Ijsrtm vol 2 (4) june july 2014 by GIAP Journals

Vol 2 (4) June 2014

International Journal of Studentsâ&#x20AC;&#x2122; Research in Technology & Management (IJSRTM)

Content List 1.Exergy Analysis of Vapor Compression Refrigeration System Using R12 and R134a as Refrigerants Mohan Chandrasekharan 2. Investigation of Mechanical Properties of Aluminium 6061 Alloy Friction Stir Welding J. Stephen Leon and Dr. V. Jayakumar 3. Microwave Assisted Trans-esterification of Waste Cooking Oil in Presence of Alkali Catalyst Hasna Khalfan AlSuleimani, Priy Brat Dwivedi 4. Prediction of Excess Air Requirement Using ANN for the Improvement of Boiler Efficiency Arun. S. Gopinath and N. Sreenivasa Babu 5. Study of Microwave Radiation on Transesterification of Jatropha Oil in Presence of Alkali Catalyst Nadira Hassan Mohammed Al Balushi, Priy Brat Dwivedi

International Journal of Students’ Research in Technology & Management Vol 2 (04), June-July 2014, ISSN 2321-2543, pg 134-139

Exergy Analysis of Vapor Compression Refrigeration System Using R12 and R134a as Refrigerants Mohan Chandrasekharan#1 # Department of Engineering, Mechanical Engineering Section, Al Musanna College of Technology, Muladdah, Post Box 191, Postal Code 314, Sultanate of Oman. 1

Chandra@act.edu.om

Abstract— This paper deals with a comparative analysis of the influence of refrigerant on the performance of a simple vapor compression refrigeration system. The study is based on the refrigerants R12 and R134a. A computational model based on energy and exergy analysis is presented for investigation of the effects of evaporating temperature and degree of sub-cooling on the coefficient of performance and exergitic efficiency of the refrigerator. A considerable part of the energy produced worldwide is consumed by refrigerators. So it is crucial to minimize the energy utilization of these devices. The exergy analysis has been widely used in the analysis of all engineering systems including refrigerators. It is a powerful tool for the design, optimization and performance evaluation of energy systems. It is well known fact that the CFC and HCFC refrigerants have been forbidden due to chlorine content and there high ozone depleting potential (ODP) and global warming potential (GWP). Hence HFC refrigerants are used now-a-days. Many research papers have been published on the subject of replacing CFC and HCFC refrigerants with other types of refrigerants. This paper presents a comparative analysis of two refrigerants working in a one stage vapor compression refrigeration system with sub-cooling and superheating. These refrigerants are: Dichlorodifluoromethane (R-12) and Tetrafluoroethane (R-134a). Keywords —Vapor compression refrigeration system, Exergy, COP, Exergetic efficiency, Degree of sub-cooling.

I. INTRODUCTION Chlorofluorocarbons (CFCs) have been used widely over the last eight decades in refrigeration and air-conditioning due to their favorable characteristics such as low freezing point, non-flammability, non-toxicity and chemically stable behavior with other materials. Unfortunately, in recent years it has been recognized that the chlorine released from CFCs migrate to the stratosphere and destroys the earth’s ozone layer, causing serious health problems [1, 2].

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The Montreal Protocol signed by the international community in 1987 regulates the production and marketing of ozone depleting substances. The CFCs were prohibited completely in 2010. Hydro-fluorocarbons (HFCs) are presently replacing CFCs as they do not contain any chlorine atoms and their ozone depletion potential (ODP) is zero. Refrigerator pumps heat from a closed space to the atmosphere. Heat transfer between the system and the surroundings takes place at a finite temperature difference, which is a major source of irreversibility for the cycle. Irreversibility causes the system performance to degrade. The losses in the cycle need to be evaluated considering individual thermodynamic processes that make up the cycle. Energy analysis is still the most commonly used method in the analysis of thermal systems. The first law is concerned only with the conservation of energy, and it gives no information on how, where, and how much the system performance is degraded. Exergy analysis is a powerful tool in the design, optimization, and performance evaluation of energy systems [9]. The principles and methodologies of exergy analysis are well established [6-8]. An exergy analysis is usually aimed to determine the maximum performance of the system and identify the sites of exergy destruction. Analyzing the components of the system separately can perform exergy analysis of a complex system. Identifying the main sites of exergy destruction shows the direction for potential improvements. There have been several studies on the performance of alternative environment-friendly refrigerants on the basis of energy and exergy analysis of refrigeration systems. Said and Ismail [8] assessed the theoretical performances of R123, R134a, R11 and R12 as coolants. It was established that for a specific amount of desired exergy, more compression work is required for R123 and R134a than R11 and R12. The

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differences are not very significant at high evaporation temperatures and hence R123 and R134a should not be excluded as alternative coolants. Also, in their study they obtained an optimum evaporation temperature for each condensation temperature, which yields the highest exergetic efficiency. Aprea and Greco [9] compared the performance between R22 and R407C (a zeotropic blend) and suggested that R407C is a promising drop-in substitute for R22. Experimental tests were performed in a vapour compression plant with a reciprocating compressor to evaluate the compressor performance using R407C in comparison to R22. The plant overall exergetic performance was also evaluated and revealed that R22 performance is consistently better than that of its candidate substitute (R407C). Aprea and Renno [9] studied experimentally, the performance of a commercial vapour compression refrigeration plant, generally adopted for preservation of foodstuff, using R22 and its candidate substitute (R417A) as working fluids. The working of the plant was regulated by on/off cycles of the compressor, operating at the nominal frequency of 50 Hz, imposed by the classical thermostatic control. The reported result indicated that the substitute refrigerant (R417A), which is a non-azeotropic mixture and non-ozone depleting, can serve as a long term replacement for R22; it can be used in new and existing direct expansion R22 systems using traditional R22 lubricants. Also in their analysis, the best exergetic performances of R22 in comparison with those of R417A were determined in terms of the coefficient of performance, exergetic efficiency and exergy destroyed in the plant components. Khalid [10] studied the performance analysis of R22 and its substitute refrigerant mixtures R407C, R410A and R417A on the basis of first law. It was found that the COP of R417A is 12% higher than R22, but for R407C and R410A, COP is 5% lowered as compared to R22, and R417A can be used in existing system without any modification. Various studies reviewed above focused mostly on the exergetic analysis of R22 and its alternative refrigerants. R12 is used solely in the majority of conventional household refrigerators, and there is currently little information on the exergetic performance of R12 alternatives. Therefore, in this paper, exergetic performances of a domestic refrigeration system using R12 and its environmentfriendly alternative refrigerant R134a are theoretically studied and compared. II. SYSTEM DESCRIPTION A one stage vapor compression refrigeration system is considered as numerical exemplification of the proposed

