 3. Tensile tests of porous specimens and homogenous specimens

Fig. 2. X-ray images of samples; a) porosity level A, b) porosity level B (macro-pores are indicated with arrows) and, c) porosity level C

Out of the 33 samples examined, 15 were characterized with the porosity level A, 10 were characterized with the porosity level B and 8 were characterized with the porosity level C. In addition, another series of AlSi9Cu3 fatigue-life data from our previous research [12] was included in the study.

410

When the material’s structure is not homogenous, the fatigue-life scatter is expected to increase compared to the homogenous structure [2]. Therefore, the specimens were loaded at many different amplitude-strain levels. The dynamic tests were fully reversal, strain controlled, with the amplitude-strain levels between 0.1 and 0.4%. All the fatigue-life experiments were performed on a MTS 810.22 servohydraulic test stand at the company CIMOS, Slovenia.

The strain was measured using an MTS 632.53F-14 extensometer with a measuring distance of 12 mm.

The tests were performed under atmospheric pressure and at a temperature of 21 °C. The experimental fatigue-life data for the four groups (MJ, A, B and C) are presented in Fig. 4. In the same figure the ε–N curves modelled by Eq. (1) and representing 10, 50 and 90% probability of rupture

Bižal, A. – Klemenc, J. – Fajdiga, M.

Strojniški vestnik - Journal of Mechanical Engineering 60(2014)6, 407-416

are also shown. The scatter of the ε–N curves was modelled using a Weibull probability density function:

β f (N ) = η

N   η 

β −1

⋅e

β   N   −   η    

. (12)

In Eq. (12) the scale factor η is dependent on the amplitude-strain level via the Basquin equation:

c + c1 ⋅log (ε )

η = η (ε ) = 10 0

; c0 > 0, c1 < 0, (13)

where: c0 = log ( N 2 ) + k ⋅ log ( ε 2 ) , c1 = −k . (14)

and the shape factor β is constant. The parameters c0, c1 and β were determined according to the procedure that was derived by Klemenc and Fajdiga [13].

From the diagram in Fig. 4 we can see that the fatigue curves differ from each other with respect to the level of porosity. The specimens with porosity levels B and C display a much greater scatter than the specimens from the groups with level A and MJ. When observing a certain strain level we find that the specimens C have the shortest fatigue life, followed by the specimens B, and the specimens A, which have the longest fatigue life. There is also a slight discrepancy between the specimens A and the specimens MJ. This suggests that the production series influences the fatigue life to a certain degree.

can lead to a false conclusion regarding the statistical significance of the differences in the fatigue life. To assess the influence of the different sample-set sizes on the statistical significance, additional fatigue-life data were generated in accordance with the ε–N curve models from Fig. 4. The data for each specimen group were generated using a Weibull random generator with its parameters set-up according to Table 2 for the amplitude-strain levels between 0.1 and 0.4%.

First, the number of sample points in each group was levelled to match the largest sample set (16 sample points). Second, to study the effect of the sample-set size on the statistical significance, additional sample points were generated so that the sample-set sizes were increased to 40 and 80 samples. The experimentally obtained and simulated data points are shown in Fig. 5. A regression equation for each data set is displayed on the presented plots. The slope of the regression line and the parameter c1 are correlated with the following relation c1 = –1/slope. In the following subsections the significance of the fatigue-life reduction due to the macro porosity is analysed.

Table 2. Parameters of A, B, C and MJ fatigue curves Por. level A B C MJ

c0 1.2622 -1.1397 -1.1281 1.2630

c1 -6.0001 -8.0143 -6.8248 -5.3798

β 2.1329 0.7252 0.7980 3.5454

3.1 ANOVA for the One-Dimensional Fatigue-Life Parameter The experimental results with two dimensions (ε, N) were transformed into a one-dimensional parameter, as described in Section 2.1, see Fig. 6. The four groups of data were then compared using a one-way ANOVA, with the results being presented in Table 3.

Table 3. ANOVA results for one-dimensional parameter with the number of different porous specimens in each sample

Fig. 4. Fatigue curves for A, B and C levels of porosity and homogenous specimens MJ

3 RESULTS AND DISCUSSION We had a relatively small number of specimens and the specimen groups were of unequal size (14 samples with level-A porosity, 9 samples with level-B porosity, 7 samples with level-C porosity and an additional 16 unaltered MJ samples). This can affect the outcome of the statistical analysis and

Sample 14 A+10 B+7 C+16 MJ 16 A+16 B+16 C+16 MJ 40 A+40 B+40 C+40 MJ 80 A+80 B+80 C+80 MJ

F-stat.

13.743 18.151 25.914 48.877

p-val.

0.000 0.000 0.000 0.000

The analyses of the experimental samples showed that the differences between the original groups of the fatigue-life data are statistically significant (F = 13.743 and p < 0.05); where the p-value is defined as the smallest significance level at which the null hypothesis would be rejected [8]. By increasing the number of samples in each set, the differences

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a)

c)

b)

d) Fig. 5. Sample sets with regression equations for different porosity levels; a) experimental samples, b) 16, c) 40, and d) 80 samples

between the groups remain significant (p < 0.05).

When comparing the results from the sample sets with 40 samples and the sample sets with 80 samples, the tests become even more significant, implying that there is no justification for increasing the size of the sample sets beyond 40 samples per set.

While this approach manages to distinguish between the groups, one should keep in mind that the slopes are assumed to be equal within the statistical scatter. From Fig. 5 it is clear that the slopes do vary between the groups and therefore the results of the ANOVA analysis are unreliable in our case.

of rejecting the null hypothesis (see Eq. 3) when it is false is very low. Regardless of the size of the sample set the multivariate test statistics (Pillai’s trace, Wilks’s lambda and Hotelling’s trace) indicate a statistically significant effect for the level of porosity at p < 0.05. The higher the porosity level, the greater is the effect on the fatigue life. But there can be more than one reason for a statistical significance found by a multivariate test, for example, the data could be shifted along the centre line or they could be shifted vertically downwards or upwards, to the left or to the

3.2 Multivariate Analysis of Variance

Table 4. MANOVA results for groups A and MJ

412

Val. p Val. p Val. p

V T2 Λ Power log ε log N

The analyses were carried out by always comparing two groups of the fatigue-life data at the same time: groups A and MJ, groups A and B, groups A and C and groups B and C. The results are given in Tables 4 to 7, respectively.

The discussion of the results is divided into two parts: first, the analyses involving group A are addressed and, second, the analyses of groups B and C are addressed. When comparing group A with the other groups, the power of the multivariate tests is large (power ≈ 1.00), suggesting that the probability

Bižal, A. – Klemenc, J. – Fajdiga, M.

p Power p Power

14-16 0.475 0.000 0.905 0.000 0.524 0.000 0.99 0.000 0.984 0.002 0.894

16-16 0.469 0.000 0.886 0.000 0.530 0.000 0.99 0.000 0.987 0.002 0.896

40-40 0.548 0.000 1.212 0.000 0.451 0.000 0.99 0.001 0.919 0.098 0.379

80-80 0.544 0.000 1.195 0.000 0.455 0.000 1.00 0.001 0.923 0.248 0.207

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a)

b)

c) d) Fig. 6. Graphical presentation of one-dimensional parameter N · ε–k for; a) experimental sample set, b) 16 samples in set, c) 40 samples in set and d) 80 samples in set; group A = (0), group B = (1), group C = (2), group MJ = (3)

test for the variable log(N) and an increased number of data points is not significant at the 0.1% significance level, which implies that the difference is not due to the porosity, but due to the production series.

Table 5. MANOVA results for groups A and B Val. p Val. p Val. p

V T2 Λ Power log ε log N

right. After each multivariate test a univariate test was performed to determine which variable contributes to the differences between the two groups. The univariate tests indicate that log(N) contributes to the differences between the groups, regardless of which group is being compared to group A and regardless of the sample-set size. The univariate tests yield a different result for log(ε). The only case where it reaches a significance level is in the analysis of groups A and MJ, when the number of samples was no more than 16 samples per set. The reason for this can be found in Fig. 6. Note that the tests for specimens A and specimens MJ were not performed in the same strain range; therefore, the univariate tests are significant with respect to log(ε).

When the number of specimens is increased and the data is more equally distributed across the strain range, the test becomes significant. A similar reason explains why log(ε) is not significant when comparing group A to group B, and group A to group C. Despite all the MANOVA tests involving the group A being significant, we can see from Table 3 that the ANOVA

p Power p Power

14-10 0.713 0.000 2.485 0.000 0.286 0.000 0.99 0.004 0.859 0.971 0.040

16-16 0.653 0.000 1.888 0.000 0.346 0.000 0.99 0.001 0.960 0.847 0.044

40-40 0.704 0.000 2.380 0.000 0.295 0.000 0.99 0.000 0.999 0.925 0.035

80-80 0.701 0.000 2.347 0.000 0.298 0.000 1.00 0.000 1.00 0.950 0.032

When discussing the analysis results of groups B and C it is clear that all the test statistics show a non-

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significant difference between the groups (p = 0.081).

The univariate tests indicate that none of the means are significantly different for the two groups. However, a level of statistical significance (p < 0.05) is reached as soon as the sample sets are made equal and the number of samples in each set is increased to 16. At this point log(N) becomes significant, while log(ε), like in the other analyses, never does. Nevertheless, it can be concluded that the statistical difference in the fatigue-life data is the smallest between the groups representing level-B and level-C porosity.

V T2 Λ

log ε log N

Power p Power p Power

14-7 0.824 0.000 4.684 0.000 0.175 0.000 0.99 0.000 0.999 0.471 0.127

16-16 0.818 0.000 4.500 0.000 0.181 0.000 0.99 0.000 1.000 0.494 0.107

40-40 0.869 0.000 6.634 0.000 0.130 0.000 0.99 0.000 1.000 0.740 0.049

80-80 0.878 0.000 7.212 0.000 0.121 0.000 1.00 0.000 1.000 0.824 0.040

V T2 Λ

log ε log N

Power p Power p Power

14-7 0.301 0.081 0.431 0.081 0.698 0.081 0.99 0.49 0.515 0.436 0.142

16-16 0.281 0.008 0.392 0.008 0.718 0.008 0.99 0.013 0.725 0.567 0.060

40-40 0.182 0.000 0.222 0.000 0.817 0.000 0.49 0.066 0.453 0.806 0.439

80-80 0.301 0.000 0.432 0.000 0.698 0.000 0.82 0.003 0.854 0.871 0.036

Using MANOVA we can detect a multivariate significance even in the cases where no univariate significance is detected. The MANOVA weaknesses are displayed in Table 4 when observing the univariate results for log(ε): it is clear that the MANOVA would fail to identify data belonging to the same fatigue curve if the tests were carried out at different strain levels.

3.3 Linear Regression Using Dummy Variables Altogether, four regression models with dummy variables were built: the first comparing groups A 414

Model

A-B-C B-C A - BC

Group A MJ A B C B C A BC

DV1 0 1 0 1 0 0 1 0 1

DV2 / / 0 0 1 / / / /

Table 9. Regression with indicator coding results for groups A and MJ Sample 14A+16MJ R2adj=0.939

Table 7. MANOVA results for groups B and C Val. p Val. p Val. p

Table 8. Indicator variable coding system for performed analysis

A - MJ

Table 6. MANOVA results for groups A and C Val. p Val. p Val. p

and MJ, the second comparing groups A, B and C and the third comparing groups B and C. Based on the considered number of fatigue-life data groups in the individual regression models, the number of required dummy variables was defined. The dummyvariable coding system is given in Table 8. The linearregression coefficient together with their significances are presented in Tables 9 to 12.

16A+16MJ R2adj=0.938

40A+40MJ R2adj=0.969

80A+80MJ R2adj=0.976

b0 b1 b2 b3 b0 b1 b2 b3 b0 b1 b2 b3 b0 b1 b2 b3

bi 0.088 -0.148 0.106 -0.031 0.086 -0.147 0.107 -0.032 0.158 -0.159 0.029 -0.019 0.167 -0.162 0.038 -0.020

p-value 0.180 0.000 0.234 0.104 0.161 0.000 0.210 0.088 0.000 0.000 0.399 0.008 0.000 0.000 0.070 0.000

The analysis with group A and group MJ was carried out with the intension to investigate the effect of the production series on the fatigue life.

Observing the results (see Table 9) we see that the adjusted R2 values are very high (R2 > 0.93); where the R2 coefficient is defined as the squared correlation of the dependent variable and the fitted values. [9] Experimental sample sets and sets with 16 samples are not significantly different with respect to all the model parameters (intercept and slope). The fact that neither the slope nor the intercept differ significantly at the 5% significance level between the two groups indicates

Bižal, A. – Klemenc, J. – Fajdiga, M.

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that micro-porosity does not have a significant impact on the fatigue life. Increasing the sample-set size to 40 samples and above the significance of the slope differences increases. Even when the set size is increased to 80 the intercepts are not significantly different at the 5% significance level.

Once we established that the production series does not have a significant effect on the fatigue life, an analysis was conducted to see whether macro-porosity has a significant effect on the fatigue life. Groups B and C were compared to the reference group A. Observing the results of the analysis (Table 10) we see that in the experimental data and the 16 sample data sets the intercepts of groups B and C are significantly different from that of group A (p < 0.05). The slopes, however, are not significantly different (p > 0.05).

When the number of samples per set is increased to 40 the slopes as well as the intercepts of groups B and C differ significantly from group A. From these results it is possible to conclude that the macro-porosity in the critical cross-section has a significant effect on the fatigue life. The results also suggest that there is no point in increasing the sample-set size beyond 40.

Table 10. Regression with indicator coding results for groups A, B and C Sample

14A+10B+7C R2adj=0.722

16A+16B+16C R2adj=0.691

40A+40B+40C R2adj=0.882

80A+80B+80C R2adj=0.908

b0 b1 b2 b3 b4 b5 b0 b1 b2 b3 b4 b5 b0 b1 b2 b3 b4 b5 b0 b1 b2 b3 b4 b5

bi 0.088 -0.148 -0.377 -0.500 0.046 0.067 0.086 -0.147 -0.396 -0.456 0.056 0.058 0.158 -0.159 -0.441 -0.425 0.058 0.040 0.167 -0.162 -0.395 -0.421 0.052 0.039

p-value 0.442 0.000 0.015 0.002 0.136 0.080 0.391 0.000 0.003 0.001 0.036 0.043 0.001 0.000 0.000 0.000 0.000 0.001 0.000 0.000 0.000 0.000 0.000 0.000

Once the significance in the differences between groups A, B and C was identified, groups B and C were

compared in a separate analysis (see Table 11). The experimental samples show no significant difference between the two groups in terms of slope or intercept (p > 0.05). However, increasing the sample size to 40 does increase the adjusted R2 value. Neither the slope nor the intercept reach the level of significance (p > 0.05).

After failing to find a significant difference between the levels of porosity B and C we conducted an additional analysis in which we joined the samples with porosity levels B and C to form a new group named BC. Group BC contains all the specimens with macro-pores within the structure. Only the experimental samples were analyzed (see Table 12).

The results show that the intercept as well as the slope differ significantly between the groups (p < 0.05). The adjusted R2 value (R2 =0.721, Table 12) is roughly the same as in the analysis with three porosity levels (R2 =0.722, Table 9).

Table 11. Regression with indicator coding results for groups B and C Sample 14A+16MJ R2adj=0.939

16A+16MJ R2adj=0.938

40A+40MJ R2adj=0.969

80A+80MJ R2adj=0.976

bi -0.290 -0.102 -0.123 0.021 -0.310 -0.092 -0.059 0.002 -0.283 -0.101 0.016 -0.019 -0.228 -0.110 -0.026 -0.012

b0 b1 b2 b3 b0 b1 b2 b3 b0 b1 b2 b3 b0 b1 b2 b3

p-value 0.019 0.002 0.448 0.643 0.001 0.000 0.602 0.938 0.000 0.000 0.683 0.083 0.000 0.000 0.307 0.076

Table 12. Regression with indicator coding results for groups A and joined groups BC Sample 14A+17BC R2adj=0.721

b0 b1 b2 b3

bi 0.088 -0.148 -0.469 0.064

p-value 0.443 0.000 0.001 0.019

5 CONCLUSIONS The study showed that macro-porosity at a critical specimen cross-section affects the fatigue life of an AlSi9Cu3 aluminium alloy. Among the three defined

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levels of porosity, the level without macro-porosity was proven to have the least impact on fatigue.

However, if larger pores are present within the critical cross-section of the sample, the fatigue life is drastically reduced.

The performed statistical analysis using three different methods provides guidelines for selecting the proper approach for large-scatter fatigue-data analysis.

Despite reducing to a single-dimensional value the MANOVA proved to have a major advantage over the one-dimensional fatigue parameter combined with the one-way ANOVA. The MANOVA does not include a transformation where the slope would be regarded; therefore, allowing the researcher to compare fatigue curves with various slopes. The downside is that the MANOVA is not able to identify sample sets belonging to the same fatigue curve if the fatigue-life data in different data sets are shifted along the fatiguelife curve in the direction of the amplitude-strain levels. Linear regression with indicator variables proved to be the most informative approach, offering information about the significance of the differences between groups as well as the sources of the observed differences. Based on the results it is possible to identify data belonging to the same fatigue curve, even if the data are acquired for different strain ranges.

Our analysis also provides some guidelines for planning an experiment to investigate the fatigue life of inhomogeneous materials. A large amount of experimental data are always desired; however, for large sample sizes even small differences between different sample sets become statistically significant.

When proving that even production series differ between each other, it would also be useful to assess the practical significance of the differences between groups. For that reason we suggest no more than 40 samples per data set in order to obtain relevant results regarding the significance of the differences between the groups.

The results of this study clearly show that specimens without macro-porosity do not exhibit a major change in the fatigue life between different production series if the processing parameters are kept constant. On the other hand, the presence of macro-porosity within the critical cross-section of the specimen has a detrimental effect on the fatigue life and reduces it drastically, regardless of the pore distribution. One of the most significant added values of our research was that we have calculated the magnitude and the statistical significance of the

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fatigue-life reduction due to the macro-porosity. This is a very favourable result for a practical application, since macro-porosity can be estimated beforehand using numerical simulations and by knowing its effect we can estimate whether the predicted macro-porosity for different cross-sections of the product would result in a significant fatigue-life reduction for that product.

6 REFERENCES [1] Skallerund, B., Iveland, T., Harkegard, G. (1993).

Fatigue life assessment of aluminum cast alloys. Part I. Engineering Fracture Mechanics, vol. 44, p. 857-874, DOI:10.1016/0013-7944(93)90108-5.

[2] Murakami, Y., Endo, M. (1994). Effects of defects, inclusions and inhomogeneities on fatigue strength.

International Journal of Fatigue, vol. 16, p. 163-182, DOI:10.1016/0142-1123(94)90001-9.

[3] Gwiżdż, A., Pysz, S., Dworak, P. (2010). MAGMAsoft simulations applied in verification of technology to produce new range of alloy steel castings. Archives of Foundry Engineering, vol. 10, p. 67-72.

[4] Linder, J., Axelsson, M., Nilsson, H. (2006). The influence of porosity on the fatigue life for sand and permanent mould cast aluminium. International Journal of Fatigue, vol. 28, p. 1752-1758, DOI:10.1016/j. ijfatigue.2006.01.001.

[5] Wang, Q.G. (2001). Fatigue behaviour of A356/357 aluminum cast alloys. Part II – Effect of micro structural constituents. Journal of Light Metals, p. 8597, DOI:10.1016/S1471-5317(00)00009-2.

[6] Manson, S.S. (1953). Behaviour of Material under Conditions of Thermal Stress. Technical note no.

2933. National Advisory Committee for Aeronautics, Cleveland.

[7] Coffin, L.F. (1954). A study of cyclic- thermal stresses in a ductile metal. ASME, vol. 76, p. 931-950.

[8] Rice, J.A. (2007). Mathematical Statistics and Data Analysis, 3rd ed. Thompson Brooks/Cole, Belmont.

[9] Sharma, S. (1996). Applied Multivariate Techniques.

John Wiley &Sons, Hoboken.

[10] Tabachnick, B., Fidell, L.S. (2007). Using Multivariate Statistics, 5th ed. Pearson, Essex.

[11] ASTM. E 606-92 (1996). Standard practice for straincontrolled fatigue testing. ASTM International, West Conshohocken, DOI:10.1520/E0606_E0606M-12.