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study. The system is composed by a mechanical piston compressor, a condenser, a throttling valve and an evaporator, as shown in Figure 1. The refrigerant enters the compressor at state 1, with a superheating degree ΔT SH with respect to the evaporation temperature TV. It follows the irreversible compression process 1-2, characterized by an increase in entropy from state 2s (adiabatic reversible compression) to state 2. The refrigerant leaves the compressor as superheated vapor at pressure PC and enters the condenser and sub-cooler, arriving in state 3 as sub-cooled liquid that is further throttled during the process 3-4. Its pressure is the vaporization pressure PV and the cycle is closed by a vaporization process 4-1 in the evaporator and super-heater.

Fig. 1: Single stage Vapor Compression Refrigeration System

III. MATHEMATICAL MODEL The system is analyzed both from energetic and exergetic points of view. A. Energetic Approach This analysis is applied either to each device (seen as a control volume) or to the entire system (a control mass). It is based on the First Law of Thermodynamics, whose mathematical expression for a control volume is:

∑ )

̇ ( ̇

)

∑

̇ ( (1)

where E represents system energy (J), t stands for time (s), h is the specific enthalpy of refrigerant (J/kg), v2/2 is the specific kinetic energy (J/kg), gz is the specific potential energy (J/kg), ̇ is the mass flow rate of refrigerant (kg/s), ̇ and ̇ are the energetic exchanges of the control volume with its surroundings in form of heat flux and work rate (power).

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The subscripts i and o stands for inlet and outlet states, respectively.

(8)

For steady state operation, equation (1) becomes: B. Exergetic Approach ̇

∑ ̇ (

)

∑ ̇ (

)

̇ (2)

In vapor compression refrigeration system, changes in kinetic and potential energies are negligible. So equation 2 becomes: ̇ ̇

∑

∑ ̇ ̇

(3) which is applied to each device of the system: (a) for the evaporator: ̇

The exergetic balance equation for a control volume is: ̇ (4)

where ̇ represents the refrigeration load.

∑(

) ̇ ∑ ̇

(b) for the condenser: ̇

A reversible thermodynamic process can be reversed without leaving any trace on the surroundings. This is possible only if the net heat and net work exchange between the system and the surrounding is zero [9]. All real processes are irreversible. Some factors causing irreversibility in a refrigeration cycle include friction and heat transfer across a finite temperature difference in the evaporator, compressor, condenser, and refrigerant lines, sub-cooling to ensure pure liquid at capillary tube inlet, super heating to ensure pure vapour at compressor inlet, pressure drops, and heat gains in refrigerant lines [11]. Accurate analysis of the system is obtained by evaluating the exergy used in the system components. The p-h diagram of the vapor compression refrigeration cycle is presented in Figure 2. Exergy flow destroyed in each of the components is evaluated as follows [3, 9]:

( ̇

)

∑ ̇

̇ (9)

̇ (5)

where ̇ is the rate of heat rejected at the condenser (c) for the compressor: ̇ ̇ (6) where ̇ is the rate of work input to the compressor. (d) for the throttling valve: ̇

̇ (7)

The energetic efficiency of the system is measured by the coefficient of performance:

Fig. 2: Vapor compression refrigeration system on p-h diagram.

For steady state operation, equation 9 becomes:

̇ ̇

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) ̇

∑(

The only source of exergy input to the system is through the electrical power supplied to the compressor ( ̇ ), that is, ̇ = ̇ and Eq. (17) can be expressed as:

∑ ̇

∑ ̇ (10)

(

Applying the exergetic balance equation to each component of the vapor compression refrigeration system, (a) for the evaporator: ̇

̇ ̇

)

or (

) ̇

(

̇ ̇

) (19)

̇ (11) IV. RESULTS AND DISCUSSION

(b) for the compressor: ̇

̇ ̇

̇ (12)

Figure 3 shows the variation of COP with varying evaporator temperature for R134a and R12. The graph shows that the COP increases with increase in evaporator temperature for both the refrigerants. At lower temperatures COP is slightly higher for R134a than R12. However, at higher evaporator temperatures, COP of R12 is higher than that of R134a.

(13) (d) for the throttling valve: ̇ ̇

̇ (14)

The throttling process is isenthalpic process. h3 = h4. Therefore, equation 14 can be expressed as: ̇ ̇ (15) The total exergy destruction rate, ̇

̇ Fig. 3: Variation of COP with evaporator temperature

The overall system exergetic efficiency ( ) is the ratio of the exergy output ( ̇ ) to exergy input ( ̇ ) [3]. (

) ̇

(17) ̇

Variation of exergetic efficiency with evaporator temperature is given in figure 4. Exergetic efficiencies of both the refrigerants decrease with increase in evaporator temperature. At lower evaporator temperatures, the exergetic efficiency of VCRS operating on R134a is higher than those operating on R12. But at higher evaporator temperatures R12 system has higher exergetic efficiency than R134a system.