[12] Janežič, M. (2010). The Influence of Randomness of Damage Model Parameters on Development Prediction of Product Durability. PhD Thesis, University of Ljubljana, Faculty of Mechanical Engineering, Ljubljana. (in Slovene) [13] Klemenc, J., Fajdiga, M. (2012). Estimating S-N curves and their scatter using a differential ant-stigmergy algorithm. International Journal of Fatigue, vol. 43, p.

90-97, DOI:10.1016/j.ijfatigue.2012.02.015.

Bižal, A. – Klemenc, J. – Fajdiga, M.

Strojniški vestnik - Journal of Mechanical Engineering 60(2014)6, 417-424 © 2014 Journal of Mechanical Engineering. All rights reserved.

DOI:10.5545/sv-jme.2013.1451

Original Scientific Paper

Received for review: 2013-09-21 Received revised form: 2014-03-01 Accepted for publication: 2014-04-01

Analysis of the Influence of Contaminants on the Biodegradability Characteristics and Ageing of Biodegradable Hydraulic Fluids Asaff, Y. – De Negri, V.J. – Theissen, H. – Murrenhoff, H. Yesid Asaff 1 – Victor J. De Negri1,* – Heinrich Theissen2 – Hubertus Murrenhoff2 1 Federal

University of Santa Catarina, Mechanical Engineering Department, Brazil University, Institute for Fluid Power Drives and Controls, Germany

2 RWTH Aachen

Ongoing concerns regarding environmental protection encourage further research aimed at the development of environmentally-friendly products. Certain research activities and industrial applications have broken the paradigm of using mineral oil for hydraulic systems by providing solutions with biodegradable hydraulic fluids. Petroleum-based hydraulic fluids are not able to meet this demand due to their often toxic properties and their environmental effects. Therefore, ecologically-acceptable fluids based on natural and synthetic esters are increasingly used as pressure fluids. Knowledge of the influence of contaminants on the biodegradability characteristics and ageing of biodegradable hydraulic fluids is a prerequisite for the successful application of these fluids in hydraulic systems. Accordingly, in this study, new information obtained from commercial biodegradable fluids (hydraulic oil environmental ester synthetics (HEES)) under the influence of common contaminants (water, mineral oil, copper solid particles, and oxygen) present in current hydraulic systems has been investigated.

Based on oxidation and hydrolytic stability tests, the biodegradability characteristics and ageing of biodegradable fluids are analysed, and the influence of contaminants is described. A comparison between fluid samples with different contaminants has shown that both the total acid number (TAN) and viscosity change significantly as a consequence of ageing in the presence of water and solid particles of copper, while the biodegradability characteristic was modified mainly by contamination with mineral oil.

Keywords: biodegradable hydraulic fluids, oxidation, hydrolysis, biodegradability, contamination, ester hydraulic fluids

0 INTRODUCTION The future of hydraulic fluids has greatly been influenced by the development of hydraulic components and systems as well as requirements from new applications.

Although mineral oils have traditionally been the most commonly used hydraulic fluids in the fluid power industry, they are being subjected to ever-increasing controls, particularly because of the increasingly stringent governmental regulations regarding the impact of hydraulic fluid spill and fluid leakage on the environment [1].

A consequence of this situation has been a global effort to identify hydraulic fluids that exhibit reduced environmental and toxicological impacts upon incidental contact with the environment.

According to Majdic and Pezdirnik [2], fluid suppliers and researchers have responded by developing new solutions focused on two approaches: using biodegradable oil instead of mineral oil or water hydraulics [2] to [4].

The basic requirements for an environmentallyacceptable hydraulic fluid are not only high biodegradability and low eco-toxicity, but also that the fluid performance guarantees satisfactory operation in the most demanding hydraulic components. However, to present good performance over long periods of operation, the physico-chemical properties of the fluid must remain stable. These properties include good

performance at high and low temperatures, oxidation stability, thermal stability, shear stability, wear protection, demulsibility, low foaming tendency and good filterability.

Ageing tests can analyse which properties are affected, and to what extent they are affected by the different ageing conditions. Fig. 1 shows factors that can provoke ageing mechanisms such as oxidation, polymerization, cracking, and hydrolysis, which modify the fluid’s properties and consequently decrease the fluid usability.

According to Héry and Battersby [5] and Murrenhoff and Schmidt [6], the most important ageing mechanism is oxidation. Regarding the causes of ageing, Murrenhoff and Schmidt [6] observed that a combination of high pressure and high temperature leads to a significant increase in the viscosity and total acid number (TAN), which prevents the fluid from performing its tasks properly. Additionally, it can be concluded that high temperature affects the fluid properties more than high pressure.

The contamination of biodegradable hydraulic fluids with mineral oils has been discussed by Theissen [7], who showed that the degree of deterioration is not correlated to the amount of mineral oil added but instead to the amount of metals introduced through additives present in some mineral oils. Problems such as foaming and poor air release are reported to occur at high levels of contamination with mineral oil. The general impact of catalysts on the oxidation stability

*Corr. Author’s Address: Federal University of Santa Catarina, Mechanical Engineering Department, 88040-900, Florianópolis, SC, Brazil, victor.de.negri@ufsc.br

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of environmentally-acceptable fluids was studied by Murrenhoff and Schmidt [6]. Their investigations showed that, according to oxidation test results, the significant impact of catalyst contaminants on the oxidation stability is strongly dependent on the ratio between the catalyst surface area and the amount of fluid. The same authors have analysed the ageing of environmentally-friendly hydraulic fluids as a function of friction and wear [8].

carried out. In Section 3, the laboratory tests followed by the results obtained in the investigation are reported. The conclusions are outlined in Section 4.

1 TEST DESCRIPTIONS 1.1 Introduction An analysis of the influence of contaminants on biodegradable fluids was carried out through oxidation tests and hydrolytic stability tests at the Institute for Fluid Power Drives and Controls (IFAS), RWTH Aachen University. The procedure and tasks of this research are shown in Fig. 2.

The first step of the strategy is related to the requirements that include the selection of the different types of biodegradable hydraulic fluids. For this purpose, three different biodegradable fluids from two different manufactures were used in the laboratory tests.

Fig. 1. Causes and effects of ageing

Biodegradation is a natural process driven by the action of microorganisms. According to Rhee [9], in the presence of oxygen, nitrogen, phosphorous, and trace minerals, organic compounds can support microbial growth and are converted into a series of oxidation products that that commonly have carbon dioxide and water as end-products.

Several international environmental standards and labelling procedures have been established to define biodegradability and how it should be experimentally determined. An overview of such test methods and an illustration of some different eco-labels are provided

by Rhee [10].

This paper studies the influence of contaminants, such as water, mineral oil, copper particles, and oxygen on the biodegradability characteristics and ageing of biodegradable fluids used in hydraulic circuits.

In the next section, the investigation strategy is described, including the actions undertaken in each stage of the research and the experimental bench tests 418

Fig. 2. Investigation strategy Table 1. Biodegradable hydraulic fluids used in the experiments

Fluid A Fluid B Fluid C

Kin. viscosity at 40 ºC [mm²/s]* 34.93 46.59 69.05

*Experimental measurement (IFAS) ** Product datasheet

Asaff, Y. – De Negri, V.J. – Theissen, H. – Murrenhoff, H.

Biodegradability OECD 301** [%] ≈70 >70 >70

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The three fluids studied were based on synthetic esters complying with the HEES specifications in ISO 15380. In this paper, they are identified as Fluid A, B, and C. Table 1 shows their relevant properties.

The major factors associated with the ageing of hydraulic fluids are temperature, oxygen, water, and metallic catalysts [11]. The effect of contamination with mineral oil on ageing was also considered in this study.

The rotary pressure vessel oxidation test (RPVOT), hydrolysis test and the biodegradability test were carried out with the addition of a known percentage of mineral oil, water, and copper particles to the biodegradable hydraulic fluids. The parameters considered as indicators of the ageing of the biodegradable fluids were the viscosity and TAN in the hydrolysis and the oxidation in the RPVOT. 1.2 Oxidation Stability Test A modified RPVOT was used to determine the oxidation stability of the fluids by subjecting the oil to extreme oxidation conditions without using the copper catalyst. The RPVOT is normally carried out according to ASTM D2272-11, [12]; however, for the research reported herein, the measurement criterion was modified, taking into account the large amount of samples to be tested. Instead of measuring the time to achieve a 1.75 bar pressure drop, the test time was fixed, and the resulting pressure drop recorded.

The criterion used to determine the oxidation stability was the pressure drop in the vessel from the maximum value to that observed in 24 hours of experimentation. The temperature set for the tests was 120 °C, lower than the standard procedure to be allowed a quicker stabilization and checking a larger number of samples. The test rig set up at the IFAS laboratory is depicted in Fig. 3.

1.3 Hydrolytic Stability Test The investigation of hydrolytic stability is of central importance for the evaluation of the useful properties of ester-based fluids that undergo rapid biological degradation. Factors that influence hydrolysis are primarily water content, temperature, and retention time of water in the fluid. Furthermore, the presence of metals significantly affects hydrolytic action.

When esters are synthesized from fatty acids and alcohols, water is generated and subsequently removed. If the water contaminates the fluid during the operation, the process is reversed, the hydrolytic equilibrium is adjusted, and alcohols and acids are produced.

The hydrolytic stability of the reference fluids was tested according to ATSM D2619-09 [13] in the presence of water (1%), with the exception of the test in which 0.1% of water was used. The test rig built at IFAS for these experiments can be seen in Fig. 4.

a) b) Fig. 4. Hydrolytic stability test: a) test bench; b) test procedure [14]

a)

For the test, a fluid sample (75 g) was placed into a glass jar enclosed in a stainless steel container with 1% of water and left there for a specific period, in this case for 72 hours. The stainless steel container stands in a heating bath that can be set to the desired temperature (90 ºC). The container has an irregular shape and was rotated at 50 rpm to ensure that the sample was thoroughly mixed (Fig. 4). b) Fig. 3. Oxidation stability test: a) RPVOT bench; b) test procedure Analysis of the Influence of Contaminants on the Biodegradability Characteristics and Ageing of Biodegradable Hydraulic Fluids

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1.4 Biodegradability Tests Based on Eisentraeger et al. [15], the biodegradability can be evaluated by ‘O2=CO2 Headspace test with gas chromatography - thermal conductivity detection (GC-TCD)’, which is carried out in accordance with the standard procedures: ISO 10708:1997 [16], ISO 11266:1994 [17] and ISO 14593:1999 [18] with slight modifications (Fig. 5).

Results are expressed as biological oxygen demand in relation to the theoretical oxygen demand (BOD/ThOD) and as carbon dioxide production in relation to the theoretical carbon dioxide production (TIC/ThIC). The results are calculated on the basis of values from the elemental analysis (Elemental Analyzer Vario EL) in duplicate.

Biodegradable hydraulic fluids are defined in the ISO 15380:2011 [21] standard which recommends their contamination with mineral hydraulic fluid, e.g. during an oil change, not to exceed 2% (or 1% in the presence of HLP-D or engine oils). HLP and HLP-D fluids are categories of anti-wear hydraulic fluids according to DIN 51524. The mineral oil used in these experiments is standard HLP 46 hydraulic fluid.

The concentrations studied were 2% (ISO limit as mentioned above) and 10%. The copper sample used as a contaminant consisted of 0.25 g of solid particles of 40 µm size and fluid samples with 75 g and 50 g for the hydrolytic and oxidation tests, respectively. The mass was calculated to be equivalent to the copper surface used in the oxidation tests according to ASTM D 2272-11 [12]. The other quantity of copper used in the tests was 1 g.

The water concentration investigated was 1%, according to ISO 12937:2000 [22] and ISO 6296:2000 [23] standards. In the second test in which water was the contaminant 10% was applied.

2.2 Oxidation Stability

a) b) Fig. 5. Biodegradability test: a) samples in glass flasks; b) autosystem gas chromatograph

Both hydrolysis and oxidation tests were applied once for each fluid sample because they consume 24 and 72 h, respectively. Forty-two different samples were analysed to achieve the results discussed in following sections, resulting in more than 2000 hours of tests. The equipment used for these tests is the same that has been used in the research presented by Murrenhoff and Schmidt [6] and [8].

The determination of TAN and kinematic viscosity was carried out according to DIN 515581:1979 [19] and DIN 51562-1:1999 [20], respectively.

The tests are repeated three times for each fluid sample.

The oxidation stability of the fluids was investigated through the use of the modified RPVOT. A visual comparison of Fluid A before and after the oxidation tests is shown in Fig. 6.

It can be observed that, in most cases, a visual inspection can provide an early indication regarding the extent to which the fluid properties are modified.

Chemical reactions typically result in the fluids having a dark colour after oxidation tests.

2 RESULTS AND DISCUSSION 2.1 Introduction The goal of the laboratory tests was to determine how the contaminants can influence the biodegradability characteristics and ageing of the fluids as well as to obtain information on the effects observed on applying different concentrations and combinations of contaminants (mineral oil, solid copper particles, and water).

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Fig. 6. Visual comparison of Fluid A: a) new fluid, b) fluid after oxidation test, c) fluid with mineral oil (2%) after oxidation test, d) fluid with mineral oil (10%) after oxidation test

Fig. 7 shows the oxidation stability results for Fluid A. A smaller pressure drop corresponds to a better oxidation stability of the fluid. It is clear that the mineral oil slightly improves the oxidation stability of the biodegradable fluid, in contrast to the influence of

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water and copper. This minor influence of the mineral oil can also be seen in Figs. 8 and 9, which show the oxidation stability of the biodegradable fluids B and C, respectively.

Fig. 7. Oxidation stability of Fluid A as a function of the contaminants

A possible reason for this minor influence of the mineral oil on the biodegradable fluids is that the effects of the contaminant (additives in the mineral oil) may take several hours or days to occur.

According to Theissen [7], some deteriorating effects may not even be caused by the mineral oil itself, but rather by metal-containing additives that attack the ester molecules and eventually lead to the formation of soap-like reaction products.

the oxidation of the biodegradable fluids, reaching a percentage variation of approximately 200% for Fluids A and B relative to the uncontaminated fluid. In Fig. 9, the extremely low oxidation stability of Fluid C when mixed with copper can be noted.

Fig. 9. Oxidation stability of Fluid C as a function of the contaminants

2.3 Influence of the Contaminants on Viscosity and TAN after the Oxidation Test Viscosity is one of the most important properties of hydraulic fluids, and also an early indicator of ageing.

The acidity of fluids as expressed by the total acid number (TAN) is of interest because it indicates the degree of fluid oxidation.

Fig. 8. Oxidation stability of Fluid B as a function of the contaminants

Fig. 10. Influence of the contaminants on viscosity after the oxidation test

The results presented in Figs. 7 to 9 clearly indicate that a water content of 1% can considerably increase

The acidity of new fluids (i.e. before the oxidation test) is normally determined by the type and

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concentration of ester and specific additive materials.

Both viscosity and TAN were chosen to describe the degree of ageing of the hydraulic fluids and the results for these parameters are presented in Figs. 10 and 11, respectively.

The ISO 15380: 2011 [21] standard specifies that the maximum increase in viscosity at 40 °C for these biodegradable fluids after a Baader oxidation stability test (DIN 51554-3:1978-09 [24] standard) is 20%.

According to Fig. 10, the maximum increase in the viscosity of Fluids A and B was 4% for all contaminants. For Fluid C, the increase in the viscosity was around 8% in the presence of water and mineral oil and approximately 45% in the presence of copper.

In Fig. 11, it is also possible to observe that the presence of water in high concentrations and of solid copper particles increases in the TAN of the three fluids, especially Fluid C, which reached very high values above 50 mg KOH/g.

or copper) exerts a significant influence on acid production in the fluids.

Fig. 12. Influence of the contaminants on viscosity after the hydrolysis test

Fig. 13 illustrates the adverse effect of water contamination on biodegradable fluids, generating the production of acids. Additionally, the presence of other contaminants, such as copper and mineral oil, in considerable quantities increases the production of acids and, consequently, promotes the ageing of the fluid and decreases usability.

Fig. 11. Influence of the contaminants on TAN after the oxidation test

2.4 Influence of the Contaminants on Viscosity and TAN after Hydrolysis Test The hydrolysis resistance of hydraulic fluid is a significant issue, as strong acids may ultimately be formed in the fluid and cause corrosion in components of the circuit.

A low influence of the contaminants on viscosity after the hydrolysis test is observed in Fig. 12, where the maximum variation was 5% for all analysed oils in relation to the new oil before the hydrolysis test.

In relation to the influence of the contaminants on the TAN after hydrolysis, Fig. 13 shows that the presence of contaminants (water, mineral oil, 422

Fig. 13. Influence of the contaminants on TAN after the hydrolysis test

2.5 Biodegradability Test For the biodegradability test, the methodology described by Eisentraeger et al. [15] was adopted. In this research, the extent of biodegradation is expressed as a percentage of the theoretical O2 uptake (ThOD) or

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CO2 production (ThIC) associated with the complete biodegradation of the test substance.

The biodegradability tests for Fluid A are demonstrated in Fig. 14. These tests were carried out at the Institute of Hygiene and Environmental Medicine at RWTH, Aachen University. The results show that the biodegradability in the Fluid A (new) almost achieved the OECD limit value of 60% for ready biodegradability [25].

As expected, mineral oil is far less degradable than the biodegradable fluids analysed in this study. In Fig. 14, it can also be observed that the biodegradability of Fluid A decreased by 10 and 12% when mixed with common mineral oil.

After the hydrolytic stability test, Fluid A presented a 4% decrease in biodegradability. The oxidation stability test revealed a biodegradability of 21%, which is considerably below the OECD limit for classification as a material of ready biodegradability.

Furthermore, the modified RPVOT test revealed that the effect of copper particles (as contaminant) on the oxidation stability of the fluids is not dependent on the amount of copper present. The results clearly show that a water content higher than 1% can considerably affect the oxidation and hydrolysis stability of the biodegradable fluids.

For all fluids analysed, the trend of the change in TAN resulting from oxidation is generally in the same direction as that resulting from hydrolysis. This implies that the conditions (type of contaminant) that exert a negative influence on oxidation stability also exert a significant influence on hydrolysis, both effects are expressed in the terms of an increase in the TAN. The oxidation and hydrolysis tests show a significant effect on the biodegradability of the Fluid A. In this study, this effect was demonstrated through the O2=CO2 Headspace Test with GC-TCD test.

As expected, the fluids analysed are more biodegradable than mineral oil, and their biodegradability is significantly affected by their mixture with mineral oil, decreasing by 10 to 12%.

4 ACKNOWLEDGEMENTS

Fig. 14. Biodegradability of Fluid A with different contaminants and ageing procedures

3 CONCLUSIONS In this study, the general impact of typical contaminants on the oxidation stability and hydrolysis stability of samples of commercial biodegradable hydraulic fluids has been presented. The commercial biodegradable fluids analysed were sensitive to contamination by copper solid particles, oxygen (oxidation), water (hydrolysis), common mineralbased hydraulic fluids, and also to the exposure to higher temperatures. This oil degradation results in the formation of acidic compounds, an increase in oil viscosity, decreased additive performance, and varnish formation.

According to the test results, it is initially possible to note the positive influence of the mineral oil on the oxidation stability of the biodegradable fluids, in contrast to the influence of water and copper.

This research was carried out in the framework of a bilateral research program supported by DAAD (German Academic Exchange Service) and CNPq (Brazilian National Council for Scientific and Technological Development). The support of these institutions, as well as the experimental support of the Institute for Fluid Power Drives and Controls and Institute of Hygiene and Environmental Medicine at RWTH Aachen University, is gratefully acknowledged.

5 NOMENCLATURE Bio-oil: Biodegradable fluid BOD: Biological oxygen demand Cu: Contamination by copper solid particles HYD: Hydrolytic stability test H2O: Contamination by water MO: Contamination by mineral oil OECD: Organization for Economic Co-operation and Development RPVOT: Rotary pressure vessel oxidation test OXID: Oxidation stability test TAN: Total acid number ThIC: Theoretical carbon dioxide production ThOD: Theoretical oxygen demand TIC: Carbon dioxide production

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6 REFERENCES [1] Jones, N. (1996). Managing used oil. Lubes’n’Greases, vol. 2, no. 6, p. 20-23.

[2] Majdič, F., Pezdirnik, J. (2008). Advances in water power-control hydraulics experimental research.