(18)

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Fig. 4: Variation of exergetic efficiency with evaporator temperature

The figure 5 shows the variation of COP with degree of subcooling. COP increases with increase in degree of sub-cooling for both the refrigerants. R134a is more sensitive to variation in degree of sub-cooling

Fig. 6: Variation of exergetic efficiency with degree of sub-cooling

V. CONCLUSION A comparative analysis of the refrigerant impact on the operation and performances of a one stage vapor compression refrigeration system was presented. The effects of evaporator temperature and sub-cooling were studied on the system operation and performances. Based on the exergy analysis, exergy destruction rates were estimated for each component of the system in a comparative manner for two refrigerants (R12, R134a).

Fig. 5: Variation of COP with degree of sub-cooling The variation of exergetic efficiency with degree of subcooling is shown in the figure 6 below. Exergetic efficiency increases with degree of sub-cooling for both the refrigerants. The variation is steeper for R134a than R12.

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REFERENCES [1]

[2]

[3]

[4] [5]

Akash, B.A.; and Said, S.A. (2003). Assessment of LPG as a possible alternative to R12 in domestic refrigerators. Energy Conversion and Management, 44(3), 381-388. Sattar, M.A.; Saidur, R.; and Masjuki, H.H. (2007). Performance investigation of domestic refrigerator using pure hydrocarbons and blends of hydrocarbons as refrigerants. Proceedings of World Academy of Science, Engineering and Technology, ISSN 1307-6884, 23, 223-228. Bolaji, B.O. (2005). CFC refrigerants and stratospheric ozone: past, present and future. In: Environmental sustainability and conservation in Nigeria, Okoko, E. and Adekunle, V.A.J. (Eds.); Book of Readings of Environment Conservation and Research Team, 37, 231-239. Moran, M.J. (1992). Availability analysis: a guide to efficient energy use. New Jersey: Prentice-Hall, Englewood Cliffs. Aprhornratana, S.; and Eames, I.W. (1995). Thermodynamic analysis of absorption refrigeration cycles using the second law of thermodynamics. International Journal of Refrigeration, 18(4), 244252.

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[6] [7] [8]

[9] [10] [11]

Bejan, A. (1998). Advanced engineering thermodynamics. New York: John Wiley and Sons Inc. Dincer, I.; and Cengel, Y.A. (2001). Energy, entropy and exergy concepts and their roles in thermal engineering. Entropy, 3, 116-149. Said, S.A.M.; and Ismail, B. (1994). Exergetic assessment of the coolants HCFC123, HFC134a, CFC11, and CFC12. Energy, 19(11), 1181-1186. Aprea, C.; and Greco, A. (2002). An exergetic analysis of R22 substitution. Applied Thermal Engineering, 22(13), 1455-1469. Khalid, M.A. (2006). Comparison of performance analysis of R22 and its alternate. 11th HVACR Conference, Krachi, 56-67. Kilicaslan, C.; Songnetichaovalit, T.; and Lokathada, N. (2004). Experimental comparison of R22 with R417A performance in a vapour compression refrigeration system. Energy Conversion Management, 45, 1835-1847.

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Investigation of Mechanical Properties of Aluminium 6061 Alloy Friction Stir Welding J. Stephen Leon1 and Dr. V. Jayakumar2 Faculty of Mechanical and Engineering, Department of Engineering Ibri College of Technology, Ibri, Sultanate of Oman 1

stephenleonj@gmail.com

Abstract– Aluminium 6061 alloy is commonly used for construction of aircraft structures, such as wings and fuselages, more commonly in homebuilt aircraft than commercial or military aircraft. Aluminium 6061 alloy generally present low weldability by traditional fusion welding process. The development of Friction Stir Welding (FSW) has provided an alternative improved way of satisfactorily producing weld joint in aluminium 6061 alloy. In FSW, the welding tool motion induces frictional heating and severe plastic deformation and metal joining process is done in solid state results, which results in defect free welds with good mechanical properties in aluminium alloy 6061. Unlike in traditional fusion welding, friction stir welds will not encounter problems like porosity alloy segregation and hot cracking, and welds are produced with good surface finish. In this paper, an attempt was made to investigate the impact of process parameters of FSW in the mechanical properties of the joint. The tensile properties, microstructure, hardness of the FSW joints were investigated in the weldment and heat affected zone. The changes of mechanical properties are compared with the parental metal. The welding parameters such as tool rotational speed and welding speed plays a major role in deciding the joint characteristics. This paper focusses on optimization of all these parameters. From this investigation it was found that the joint made from the FSW yielded superior tensile properties and impact strength due to the higher hardness and fine microstructure.

welded is not melted rather the two parts of weld joints are brought into contact and the interface is strongly forged together under the effect of heavy plastic deformation caused by the inserted rotating stir probe pin [2]. In FSW a rotating cylindrical, shouldered tool with a profiled probe penetrates into the material until the tool shoulder contacts with the upper surface of the plates, which are butted together as shown in figure 1.

Fig 1 Principle of FSW

Key Words– FSW, welding speed, axial force, mechanical properties, microstructure.

INTRODUCTION

In recent years, demands for aluminium alloy 6061 have steadily increased in aerospace, aircraft and automobile applications because of their excellent strength to weight ratio, good ductility, corrosion resistance and cracking resistance in adverse environment. Welding of these alloys, however, still remains a challenge. Apart from softening in the weld fusion zone and heat affected zone, hot cracking in the weld can be a serious problem [1]. Thus, the solid state bonding process is highly recommended to solve these problems. FSW is an innovative solid state welding process in which the metal to be

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The parts have to be clamped on to a backing bar in a manner that prevents the abutting joint faces from being forced apart. Frictional heat is generated between the wear resistant welding tool and the material of the work pieces. This heat causes the later to soften without reaching the melting point and allows traversing of the tool along the weld line. In FSW, tool rotation rate (rpm) in clockwise or counter clockwise direction and tool traverse speed (mm/min) along the joint are the most important parameters [3]. II.