Strojniški vestnik - Journal of Mechanical Engineering, vol. 54, no. 12, p. 841-849.

[3] Backé, W. (1999). Water- or Oil-Hydraulics in the Future, Scandinavian International Conference on Fluid Power, Tampere, pp. 51-65.

[4] Majdič, F., Pezdirnik, J., Kalin, M. (2009).

Experimental validation of the life-time performance of a proportional 4/3 hydraulic valve operating in water.

Tribology International, vol. 44, no. 12, p. 2013-2021, DOI:10.1016/j.triboint.2011.08.020.

[5] Héry, C., Battersby, N. (1998). Development and applications of environmentally acceptable hydraulic fluids. SAE Technical Paper, no. 981493, DOI:10.4271/981493.

[6] Murrenhoff, H., Schmidt, M. (2002). Influence of ageing on fluid properties of environmentally acceptable fluids, 13th International Colloquium Tribology, Stuttgart.

[7] Theissen, H. (2009). Effects of contamination of biobased hydraulic fluids with mineral oil. Journal of ASTM International, vol. 6, no. 1, DOI:10.1520/ JAI101598.

[8] Murrenhoff, H., Schmidt, M. (2003). Analysis of aging of environmentally friendly hydraulic fluids and resulting effects on tribological fluid properties. The 8th Scandinavian International Conference on Fluid Power, Tampere.

[9] Rhee, I.-S. (2008). Assessing the biodegradability of hydraulic fluids using a biokinetic model.

Tribology Transactions, vol. 51, no. 1, p. 68-73, DOI:10.1080/10402000701739347.

[10] Rhee, I.-S. (2011). Biodegradable hydraulic fluids, in: Totten, G., De Negri, V.J. (eds.). Handbook of Hydraulic Fluid Technology. 2nd ed. CRC Press, London, p. 319-362, DOI:10.1201/b11225-9.

[11] Stammen, C. (2003). Elektrohydraulische Linearantriebe Entwicklung von Condition Monitoring Funktionen, Ölhydraulik und Pneumatik, vol. 47, no.

10, p. 640-648.

[12] Klaas, H., Gold, P.W., Murrenhoff, H., Schmidt, M. (2003). Analysing the results of fluid ageing using modern database techniques. Ölhydraulik und Pneumatik, vol. 47, no. 2, p. 96-101.

[13] ASTM D2272-11 (2011). Standard Test Method for Oxidation Stability of Steam Turbine Oils by Rotating Pressure Vessel. ASTM International, West Conshohocken, DOI:10.1520/D2272-11.

[14] ASTM D2619-09 (2009). Standard Test Method for Hydrolytic Stability of Hydraulic Fluids (Beverage

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Bottle Method). ASTM International, West Conshohocken, DOI:10.1520/D2619-09.

[15] Eisentraeger, A., Schmidt, M., Murrenhoff, H., Dott, W., Hahn, S. (2002). Biodegradability testing of synthetic ester lubricants-effects of additives and usage.

Chemosphere, vol. 48, no. 1, p. 89-96, DOI:10.1016/ S0045-6535(02)00084-X. [16] ISO 10708:1997 (1997). Water quality - Evaluation in an aqueous medium of the ultimate aerobic biodegradability of organic compounds Determination of biochemical oxygen demand in a twophase closed bottle test. International Organization of Standardization, Geneva.

[17] ISO 11266:1994 (1994). Soil quality - Guidance on laboratory testing for biodegradation of organic chemicals in soil under aerobic conditions.

International Organization of Standardization, Geneva.

[18] ISO 14593:1999 (1999). Water quality - Evaluation of ultimate aerobic biodegradability of organic compounds in aqueous medium - Method by analysis of inorganic carbon in sealed vessels (CO2 headspace test). International Organization of Standardization, Geneva.

[19] DIN 51558-1:1979 (1979) Testing of Mineral Oils; Determination of the Neutralization Number, Colourindicator titration. German Standard (Deutsches Institut für Normung), Berlin. (in German) [20] DIN 51562-1:1999 (1999). Messung der kinematischen Viskositaet mit dem Ubbelohde-Viskosimeter (measurement of the kinematic viscosity with the Ubbelohde-viscosimeter). German Standard (Deutsches Institut für Normung), Beuth Verlag, Berlin. (in German).

[21] ISO 15380:2011 (2011). Lubricants, industrial oils and related products (class L) - Family H (Hydraulic systems) - Specifications for categories HETG, HEPG, HEES and HEPR. International Organization of Standardization, Geneva.

[22] ISO 12937:2000 (2000). Petroleum products Determination of water - Coulometric Karl Fischer titration method. International Organization of Standardization, Geneva.

[23] ISO 6296:2000 (2000). Petroleum products Determination of water - Potentiometric Karl Fischer titration method. International Organization of Standardization, Geneva.

[24] DIN 51554-3:1978 (1979). Testing of mineral oils; Test of susceptibility to ageing according to Baader; Testing at 95 °C German Standard (Deutsches Institut für Normung). Berlin. (in German).

[25] OECD (1992). Guidelines for Testing of Chemicals: Summary of Considerations in the Report from the OECD Expert Group on Degradation and Accumulation. Organization for Economic Cooperation and Development, Paris.

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Strojniški vestnik - Journal of Mechanical Engineering 60(2014)6, 425-436 © 2014 Journal of Mechanical Engineering. All rights reserved.

DOI:10.5545/sv-jme.2013.1561

Original Scientific Paper

Received for review: 2013-11-21 Received revised form: 2014-01-27 Accepted for publication: 2014-03-03

A Simple Method for Evaluating the Sustainable Design of Energy Efficient Family Houses Praznik, M. – Butala, V. – Zbašnik-Senegačnik, M. Miha Praznik1,* – Vincenc Butala2 – Martina Zbašnik-Senegačnik3 1 Building

and Civil Engineering Institute, Slovenia of Ljubljana, Faculty of Mechanical Engineering, Slovenia 3 University of Ljubljana, Faculty of Architecture, Slovenia

2 University

Buildings have negative effects on the environment throughout their life cycle, i.e. from the phase of obtaining raw materials and manufacturing materials and components up to the sale, building and use through the final phase of removal when the building is decommissioned. In general, current legislation limits both the use of energy and the emissions allowed during operation, but does not limit the other parameters that define the design of contemporary sustainable buildings. Determining the sustainability of buildings should take place in the planning phase of the project, when it is still possible to influence the outcome. In this article, a simplified method using five chosen indicators is employed to evaluate the level of sustainability. The areas to be evaluated are energy efficiency, use of primary energy, CO2 emissions, costs, and the level of living comfort achieved. The evaluation using these indicators is carried out using three subjective and objective weighting methods, such that the final evaluation includes the viewpoints of an independent evaluator and the points of view of both the user and the state.

In the case of an assessment of the five indicators for new constructions, it is ensured that the designs for the new building in energy class A have the best total result of the assessment and therefore the best sustainable design, regardless of additional energy, environmental and economic investment during the building phase. With a suitable choice of heat supply, even new buildings in energy class C can come close to the effectiveness of a building design in energy class B. Keywords: energy efficiency, sustainable concept, single family house, efficiency evaluation, simplified method, primary energy use, CO2 emissions, living environment, life cycle cost

0 INTRODUCTION The life cycle of every building can be divided into six phases: obtaining raw materials, manufacturing of materials and components, sale, construction, use and maintenance of the building, and demolition. Each of these phases creates a burden on the environment in the form of energy use, as well as of emissions of CO2 and other harmful or even dangerous substances.

Individual phases of the cycle may take place at some distance from one another, which requires transportation. The use of energy and the associated emissions must therefore be looked at in the light of the entire life cycle of the building.

The built environment in Europe is responsible for 30 to 40 % of the total use of primary energy. This represents a great potential for reductions in the use of energy, as well as in the emissions of CO2 [1]. In the past two decades society has become more aware of this and therefore European legislation is demanding more energy efficient buildings [2]. However, reducing the use of energy in buildings does not mean that the user faces decrease in living comfort.

Sustainable development states that one must strive for buildings that provide equal or higher levels of living comfort with a limited use of natural resources and with the least possible negative effect on the

environment throughout the building’s total life cycle [3]. Users are becoming increasingly aware of this [4].

Buildings require energy both directly and indirectly. Directly, energy is needed in the construction, use and maintenance (operational energy), renovation and removal phases. Indirectly, energy is used to obtain the raw materials and manufacture the materials necessary to make the building and its technical installations functional (embodied energy). The percentage of energy needed in the construction, removal and transportation of materials phases is minimal [5] and is estimated to be around 1% of the total energy needed for the life cycle.

The phases of recycling the building are not treated as part of the life cycle in the majority of studies [6].

The greatest percentage of the total energy use in the building life cycle is represented by the energy necessary for the use and maintenance of the building and the energy put into the building during construction. Studies show that for conventional buildings the operational energy is 85 to 95% of the total energy use over the lifetime of the building, which functions in a cycle of between 50 and 80 years [7] and [ 8]. This is particularly true for buildings in cold or moderate climates [9] and [10]. Embodied energy is more dominant in milder climates [11].

The most important measure for decreasing the amount of operational energy necessary is to

*Corr. Author’s Address: Building and Civil Engineering Institute, Dimičeva 12, 1000 Ljubljana, Slovenia, miha.praznik@gi-zrmk.si

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increase the energy efficiency of the building [2]: with a greater thickness of built-in thermal insulation and windows with better thermal insulation, with an airtight thermal envelope, a building envelope without heat bridges, and the use of controlled ventilation with heat recovery. A number of types of energy efficient buildings have been developed using various concepts, such as very good low-energy houses, passive houses, zero-energy houses, self-sufficient houses, etc.

Analyses by the authors show that the optimal type of energy efficient house is in fact the passive house [12]. The use of energy in the built environment will increase in the future due to the increase in the use of materials and new components [13].

The need for energy to heat spaces is strongly decreased in the most energy efficient buildings. The focus on energy savings comes from the decrease in the consumption of the final energy in the use and maintenance phase. However it is the energy necessary for the other phases of the life cycle of the building that is mostly disregarded [3]. The fact is that measures taken to decrease the operational energy necessary cause the increased use of energy in the phase of manufacturing of materials and components.

Due to this, in the future more focus will have to be given to embodied energy. The total use of energy in low-energy buildings is, due to the higher percentage of embodied energy, even higher than in buildings with higher operational energy [14]. Measures to reduce the use of energy in the operation of the building therefore do not necessarily lower the primary energy use of the entire life cycle [13]. Therefore the choice of materials for a building with high energy efficiency becomes that much more important [15] and strategies for reducing the use of primary energy for the production of materials and components becomes key [16] and [17]. There are different ways mentioned in the literature to reduce the embodied energy of dwellings such as using low embodied energy materials, designing a lightweight/efficient structure to minimize material consumption, using recycled/ reusable materials, future refurbishment instead of demolition and use local sourced materials as much as possible. [18] and [19] The negative effect of materials on the environment is defined by two basic environmental parameters, which should be included in the evaluation. The first is concerned with the use of primary energy from non-renewable resources that is necessary for the manufacture of building elements (PECn.r. = primary energy content, non-renewable).

The second is concerned with the burden on the environment in the phase of manufacturing of building 426

elements via substances having a greenhouse effect, i.e. a potential for global warming (GWP100 = global warming potential, 100 years).

In addition to the energy and environmental parameters, the evaluation of the design of new buildings should also include economic and user parameters where suitable. The economic criteria, which is of key importance from the point of view of the owner and user, is usually the subject of a simultaneous optimization of the project energy efficiency, an investment in measures for efficient use, and use of renewable resources for the new buildings.

Use of low embodied energy and cost effective building materials in the building construction can significantly reduce the overall energy consumption and investment [20]. The percentage of the investment going for costs over the whole life cycle can reach up to 70%, therefore finding suitable concepts for energy efficient new buildings is of key importance [6] and [10]. The quality of the living conditions in contemporary new buildings can be indirectly increased by increasing their energy efficiency, however only through the use of suitable concepts for heating and ventilating spaces that take into account the specific characteristics of the new buildings.

A contemporary building must answer to a number of demands and therefore must be designed accordingly. In this article, a simple method is presented that allows us to check the suitability of the design of sustainable family houses using a small number of key chosen indicators. The simplicity of the new method ensures that planners use it in the design phase so that they seek the most optimal design for the building from the beginning.

1 METHODOLOGY FOR CHECKING THE EFFICIENCY OF THE DESIGNS There are various parameters one can use to evaluate the choice of technologies for the design of contemporary family houses: living, economic, energy and environmental. These parameters complement one another, but they can also exclude, which is consequently felt in the overall evaluation of the concept for the new building. For an all-encompassing assessment of the rationality of the design for energy efficient family houses it is therefore of prime importance to recognize the interaction of the effects of the above parameters. In order to evaluate the design in the planning process stage, one must create a method for the quick evaluation of energy efficiency and a simple method for a comprehensive evaluation of the design.

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From the viewpoint of the wider and above all timely use of these new methods for the preliminary evaluation of designs, i.e. in the idea phase of the design, the simplicity and the ability to quickly obtain a smaller number of pieces of data for the calculation are the most important aspects of the method. This is the basic difference between the new methods and the current methods used for the energy efficiency evaluation of new buildings, for example the PHPPâ&#x20AC;&#x2122;07 tool, i.e. the Passive house planning package - the energy balance and Passive House design tool [21], and the existing approach to a comprehensive evaluation of building design, which is, in practice, in the form of a voluntary environmental certification such as TQB (Total Quality Building Assessment) in Austria [22], DGNB (German Sustainable Building Council) in Germany [23], CasaClima Nature in Italy [24], HQE (High Quality Environmental standard) in France [25], Minergie in Switzerland [26] and the wider use of the LEED (Leadership in Energy and Environmental Design) [27] and BREEAM (Building Research Establishment Environmental Assessment Method) systems [28]. The above methods are extremely complex, require a lot of data and evaluate the building only after construction is completed, when improving the quality of the building or rather the sustainability concept is no longer possible.

1.1 Ranking Criteria and Methods of Ensuring Effective Design In this section the presented methodology comes out of a hierarchical ranking of various criteria and

methods in order to ensure the efficiency concept in new buildings (Fig. 1). The criteria are ranked on three levels: primary, secondary and tertiary.

The primary and secondary levels have a cause and effect relationship. At the primary level the criteria for energy demands (use of heating to heat a building) are ranked, while at the second level the environmental criteria (use of primary energy and CO2 emissions), economic criteria (costs) and living criteria (thermal comfort and air quality) are ranked. For these two levels it is possible to use a new method for a comprehensive evaluation of the energy efficiency of a single-family house, presented in this article, using five indicators (Qnh/Au, PECn.r., GWP100, Cost, LE) to identify the various effects on the buildingâ&#x20AC;&#x2122;s life cycle. Due to disproportionality comes the decision to separate the evaluation of primary energy use and CO2 emissions. The difference appears in the evaluation of primary energy use and CO2 emissions in the production and installation of materials and components, for which the conversion factors are different. Furthermore, various conversion factors are used for different energy carriers as well.

Higher values for these indicators indicate a greater negative environmental or living effect, as well as a higher energy or cost burden. The values of the indicators are assigned to different scenarios of design ideas for new buildings. An individual indicator will have a maximal value for the least favourable scenario. From the viewpoint of sustainable design, the optimal solution has the lowest total value for the five indicators. Given the objective and subjective estimates of the criteria for the secondary

Fig. 1. Representation of the first two levels of demand or the criteria for evaluation using 5 key indictors A Simple Method for Evaluating the Sustainable Design of Energy Efficient Family Houses

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level, the indicators can be shaped by weighting them differently. With an objective approach, all the indicators have an equal effect on the evaluation.

From the subjective point of view of the user or the state demands for new buildings it is possible to give different indicators different effects in the process of evaluation.

In the ranking of criteria for the energy efficiency of new buildings we can, in the lower so-called tertiary level of criteria, rank the architectural and technological measures for achieving a higher level of energy efficiency and the measures for the co-use of renewable energy sources in the energy balance of the buildings. Research by the authors shows [29] that an effective design starts with the architecture of the building, such as defining the size of the building, heat zoning, floor-plan design, creating the building envelope, and the orientation of the glass parts of the facade of the building. Technological solutions for construction must then be sought, where it is equally important to weigh both the elements of construction joints from the viewpoint of heat protection achieved as from the point of view of the environmental burden, which is linked to the manufacture and construction of the materials themselves [30]. The heating and ventilation system must also be suitably adapted to the characteristics of new building. [31].

It is only through this that an energy efficient new building can reach its energy efficiency potential and create the optimal living conditions [32]. The heating system that provides heating for the building is of key importance for a comprehensive evaluation of the influences on the new building’s life cycle.

Analyses have shown [33] that the choice of systems for heat generation, which includes in large measure the use of renewable sources of energy, is of key importance. A suitable system for the generation of heat can also strongly influence improvements in the environmental and economic indicators in less energy efficient houses. In the case where such a system is used in energy efficient buildings built with wood and thermally insulated using natural materials, the wider environmental footprint of the building is minimal.

The key qualitative parameters through which the energy efficiency of the new building can be easily determined in the design phase should be placed at the level of the definition of measures, when calculations of the energy balance of buildings including the use of a larger number of known project parameters are otherwise not possible. The project leader must integrate the energy efficiency, environmental burden and investment in the construction of the building when choosing the technical building system, which 428

is in practice only possible using simple procedures.

Therefore, this phase of planning must incorporate knowledge of all relevant mechanisms.

1.2 Indicators for a Comprehensive Evaluation of the Efficiency of Designs In energy efficient residential buildings we use various levels of indicators to show the rationality on many levels. By using the values of various indicators, which are ranked by criteria levels (Fig. 1), we can evaluate the wider effects of the designs of new buildings.

The starting point, i.e. the primary level of evaluation, is the energy efficiency of the building.

This is the causal level, where only the indicator for the use of heat for heating the building QNH/Au is placed. This level of evaluation has been carried out in the past and used to judge the suitability of designs for new buildings (e.g. regulations concerning new buildings) and operations of buildings (e.g. energy check-ups for new buildings). The viewpoints and interests of the various parties involved in the evaluation are equal at this level.

On the secondary level of evaluations of buildings, which can be called the »effect« level, four indicators can be used to evaluate the key effects of the building on the use of primary energy, CO2 emissions, costs and living environment. This is a new level of evaluating buildings, which has not yet been applied in practice. Because the interests and priorities of the various parties involved (e.g. state, investors) are different with regard to the four indicators, the viewpoints at this level regarding the efficiency of the building design may be completely different. Consequently, the two involved parties may weigh the indicators used in the procedure to evaluate the building concept differently. For the user of the building, living comfort and costs are more important.

While from the state point of view, the use of primary energy and CO2 emissions are regarded as more significant and therefore weighted more heavily.

The tertiary level of evaluating designs of new buildings concerns evaluating the engineering measures from various fields of expertise, which ensure that the demands of the primary and secondary levels are met. At this level we have to optimize and bring into accord the various indicators for architectural, construction and energy designs and take into account what constitutes efficiency from the point of view of the user and the state. The demands on this level are judged internally, only at the level of the involved professionals. Therefore it is not necessary

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to directly include this level of internal evaluation in the process of comprehensively evaluating buildings, since the results of the enacted measures are indirectly evaluated through their effects on the previous two levels.

•

the owner and use of the building and therefore a higher economic efficiency of the design, the indirect influence of the new building concept on living comfort: a low value for the LE (living environment) indicator means better living conditions and therefore a more suitable design for the user.

1.3 Possible Approaches to Weighting the Indicators

Fig. 2. Effects of weighting the five key indicators used in the building evaluation

Determining the effects of the project design of buildings using the five chosen indicators with values between 0 and 100%, as shown in the first and second level of the criteria, is suggested in order to carry out a comprehensive evaluation of the rationality of a new building. Using the five indicators we can evaluate the effects of the building design on: • the achieved energy efficiency: a lower level for indicator QNH/Au shows a higher energy efficiency of the design, • the use of primary energy for the construction of the building and the generation of heat during operation: a low value for the PECn.r. indicator shows a higher environmental efficiency of the design, • the generation of CO2 emissions in the manufacturing of materials and construction phase, as well as the generation of heat during operation: a low value for the GWP100 indicator means a lower environmental burden and therefore a higher environmental efficiency of the design, • the costs for the construction of the new building and the energy costs for the generation of heat during operation of the building: a low value for the Cost indicator means a lower cost burden on

Different weighting proportions between the five indicators are shown comparatively for the objective evaluation and for both possible forms of the subjective evaluation, i.e. from either the state or user point of view (Fig. 2).