LITRATURE REVIEW

The effect of FSW parameters on temperature was examined by Muhsin et al .[4]. They concluded that the maximum

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temperature is a function of tool rotation rate while the rate of heating was a function of traverse speed. Munoz et al. [5] investigated the microstructure and mechanical properties of friction stir welded and TIG welded Al-Mg-Sc alloy and reported that the yield strength FSW welded joint is decreased 20 % compared to base metal. Apart from this, there have been lot of efforts to understand the effect of process parameters on material flow behaviour, microstructure formation and mechanical properties of friction stir welded joints. Finding the most effective parameters on properties of friction stir welds as well as realizing their influence on the weld properties has been major topics for researchers [6â&#x20AC;&#x201C;8]. Extensive literature of friction stir welding of Al alloys does indicate that there are few areas particularly on the relationship between welding parameters and change in the mechanical properties of weldment. This paper focuses on finding the optimal speed (rpm) and feed rate (mm/s) with respect to mechanical properties such as hardness number and tensile strength. III. EXPERIMENTAL PROCEDURE AA 6061 aluminum alloy chemical composition and mechanical properties are given in table 1 and 2 respectively. TABLE 1 CHEMICAL COMPOSITION IN %WT

Name of Mg the Al alloy

AA 6061 0.9 0.62 0.33 0.28 0.17 0.06 0.02 0.02 Balance

TABLE 2 MECHANICAL PROPERTIES

Name of the Aluminum alloy

Yield strength in MPa

Ultimate strength in MPa

Elangation %

AA 6061

110

207

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Hardness in HV

All dimensions are in mm Fig 2 Square Butt joint

The rolled plates of AA6061 aluminium alloy were machined to the required dimensions (300 mm X 150 mm). Square butt joint configuration as shown in fig 2 was prepared to fabricate FSW joints. A non-consumable, rotating tool made up of high carbon steel was used. Probe diameter is 6 mm, shoulder diameter is 18 mm and pin length is 5.5 mm. FSW was carried out on a FSW machine manufactured by RV machine tools, India. Machine specifications are given in table 3. TABLE 3. MACHINE SPECIFICATIONS

Spindle Spindle speed Z axis thrust X axis thrust Spindle motor Version

ISO 40 1000 to 3000 rpm (infinitely variable) 3000 to 10000 kgf 1000 to 5000 kgf 11 kW/440 v, AC spindle servo motor CNC

The Aluminium plates are positioned in the fixtures, which is prepared for fabricating FSW joints by using mechanical clamps so that the plates will not separate during welding. In present work, different FSW butt welds were obtained by varying tool rotation speed and welding speed with in the range obtained by the previous works [9, 10] by keeping the axial force constant. In this work FSW process was conducted with two variables: rotational speed (rpm) of the tool pin and traverse speed (mm/min) of the machine table. The rotational speed was chosen as: 720, 910, 1120 and 1400 rpm while the traverse speeds were 16, 20, and 31.5 mm/min. IV. RESULT AND DISCUSSION

A. Macro and Microscopic Visual Examination The optical microstructures of the base metal and weld centre are shown in fig 3 Macroscopic visual examination of all welded specimens in transverse and longitudinal cross section showed defect-free sound weldments, produced under all applied experimental conditions. Uniform semicircular surface ripples in weld track were observed. These surface ripples, which have onion rings configuration, were caused by the final sweep of the

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trailing edge of the continuously rotating tool shoulder. A similar observation was made by many researchers [11-14].

Base metal

Fig 4. Hardness Vs distance from weldment at 1400 rpm

Comparing with base metal hardness decreases towards the weld centre. This is due to the shear stress induced by the tool motion which lead to the generation of very fine grain structure as shown in fig 3. Dynamic recovery and recrystallization are the main softening mechanisms during FSW. When the average values of hardness in the welding centre were plotted against different tool rotation speed in fig 5, it was observed that when rotation speed increases more than 1200 rpm hardness in the weldment increases. This is because of the relatively high stacking fault energy which causes cross slip. This explanation was reached also by many researchers [15-19]. The result also reveals that 80-90% reduction in hardness comparing with base metal when traverse speed increases from 16 to 31.5 mm/min.

FSW

Combined influence of temperature and plastic deformation induced by the stirring action causes the recrystallized structure. In many FSW references on aluminum alloys, the initial elongated grains of the base materials are converted to a new equiaxed fine grain structure. This experiment confirms that behavior. The grain structure within the nugget is fine and equiaxed and the grain size is significantly smaller than that in the base materials due to the higher temperature and extensive plastic deformation by the stirring action of the tool pin. During FSW, the tool acts as a stirrer extruding the material along the welding direction. The varying rate of the dynamic recovery or recrystallization is strongly dependent on the temperature and the strain rate reached during deformation.

Hardness in HV

Fig 3. Optical Micrographs of base metal and weldment

80 60

Welding Speed 16 mm/min

40 20 0 720

910 1120 1400

Welding Speed 31.5 mm/min

Speed in rpm

Fig 5. Hardness vs speed

B. Hardness Using Vickerâ&#x20AC;&#x2122;s hardness testing machine hardness across the welds cross-section was measured. Hardness values are taken from weld face, midway through the weld nugget and near to the root of the FSW joint. The average values were plotted against the distance from the welding centre (fig 4).

Hardness in HV

80 60

Welding Speed 16 mm/min

40 20 -40 -30 -20 -10 0 10 20 30 40

Welding Speed 31.5 mm/min

Distance from Weldment in mm

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C. Tensile Properties

the base material strength, while the highest yield strength found was over 90% of the base material strength. When the welding speed reduces, the specimen elongation in the weldment is nearly equal to the base metal.