An independent evaluator can objectively assess the new building using an equal or equivalent weighting of all five indicators (Fig. 2, Weighting A).

The two cases of subjective evaluation of the new building are typical and look as if they would arise out of a wider state viewpoint or from the viewpoint of the user of the building. In the first case, one assigns a double weighting to the indicators for the use of primary energy and CO2 emissions, which are most relevant from a state point of view (Fig. 2, Weighting B). In the second case (user), one assigns a double weighting to the indicators for costs and living comfort (Fig. 2, Weighting C).

2 CALCULATION APPROACHES FOR DEFINING THE VALUES OF THE INDICATORS The values for the indicators are assigned as percentages when comparing the results obtained or estimated for various designs. Therefore, the highest value (100%) for each of the indicators (QNH/Au, PECn.r., GWP100, Cost, LE) is assigned to the variant of the design that has the least favorable cumulative result. For the other variants of the design, the value of the indicator is proportionately lowered depending on the degree to which its results stand out from the maximal value for the comparable group of variants.

2.1 Determining the Value of Indicator QNH/Au The value of indicator QNH/Au is assigned on the basis of the result of the calculation or estimation of the energy balance of the building. A quick estimation of the building’s energy need for heating can be obtained using a simple calculation method, given that one understands the key quantitative parameters of the design phase. In an article by the authors [34], a new calculating method for the simple estimation

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of energy consumption of buildings in a sample of 106 representative Slovenian highly energy efficient buildings was created using key qualitative parameters. An analysis of the correlations within the statistical sample of representative buildings in the study confirmed the assumption that for the estimation of energy consumption in contemporary singlefamily houses it is possible to use a small number of influential qualitative parameters linked to the design and use of the building, the characteristics of its heat envelope and the characteristics of the ventilation system. The new method can be used for a quicker evaluation in the form of two approaches depending on the available starting parameters. This approach for estimating the energy flows, which we can use in the above methodology, is linked to the parameters, which usually require a higher level of preparation of the starting data (Eq. (1)).

Q NH / A u ≈ ( 78.3 × H 'T × f d + 64.2 × n v ) − −ηG × ( 4.9 × q i / A u + 78.7 × ASF / A u − 2.3) . (1)

These key parameters are: specific transmission heat loss coefficient of the building envelope H’T (W m-2 K–1), building envelope surface area to heated surface area ratio fd (m2 m–2), total equivalent air exchange per hour in the building nv (h–1), internal heat sources qi (W), building treated floor area Au (m2) and weighted window surface ASF (m2).

evaluation of individual new buildings, e.g. when forming the key parameters for the idea design, identifying the effects of possible improvements or, in this case, when assigning the values of the indicator QNH/Au. 2.2 Defining the Value of the Indicators PECn.r., GWP100, and Cost In an environmental analysis of the building materials, building components and installation systems in new buildings we can limit ourselves to the time period of their manufacture. The project leader can obtain key data for all the planned systems for determining both environmental indicators (i.e. use of primary energy and CO2 emissions) using publicly accessible internet databases, e.g. ref. [35]. To further analyse the systems, one can also obtain any necessary data from the equipment producers and construction materials manufacturers regarding their investments in these areas for an on-going evaluation of the cost indicator.

We can limit ourselves to a period of 60 years when determining the value of the parameters in the building operation phase. From an estimation of the electrical energy use and fuel use that are necessary to generate heat, we can use known conversion factors [36] to estimate the consequent primary energy use and CO2 emissions, along with the associated estimated energy costs. In the above manner, we can also estimate in a simple manner the values according to the maintenance and upkeep of the building envelope and the energy systems for the time period of operation. On the basis of these values, we can also collect data on the consumption of primary energy, CO2 emissions and the associated costs.

2.3 Defining the Value of Indicator LE

Fig. 3. Correlation between estimated heat demand for space heating and the actual calculated values

This is consequently seem in the higher correlation between the results of the evaluation, i.e. in their lower deviation from the actual calculated values, which are the real result of complex calculated energy balances (Fig. 3). Due to these characteristics, a more complex model is used in the preliminary 430

In assessing the value of the indicator LE for different design variants, which are purely of a technological nature, it is not necessary to address the effects of architectural design, since it is the same for all cases.

All treated variants have therefore equal conditions with respect to the architectural design of the glazing parts of the building envelope, orientation, and consequently their natural lighting of living spaces.

The value for indicator LE is assigned by evaluating the effects on living comfort in three areas: • The achieved negative effect on the thermal comfort of the space, which is largely a consequence of the thermal protection offered by the building envelope, which is assigned a value from 0 to 35%, for example 0% for variants

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•

•

with the highest efficiency thermal envelope or 35% for variants with a still acceptable level of thermal protection and temperature asymmetry.

When allocating values, thermal comfort can be estimated in proportion to thermal envelope characteristics, e.g. calculated value H'T, Uw, etc.

The negative effects of the planned heating system for ensuring thermal comfort are evaluated within the same size class. A value of 0% is assigned to a system with minimal negative effects on living comfort or 35% for a system with still acceptable functional characteristics. In the evaluation of the heating system effects on thermal comfort it is necessary to evaluate the characteristics of the designed systems. Those can have in certain combinations different effects. E.g. lowtemperature floor heating system in a low-energy house is in precedence over conventional radiator heating system, in a passive house floor heating system is less responsive and has more negative impact on the living comfort, as e.g. wall heating system or a heating system, which is integrated in the central ventilation [31].

The third area concerns the negative effects of the means of ventilating spaces, which is expressed through a determination of air quality and associated living comfort. A value of 0% is assigned to a ventilation method with minimal negative effects and 30% to a ventilation system with an acceptable effect on living comfort. Assessing the impact of the ventilation system in the living comfort takes into account characteristics of different design solutions. Less favourable impacts on the living comfort usually has a natural ventilation system. E.g., central ventilation systems as well have an advantage over local systems. Systems with devices that enable high-heat recovery and humidity are in advantage over devices that only provide a less efficient heat recovery.

3 CASES OF EVALUATIONS OF DESIGN METHODS USING THE PROPOSED METHOD

Use of this method for a comprehensive evaluation of buildings using the five indicators is shown for five different energy efficiency concepts on one selected family house. Variants V1 to V5 of this model house have different energy efficiencies due to different thermal envelope components, different heat generation systems and different ventilation systems.

A single architectural model using a wooden construction, with a technologically modified

heat envelope, different classes of targeted energy efficiency QNH/Au and different systems for heat generation, is used to allow comparisons between the buildings. Table 1 shows the key data. Other common parameters of the model family house are: heated area of the building Au = 133 m2, thermal surface envelope A = 454 m2, window area Aw = 30 m2, shape factor fo = 0.68 m2 m–3.

• Variant V1 design fulfils the minimal energy efficiency demands. Due to the greater heat needs for heating the space, a more economical and environmentally efficient system was chosen to generate heat, i.e. a boiler apparatus with pellets and solar energy panels for providing hot sanitary water.

• Variant V2 has a more energy efficient building design. To maintain the investment value, a simple system for generating heat using fossil fuels was chosen, however this is less effective economically and environmentally in the long run.

Variant V3 is a very good low-energy building, where heat is generated by a heat pump.

• Variant V4 is designed as a standard passive house. The heating system is integrated into the ventilation system, which lowers the investment in installations.

• Variant V5 is a slightly improved new building both energy-wise and environmentally, at the standard of a passive house. In order to give the building better environmental indicators, the envelope is thermally insulated using cellulose flakes in place of mineral wool.

The analysed case refers to new construction in reference climate location for Slovenia (city Ljubljana, heating degree days HDD = 3100 K d a−1). All data, linked to a reference location, are used in calculating the values for all indicators. For individual assessment of design concepts, as proposed by the method described, while evaluating the indicator QNH/Au and operating values for indicators PECn.r., GWP100 and Cost, it is necessary to use calculated values for all major parameters as they apply to the micro-location of a new construction.

The results of primary energy use, CO2 emissions and costs for the construction phase and operation are summed due to the integrity of the assessment concepts with indicators. The diagrams (Figs. 4 to 6) show their values comparatively, for the separate phases of the construction and operation. The results on primary energy consumption and CO2 emissions were, for the construction phase, calculated for each variant using the online tools [35]. For the operational phase the

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Table. 1. Key data presentation for the five different single family house design concepts Variant

QNH/Au [kWh/(m2a)] Um [W/(m2K)] Uw [W/(m2K)] n50 [h–1] Window frames Thermal envelope Ventilation system Heat generation Heating system

V1 50

V2 40

V3 25

V4 15

V5 10

0.25

0.21

0.20

0.16

0.14

1.0

0.90

0.90

0.75

0.75

1.0

1.0

0.8

0.6

1.0

wood mineral wool and extruded polystyrene mechanical with 90% heat recovery heat pump, horizontal ground collector integrated in ventilation

wood cellulose flakes and extruded polystyrene mechanical with 90% heat recovery heat pump, horizontal ground collector integrated in ventilation

PVC expanded polystyrene and mineral wool natural ventilation pellets boiler, thermal solar system radiator system

Materials: PVC wood expanded polystyrene mineral wool and mineral wool natural ventilation mechanical with 85% heat recovery gas condensing boiler, heat pump, horizontal thermal solar system ground collector radiator system floor heating

latter was determined according to the annual use of energy carriers using data from energy distributors and certain national conversion factors [36]. Data on investment for individual variants were obtained from the selected contractor, which excludes divergences

in the assessments by different companies. The data related to renovation and modernization are evaluated according to the inventory of necessary works on the building over the years. E.g. depending on the lifetime it is necessary to replace equipment and components in the systems of heat generation and ventilation, foreseen are as well works on maintaining the outer surfaces of the thermal envelope and such alike.

The data forming the basis for the assignment of the values of indicators PECn.r., GWP100 and Cost are calculated for the five variant building designs and are shown (Figs. 4 to 6) from the viewpoint of the investment (construction and renovation) and operation. On the basis of this data, the value of the indicators is assigned, which are then compared for all five designs for new buildings (Fig. 7).

Fig. 4. The use of primary energy for the five variants (60 year period)

Fig. 6. The costs for the five variants (60 year period)

Fig. 5. CO2 emissions for the five variants (60 year period)

432

Primary energy consumption and associated CO2 emissions for the transportation of building materials in the analysed case have not been taken into account.

This stems from the specifics of the construction

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(V1)

(V2)

of family houses in Slovenia, for which almost exclusively apply building materials and products of domestic manufacturers (e.g., wood, brick, concrete, thermal insulation, windows), which are typically produced within a radius up to 150 km depending on the location of new buildings. When at design stage the use of components and materials is intended, which clearly reflect the increasing energy needs for transportation, the designer must consequently take this into account in the calculation, as this is an integral part of the total energy requirements during the construction phase of the building.

A comprehensive evaluation of the different design variants can take place in the three previously described manners. In the objective evaluation (Weighting A), all indicators have the same weighting in the total score. In the two subjective approaches to the evaluation (Weighting B and C), the indicators are given different weightings (Fig. 8) according to the different viewpoints of those involved.

These results confirm the assumption that the optimized design concept for the most energy efficient new building, which is represented by both passive house variants (V4 and V5), also has the best or rather the lowest total score for the comprehensive evaluation, which also parallels the objective and both subjective evaluation methods.

(V3)

(V4)

Fig. 8. Graph of the values for five key indicators for five variant designs for new buildings

(V5) Fig. 7. Comparison of the evaluation of indicators for the new building variants with different indicator weightings

For variant V5, the results of the evaluation are between 58 and 61% (Fig. 8), and for variant V4 between 66 and 73%. The very good low energy house concept (variant V3) comes next and is ranked third with a score between 77 and 80% for the comprehensive evaluation according to the three

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assessment methods. The worst result of the total evaluation was the less energy efficient new building (variant V2), where heat was mostly generated using fossil fuels. This amount (100%) is the total for all three weighting methods. A comprehensive evaluation of the designs also confirms that even a less energy efficient new building (variant V1) can be improved by applying suitable correctional methods of thermal supply, i.e. by using totally renewable sources of energy. Variant V1 achieved a score of between 76 and 93% due to this kind of measure.

5 CONCLUSION Energy efficient family houses generally provide residents a high quality of living comfort, thus thermal comfort, daylight and air quality. Improved thermal insulation of the building envelope ensures appropriate internal surface temperatures. Architectural solutions in the design of the building envelope include larger glazing surfaces, thereby more daylight. A central ventilation system, that all buildings have, continuously ensures the quality of air in living spaces. To maintain the expected temperatures in living spaces is of paramount importance to plan adequate heating system and its control, which should enable dynamic adaptation to changes in individual rooms. It should be stressed that the first step to provide efficient concept for modern family house is optimal architectural design. By exploiting the natural resources of new construction’s micro location and with the appropriate building design and orientation, we define any consequential energy requirements and technological measures. Before using the presented method is therefore necessary to ensure that all previous architect’s decisions were optimal. Only after this verification of the architectural concept, we are able to design different technological variants, which are subject to assessment by the presented method.

The demand for higher energy efficiency in new single family houses can be understood as the need for heat to heat spaces (QNH/Au), which is fundamental and at the same time an established criteria for judging the design of new buildings in Slovenia. The judgement of designs for new buildings include the regulations set by domestic legislation in the area of energy efficient buildings [37] and the methodology for determining the energy characteristics of buildings [38], as well as the fulfilment of criteria for allowed primary energy use and emissions of CO2 during the operation of the building. The above three criteria, which are checked via calculations during the planning process for the new building, only 434

concern the operation of the building. Because these calculations do not take into account the other phases of the building life cycle, this kind of evaluation is not complete or rather not comprehensive enough from the point of view of sustainable design for new buildings.

With the aim of creating a timely and comprehensive evaluation of the design for contemporary new buildings, a simple methodology has been developed that can be used by project planners at the starting phase of planning. Five key indicators are used to evaluate different variants of conceptual designs for new buildings, whose values are determined using simple calculation methods. The values are determined for the operation phase and the construction and renovation phase. Presented method for assessing different concepts of energy efficient family houses is straightforward. It is intended for experienced engineers who use the software for the design of modern family houses [21] and [35], and simple calculations to obtain the information necessary to assign a value to each indicator. The method is designed to assess the concepts of the family house. For the evaluation of more complex cases, which are typically larger public or commercial buildings, with a similar approach, it would be necessary to introduce additional indicators that are not needed for the modern family houses (e.g. related to the use of energy for cooling). The aim of using this method is to obtain a preliminary assessment for the various designs, which includes the living, economic, energy and environmental parameters.

Using the obtained evaluation the project planner and investor can decide to choose those design variants with the best total result in a rational way. It is demonstrated in this paper that with using an optimal combination of different characteristics of the chosen variant proves to be the most sustainable design.

The results of the evaluation using the new methodology in the case of different design variants for family houses show that the solutions for the most energy efficient building (two design variants of passive houses in energy classes A1 and A2) have the best total result out of the assessment, taking into account the objective and subjective methods of evaluation. A precondition for such a favourable result is the optimization of the building construction and of the kind of heat supply used. By using materials that are more environmentally friendly in the phase of manufacturing and building (e.g. wood, cellulose insulation), we can ensure fewer negative effects for highly energy efficient buildings by comparison with less energy efficient new buildings. By using suitable

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heat supply systems, which utilize renewable sources of energy (e.g. wood biomass, solar radiation), we can decrease the negative effects over the total life cycle, even for less energy efficient buildings (the design variant with energy class C) and come close to the effectiveness of more energy efficient buildings (design variant in energy class B).

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Praznik, M. – Butala, V. – Zbašnik-Senegačnik, M.

Strojniški vestnik - Journal of Mechanical Engineering 60(2014)6, 437-446 © 2014 Journal of Mechanical Engineering. All rights reserved.

DOI:10.5545/sv-jme.2013.1366

Received for review: 2013-08-13 Received revised form: 2013-12-03 Accepted for publication: 2014-01-24

Original Scientific Paper

RBF Neural Network Based Sliding Mode Control of a Lower Limb Exoskeleton Suit Song, S.– Zhang, X. – Tan, Z. Shengli Song* – Xinglong Zhang – Zhitao Tan

PLA University of Science & Technology, Department of Mechanical Engineering, China A new force tracking control algorithm of partial actuated lower limb exoskeleton suit, which is designed for enhancing human motion is presented in this paper. Firstly, a mathematical model of the electro-hydraulic servo system was created, and equations for the frictions in the hydraulic valve and actuator were obtained. Secondly, the appropriate observer based on the estimated functions and the measurement error equations are presented for the sliding mode control algorithm. Thirdly, a sliding mode controller with applicable surface coefficient has been designed for force tracking control of the servo system. Fourthly, so as to reduce the error caused by the unchangeable surface of the sliding mode control, a radial basis functions (RBF) neural network control algorithm has been introduced to offset the disadvantage of the sliding mode control by moving the sliding surface effectively. Finally, the simulation results under conditions of different frequencies and the trial results based on the human motion of sliding mode control and the RBF based sliding control are presented, which indicate that RBF based sliding control provides a better performance than regular sliding mode control.

Keywords: exoskeleton suit, hydraulic servo system, force tracking, sliding mode control, RBF neural network

0 INTRODUCTION Heavy goods are usually transported by vehicles.

However, natural disasters such as earthquakes or debris flow eruption, soldiers in the field, workers going up and downstairs, and other situations force humans to transport heavy goods on foot. A lower limb exoskeleton suit is a good way of easing the burden on the body and enhancing human motion. A new lower exoskeleton suit with a hydraulic actuator, as well as a spring in each knee and a spring in each hip and ankle, is presented in Fig. 1. Control of the hydraulic servo leg is necessary to provide a high-level humanmachine interaction performance. During operation, the computer computes and transmits data from sensors in the suit to the controller in near real-time, an input signal is generated by the controller to drive the actuator to offer an assistant force to the human. The problem here is that in systems with high sensitivity to external load, the system performance will be proportional to the precision of the mathematical model [1]. Force control of uncertain hydraulic servo systems has been documented for several years since it has many advantages such as robustness and higher precision, but less control over position and velocity.

Uncertainties in structural stiffness and hydraulic plant parameters require a “robust approach to the design of the force control” [2]. Many control algorithms, such as optimal control [3], predictive control [4], classical H∞ theories [5], neural network [6], and fuzzy control [7] and [8], have been applied to protecting structures subjected to external disturbance excitation and to eliminating uncertainties. Hence, the system should have both good stability and good speed of response.

Knee spring Sole

Hydraulic cylinder Ankle spring Shank Flexion/Extension Abduction/Adduction

Fig. 1. Structure of ankle and shank; the flexion/extension freedom is driven by a cylinder and a spring; The abduction/ adduction and rotation freedoms are passive

Control of the servo systems represents a significant area for control applications [9]. Sliding mode control solves the problems of uncertainties, nonlinearization and robustness of the electrohydraulic servo robot well by giving satisfactory control performance. During the last several years, sliding mode control has attracted considerable attention [10] and [11]. However, the down side of this strategy is the chattering of control action due to its discontinuous switching part in the control algorithm.

Therefore, a boundary layer is needed to change the performance [12]. However, the boundary layer helps to decrease the chattering problem around the sliding surface at the expense of tracking performance [13] and [14]. Quick damping, a decrease in switching effect and increase in performance have been examined in the studies where a sliding mode controller with a moving sliding surface is used [15]. Therefore, many modified sliding mode control algorithms have been

*Corr. Author’s Address: Department of Mechanical Engineering PLA University of Sci. & Tech, No. 88, R. HouBiaoying,Dist. Baixia, Nanjing City, China, shl_s@163.com

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created to improve the performance of the above defects [16], such as intelligent complementary sliding mode control [17].

RBF neural networks were first presented in 1988 [14] and have been applied to nonlinear systems because of their good performance and simpler network structure, which averts unnecessary and tedious calculations compared to the multilayer feed-forward networks (MFN).

Specifically, nonlinear functions set with arbitrary accuracy can be approximated by RBF neural network [18] and [19].

So as to eliminate the disadvantages of sliding mode control, a new RBF network based sliding mode control with moving surface whose slope is determined by the RBF network structure is proposed in this paper. The results of the improved and regular sliding mode control are presented and examined.