Ultimate Strength in MPa

150 Welding Speed 16 mm/min

100 50 0 720 910 1120 1400 Rotational Speed in rpm

Welding Speed 31.5 mm/min

Yield Stress in MPa

Fig 6.Ultimate strength vs Rotational speed

150 Welding Speed 16 mm/min

100 50 0 720

910 1120 1400

Welding Speed 31.5 mm/min

Rotational Speed in rpm

Percent Elangation

17 Welding Speed 16 mm/min

15 14 13 720

910 1120 1400

Rotational Speed in rpm

Welding Speed 31.5 mm/min

Fig 8.Percentage Elongation vs Rotational speed

The transverse tensile properties such as yield stress, tensile strength and percentage of elongation of AA6061 aluminium alloy joints were evaluated. The measurements of ultimate tensile strength, yield stress and elongation for the welded specimen are shown in fig 6-8 respectively. The lowest ultimate tensile stress (UTS) found for welds in Al6061-T6 was 66% of

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CONCLUSION

In this paper, an attempt was made to investigate the impact of process parameters of FSW in the mechanical properties of the joint. From this investigation, the following conclusions have been derived: (i) The weld root surface of all the weldments showed visually a well joined defect free sound flat surface. (ii) The increase in stir–probe rotation speed more than 1200 rpm enhanced the weld soundness which may be a result of softening process associated with dynamic recovery and recrystallization process at the weld. (iii) The formation of fine equiaxed grains and uniformly distributed, very fine strengthening precipitates in the weld region are the reasons for the superior tensile properties of FSW joints. (iv) The width of the stir zone may depend on the balance between the total heat input and the cooling in the plasticized material. The area of the weld nugget zone size slightly decreased as the welding speed increased. Comparing with other welding speeds, the lowest speed 16mm/min results better mechanical properties and increase in the area of the weld nugget. REFERENCES

Fig 7.Yeild strength vs Rotational speed

[1] Mohandoss T, Madhusudhanan reddy G (1996) Effect of frequency of pulsing in gas tungsten arc welding on the microstructure and mechanical properties of titanium alloy welds. J Matar Sci Lett 15:626-628. [2] Larson, H,. Karlsson L “ A Welding Review”, Vol 54 N o2 ESAB AB, Sweden, PP 6-10,2000. [3] H.J. Liu, H. Fuiji, M. Maeda, K, Nogi. 2003. Tensile properties and fracture locations of friction-stir welded joints of 6061-T6 aluminium Alloy. Mater. Sci. Lett. P.22. [4] Muhsin J.J., Moneer.H, Tolephih and Muhammed.A.M., Effect of Friction Stir Welding parameters (Rotation and Transverse) speed on the transient temperature distribution in FSW of AA 7020-T53. ARPN Journal of Engineering and Applied science Vol7, 2012. [5] Munoz C, Ruckert G (2004) comparision of TIG welded and Friction stir welded Al-4.5 Mg-0.26 Sc alloy. J.Matar process Technol 152:97-105. [6] Peel M, Steuwer A, Preuss M, Withers PJ. Microstructure, mechanical properties and residual stresses as a function of welding speed in AA5083 friction stir welds. Acta Mater 2003;51:4791–801. [7] Chen CM, Kovacevic R. Finite element modeling of friction stir welding– thermal and thermomechanical analysis. J Mach Tools Manuf 2003;43:1319–26.

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[8] Schmidt H, Hattel J, Wert J. An analytical model for the heat generation in friction stir welding. Mater Sci Eng 2004;12:143–57. [9] Elangovan K, Balasubramanian V (2008) influences of tool pin profile and tool shoulder diameter on the formation of friction stir processing zone in AA6061 aluminum alloy. Mater Des 29(2) :362- 373 [10] Elangovan K, Balasubramanian V, Valliappan M (2007) Influence of tool pin profile and axial force on the formation of friction stir processing zone in AA6061 aluminium alloy. Int J Adv Manuf Technol . DOI 10.1007/s00170-007-1100-2. [11] Threadgill,P.L. Friction-Stir Welding-State of the Art, TWI, Report 678, England, 1999 [12] Lee, J.A. Carter, R.W., andDing, J.D.,”Friction Stir Welding for Aluminum Metal MatrixComposites, NASA/TM-1999 Project No.98-09. [13] Colligan, K. 1999. Material flow behavior during friction stir welding of aluminum. Welding Journal 78(7): 229-s to 237-s.

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[14] G.Elatharasan, V.S.Senthil kumar, An Experimental Analysis and optimization of process parameters of Friction Stir Welding of AA 6061 – T6 Aluminium alloy using RSM. ICONDM 2013, Vol 64, 2013. [15] A study of process parameters of Friction Stir Welded AA6061 Aluminium alloy. ARPN Journal of Engineering and Applied science Vol6, 2011. [16] Threadgill,P.L. Friction-Stir Welding-State of the Art, TWI, Report 678, England, 1999. [17] Liu, L.E. Murr, C.S Niou, J.C. McClure, and F.R. Vega, Micro structural aspects of thefriction-stir welding of 6061T6 aluminum, Scripta Mat, 1997, vol 33-3, pp 355-36 [18] Rhodes, C. G., Mahoney, M. W., and Bingel, W. H. 1997. Effects of friction stir welding on microstructure of 7075 aluminum. Scripta Materialia 36(1): 69–75. [19] Qasim M Doos, Bashar, Abdul wahab Experimental study of Friction Stir Welding of 6061-T6 Aluminium pipe. International Journal of Mechanical Engineering and Robatics. Vol 1. 2012.