1 MODEL OF A HYDRAULIC SERVO SYSTEM As shown in Fig. 2, high-pressure oil from the oil pump goes into the port valve through hole P and into the left (right) chamber of the valve core via the valve core hole. The high-pressure oil creates a right (left) pushing force to overcome resistance on the right (left) side of the core valve, which pushes the valve core to the right (left) most position.

A

Load

B

u p1 q1

Accumulator

xv

p2 q2

qL = K q xv − K c pL . (1)

The cylinder flow can be written as: 1 qL = (q1 + q2 ). (2) 2

When oil flows into the cylinder, the flow of the left and right chamber is expressed by: V q1 = A1 x c + Cin pL + Cec p1 + 1 p 1 , (3)

β

controller

V2 p 2 , (4) β

and that:

V1 = V0 + A1 xc , (5)

V2 = V0 − A2 xc . (6)

Combining Eqs. (1) to (6), the flow of cylinder becomes: C + Cec V A + A2 qL = 1 x c + Cin pL − in pL + 0 p L . (7) 2 2 2β

Defining the relevance of pressure of the load to that of chambers as:

Fdesire

Pump Relief valve Filter Reservoir

Fig. 2. The hydraulic system contains: a reservoir, filter, pump, checkvalve, reliefvalve, accumulator, servo-valve and cylinder

The oil flows through the servo-valve to actuator to drive the external load (leg) and the measured value from force sensor is transmitted to the controller, which will compute and generate input signal to the servo-valve after comparing the measured force and desire force. Valve openings are changeable according to the input signal from the controller, which determines the pressure and flow in the acting chamber of the actuator.

438

q2 = A2 x c + Cin pL − Cec p2 −

Considering the movement of the actuator, the force of the cylinder driving the external load can be written as follows: FL = A1 p1 − A2 p2 . (8)

Check valve

M

The accumulator is designed to restore energy in high pressure and release energy in low pressure. The relief valve is used to stabilize the outlet pressure of the oil pump.

The four-sided valve equation for flow is:

dp1 1 dpL dp = = − 2 . (9) dt 2 dt dt

In order to provide positional control of the robot, the dynamic equation between the load force, angular acceleration and the spool position should be concerned, which can be defined by: 1

ϕ = ( M ( FL + Ff )) − mgr sin(ϕ )), (10) J

xc = l (ϕ ) − l0 − xc 0 . (11)

The major components of friction are Coulomb force, Viscous force, Stribeck effects and position dependent forces [20]. However, experiments carried out using industrial manipulators have shown that position dependence is relatively weak and can be

Song, S.– Zhang, X. – Tan, Z.

Strojniški vestnik - Journal of Mechanical Engineering 60(2014)6, 437-446

neglected for most purposes [21]. The friction model of this hydraulic servo system can be expressed by:

2

Ff = [ FC + ( FS − FC )e − ( xc / vs ) ]sgn( x c ) + bx c . (12)

The spool position is changeable by the input signal, which is expressed by [17]: dxv 1 = (k s u − xv ), (13)

dt τ The state space equations can be expressed by:   1 ϕ = J ( M ( FL + Ff ) − mgr sin(ϕ ))   F = β ( A1 + A2 ) ( K x − A1 + A2 x q v c  L 2 V0 . (14)   − 2 K c + Cin + Cex ( 2 FL + A2 − A1 p )) s  A1 + A2 A1 + A2 2   dxv = 1 (k u − x ) v  dt τ s Simplifying Eq.(14) will give a visualized expression for the state space equations:

  1 ϕ = J ( M ( FL + Ff ) − mgr sin(ϕ ))  , (15)  FL = n1 xv − n2 x c − n3 FL + n4  dx 1  v = (k s u − xv )  dt τ

where:

n1 = n3 =

β ( A1 + A2 ) K q V0

,

n2 =

β ( 2 K c + Cin + Cex )

n4 = −

V0

β ( A1 + A2 ) 2 2V0

,

2V0

The sliding mode control observer can be given

 i

 F L = n1 x v − n2 x c − n3 F L + n4 − ε1 F o − k1 sgn( F o ) . (17) i 1  x v ) − ε 2 F o − k2 sgn( F o ) x v = α F o + (k s u −  τ The error equation of the measurement system can be written as:  F = n x − n x − n F + n − ε F − k sgn( F ) 1 v 2 c 3 L 4 1 o 1 o  L  1 . (18)  x v = (k s u − x v ) − ε 2 F o − k2 sgn( F o ) τ  L − F  F = F o  o 3 CONTROL AGORITHM 3.1 Sliding Mode Controller Sliding mode control is an effective approach for robust control of nonlinear systems with a variable structured surface. The control action is determined by a switching state space to reduce the order of the system, which requires a reasonable range of uncertainties to ensure the stability of the system during the sliding mode control. A block diagram of RBF introduced into sliding mode control is presented in Fig. 3.

If we let the desired output be FL then:

,

β (22 K c + Cin + Cex )( A2 − A1 )

by:

e = FL − Fd . (19) Sliding mode function can be designed as:

ps .

2 OBSERVER DESIGN In order to deal with nonlinear control methods, it is necessary to design an observer for the sliding mode controller. A sliding observer is robust to parameters uncertainties by estimating the load force and spool position.

The system equations can be denoted by:  FL = n1 xv − n2 x c − n3 FL + n4  1 

. (16)  x v = (k s u − xv ) τ   y = Fo

s = ce + e, (20)

where c > 0.

Design a Lyapunov function as:

V=

1 2 s . (21) 2

From Eqs. (19) to (21) into:

s = ce − e = c( FL − Fd ) + ( FL − Fd ). (22)

Combining Eqs. (15), (17) with Eq. (22) and  replacing FL by FˆL , then:

RBF Neural Network Based Sliding Mode Control of a Lower Limb Exoskeleton Suit

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L + F ) + n ) + s = c(n1 ( x v + x v ) − n2 x c − n3 ( F 4 L

The algorithm of the RBF network is: || x − c j || 2  )  h j = exp( bj . (26)   K ( x) = W *T h( x) + α 

i

i

+ F )) − cF − F = + (n1 ( x v + x v ) − n3 ( F L L d d

= (c − n3 )(n1 ( x v + xv ) − n2 x c − i

L + F ) + n ) + n (

− n3 ( F 4 1 x v + xv ) − cFd − Fd = L

 T , and The network input is presented as x = [e,e] the output of RBF is:

L + F ) + o + n1 k u − = o1 ( x v + xv ) − o2 x c − o3 ( F L 4 s τ − cF d − F d ,

o1 = n1 (c − n3 ) −

n1 , o2 = n2 (c − n3 ), τ

Then the control input can be written as: u=−

n o3 = n3 (c − n3 ), o4 = n4 (c − n3 ), o5 = 1 k s . τ So V = ss = s (o1 ( x v + x v ) − o2 x c − L + F ) + o + o u − cF − F ). (24) − o3 ( F 4 5 L d d

1 L + o − cF − F + K sgn( s )). (25) (o1 x v − o2 x c − o3 F 4 d d o5

3.2 RBF Network Controller In the sliding mode control algorithm, K is taken as the sliding surface, which keeps moving during the entire process of control. If the slope of the sliding surface gets bigger, the system will be more stable but the regulating process will take longer. So as to eliminate the disadvantage of the sliding surface, we use an RBF network (Fig. 4) to approximate K. W1

sgn( s ). − cF d − F d = o1 xv − o3 F L + K

y1

T x = [e,e]

e

layer1 layer3 layer2 Fig. 4. RBF neural network structure

y2

Only minority connection weights have effects on the output of the network, which makes the study velocity of RBF rapidly and leads to a high training speed. In order to increase the precision of the approximation, a large bandwidth is necessary.

440

(30)

According to gradient descent method, the parameters can be updated as: ∂F ∂u ∂K ∂E ∂e ∆W = −η1 = −η1e = −η1e L , (31) ∂W ∂W ∂u ∂K ∂W where: ∂FL k s ≈ n1 , 1. ∂u τ 2.

∂u 1 = − sgn(s), ∂K o4

3.

∂K = h( x)sgn(W T h( x)). ∂W

W2

e

1 L + o − cF − F + K sgn( s )). (29) (o1 x v − o2 x c − o3 F 4 d d o5

Using Eqs. (23) to (27), the derivative of the sliding surface can be expressed as: L + F ) + o + n1 k u − s = o1 ( x v + xv ) − o2 x c − o3 ( F L 4 s τ

The input signal can be obtained by: u=−

The performance index function of the training is: 1 E = e 2 . (28) 2

(23)

where:

 *T h( x) + α . (27)  ( x) = W K

The weight adjustment algorithm is given by:

∆W = W (t − 1) + ∆W (t ) + α (W (t ) − W (t − 1)), (32)

where η1 ∈[0,1] ; is the learning rate and α ∈[0,1] ; is the momentum factor.

4 RESULTS OF SIMULATION AND EXPERIMENT 4.1 Simulation In this section, a number of simulation results are presented to show the performance of sliding mode control and RBF based sliding mode control.

Song, S.– Zhang, X. – Tan, Z.

Strojniški vestnik - Journal of Mechanical Engineering 60(2014)6, 437-446

a)

b)

c) d) Fig. 5. The simulation results of sliding mode control with Fd = 200 sin(4πt); a) represents the overall simulation result, b) represents the rectangular region in a), c) shows the tracking error result, and the error reaches an approximate value of ±3.2 N; d) reveals the control signal

Sampling time for all simulations is selected as 0.001 s. In the system, the desired force can be determined by the angle of ankle joint and actuator moment.

Therefore, the joint angle can be the reference value.

However, the joint’s performance in terms of tracking forces will not be visualized. Therefore, the desired forces are chosen as the reference quantities in order to simplify the system.

The conditions with frequencies (2 and 10 Hz) and load force (200 N) are shown graphically as a kind of control to make objective comparisons. Load force can change according to the objects the robot will carry. Variations infrequency also have effects on the tracking error of the controller. Therefore, some parameters of the system were modified during the simulation to show the success of the controllers. For reasons of brevity, other parameters such as pressure, mass and damping variations, etc. are not addressed in this paper. The values of the parameters must be chosen such that the results of the system allow for error analysis of simulations. Specifically, the chosen cylinder dead length and stroke length are 0.23 and 0.1016 m, respectively. The hydraulic fluid density is 830.4 kg/m3, and the effective bulk modulus of fluid

is 1.517×109 s–1. Other key parameters are presented in Table 1. Specifically, the switch gain should be generated to move along the sliding surface. For this purpose, a sliding mode controller and a RBF sliding mode controller were designed to verify the positive effects caused by the continuous motion of the sliding surface.

Table 1. Values of key parameters Parameters m [kg] pL [MPa] b [Ns/m] Fc [N] τ [s] Kc [m3s/Pa]

Value 50 6.0 10000 4 0.0035 2.0×10–11

Parameters Cin + Cex ks [m/mA] A1 [m2] A1 [m2] l0 [m] Kq [m3s·A]

Value 2×10–14 1.54 3.25×10–4 2.10×10–4 0.28 18.2×10–3

In order to observe the effects of parametric uncertainty and the two controllers, controls were repeated with different load forces and different frequencies. The results of the tracking forces, tracking errors and control input signals are shown in Figs. 5 and 6. The tracking error of RBF based sliding mode control was 50% less than that of sliding mode

RBF Neural Network Based Sliding Mode Control of a Lower Limb Exoskeleton Suit

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Strojniški vestnik - Journal of Mechanical Engineering 60(2014)6, 437-446

a)

b)

c) d) Fig. 6. Simulation results of RBF based sliding mode control with Fd = 200 sin(4πt); a) represents the overall simulation result; b) represents the rectangular region in a);c) shows the tracking error result, andthe stable error reaches an approximate value of ±1.6 N; d) reveals the control signal

control with Fd = 200 sin(4πt) and 70% less than that of sliding mode control with Fd = 200 sin(20πt). When RBF networks are introduced to sliding mode control, the improvements in tracking errors are clearly shown.

The improvements at a high frequency (10 Hz) are more visible and caused by moving the sliding surface effectively.

and supply pressure. APC with Pentium Dual Core 2.6 GHz and Windows XP operating system was used as computing centre. A 16-bit A/D convertor and a 16-bit D/A convertor with a sampling time of0.001s were used. Desired forces of Fd = 200 sin(4πt) and Fd = 200 sin(20πt) were used. The performances of both control methods with a frequency 2 Hz

4.2 Experiment

computer

The results of the simulation show that RBF sliding mode control presents a better force tracking performance by moving the sliding surface effectively than that of sliding mode control. However, conclusions cannot be determined simply based on the simulation results, nevertheless tests have supported the results as well. The implementation of the proposed method on the robot servo system test is depicted in Fig. 7. The Rexroth CDL1-25-14-100C cylinder was selected to meet the specifications such as, maximum push, pull force, and stroke length.

The Rexroth 4WSE2EM-6-2X/20L/min 4-way flow control servo-valve with an amplifier internally installed was selected based on the required flow rates 442

D/A convertor

A/D convertor

signal processing

valve-cylinder

Fig. 7. Block diagram of the robot servo system for sliding mode control and RBF based sliding mode control

Song, S.– Zhang, X. – Tan, Z.

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a)

b)

c) d) Fig. 8. Experimental results of sliding mode control with Fd = 200 sin(4πt); a) presents the overall experimental results, b) represents the rectangularregionin a);c) shows the tracking error results, and the stable error of FL – Fd and Fsensor – Fd reaches an approximate value of ±15 N and ±30 N; d) shows the control signal

a)

b)

c) d) Fig. 9. Simulation results of RBF based sliding mode control with Fd = 200 sin(4πt); a) presents the overall simulation results; b) represents the rectangularregionin a);c) shows the tracking error results, and the stable error of FL – Fd and Fsensor – Fd reaches an approximate value of ±5 N and ±20 N; d) shows the control signal RBF Neural Network Based Sliding Mode Control of a Lower Limb Exoskeleton Suit

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a)

b)

c) d) Fig. 10. Simulation results of sliding mode control with Fd = 200 sin(20πt); a) presents the overall simulation result; b) represents the rectangular region in a); c) shows the tracking error result, and the stable error of FL – Fd and Fsensor – Fd reaches proximate value of ±30 N and ±50 N; d) reveals the control signal

a)

b)

c) d) Fig. 11. Simulation results of RBF based sliding mode control with Fd = 200 sin(20πt); ; a) presents the overall simulation result; b) represents the rectangular region in a); c) shows the tracking error result, and the stable error FL – Fd and Fsensor – Fd reaches proximate value of ±10 N and ±30 N; d) reveals the control signal

444

Song, S.– Zhang, X. – Tan, Z.

Strojniški vestnik - Journal of Mechanical Engineering 60(2014)6, 437-446

are presented in Figs. 8 and 9, which show that the tracking error FL – Fd and Fsensor – Fd of RBF based sliding mode control was 66 and 35% less than that of sliding mode control. The performances of both control methods with a frequency 10Hz are presented in Figs. 10 and 11, which show that the tracking error FL – Fd and Fsensor – Fd of the RBF based sliding mode control was 66 and 40% less than that of sliding mode control. However, compared with the simulation results, the peak of tracking error was a bit larger due to actual friction and noisy signal conditions.

5 CONCLUSION In this paper, a sliding mode controller was designed for force tracking control in order to eliminate uncertainties and disturbances. However, the precision of sliding mode control was a problem and, therefore, an RBF network based sliding mode control algorithm was introduced to tackle the problem. The slope of the sliding surface was trained to approximate the optimal value by updating with RBF algorithm technique. The simulation results for the tracking forces, tracking errors and control input signals with desire forces (200 N, 2 Hz) were presented graphically and analysed in order to compare the improved controller with the regular one. Tests of the two proposed control methods were designed using two sets of desire forces (200 N, 2 Hz) and (200 N, 10 Hz) to show the validity of the simulation results. Compared with results found for 2 Hz, the tracking error of both proposed method is greater for 10 Hz. Under the same conditions, the tracking performance of RBF based sliding mode control is better than that of sliding mode control.

Because of frictions and noisy signals, the test errors are a bit larger than those of the simulations. However, it has been effectively shown by figures and tables that RBF based sliding mode control provides features with higher performance.

6 NOMENCLATURE Kq Kc xv pL q1, q2 A1, A2 xc , x c Cin, Cec p1, p2 V1, V2

no-load flow gain of servo valve flow-pressure coefficient of valve valve spool position hydraulic pressure of load flow into chamber A and B area of piston in chamber A and B piston position and velocity of cylinder cylinder internal and external leakage coeff. hydraulic pressure of chamber A and B volume of hydraulic oil in chamber A and B

V0 FL Ff φ M(φ) m J r FC , FS b vs Fd l(φ) l0 xc0

initial volume of cylinder force of load friction force of piston joint angle of robot actuator moment arm system mass joint inertia of the system center position of mass of the system Coulomb friction and stiction force viscous friction coefficient the ultimate velocity comes after the stiction force is surmounted desire force of load length of cylinder initial length of cylinder initial piston position of cylinder 7 REFERENCES

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8 APPENDIX Shank Geometrical Analysis As shown in Fig. A1, the cylinder is placed on the shank of robot with at the mounting points d1 and d2 respectively. The position vectors from the ankle axis, O, to each mounting point are defined by:  r od1 = [ x1 , x2 ]T . (A1)

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Nonlinear and Adaptive Control with Applications.

Springer, London.

[21] Alleyne, A., Liu, R. (2000). A simplified approach to force control for electro-hydraulic systems. Control Engineering Practice, vol. 8, no. 12, p. 1347-1356, DOI:10.1016/S0967-0661(00)00081-2.

e2 O Knee joint

Shank

Ankle joint

Fig. A1. Geometrical analysis of shank with cylinder

Using the law of cosines, the length of the cylinder can be calculated by: l (ϕ ) = −2lod 1lod 2 cos(ϕ − θ1 − θ 2 ) + lod2 1 + lod2 2 , (A3) where θ1 = tan −1 (

x x1 ), θ 2 = tan −1 ( 3 ). − x2 x4

If we make a vertical line through the cylinder through point O, then the length of the vertical line is the cylinder moment arm. Using the law of sine and cosines, the cylinder moment arm can be expressed as:

M (ϕ ) = lod 2 sincos −1

lod2 1 − lod2 2 − l (ϕ ) 2 . (A4) −2lod 2l (ϕ )

The reference force of the cylinder can be calculated as a function of the joint angle: Fr = mgr sin(ϕ ) / M (ϕ ), (A5)

where Fr can be regarded as the desired force. In the simulations, the sensor force can be expressed by: Fsensor = FL + Ff . (A6)

Song, S.– Zhang, X. – Tan, Z.

Strojniški vestnik - Journal of Mechanical Engineering 60(2014)6 Vsebina

Vsebina Strojniški vestnik - Journal of Mechanical Engineering letnik 60, (2014), številka 6 Ljubljana, junij 2014 ISSN 0039-2480 Izhaja mesečno

Enrico Troiani, Lorenzo Donati, Gianluca Molinari, Raffaella Di Sante: Vpliv strategije zlaganja slojev in vrste sprožilca na odpornost pri trku laminatov z ogljikovimi vlakni, utrjenimi v avtoklavu Marjan Leber, Majda Bastič, Borut Buchmeister: Trendi uporabe in ovire za uvajanje metod inovacijskega menedžmenta pri razvoju novega izdelka Sergey Nikolaevich Grigoriev, Tatyana Vasilievna Tarasova, Galina Olegovna Gvozdeva, Steffen Nowotny: Oblikovanje strukture hiperevtektičnih zlitin Al-Si pri laserski površinski obdelavi Qihui Yu, Maolin Cai, Yan Shi, Zichuan Fan: Optimizacija energijskega izkoristka batnega motorja na stisnjen zrak Ana Bižal, Jernej Klemenc, Matija Fajdiga: Ocena statistične značilnosti vpliva makro poroznosti na padec zdržljivosti Yesid Asaff, Victor J. De Negri, Heinrich Theissen, Hubertus Murrenhoff: Analiza vpliva onesnaževal na biorazgradljivost in staranje biorazgradljivih hidravličnih tekočin Miha Praznik, Vincenc Butala, Martina Zbašnik-Senegačnik: Enostavna metoda za vrednotenje trajnostnih zasnov energijsko učinkovitih družinskih stavb Shengli Song, Xinglong Zhang, Zhitao Tan: Vodenje eksoskeleta za spodnje okončine v drsnem režimu z uporabo nevronske mreže RBF Osebne vesti Doktorska disertacija, specialistično delo, magistrska dela, diplomske naloge

SI 75 SI 76 SI 77 SI 78 SI 79 SI 80 SI 81 SI 82 SI 83

Strojniški vestnik - Journal of Mechanical Engineering 60(2014)6, SI 75 © 2014 Strojniški vestnik. Vse pravice pridržane.

Prejeto v recenzijo: 2013-10-14 Prejeto popravljeno: 2014-02-10 Odobreno za objavo: 2014-02-28

Vpliv strategije zlaganja slojev in vrste sprožilca na odpornost pri trku laminatov z ogljikovimi vlakni, utrjenimi v avtoklavu Troiani, E. – Donati, L. – Molinari, G. – Di Sante, R. Enrico Troiani* – Lorenzo Donati – Gianluca Molinari – Raffaella Di Sante Univerza v Bologni, MasterLab, Italija

Namen snovanja za odpornost pri trku je preučevanje sposobnosti konstrukcij, da absorbirajo energijo: nadzorovan in postopen kolaps delov vozila zagotavlja varno disipacijo zadostne količine kinetične energije v primeru trka.

Energijo tradicionalno in še posebej pri letalih absorbirajo kovinski deli, ki se porušijo nadzorovano in se pri tem intenzivno plastično preoblikujejo. Nadomeščanje kovin s kompoziti, zlasti z epoksidnimi smolami, ojačenimi z ogljikovimi vlakni, lahko izboljša učinkovitost absorpcije energije. Manjkajo pa podatki o odzivu teh konstrukcij pri delovnih obremenitvah, in še posebej v primeru trka. Numerični modeli, podprti s testi na vzorcih in manjših konstrukcijah, so prednostna izbira za preučevanje tega vedenja.

Zato je bil razvit inovativen eksperimentalni test manjšega obsega za karakterizacijo lastnosti materialov pod tlakom. Preizkušanci imajo samonosilno sinusoidno obliko, s čimer se je mogoče izogniti uklonu klasičnih ravnih preizkušancev. Preizkušena sta bila dva preprega iz polimera, ojačenega z ogljikovimi vlakni (CFRP): 12 slojev enosmernih trakov oz. 8 slojev v platnovi vezavi, s čimer je v obeh primerih nastal laminat debeline približno 1,8 mm. Analizirana so bila tri zaporedja zlaganja za identifikacijo konfiguracije z maksimalno specifično absorpcijo energije (SEA), t.j. absorbirano energijo na enoto mase zmečkane konstrukcije. Najboljši rezultati so se pokazali pri enosmernem preizkušancu.

Pri preizkušancih je zelo pomemben tudi sprožilni mehanizem oz. konstrukcijska značilnost, ki zagotavlja postopen kolaps konstrukcije in s tem preprečuje nenapovedljivo in včasih nestabilno odpoved kompozitnega materiala. Za preučitev SEA oslabljenih laminatov so bili izdelani preizkušanci s standardnimi posnetji ter z inovativnimi samosprožilnimi značilnostmi, kjer so vlakna prekinjena na izbranem mestu in v različnem obsegu.

Pri enosmernih preizkušancih položaj sprožilca ni vplival na maksimalno vrednost SEA in na vedenje med preizkusnim gibom. Samosprožilna konfiguracija določa položaj začetne napake v preizkušancu brez zmanjšanja varnosti, je primerna alternativa za zunanji sprožilec in odpravlja zamudno mehansko obdelavo po utrjevanju.

Glavni dosežek tega članka je opredelitev zanesljivega in dostopnega eksperimentalnega postopka za kvantifikacijo sposobnosti kompozitnih materialov za absorpcijo energije. Predstavljeno delo je tudi prvi korak modularnega programa, ki se začne z eksperimentalnimi testi na manjših preizkušancih in eksperimentalno analizo, konstruktorji pa z njimi dobijo potrebno znanje za obravnavo zahtevnejših konstrukcij.

Rezultati eksperimentov so dokazali zanesljivost metode samonosilnih preizkušancev, na katere ne vplivajo zunanji dejavniki zaradi vpenjal, ki preprečujejo uklon pri ravnih preizkušancih. Preizkušance sinusoidne oblike je tudi enostavneje izdelati kot cevi, ki so pogosteje v uporabi.

Avtorji verjamejo, da bo študija zanimiva za znanstveno skupnost, tako za raziskovalne kakor tudi za za tehnično-aplikativne namene. Objavljenih prispevkov na to temo je malo, med njimi pa verjetno ni nobenega takšnega, ki bi obravnaval isti material in konfiguracijo za absorpcijo energije.

Odpornost pri trku je tudi pomembna raziskovalna tema pri razvoju kompozitov.

Ključne besede: kompoziti, tlačni preizkus, odpornost pri trku, specifična absorpcija energije (SEA)

*Corr. Author’s Address: University of Bologna, MasterLab, via Fontanelle 40, 47121 Forlì, Italija, enrico.troiani@unibo.it

SI 75

Strojniški vestnik - Journal of Mechanical Engineering 60(2014)6, SI 76 © 2014 Strojniški vestnik. Vse pravice pridržane.

Prejeto v recenzijo: 2013-12-16 Prejeto popravljeno: 2014-02-05 Odobreno za objavo: 2014-02-18

Trendi uporabe in ovire za uvajanje metod inovacijskega menedžmenta pri razvoju novega izdelka Leber, M. – Bastič, M. – Buchmeister, B. Marjan Leber1 – Majda Bastič2 – Borut Buchmeister1,* 1 Univerza

2 Univerza

v Mariboru, Fakulteta za strojništvo, Slovenija v Mariboru, Ekonomsko-poslovna fakulteta, Slovenija

V članku so prikazani rezultati ankete o uporabi metod inovacijskega menedžmenta (MIM) s potencialom za izboljšanje učinkovitosti razvoja novih izdelkov (RNI) in zadovoljstva kupcev kakor tudi tiste ovire, ki preprečujejo njihovo uvajanje v slovenska podjetja. Anketa je bila izvedena v obdobju 2003 do 2011.

Učinkovitost RNI, merjena s pravočasnim nastopom na trgu, stroški izdelka in razvoja ter kakovostjo izdelka, se lahko izboljša z uporabo MIM. Najboljša podjetja uporabljajo veliko število teh metod pogosteje in so bolj odprta za uvajanje novih orodij in metodologij za izboljšanje učinkovitosti in uspešnosti svojih inovacijskih projektov.

Glede na vpliv uporabe MIM na učinkovitost RNI in uspešnost podjetij je bil cilj te študije analizirati uporabo in trende MIM v slovenskih podjetjih ter ugotoviti, ali zaznavajo MIM kot orodje pri izboljšanju učinkovitosti RNI in (najpomembnejše) ali poznajo ovire, ki preprečujejo uporabo MIM. Študija, opravljena v letu 2011, je bila del longitudinalne raziskave, začete v letu 2003, ki je takrat temeljila na vzorcu 19 podjetij. Vprašalniki, ki so bili uporabljeni v raziskavi 2011 (odgovorilo je 40 podjetij, od teh jih je 15 že sodelovalo v prvi anketi leta 2003), so obsegali 16 strani in so vključevali naslednja vprašanja: osnovne informacije o anketiranem podjetju, glavni razlogi za uporabo MIM, pristojnosti in pogostost uporabe MIM, uporabni potencial ter ovire za uporabo MIM pri RNI. Večina podjetij, ki so sodelovala v raziskavi, je dejavnih v kovinsko predelovalni industriji, sledila so storitvena podjetja in podjetja iz elektroindustrije. Odgovore smo vrednotili z 10 točkovno lestvico.

Rezultati kažejo, da MIM uporablja nizek delež slovenskih podjetij. Analiza potencialnih napak in mogočih učinkov (FMEA) je bila prepoznana kot najbolj uporabna MIM v slovenskih podjetjih z najvišje ocenjenim uporabnim potencialom za zmanjšanje stroškov razvoja in izboljšanje zadovoljstva kupcev. Rezultati kažejo tudi trend k vse večji uporabi Analize drevesa napak (FTA), Vrednostne analize (VA), metode ciljnih stroškov in TRIZ, še posebej v obdobju 2008 do 2011, ki sovpada z obdobjem gospodarske in finančne krize. Rezultati potrjujejo ugotovitve OECD (v 2010), da so inovacije ključnega pomena za države in podjetja, ki so si opomogli od gospodarske recesije in uspele v današnjem visoko konkurenčnem svetovnem gospodarstvu.

Premik od najpogosteje uporabljene metode SPC v letu 2008 k metodi ciljnih stroškov v letu 2011 v neprofitnih podjetjih je lahko znak, da inovacije in učinkovitost RNI postajajo vse pomembnejši cilji tudi v neprofitnih organizacijah. Pristojnosti in uporabo MIM je mogoče razumeti kot priložnost predvsem za neprofitna podjetja, da izboljšajo učinkovitost in uspešnost svojih inovacijskih procesov.

Kompleksnost MIM, nujnost usposabljanja in uvajanja ter pomanjkanje vhodnih podatkov za uporabo MIM so bili spoznani kot glavne ovire za izvajanje MIM v slovenskih podjetjih. Univerze lahko učinkovito pripomorejo pri odpravi teh ovir z vključevanjem vsebin MIM v učne načrte.

Ključne besede: metode inovacijskega menedžmenta, razvoj novih izdelkov, longitudinalna raziskava

SI 76

*Naslov avtorja za dopisovanje: Univerza v Mariboru, Fakulteta za strojništvo, Smetanova ulica 17, 2000 Maribor, Slovenija, borut.buchmeister@um.si

Strojniški vestnik - Journal of Mechanical Engineering 60(2014)6, SI 77 © 2014 Strojniški vestnik. Vse pravice pridržane.

Prejeto v recenzijo: 2013-05-16 Prejeto popravljeno: 2013-10-04 Odobreno za objavo: 2013-11-29

Oblikovanje strukture hiperevtektičnih zlitin Al-Si pri laserski površinski obdelavi Grigoriev, S.N. – Tarasova, T.V. – Gvozdeva, G.O. – Nowotny, S. Sergey Nikolaevich Grigoriev1 – Tatyana Vasilievna Tarasova1,* – Galina Olegovna Gvozdeva1 – Steffen Nowotny2 1 Državna

2 Fraunhofer

tehniška univerza “STANKIN” v Moskvi, Rusija inštitut za materiale in tehnologijo žarčenja v Dresdnu, Nemčija

Avtorji v članku preučujejo možnosti enoslednega laserskega mikronavarjanja kompozitov s kovinskim matriksom na osnovi aluminijevih zlitin.

Lasersko navarjanje zlitin Al-Si je v zadnjih desetletjih pritegnilo veliko pozornosti, saj s hitrim strjevanjem zagotavlja fino strukturo zlitin Al-Si in posledično boljšo protiobrabno obstojnost. Pri vseh dosedanjih eksperimentih je bila uporabljena širina sledi približno 3 do 5 mm, medtem ko lahko sodobni laserji fokusirajo laserski žarek v točki premera 50 µm in z njimi je torej mogoče ustvarjati tudi objekte na mikrometrski skali.

Brizganje prašnatih delcev je sicer težko nadzorovati, zlasti pri materialih z manjšo gostoto, prav tako pa ni objav o uspešnih izkušnjah z mikronavarjanjem lahkih materialov. Preučiti je treba tudi absorpcijo laserskega žarka in oblikovanje sledi med mikronavarjanjem.

Za navarjanje je bil uporabljen kontinuirni laser Yb:YAG 1kW. Premer laserske točke na površini substrata je bil 50 μm in brizganje prahu je potekalo skozi koaksialno šobo. Za zaščito talilne kopeli pred onesnaženjem in oksidacijo je bil uporabljen koaksialen curek argona. Porazdelitev velikosti delcev uporabljenega prahu je bila ugotovljena z mikroskopom OCCHIO 500nano, fazna sestava prahu pa z rentgensko difrakcijsko analizo z difraktometrom ALR X’TRA. Za mikrostrukturno analizo so bili narejeni prečni prerezi navarjenih sledi (v ravnini pravokotno na laserske sledi). Vzorci prahov za metalografsko analizo so bili hladno zaliti in mehansko polirani, nato pa jedkani s Kellerjevim reagentom. Za mikrostrukturno analizo prahov in navarjenih sledi je bil uporabljen standardni optični mikroskop Leica MEF4M, za ugotavljanje kemične sestave prahov in navarjenih sledi ter za določitev površinske morfologije prahov pa je bil uporabljen vrstični elektronski mikroskop VEGA 3 LM z energijsko disperznim rentgenskim spektrometrom.

Navarjene sledi AlSix s prečno ločljivostjo < 500 μm so bile izdelane po postopku koaksialnega laserskega navarjanja. Navarjene sledi so sestavljene iz primarnih delcev silicija, obdanih z venci α-Al in evtektično zmesjo Al/Si. Vsebnost Si v prahu ne vpliva na maksimalno trdoto prevleke 190 HV0,05 pri nobenem od preučevanih prahov z različnimi kemičnimi sestavami. V prevleki so se s povečevanjem dovoda prahu in zmanjševanjem moči laserja oblikovali večji primarni delci Si. Primarni delci Si pri AlSi30 so izjemno fini in v prevleki ni mogoče razločiti primarnega Si ter evtektika Si. Širina navarjene sledi in mešanje s substratom se zvezno povečujeta z naraščanjem moči laserja. Sprememba moči laserja ne povzroči signifikantne spremembe višine sledi. Le-ta se povečuje in mešanje s substratom se zvezno zmanjšuje s povečevanjem količine dodanega prahu v območju 4 do 10 g/min pri moči laserja P = 200 W in hitrosti žarka v = 800 mm/min, medtem ko je širina sledi nekoliko spremenljiva.

Rezultati raziskave veljajo le za mikronavarjanje aluminijevih zlitin s toplotnim gradientom 20000 K/mm.

Potrjeno je bilo, da je s koaksialnim laserskim mikronavarjanjem mogoče izdelati enojno navarjeno sled in pozneje tudi višjo stojino širine < 500 µm iz lahke zlitine Al-Si. Preučeno je oblikovanje strukture zlitin Al-Si med laserskim mikronavarjanjem. Prikazan je vpliv kemične sestave prašnatega materiala na strukturo in mikrotrdoto prevleke, kakor tudi vpliv parametrov obdelave na mikrostrukturo in geometrijo sledi.

Ključne besede: mikronavarjanje, lasersko navarjanje, aluminijeve zlitine, materiali majhne gostote, mikrostruktura, oblikovanje strukture, oblikovanje navarjene sledi

*Naslov avtorja za dopisovanje: Državna tehniška univerza “STANKIN” v Moskvi, Lenin Hills, 1, GSP-1, Moskva, Ruska federacija, science@stankin.ru

SI 77

Strojniški vestnik - Journal of Mechanical Engineering 60(2014)6, SI 78 © 2014 Strojniški vestnik. Vse pravice pridržane.

Prejeto v recenzijo: 2013-08-16 Prejeto popravljeno: 2013-12-13 Odobreno za objavo: 2014-01-17

Optimizacija energijskega izkoristka batnega motorja na stisnjen zrak Yu, Q. – Cai, M. – Shi, Y. – Fan, Z. Qihui Yu – Maolin Cai – Yan Shi* – Zichuan Fan

Univerza Beihang, Šola za avtomatizacijo in elektrotehniko, Kitajska

Kurjenje fosilnih goriv je eden glavnih vzrokov resnih okoljskih problemov, kot so učinek tople grede, tanjšanje ozonske plasti in smog. V članku je predstavljena nova vrsta pogonske opreme, ki bi lahko pomagala pri odpravljanju teh problemov. Batni motor (CAE) poganja stisnjen zrak, ki ga je mogoče pridobiti z uporabo obnovljivih virov, kot so sončna svetloba, veter in bibavica. Batni motorji CAE so okolju prijazna oprema in bi jih lahko vgrajevali v vozila prihodnosti, njihov razvoj pa je začasno zavrla nizka energetska učinkovitost.

Naša študija je posvečena optimizaciji energijskega izkoristka batnih motorjev CAE ob dani izhodni moči. Članek se začne z načeli delovanja batnega motorja CAE. Za analizo energijskega izkoristka in delovne moči batnega motorja CAE je nato razvit matematični model delovnega procesa batnega motorja CAE na osnovi energijske enačbe, zakona o ohranitvi mase, enačbe pretoka, enačbe stanj, enačbe strukture in enačbe gibanja.

Nato sta opredeljena še energijski izkoristek in izhodna moč, vpliv razmerja premera valja in giba, sesalnega tlaka in dviga ventilov na zmogljivost batnega motorja CAE pa je bil ugotovljen s simulacijami v Matlabu ob upoštevanju omenjenega energijskega izkoristka in izhodne moči. Za optimizacijo energijskega izkoristka batnega motorja CAE pri dani izhodni moči in za iskanje primernejšega razpona rešitev je bil uporabljen izboljšani elitistični nedominirani urejevalni genetski algoritem (NSGA-II). Operatorji križanja in mutacije ostanejo konstantni, medtem ko operator izbire deluje na drugačen način kot pri enostavnih genetskih algoritmih. Za izbiro je bil uporabljen operator primerjave gruč na osnovi ranga (glede na raven nedominacije) in razdalje gručenja.

Razdalja gručenja je bila izračunana z vrednostjo praga za posamezne izbire. Z izboljšanim algoritmom NSGA-II je bila nato izračunana vrsta sesalnih tlakov in dvigov ventilov za optimizacijo. Za ilustracijo izboljšanega pristopa NSGA-II je bila uporabljena razdalja generacije (GD).

Rezultati so pokazali, da se pri razmerju premera valja in giba pod 1 izhodna moč in energijski izkoristek hitro povečata na 0,8761 kW in 40,25 %. Ko se omenjeno razmerje povečuje nad 1, izhodna moč in energijski izkoristek počasi naraščata. S povečevanjem sesalnega tlaka in dviga ventilov se povečuje izhodna moč ter zmanjšuje energijski izkoristek. Sesalni tlak in dvig sesalnih ventilov sta bila prilagojena za različne hitrosti in vozne pogoje. Za povečanje energijskega izkoristka z izboljšanim algoritmom NSGA-II je bila izbrana vrednost dviga sesalnih ventilov v območju od 9 do 10 mm, sesalni tlak pa je bil v območju med minimalno in maksimalno vrednostjo. Najvišji izkoristek 31,17 % pri izhodni moči približno 2 kW je bil dosežen s sesalnim tlakom 1,99 MPa in dvigom sesalnih ventilov 9,99 mm. Potrjeno je bilo, da izboljšani algoritem NSGA-II premaga NSGA-II po bližini in raznovrstnosti.

Raziskava bo uporabna pri optimizaciji batnih motorjev CAE in nadaljnjih študijah za optimizacijo energijskega izkoristka. Nadaljnje raziskave bodo usmerjene v snovanje prototipa in gradnjo testne platforme za merjenje zmogljivosti batnih motorjev CAE ter validacijo izboljšanega algoritma NSGA-II. Ključne besede: batni motor na stisnjen zrak, optimizacija energijskega izkoristka, razmerje premera valja in giba, sesalni tlak, dvig ventila, izboljšani elitistični nedominirani urejevalni genetski algoritem, razdalja gručenja

SI 78

*Naslov avtorja za dopisovanje: Univerza Beihang, Šola za avtomatizacijo in elektrotehniko, XueYuan Road No.37, HaiDian District, Peking, Kitajska, yesoyou@gmail.com

Strojniški vestnik - Journal of Mechanical Engineering 60(2014)6, SI 79 © 2014 Strojniški vestnik. Vse pravice pridržane.