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Microwave Assisted Trans-esterification of Waste Cooking Oil in Presence of Alkali Catalyst Hasna Khalfan AlSuleimani#1, Priy Brat Dwivedi#2 Student#1 , Project Guide#2 Mechanical & Industrial Department, Caledonian College of Engineering, Oman #2

#1 Hasna318@gmail.com priy.dwivedi@caledonian.edu.om

Abstract— Depletion of world petroleum resources and air pollution has led to a search for alternative sources for fossil fuel, including diesel. Because of the similarity with petro-diesel, biodiesel fuel (fatty acid methyl ester) from vegetable oils, animal fats and recycled cooking oil is considered as the best candidate for diesel fuel substitute in diesel engines. Biodiesel helps in extending engine life, improving fuel economy, decreasing air pollution and reducing reliance on foreign and fossil fuel. In this paper the effect of microwave radiation on trans-esterification of waste cooking oil (from restaurants and from industrial food processors) in presence of alkali catalyst in batch process was studied. For optimal yield ratio of oil to methanol was 1:6, 0.4 w% KOH for 200 seconds in domestic microwave oven. Later on results were compared with conventional heating process of trans-esterification. From this work it is concluded that biodiesel can be produced from waste cooking oil using microwave radiation with significant reduction in production time. Keywords— WCO, Trans-esterification, microwave, biodiesel, alkali catalyst

I. INTRODUCTION Biodiesel (biological oil) is one of the alternative fuels that are produced from renewable sources. It is also called as mono alkyl ester of long chain fatty acid and it can be derived from various biological sources such as vegetable oil and animal fats. It can be made from a diverse mix of feed stocks including Waste cooking oil. Hundred years ago, Rudolf Diesel tested vegetable oil as fuel for his engine. In 1930s and 1940s vegetable oils (VOs) were used as diesel fuels, but only in emergency situations [1]. Alternative fuels for diesel engines are becoming increasingly important due to diminishing petroleum reserves and the environmental consequences of exhaust gases from petroleum fuelled engines [2]. Although the calorific value of VOs is as good as diesel fuel but the low volatility and high viscosity of VOs prohibits its direct application as fuel for diesel engines. However, this technical problem of higher viscosity of VOs has been overcome by trans-esterification [3]. Trans-esterification is the process of reacting triglyceride (vegetable oils) with alcohol in presence of

catalyst. During the transesterification process, triglycerides are first converted to diglycerides, which in turn are converted to monoglycerides, and then to glycerol. Each step produces a molecule of an ester of a fatty acid [4]. Waste cooking oil is taken as feed stock for production of Biodiesel; it offers a triple fact solution: economic, environmental and waste management. The term “waste vegetable oil” (WVO) refers to vegetable oil which has been used in food production and which is no longer viable for its intended use. It is can be collect from variety of sources, e.g., food industry, restaurants or houses. Production of biodiesel from Waste cooking oil to partially substitute petroleum diesel is an alternative way for environment protection and energy security. Trans-esterification is a process in which the glycerin is separated from WVO. It refers to catalyzed chemical reaction involving vegetable oil and an alcohol to yield fatty acid alkyl esters (i.e. Biodiesel) and glycerol.

Fig 1.1: A schematic representation of the Transesterification of triglycerides (vegetable oil) with methanol to produce fatty acid methyl esters (Biodiesel) (R=CH3).

This process can convert oil to biodiesel up to 80 to 94% in 30 min to 2 hr [5]. The yields were dictated by molar ratio of the oil to alcohol, reaction time, temperature, catalyst type,

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catalyst concentration, triglyceride properties, and mixing intensity. An alternative to conventional heating trans-esterification is the microwave-assisted trans-esterification. This means that microwave radiation for biodiesel synthesis is more efficient in reducing the time required for the reaction and separation of the products and offers a better way to synthesize biodiesel when compared to conventional mode of heating as well as improve product yields under atmospheric conditions [6] [7]. It is due to the fact that microwave radiation activates the smallest degree of variance of polar molecules and ions such as alcohol with the continuously changing magnetic field. The use of vegetable oils as alternative fuels has been around for one hundred years when the inventor of the diesel engine Rudolph Diesel first tested peanut oil, in his compression-ignition engine. In 1970, scientists discovered that the viscosity of vegetable oils could be reduced by a simple chemical process and that it could perform as diesel fuel in modern engine. Considerable efforts have been made to develop vegetable oil derivatives that approximate the properties and performance of the hydrocarbon-based diesel fuels. Bio-diesel production is a very modern and technological area for researchers due to the relevance that it is winning every day because of the increase in the petroleum price and the environmental advantages. Trans-esterification is the most common method and leads to mono-alkyl esters of vegetable oils and fats, now called bio-diesel when used for fuel purposes [8]. The diesel fuel has a closer properties, biodiesel fuel (fatty acid methyl ester) from vegetable oil is considered as the best candidate for diesel fuel substitute in diesel engines. Biodiesel is the fastest growing alternative fuel in the country. Biodiesel’s has ability to extend engine life, improve fuel economy, decrease air pollution and reduce reliance on foreign fuel. The use of waste cooking oil to produce biodiesel reduced the raw material cost [9]. II. MATERIALS Waste Cooking Oil was collected from the local restaurant in Muscat, Oman. This oil was filtered and used for the production of biodiesel. In this work, Potassium hydroxide was used as alkali catalyst. In comparison with other alcohols, methanol is cheaper and has better physical and chemical properties (polar and shortest chain alcohol), and it was used as a reactant. Potassium hydroxide, methanol and sulphuric acid were purchased from Schalau Chemie S.A, Spain. Other required chemicals purchased from local market were of analytical reagent great. In this study domestic oven was used of LG company make. Total work was done at fixed power of 160 wt. III. BIODIESEL PRODUCTION

Waste cooking oil was used in this study. Waste Cooking Oil contains an initial acid value of 2.3 mg which is >1 mg KOH per gram of oil. Therefore, biodiesel production was performed in two-step reaction mechanisms: 

Acid-Catalyzed Esterification.



Base-Catalyzed Trans-esterification.