Prejeto v recenzijo: 2013-09-23 Prejeto popravljeno: 2013-11-06 Odobreno za objavo: 2013-11-13

Ocena statistične značilnosti vpliva makro poroznosti na padec zdržljivosti Bižal, A. – Klemenc, J. – Fajdiga, M. Ana Bižal*,1 – Jernej Klemenc2 – Matija Fajdiga2 1Hella

2Univerza

Saturnus Slovenija d.o.o., Slovenija v Ljubljani, Fakulteta za strojništvo, Slovenija

V strojni industriji je težnja po zmanjševanju teže konstrukcij odprla pot uporabi ulitkov iz aluminijevih zlitin kot alternativo jeklu. Medtem ko so dobre mehanske lastnosti, cenovno ugodne proizvodnje tehnologije in možnost recikliranja utrjevale položaj aluminijevih so vedno bolj prihajale do izraza tudi njihove slabe lastnosti. Ulitki so namreč podvrženi pojavu nehomogenosti v strukturi. Kljub temu, da je njihova prisotnost navadno razlog za padec zdržljivostnih sposobnosti ulitka, pa se nehomogenostim v celoti ne moremo izogniti. Pri ulitkih so najbolj kritične tiste nehomogenosti, ki so posledica tehnološkega procesa, saj so navadno večje od ostalih, mikro strukturnih značilnosti ulitka (hrapavost površine, mikrostruktura, mikro-poroznost, itn.). Najbolj nevarna tipa nehomogenosti pri ulitkih sta poroznost in vključki.

Raziskava se osredotoča na statistični popis vpliva makro poroznosti na padec zdržljivostnih lastnosti tlačno litih preskušancev iz AlSi9Cu3 zlitine. Statistična značilnost vpliva je bila raziskana s tremi statističnimi modeli in sicer z: univariantno analizo variance, multivariantno analizo variance in linearno regresijo z indikacijskimi spremenljivkami. Izbrani trije statistični modeli so bili uporabljeni za analizo eksperimentalnih podatkov zdržljivostnih testov AlSi9Cu3 preskušancev z različnimi stopnjami makro poroznosti. Preskušanci so bili izdelani s procesom tlačnega litja, makro pore pa so bile v preskušance vpeljane z variiranjem tlaka in temperature litja. Geometrija preskušancev je bila povzeta po standardu ASTM E606. Proizvedeni preskušanci so bili na podlagi neporušnih testov razdeljeni v tri skupine glede na zaznano stopnjo makro poroznosti. Z vsako skupino preskušancev so bili izvedeni deformacijsko kontrolirani zdržljivostni testi na več obremenitvenih nivojih.

Med tremi uporabljenimi metodami se je linearna regresija z indikacijskimi spremenljivkami izkazala kot optimalna. Metoda omogoča oceno stopnje značilnosti razlik med nakloni in konstantnimi členi različnih skupin ter prepoznavanje točk, ki pripadajo isti zdržljivostni krivulji tudi, če se le-ti nahajajo na različnih obremenitvenih nivojih.

Ključne besede: AlSi9Cu3 zlitina, poroznost, zdržljivost, ANOVA, MANOVA, linearna regresija z indikacijskimi spremenljivkami

*Naslov avtorja za dopisovanje: Hella Saturnus Slovenija d.o.o., Letališka c. 17, 1001 Ljubljana, Slovenija, ana.bizal@hella.com

SI 79

Strojniški vestnik - Journal of Mechanical Engineering 60(2014)6, SI 80 © 2014 Strojniški vestnik. Vse pravice pridržane.

Prejeto v recenzijo: 2013-09-21 Prejeto popravljeno: 2014-03-01 Odobreno za objavo: 2014-04-01

Analiza vpliva onesnaževal na biorazgradljivost in staranje biorazgradljivih hidravličnih tekočin Asaff, Y. – De Negri, V.J. – Theissen, H. – Murrenhoff, H. Yesid Asaff 1 – Victor J. De Negri1,* – Heinrich Theissen2 – Hubertus Murrenhoff2 1 Zvezna

2 Univerza

univerza v Santa Catarini, Oddelek za strojništvo, Brazilija RWTH Aachen, Institut za hidravlične pogone in upravljanje, Nemčija

Članek preučuje vpliv onesnaževal, kot so voda, mineralna olja, delci bakra in kisik, na biorazgradljivost in staranje biorazgradljivih tekočin v hidravličnih sistemih. Kljub temu, da so mineralna olja tradicionalno najbolj razširjena vrsta hidravličnih tekočin v fluidni tehniki, pa so ta olja danes podvržena vse večjemu nadzoru, zlasti zaradi vse strožjih vladnih predpisov za preprečevanje posledic razlitja hidravličnih tekočin in iztekanja tekočin v okolje. Večja moč hidravličnih sistemov se poleg tega dosega s povečevanjem delovnega tlaka, kar pa pomeni tudi večje tveganje netesnosti. Tovrstne nezgode lahko resno škodujejo okolju pri aplikacijah kot so npr. hidroelektrarne, kmetijski stroji in stroji v pomorstvu. Opisana situacija je privedla do globalnih poskusov identifikacije hidravličnih tekočin, ki imajo manjši okoljski in toksični vpliv pri nenamernem stiku z okoljem.

Poznavanje vpliva onesnaževal na biorazgradljivost in staranje biorazgradljivih hidravličnih tekočin je pogoj za uspešno uporabo teh tekočin v hidravličnih sistemih. Predstavljena študija obravnava nove podatke o komercialnih biorazgradljivih tekočinah (okoljsko sprejemljiva hidravlična olja na osnovi sintetičnih estrov oz. HEES) pod vplivom splošnih onesnaževal (voda, mineralno olje, delci bakra in kisik), ki so prisotna v današnjih hidravličnih sistemih.

V laboratorijskih preiskavah so bile uporabljene tri različne biorazgradljive tekočine dveh proizvajalcev.

Tekočine na osnovi sintetičnih estrov so skladne s specifikacijami HEES v standardu ISO 15380. Analiza vpliva onesnaževal na biorazgradljive tekočine je bila opravljena z oksidacijskim testom v modificirani rotirajoči tlačni posodi (RPVOT), testi hidrolitične stabilnosti in testom biorazgradljivosti (O2 = CO2 test parne faze s testom GC-TCD). Biorazgradljivim hidravličnim tekočinam so bila dodana onesnaževala v znanih koncentracijah in kombinacijah: mineralno olje, voda in delci bakra. Kazalniki staranja biorazgradljivih tekočin so bili viskoznost in TAN pri hidrolizi ter oksidacija pri testu RPVOT. Analizirane komercialne biorazgradljive tekočine so občutljive na onesnaženje s trdnimi delci bakra, kisikom (oksidacija), vodo (hidroliza) in standardnimi mineralnimi hidravličnimi tekočinami, kakor tudi na visoke temperature. Degradacija olja povzroči oblikovanje kislih komponent, povečanje viskoznosti, zmanjšanje učinkovitosti aditivov in nalaganje oblog. Rezultati testov kažejo, da lahko dodatek mineralnega olja za razliko od vode in bakra sprva pozitivno vpliva na oksidacijsko stabilnost biorazgradljivih tekočin. Modificirani test RPVOT je tudi razkril, da vpliv delcev bakra (kot onesnaževal) na oksidacijsko stabilnost tekočin ni odvisen od količine bakra. Rezultati tudi jasno kažejo, da lahko vsebnost vode nad 1% bistveno vpliva na oksidacijsko in hidrolitično stabilnost biorazgradljivih tekočin. Pri vseh analiziranih tekočinah je bil trend spremembe TAN zaradi oksidacije enak kot pri vplivu hidrolize. Pogoji (vrste onesnaževal), ki negativno vplivajo na oksidacijsko stabilnost, torej tudi pomembno vplivajo na hidrolizo, oboje pa se odraža v povečanju TAN. Testi oksidacije in hidrolize kažejo pomemben vpliv na biorazgradljivost ene od treh tekočin.

Analizirane tekočine so po pričakovanjih bolj biorazgradljive od mineralnega olja, mešanje z mineralnimi olji pa jim pomembno zmanjša biorazgradljivost (za 10 do 12%).

Ključne besede: biorazgradljive hidravlične tekočine, oksidacija, hidroliza, biorazgradljivost, kontaminacija, hidravlične tekočine na osnovi estrov

SI 80

*Naslov avtorja za dopisovanje: Zvezna univerza v Santa Catarini, Oddelek za strojništvo, 88040-900, Florianópolis, SC, Brazilija, victor.de.negri@ufsc.br

Strojniški vestnik - Journal of Mechanical Engineering 60(2014)6, SI 81 © 2014 Strojniški vestnik. Vse pravice pridržane.

Prejeto v recenzijo:2013-11-21 Prejeto popravljeno: 2014-01-27 Odobreno za objavo: 2014-03-03

Enostavna metoda za vrednotenje trajnostnih zasnov energijsko učinkovitih družinskih stavb Miha Praznik1,* – Vincenc Butala2 – Martina Zbašnik-Senegačnik3 1 Gradbeni

inštitut ZRMK d.o.o., Slovenija v Ljubljani, Fakulteta za strojništvo, Slovenija 3 Univerza v Ljubljani, Fakulteta za arhitekturo, Slovenija 2 Univerza

Stavbe imajo negativne vplive na okolje v celotnem življenjskem ciklusu, torej od faze pridobivanja surovin ter proizvodnje gradiv in polizdelkov, do prodaje, vgradnje in uporabe do končne faze odstranitve, ko stavba odsluži svojemu namenu. Trenutna zakonodaja omejuje v glavnem rabo energije in emisije v obratovanju, manj pa ostale ključne parametre in relevantne faze življenjskega cikla, ki prav tako definirajo zasnovo sodobne trajnostne stavbe. Energijsko učinkovite novogradnje izhodiščne omejitve regulative s kakovostnimi rešitvami in pristopi v zasnovi bistveno presegajo. Pri njihovi zasnovi pa se pogosto izpostavljajo vprašanja o upravičenosti ali pa npr. mejnih vrednostih dodatnih finančnih, energijskih in okoljskih vlaganj, ki so potrebna za nastanek takšne sodobne stavbe. Tovrstna vrednotenja stavb se v praksi izvajajo z različnimi kompleksnimi metodami, ki zahtevajo veliko podatkov in običajno ocenjujejo stavbo po zaključku gradnje, ko izboljšanje kakovosti stavbe oz. trajnostnega koncepta ni več mogoče.

Učinkovitost koncepta za novogradnjo lahko zagotavljamo s preverjanjem načrtovanih rešitev in njihovih učinkov glede na različne kriterije. Te lahko hierarhično razvrstimo v tri nivoje. Primarni nivo, v katerem so uvrščeni kriteriji zahtev po energijski učinkovitosti, in sekundarni nivo, ki vsebuje okoljske kriterije, sta v vzročno posledičnem odnosu. Za preverjanje izpolnjevanja kriterijev na teh dveh nivojih je razvit novi način celovitega vrednotenja, ki je predstavljen v članku. V terciarnem nivoju kriterijev, ki imajo naravo inženirskih ukrepov različnih strok, se nahajajo rešitve za arhitekturne in tehnološke ukrepe. Z njimi se zagotavlja doseganje višje energijske učinkovitosti in souporaba obnovljivih virov energije v energijski bilanci stavbe. Interdisciplinarno optimiranje zasnove stavbe z ukrepi tretjega nivoja zagotavlja izpolnjevanje zahtev predhodnih dveh nadrejenih nivojev in zato ni vključeno v novo metodo ocenjevanja.

Preverjanje trajnostne zasnove stavbe je smiselno že v začetnih fazah projektiranja, ko je še mogoče vplivati na rezultat. V ta namen je razvita enostavna metoda, s pomočjo katere se z izbranimi petimi indikatorji, ki vrednotijo vplive stavbe v njenem življenjskem ciklu, ocenjuje kakovost trajnostnih zasnov. Področja ocenjevanja se nanašajo na doseženo energijsko učinkovitost stavbe, rabo primarne energije, emisije CO2, stroške ter na doseženo bivalno ugodje. Z višanjem njihove vrednosti se indicirajo večji negativni okoljski ali bivalni vplivi ter višje energijsko ali stroškovno obremenjevanje. Optimalna rešitev z vidika trajnosti zasnove ima najmanjšo skupno vrednost na petih indikatorjih. Ocenjevanje s pomočjo indikatorjev poteka po treh načinih objektivnega in subjektivnega ponderiranja, s čimer se v skupno oceno vključijo različni vidiki neodvisnosti presojevalca ter vidiki nacionalnih in uporabniških zahtev.

Na primeru ocenjevanja petih zasnov za novogradnjo je ugotovljeno, da imajo zasnove za novogradnje v energijskem razredu A (tehnologija gradnje pasivnih družinskih stavb) najboljši skupni rezultat ocenjevanja ter s tem najboljšo trajnostno zasnovo, ne glede na dodatna energijska, okoljska in ekonomska vlaganja v fazi gradnje.

Rezultati ocenjevanja kažejo tudi na izreden pomen izbora energijskih sistemov. Z ustreznim reševanjem toplotne oskrbe, ki vključuje večji delež obnovljivih virov energije (npr. energija sončnega obsevanja, lesna biomasa) se namreč tudi pri energijsko manj učinkovitih novogradnjah energijskega razreda C lahko približamo skupnim učinkom zasnov učinkovitejših stavb iz energijskega razreda B. Ključne besede: energijska učinkovitost, trajnostna zasnova, enodružinska stavba, ocena učinkovitosti, enostavna metoda, raba primarne energije, emisije CO2, bivalno okolje, stroški v življenjski dobi

*Naslov avtorja za dopisovanje: Gradbeni inštitut ZRMK d.o.o., Dimičeva 12, 1000 Ljubljana, Slovenija, miha.praznik@gi-zrmk.si

SI 81

Strojniški vestnik - Journal of Mechanical Engineering 60(2014)6, SI 82 © 2014 Strojniški vestnik. Vse pravice pridržane.

Prejeto v recenzijo: 2013-08-13 Prejeto popravljeno: 2013-12-03 Odobreno za objavo: 2014-01-24

Vodenje eksoskeleta za spodnje okončine v drsnem režimu z uporabo nevronske mreže RBF Song, S.– Zhang, X. – Tan, Z. Shengli Song* – Xinglong Zhang – Zhitao Tan

Znanstveno-tehniška univerza PLA, Oddelek za strojništvo, Kitajska

Glavni cilj projekta je razvoj novega eksoskeleta za izboljšanje človekovega gibanja v spodnjem delu telesa, ki je opremljen s hidromotorjem in vzmetjo v obeh kolkih in gležnjih, ter z vzmetjo v obeh kolenih. Ugotovili smo, da se pri vodenju v drsnem režimu s sledenjem sile eksoskeleta za spodnji del telesa, ki je delno opremljen z motorji, pojavlja določena napaka, ki vpliva na zmogljivost robota. Zato je bil uveden nov krmilni algoritem za sledenje sile pri vodenju v drsnem režimu z radialno bazično nevronsko mrežo (RBF), ki je zasnovan za zmanjšanje napake sledenja vodenja v drsnem režimu.

Najprej je oblikovan matematični model elektrohidravličnega servosistema in zapisane so enačbe za trenje hidravličnega ventila in motorja. Nato so izbrane primerne opazovalne funkcije in enačbe za napako krmilnega algoritma z drsnim režimom. Postavljen je krmilnik drsnega režima s primernim koeficientom površine za vodenje servosistema s sledenjem sile. Za zmanjšanje napake zaradi nespremenljive površine vodenja v drsnem režimu je uveden krmilni algoritem z radialno bazično nevronsko mrežo (RBF), ki z učinkovitim premikanjem drsne površine odpravlja težave pri vodenju v drsnem režimu. Končno so predstavljeni rezultati simulacije pri različnih frekvencah in rezultati preskusov vodenja s človeškim gibanjem v drsnem režimu in v drsnem režimu z RBF. Postopek obsega več korakov: (1) oblikovanje matematičnega modela elektrohidravličnega servosistema, (2) zasnovo opazovalnih funkcij krmilnika, (3) zasnovo krmilnika sistema.

Končno je zasnovan tudi nov krmilni algoritem za sledenje sile pri krmilniku z drsnim režimom RBF, s čimer je zaključen teoretični del članka.

Po simulacijah ter preskusih vodenja in krmilnika RBF z drsnim režimom pri različnih frekvencah na osnovi človeškega gibanja je bilo ugotovljeno, da je zmogljivost sledenja novega krmilnika z drsnim režimom RBF boljša kot pri navadnem krmilniku z drsnim režimom – tako pri nizkih kot pri visokih frekvencah. Rezultati so skladni s cilji raziskave. Čeprav daje predlagana metoda boljšo učinkovitost sledenja kot vodenje v drsnem režimu pri različnih frekvencah, pa se še vedno pojavlja določena napaka pri visokih frekvencah. Zato so potrebne še dodatne raziskave za večjo učinkovitost pri visokih frekvencah.

V članku je predstavljeno novo vodenje v drsnem režimu z nevronsko mrežo RBF s premično površino, katere naklon je določen z zgradbo mreže RBF. Predstavljene so tudi opazovalne funkcije vodenja za oceno parametrov.

Predlagana metoda vodenja izboljšuje sledenje sile pri robotu za spodnje okončine, podana je tudi predstavitev in diskusija rezultatov predlagane metode. Metoda je uporabna tudi za druge elektrohidravlične servosisteme, električne servosisteme, sisteme za krmiljenja položaja in lege robotov in letal, ter za druge nelinearne krmilne sisteme.

Ključne besede: eksoskelet, hidravlični servosistem, sledenje sile, vodenje v drsnem režimu, nevronska mreža RBF

SI 82

*Naslov avtorja za dopisovanje: Znanstveno-tehniška univerza PLA, Oddelek za strojništvo, No. 88, R. HouBiaoying,Dist. Baixia, Nanjing City, Kitajska, shl_s@163.com

Strojniški vestnik - Journal of Mechanical Engineering 60(2014)6, SI 83-84 Osebne objave

Doktorska disertacija, specialistično delo, magistrska dela, diplomske naloge

DOKTORSKE DISERTACIJE

DIPLOMSKE NALOGE

Na Fakulteti za strojništvo Univerze v Mariboru je obranil svojo doktorsko disertacijo: ● dne 20. maja 2014 Mihael DEŽELAK z naslovom: »Torzijsko elastično izravnavanje pri preoblikovanju pločevin z visoko trdnostjo« (mentor: izr. prof. dr. Ivo Pahole); Pojem elastično izravnavanje označuje spremembo geometrije pločevinastega izdelka po končanem preoblikovalnem procesu. Razčlenimo ga na kotno elastično izravnavanje, ukrivljenje stene in torzijsko elastično izravnavanje. Za slednjega, katerega analiza je temelj te disertacije, smo zaradi lažjega odčitavanja podali predlog izboljšane definicije.

Glavni razlog torzijskega elastičnega izravnavanja so zaostale membranske napetosti, ki se pri parcialni analizi testnega izdelka (laserski izrez posameznih področij) kažejo kot ukrivljenje stene. Na robustnost končne geometrije izdelkov zaradi variiranja vrednosti torzijskega elastičnega izravnavanja v veliki meri vplivajo stohastične lastnosti pločevin. Simulacije po metodi končnih elementov so danes v fazi načrtovanja preoblikovalnega procesa pločevin nenadomestljivo orodje. Toda natančno napovedovanje elastičnega izravnavanja je kljub temu zelo težavno, saj je izdelek med preoblikovalnim procesom podvržen kompleksnemu razvoju deformacijskega stanja, poleg tega pa določitev vrednosti materialnih, tehnoloških in numeričnih parametrov izrazito vpliva na rezultate simulacij. Za rešitev tega problema je podan predlog metode izboljšanja napovedi na podlagi izvedbe numeričnih eksperimentov in vrednotenja odstopanja rezultatov simulacij od eksperimentalnih vrednosti.

Na predstavljen način se je mogoče z računalniško simulacijo torzijskega elastičnega izravnavanja bolj približati rezultatom eksperimentov. Glavni potencial novega pristopa vidimo v podpori pri izvajanju geometrijskih korekcij na dejanskem orodju za doseganje zahtevanih toleranc izdelka.

Na Fakulteti za strojništvo Univerze v Ljubljani so pridobili naziv univerzitetni diplomirani inženir strojništva: dne 28. maja 2014: Matej MARUŠIČ z naslovom: »Razvoj naprave za preskušanje elektromagnetnih stikal zaganjalnikov« (mentor: izr. prof. dr. Jernej Klemenc); Klemen PODGORŠEK z naslovom: »Razvojno vrednotenje daljinsko vodenega regulatorja « (mentor: prof. dr. Marko Nagode, somentor: izr. prof. dr. Ivan Bajsić); dne 30. maja 2014: Blaž KRAŠČEK z naslovom: »Analiza delovanja aktivnega magnetnega regeneratorja pri uporabi tekočinskega toplotnega stikala« (mentor: izr. prof. dr.

Andrej Kitanovski, somentor: prof. dr. Alojz Poredoš).