A. Acid Catalyzed esterification The Waste Cooking Oil used in this study had an initial acid value of 2.3 mg KOH/g corresponding to a free fatty acid (FFA) level of 3.1%, which is above the 1% limit for a satisfactory trans-esterification reaction using an alkaline catalyst [10]. In this pretreatment, methanol-to-oil ratio was taken as 4:1 w/w and 0.4 w% of H2SO4 was used. This mixture was heated in LG make domestic microwave oven with occasional shaking for 60 seconds. Power level was set at 160 W. This pretreatment was done with every set before mixture was set for transesterification. B. Base-Catalyzed Trans-esterification The method applied for the production of biodiesel from WCO in this study is base-catalyzed trans-esterification in a laboratory-scale setup. The reaction was performed using methanol as alcohol and KOH as catalyst. The transesterification process was studied at three KOH catalyst loadings (0.01, 0.02 and 0.04 g), three oil to methanol w/w ratios (1:6, 1:8, and 1:10) and three time variations. Results are listed in table. After the reaction, the excess methanol was removed by vacuum distillation and then the trans-esterification products were poured into a separating funnel for phase separation. After phase separation, the top layer (biodiesel), was separated and washed with distilled water in order to remove the impurities. Then the biodiesel was heated above 100 0C, to remove the moisture. IV. RESULT AND DISCUSSION Conventional heating set was also studied for methanol, catalyst and time variation and results are given in table 1. Maximum yield of biodiesel yield was 3.1g with 50g methanol in 5 hrs refluxing set. In table 2, 3 and 4 results of methanol, time and catalyst variation are summarized. It is clear that microwave radiation is one of the best tools for transesterification of waste cooking oil. Optimum yield was found when methanol to oil ratio was 6:1. As clear from table 2, biodiesel yield was decreasing with increasing the amount of methanol. More study is required in this area to find the reasons behind this observation. In case of alkali catalyst variation biodiesel yield increased with increase in alkali catalyst concentration. But due to soap formation and difficulty in product separation, yield decreased as catalyst amount increased to 0.4 w%. During this study,

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effect of time was also studied. Yield of biodiesel was found to be increasing with time. But to avoid bumping and overheating, no study was done after 200 seconds. Biodiesel production by microwave irradiation was due to direct adsorption of the radiation by the polar group (OH group) of methanol. It is speculated that the OH group is directly excited by microwave radiation, and the local temperature around the OH group would be very much higher than its environment. Hence, microwave assisted trans-esterification is a way of reducing the reaction time, the electrical energy and labour costs as compared to the conventional method. And Gas Chromatography analysis of biodiesel from waste cooking oil is given in table 5. TABLE 1

TABLE 5 GC RESULT OF BIODIESEL FROM WCO

Component

% Concentration

9-Octadecenoic acid

40.898 %

Pentadecanoic acid

40.779 %

8,11-octadecadienoic acid

10.052 %

Heptadecanoic acid

3.699 %

9-Octadecenoic acid

1.125 %

n-Hexadeecanoic acid

1.094 %

V. CONCLUSION

MEOH: OIL (CONVENTIONAL HEATING)

MeOH : Oil (w/w) 20:5 20:5 50:5

Time (hr)

Catalyst (g)

BD Yield (g)

3 3 5

0.15 0.02 0.02

No Result 2.9 3.1

TABLE 2 MEOH: OIL VARIATION

MeOH : Oil (w/w) 30:5 40:5 50:5

Time (s)

Catalyst (g)

BD Yield (g)

80 80 80

0.02g 0.02g 0.02g

4.7 4.5 4.2

TABLE 3 CATALYST VARIATION

Catalyst (g)

Time (s)

0.01 0.02 0.04

140 140 140

MeOH : Oil (w/w) 40:5 40:5 40:5

BD Yield (g) 4.2 4.5 4.1

TABLE 4 TIME VARIATION

Time (s)

MeOH: Oil

Catalyst

BD Yield

(w/w)

(g)

50:5

0.02

4.2

140

50:5

0.02

4.3

200

50:5

0.02

4.4

In this work, biodiesel was produced from Waste cooking oil using microwave radiation and with the help of two-step trans-esterification. It was observed that microwave radiation helps the synthesis of fatty acid methyl esters (biodiesel) from waste cooking oil, and higher biodiesel conversion can be obtained within a few minutes, whereas the conventional heating process takes more than 5 hrs. In the current investigation, it has confirmed that Waste cooking oil may be used as resource to obtain biodiesel. The experimental result shows that alkali catalyzed transesterification is a promising area of research for the production of biodiesel in large scale. Effects of different parameters such as time, reactant ratio and catalyst concentration on the biodiesel yield were analyzed. The best combination of the parameters was found as 6:1 w/w ratio of Methanol to oil, 0.4 w% (0.02g) of KOH as catalyst and 200 seconds of reaction time. The viscosity of Waste cooking oil reduces substantially after trans-esterification and is comparable to diesel. Biodiesel characteristics like density, viscosity, flash point, and pour point were studied and are found as comparable to diesel. I take this opportunity to express my profound gratitude and deep regards to my guide Dr. Priy Brat Dwivedi and Ms. Shah Jahan for their exemplary guidance, monitoring and constant encouragement throughout this work. I thank almighty, my parents, sisters and friends for their constant encouragement without which this assignment would not be possible. I am also thankful to Caledonian College of Engineering, Muscat Oman for providing me all facilities in lab. REFERENCES [1] Schumacher LG, Peterson CL, Grepen JV. 2001. Fuelling direct diesel engines with 2 % biodiesel blend. Written for presentation at the 2001 annual international meeting sponsored by ASAE. [2] Ghobadian B, Rahimi H. 2004. Biofuels-past, present and future perspective. International Iran and Russian congress

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of agricultural and natural science.Shahre cord university. Shahrekord. Iran. [3] Ma F, Hanna MA. 1999. Biodiesel production: a review. Bioresource technology, 70: 1-15. [4] Freedman B, Butterfield RO, Pryde EH.1986.Transesterification kinetics of soybeen oil. JAOCS 63, 1375–1380.