SPECIALISTIČNO DELO Na Fakulteti za strojništvo Univerze v Ljubljani je z uspehom zagovarjal svoje specialistično delo: dne 5. maja 2014: Rok OGRIN z naslovom: »Tehnične osnove za prevzem, prevoz in montažo povezanih jeklenih konstrukcij zgradb in njihovih fasadnih oblog« (mentor: izr. prof. dr. Janez Kramar)

* Na Fakulteti za strojništvo Univerze v Mariboru je pridobila naziv univerzitetni diplomirani inženir strojništva: dne 29. maja 2014: Nina ŠKET z naslovom: »Uporabnost nizkotlačnih postopkov preoblikovanja visokoodpornih termoplastov« (mentorja: izr. prof. dr.

Igor Drstvenšek, asist. dr. Tomaž Brajlih). * Na Fakulteti za strojništvo Univerze v Mariboru sta pridobila naziv univerzitetni diplomirani gospodarski inženir: dne 29. maja 2014: Primož BUČAR z naslovom: »Vzpostavitev proizvodnje prezračevanih kuhinjskih stropov« (mentorja: doc. dr. Ignacijo Biluš, doc. dr. Igor Vrečko); Gregor OBLAK z naslovom: »Prihodnost fotovoltaike« (mentorja: doc. dr. Marjan Leber, prof. dr. Duško Uršič). * Na Fakulteti za strojništvo Univerze v Ljubljani so pridobili naziv magister inženir strojništva: dne 28. maja 2014: SI 83

Strojniški vestnik - Journal of Mechanical Engineering 60(2014)6, SI 83-84

Simon TROŠT z naslovom: »Meritve lastnosti vodnega skoka« (mentor: izr. prof. dr. Marko Hočevar, somentorja: prof. dr. Branko Širok, prof. dr. Franc Steinman); dne 30. maja 2014: Anica KOKELJ z naslovom: »Vpliv tehnologije izdelave krmilnega bata na karakteristike zavornega ventila« (mentor: doc. dr. Franc Majdič); Marko MEDEN z naslovom: »Razvoj novega zvezno delujočega potnega ventila za mobilno hidravliko« (mentor: doc. dr. Franc Majdič); Matej RAZPOTNIK z naslovom: »Vpliv togosti ležajev na vibracijske lastnosti statično predoločenih menjalnikov« (mentor: prof. dr. Miha Boltežar ); Andrej ČERNE z naslovom: »Lasersko navarjanje visokopoliranih jeklenih površin« (mentor: prof. dr. Janez Tušek); Borut ČERNE z naslovom: »Izdelava reološkega modela za napoved asimetričnega odziva polipropilena na natezne in tlačne obremenitve« (mentor: prof. dr.

Boris Štok, somentor: prof. dr. Volker Ulbricht); Nejc ŠKOBERNE z naslovom: »Numerično modeliranje mehanskega odziva zadebeljene arterije na tok krvi« (mentor: prof. dr. Boris Štok).

Benjamin ŠKAFAR z naslovom: »3D digitalizacija eksponatov kulturne dediščine in potencialna uporaba pridobljenih podatkov« (mentor: izr. prof. Vojmir Pogačar). * Na Fakulteti za strojništvo Univerze v Ljubljani so pridobili naziv diplomirani inženir strojništva: dne 15. maja 2014: Ivo GALOVIĆ z naslovom: »Bradavično uporovno varjenje matic na tanko pločevino« (mentor: prof. dr. Janez Tušek); Bojan MAROLT z naslovom: »Modeliranje kalupov na osnovi 3D slik« (mentor: prof. dr. Alojzij Sluga, somentor: doc. dr. Drago Bračun); Alenka VOGRIČ z naslovom: »Avtomatsko spajkanje« (mentor: prof. dr. Janez Tušek, somentor: doc. dr. Joško Valentinčič); dne 16. maja 2014: Boris KALŠAN z naslovom: »Namenska hidravlična stiskalnica« (mentor: doc. dr. Boris Jerman).

*

*

Na Fakulteti za strojništvo Univerze v Mariboru je pridobil naziv magister inženir strojništva: dne 28. maja 2014: Vid ŠARMAN z naslovom: »Zasnova varilne tehnologije dvižne roke bagerja iz mikrolegiranega jekla« (mentor: doc. dr. Tomaž Vuherer, somentor: doc. dr. Janez Kramberger).

Na Fakulteti za strojništvo Univerze v Mariboru sta pridobila naziv diplomirani inženir strojništva: dne 29. januarja 2014: Marija JAVORNIK z naslovom: »Avtomatizacija vijačenja vgradnih elementov na centralni prečni profil pečice« (mentor: doc. dr. Marjan Leber); David ŠUC z naslovom: »Zasnova orodja za izdelavo pogonskih gredi programatorja štedilnikov iz termoplastov« (mentor: izr. prof. dr. Igor Drstvenšek, somentor: asist. dr. Tomaž Brajlih).

* Na Fakulteti za strojništvo Univerze v Mariboru je pridobila naziv magister inženir tehniškega varstva okolja: dne 28. maja 2014: Nina GOSAK z naslovom: »Analiza onesnaženja zraka z delci v Sloveniji« (mentor: prof. dr. Lučka Kajfež Bogataj). * Na Fakulteti za strojništvo Univerze v Mariboru je pridobil naziv magister inženir oblikovanja izdelkov: dne 28. maja 2014:

SI 84

* Na Fakulteti za strojništvo Univerze v Ljubljani sta pridobila naziv diplomirani inženir strojništva (VS): dne 16. maja 2014: Gregor KOCJAN z naslovom: »Konstrukcija vpenjalne naprave za natančnejše pozicioniranje« (mentor: prof. dr. Jožef Duhovnik); Darko ŠUMAN z naslovom: »Razvoj manipulatorja za zlaganje in pozicioniranje grelnih plošč« (mentor: prof. dr. Jernej Klemenc, somentor: izr. prof. dr. Niko Herakovič).

Strojniški vestnik – Journal of Mechanical Engineering (SV-JME) Aim and Scope The international journal publishes original and (mini)review articles covering the concepts of materials science, mechanics, kinematics, thermodynamics, energy and environment, mechatronics and robotics, fluid mechanics, tribology, cybernetics, industrial engineering and structural analysis.

The journal follows new trends and progress proven practice in the mechanical engineering and also in the closely related sciences as are electrical, civil and process engineering, medicine, microbiology, ecology, agriculture, transport systems, aviation, and others, thus creating a unique forum for interdisciplinary or multidisciplinary dialogue.

The international conferences selected papers are welcome for publishing as a special issue of SV-JME with invited co-editor(s).

Editor in Chief Vincenc Butala University of Ljubljana, Faculty of Mechanical Engineering, Slovenia

Technical Editor Pika Škraba University of Ljubljana, Faculty of Mechanical Engineering, Slovenia

Founding Editor Bojan Kraut

University of Ljubljana, Faculty of Mechanical Engineering, Slovenia

Editorial Office University of Ljubljana, Faculty of Mechanical Engineering SV-JME, Aškerčeva 6, SI-1000 Ljubljana, Slovenia Phone: 386 (0)1 4771 137 Fax: 386 (0)1 2518 567 info@sv-jme.eu, http://www.sv-jme.eu Print: Littera Picta, printed in 400 copies Founders and Publishers University of Ljubljana, Faculty of Mechanical Engineering, Slovenia University of Maribor, Faculty of Mechanical Engineering, Slovenia Association of Mechanical Engineers of Slovenia Chamber of Commerce and Industry of Slovenia, Metal Processing Industry Association President of Publishing Council Branko Širok University of Ljubljana, Faculty of Mechanical Engineering, Slovenia

Vice-President of Publishing Council Jože Balič

University of Maribor, Faculty of Mechanical Engineering, Slovenia Cover: The energy-absorption devices, particular in the case of aircraft, allow a controlled collapse of the structure during which they absorb energy involving extensive plastic deformation. A small-scale experimental test is able to characterize the energy absorption of a material under compression by innovatively introducing self-supporting sinusoidal shape specimens (upper picture).

Lower pictures show typical broken specimens for both unidirectional and plain weave configurations.

Courtesy: MasterLab, University of Bologna, Italy

International Editorial Board Koshi Adachi, Graduate School of Engineering,Tohoku University, Japan Bikramjit Basu, Indian Institute of Technology, Kanpur, India Anton Bergant, Litostroj Power, Slovenia Franci Čuš, UM, Faculty of Mechanical Engineering, Slovenia Narendra B. Dahotre, University of Tennessee, Knoxville, USA Matija Fajdiga, UL, Faculty of Mechanical Engineering, Slovenia Imre Felde, Obuda University, Faculty of Informatics, Hungary Jože Flašker, UM, Faculty of Mechanical Engineering, Slovenia Bernard Franković, Faculty of Engineering Rijeka, Croatia Janez Grum, UL, Faculty of Mechanical Engineering, Slovenia Imre Horvath, Delft University of Technology, Netherlands Julius Kaplunov, Brunel University, West London, UK Milan Kljajin, J.J. Strossmayer University of Osijek, Croatia Janez Kopač, UL, Faculty of Mechanical Engineering, Slovenia Franc Kosel, UL, Faculty of Mechanical Engineering, Slovenia Thomas Lübben, University of Bremen, Germany Janez Možina, UL, Faculty of Mechanical Engineering, Slovenia Miroslav Plančak, University of Novi Sad, Serbia Brian Prasad, California Institute of Technology, Pasadena, USA Bernd Sauer, University of Kaiserlautern, Germany Brane Širok, UL, Faculty of Mechanical Engineering, Slovenia Leopold Škerget, UM, Faculty of Mechanical Engineering, Slovenia George E. Totten, Portland State University, USA Nikos C. Tsourveloudis, Technical University of Crete, Greece Toma Udiljak, University of Zagreb, Croatia Arkady Voloshin, Lehigh University, Bethlehem, USA General information Strojniški vestnik – Journal of Mechanical Engineering is published in 11 issues per year (July and August is a double issue).

Institutional prices include print & online access: institutional subscription price and foreign subscription €100,00 (the price of a single issue is €10,00); general public subscription and student subscription €50,00 (the price of a single issue is €5,00). Prices are exclusive of tax.

Delivery is included in the price. The recipient is responsible for paying any import duties or taxes. Legal title passes to the customer on dispatch by our distributor.

Single issues from current and recent volumes are available at the current single-issue price. To order the journal, please complete the form on our website. For submissions, subscriptions and all other information please visit: http://en.sv-jme.eu/.

You can advertise on the inner and outer side of the back cover of the magazine. The authors of the published papers are invited to send photos or pictures with short explanation for cover content.

We would like to thank the reviewers who have taken part in the peerreview process.

ISSN 0039-2480 © 2014 Strojniški vestnik - Journal of Mechanical Engineering.

All rights reserved. SV-JME is indexed / abstracted in: SCI-Expanded, Compendex, Inspec, ProQuest-CSA, SCOPUS, TEMA. The list of the remaining bases, in which SV-JME is indexed, is available on the website.

The journal is subsidized by Slovenian Research Agency.

Strojniški vestnik - Journal of Mechanical Engineering is also available on http://www.sv-jme.eu, where you access also to papers’ supplements, such as simulations, etc.

Instructions for Authors All manuscripts must be in English. Pages should be numbered sequentially. The maximum length of contributions is 10 pages. Longer contributions will only be accepted if authors provide justification in a cover letter. Short manuscripts should be less than 4 pages. For full instructions see the Authors Guideline section on the journal’s website: http://en.sv-jme.eu/.

Please note that file size limit at the journal’s website is 8Mb. Announcement: The authors are kindly invited to submitt the paper through our web site: http://ojs.sv-jme.eu. Please note that file size limit at the journal’s website is 8Mb. The Author is also able to accompany the paper with Supplementary Files in the form of Cover Letter, data sets, research instruments, source texts, etc. The Author is able to track the submission through the editorial process - as well as participate in the copyediting and proofreading of submissions accepted for publication - by logging in, and using the username and password provided.

Please provide a cover letter stating the following information about the submitted paper: 1. Paper title, list of authors and affiliations.

2. The type of your paper: original scientific paper (1.01), review scientific paper (1.02) or short scientific paper (1.03).

3. A declaration that your paper is unpublished work, not considered elsewhere for publication.

4. State the value of the paper or its practical, theoretical and scientific implications. What is new in the paper with respect to the state-of-the-art in the published papers?

5. We kindly ask you to suggest at least two reviewers for your paper and give us their names and contact information (email).

Every manuscript submitted to the SV-JME undergoes the course of the peer-review process.

THE FORMAT OF THE MANUSCRIPT The manuscript should be written in the following format: - A Title, which adequately describes the content of the manuscript.

- An Abstract should not exceed 250 words. The Abstract should state the principal objectives and the scope of the investigation, as well as the methodology employed. It should summarize the results and state the principal conclusions.

- 6 significant key words should follow the abstract to aid indexing.

- An Introduction, which should provide a review of recent literature and sufficient background information to allow the results of the article to be understood and evaluated.

- A Theory or experimental methods used.

- An Experimental section, which should provide details of the experimental set-up and the methods used for obtaining the results.

- A Results section, which should clearly and concisely present the data using figures and tables where appropriate.

- A Discussion section, which should describe the relationships and generalizations shown by the results and discuss the significance of the results making comparisons with previously published work. (It may be appropriate to combine the Results and Discussion sections into a single section to improve the clarity).

- Conclusions, which should present one or more conclusions that have been drawn from the results and subsequent discussion and do not duplicate the Abstract.

- References, which must be cited consecutively in the text using square brackets [1] and collected together in a reference list at the end of the manuscript.

Units - standard SI symbols and abbreviations should be used. Symbols for physical quantities in the text should be written in italics (e.g. v, T, n, etc.).

Symbols for units that consist of letters should be in plain text (e.g. ms-1, K, min, mm, etc.)

Abbreviations should be spelt out in full on first appearance, e.g., variable time geometry (VTG).

Meaning of symbols and units belonging to symbols should be explained in each case or quoted in a special table at the end of the manuscript before References.

Figures must be cited in a consecutive numerical order in the text and referred to in both the text and the caption as Fig. 1, Fig. 2, etc. Figures should be prepared without borders and on white grounding and should be sent separately in their original formats.

Pictures may be saved in resolution good enough for printing in any common format, e.g. BMP, GIF or JPG. However, graphs and line drawings should be prepared as vector images, e.g. CDR, AI. When labeling axes, physical quantities, e.g. t, v, m, etc. should be used whenever possible to minimize the need to label the axes in two languages.

Multi-curve graphs should have individual curves marked with a symbol. The meaning of the symbol should be explained in the figure caption.

Tables should carry separate titles and must be numbered in consecutive numerical order in the text and referred to in both the text and the caption as

Table 1, Table 2, etc. In addition to the physical quantity, e.g. t (in italics), units (normal text), should be added in square brackets. The tables should each have a heading. Tables should not duplicate data found elsewhere in the manuscript.

Acknowledgement of collaboration or preparation assistance may be included before References. Please note the source of funding for the research.

REFERENCES A reference list must be included using the following information as a guide. Only cited text references are included. Each reference is referred to in the text by a number enclosed in a square bracket (i.e., [3] or [2] to [6] for more references). No reference to the author is necessary.

References must be numbered and ordered according to where they are first mentioned in the paper, not alphabetically. All references must be complete and accurate. All non-English or. non-German titles must be translated into English with the added note (in language) at the end of reference. Examples follow.

Journal Papers: Surname 1, Initials, Surname 2, Initials (year). Title. Journal, volume, number, pages, DOI code.

[1] Hackenschmidt, R., Alber-Laukant, B., Rieg, F. (2010). Simulating nonlinear materials under centrifugal forces by using intelligent crosslinked simulations. Strojniški vestnik - Journal of Mechanical Engineering, vol. 57, no. 7-8, p. 531-538, DOI:10.5545/sv-jme.2011.013.

Journal titles should not be abbreviated. Note that journal title is set in italics.

Please add DOI code when available and link it to the web site.

Books: Surname 1, Initials, Surname 2, Initials (year). Title. Publisher, place of publication.

[2] Groover, M.P. (2007). Fundamentals of Modern Manufacturing. John Wiley & Sons, Hoboken.

Note that the title of the book is italicized.

Chapters in Books: Surname 1, Initials, Surname 2, Initials (year). Chapter title. Editor(s) of book, book title. Publisher, place of publication, pages.

[3] Carbone, G., Ceccarelli, M. (2005). Legged robotic systems. Kordić, V., Lazinica, A., Merdan, M. (Eds.), Cutting Edge Robotics. Pro literatur Verlag, Mammendorf, p. 553-576.

Proceedings Papers: Surname 1, Initials, Surname 2, Initials (year). Paper title. Proceedings title, pages.

[4] Štefanić, N., Martinčević-Mikić, S., Tošanović, N. (2009). Applied Lean System in Process Industry. MOTSP 2009 Conference Proceedings, p.

422-427.

Standards: Standard-Code (year). Title. Organisation. Place.

[5] ISO/DIS 16000-6.2:2002. Indoor Air – Part 6: Determination of Volatile Organic Compounds in Indoor and Chamber Air by Active Sampling on TENAX TA Sorbent, Thermal Desorption and Gas Chromatography using MSD/FID. International Organization for Standardization. Geneva. www pages: Surname, Initials or Company name. Title, from http://address, date of access.

[6] Rockwell Automation. Arena, from http://www.arenasimulation.com, accessed on 2009-09-07.

EXTENDED ABSTRACT By the time the paper is accepted for publishing, the authors are requested to send the extended abstract (approx. one A4 page or 3.500 to 4.000 characters). The instructions for writing the extended abstract are published on the web page http://www.sv-jme.eu/ information-for-authors/.

COPYRIGHT Authors submitting a manuscript do so on the understanding that the work has not been published before, is not being considered for publication elsewhere and has been read and approved by all authors. The submission of the manuscript by the authors means that the authors automatically agree to transfer copyright to SV-JME and when the manuscript is accepted for publication. All accepted manuscripts must be accompanied by a Copyright Transfer Agreement, which should be sent to the editor. The work should be original by the authors and not be published elsewhere in any language without the written consent of the publisher.

The proof will be sent to the author showing the final layout of the article. Proof correction must be minimal and fast. Thus it is essential that manuscripts are accurate when submitted.

Authors can track the status of their accepted articles on http://en.svjme.eu/.

PUBLICATION FEE For all articles authors will be asked to pay a publication fee prior to the article appearing in the journal. However, this fee only needs to be paid after the article has been accepted for publishing. The fee is 300.00 EUR (for articles with maximum of 10 pages), 20.00 EUR for each addition page.

Additional costs for a color page is 90.00 EUR.

http://www.sv-jme.eu

60 (2014) 6

Strojniški vestnik Journal of Mechanical Engineering

Since 1955

Papers

375

Enrico Troiani, Lorenzo Donati, Gianluca Molinari, Raffaella Di Sante: Influence of Plying Strategies and Trigger Type on Crashworthiness Properties of Carbon Fiber Laminates Cured through Autoclave Processing

382

Marjan Leber, Majda Bastič, Borut Buchmeister: The Trends in Usage and Barriers of Innovation Management Techniques in New Product Development

389

Sergey Nikolaevich Grigoriev, Tatyana Vasilievna Tarasova, Galina Olegovna Gvozdeva, Steffen Nowotny: Structure Formation of Hypereutectic Al-Si-Alloys Produced by Laser Surface Treatment

395

Qihui Yu, Maolin Cai, Yan Shi, Zichuan Fan: Optimization of the Energy Efficiency of a Piston Compressed Air Engine

407

Ana Bižal, Jernej Klemenc, Matija Fajdiga: Evaluating the Statistical Significance of a Fatigue-Life Reduction Due to Macro-Porosity

417

Yesid Asaff, Victor J. De Negri, Heinrich Theissen, Hubertus Murrenhoff: Analysis of the Influence of Contaminants on the Biodegradability Characteristics and Ageing of Biodegradable Hydraulic Fluids

425

Miha Praznik, Vincenc Butala, Martina Zbašnik-Senegačnik: A Simple Method for Evaluating the Sustainable Design of Energy Efficient Family Houses

437

Shengli Song, Xinglong Zhang, Zhitao Tan: RBF Neural Network Based Sliding Mode Control of a Lower Limb Exoskeleton Suit

Journal of Mechanical Engineering - Strojniški vestnik

Contents

6 year 2014 volume 60 no.