[5] Encinar J, Gonzalez J, Rodriguez J, Tejedor A. 2002. Biodiesel Fuels from Vegetable Oils: Transesterification of Cynara c ardunculus L. [6] Dasgupta A, Banerjee P, Malik S. 1992. Use of microwave irradiation for rapid transesterification of lipids and accelerated synthesis of fatty acyl pyrrolidides for analysis by gas chromatography-mass spectrometry: study of fatty acid profiles of olive oil, evening primrose oil, fish oils and phospholipids from mango pulp. Chemistry and physics of lipids, 62: 281-291. [7] Lertsathapornsuk V, Pairintra R, Krisnangkura K, Chindaruksa S. (Eds.) 2003. Proceeding of the 1st International Conference on Sustainable Energy and Green Architecture, Bangkok, SE091. [8] Balat, M. and Balat, H. 2008. A critical review of bio-diesel as a vehicular fuel. Energy conversion and management, 49 (10), pp. 2727--2741. [9] Mistry, M. and Khambete, A. Extraction of Biodiesel from waste vegetable oil. [10] Freedman B, Butterfield RO, Pryde EH. Transesterification kinetics of soybean oil 1. J Am Oil Chem Soc (JAOCS) 1986;63(10):1375–80.

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Prediction of Excess Air Requirement Using ANN for the Improvement of Boiler Efficiency Arun. S. Gopinath#1, N. Sreenivasa Babu*2 Engineering Department, Shinas College of Technology Sultanate of Oman arun@shct.edu.om babu@shct.edu.om

Abstract—An improvement in the efficiency on converting fuel energy to useful thermal energy could result in significant fuel saving for industrial Sector. In this paper artificial intelligence concept using Artificial Neural Network (ANN) is used to predict the optimized excess air requirement using real time and calculated data. This work determines the excess air requirement for complete combustion corresponding to theoretical CO2 in flue gases and realtime values obtained from remote measurements of CO2 (actual) in flue gases.

type with direct fired pulverized coal system boiler is considered for this analysis. Data from the Proximate and Ultimate analysis of Coal used in the boiler is as shown in Table1&2. In situ Measurements from 210MW Boiler is shown in Table 3 & 4. TABLE I SAMPLE OF PROXIMITY ANALYSIS RESULT OF COAL

Keywords— ANN, Flue gas Analysis, Excess Air Control, Boiler Efficiency, Losses

I. INTRODUCTION The operating efficiency of industrial boilers is one of the critical concerns in National Energy Consumption.The improvement in boiler efficiency will increase the steam input to the turbine and hence the alternator output power as well. Improvement in boiler efficiency can be done by optimizing the combustion with excess air control. Moreover Optimized combustion directly minimizes the emission of hazardous pollutants into the atmosphere like CO, Oxides of Sulphur and Nitrogen etc. which will minimize air pollution. II. FUELS, COMBUSTION & FORMULATION Coal is one among the prominent fuel using in the power generation industry. For the Complete combustion of Coal as fuel, air is required. Normally Oxygen (O2) is required for the combustion. It is obtained from the air which is supplied to the furnace. The amount of air required to supply sufficient Oxygen for the complete combustion of fuel is the Theoretical air. Excess Air is the amount of air required in addition to the stoichiometric air to make sureof complete oxidation during burning of fuel. Among the types of fuels ,Natural gas requires less and coal requires the maximum amount of excess air for the complete combustion[1].A typical 210 MW natural circulation , dry Bottom , tangentially fired , balanced draft and radiant Reheat

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Content

Percentage

Ash

Volatile Matter

Moisture

7.1

Fixed Carbon

34.6

GCV of Coal : 4210 K Cal/kg

TABLE-2 SAMPLE OF ULTIMATE ANALYSIS OF COAL FROM PROXIMITY ANALYSIS

Sl. No

Content

Percentage

Carbon

45.957

Hydrogen

2.835

Nitrogen

0.935

Sulphur

0.3

Oxygen

4.873

TABLE-3 PERFORMANCE DATA FROM 210MW BOILER

Sl. No

Parameter

Unit

Test value

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Load PA In Temp.to APH A PA In Temp.to APH B SEC. AIR TEMP.TO APH A SEC. AIR TEMP.TO APH B Flue Gas TEMP APH A INLET Flue Gas TEMP APH B INLET Flue Gas TEMP. APH A OUTLET Flue Gas TEMP. APH B OUTLET SEC.AIR TEMP. APH A OUTLET SEC.AIR TEMP.APH B OUTLET PA OUTLET TEMP.APH A PA OUTLET TEMP.APH B TOTAL SEC. AIR FLOW TOTAL PA FLOW TOTAL AIR FLOW

MW 0 C 0 C 0 C 0 C 0 C 0 C 0 C 0 C 0 C 0 C 0 C 0 C T/Hr. T/Hr. T/Hr.

210 42 42 42 42 147.7 159.0 333 331 262.5 280 292 282 405 340 705

TABLE IV IN SITE MEASUREMENTS

Sl. No 1 2 3 4 5

Parameters O2 INLET O2 OUTLET CO2 INLET CO2 OUTLET CO OUTLET

Quantity in % 3.585 5.115 15.715 14.185 0.005

An Indirect Method is followed in this analysis for evaluating boiler efficiency. In Indirect method the following losses are considered [2];

       

Percentage heat loss due to dry flue gas, L1 Percentage heat loss due to evaporation of water formed, L2 Percentage heat loss due to moisture present in fuel,L3 Percentage heat loss due to moisture present in air, L4 Percentage heat loss due to Partial Conversion of C to CO , L5 Percentage heat loss due to Radiation & Convection, L6 Percentage heat loss due to Un burnt carbon in Fly ash, L7 Percentage heat loss due to Unburnt carbon in Bottom Ash, L8

The Excess air required for the complete combustion is calculated by comparing the actual CO2measured from insitu and the theoretical CO2 value derived from the theoretical air required for complete combustion [6]. The steps followed for the calculation is as follows: Step 1: Fuel Parameters after Proximity Analysis and Ultimate Analysis should be given as input Step 2: Boiler parameters & Ambient parameters from the In site measurements to be given as input Step 3: Calculate the Theoretical Air required for the Combustion of Fuel Step 4: Calculate the Theoretical CO2 Required for the complete Combustion of fuel Step 5: Actual CO2 from the Flue gas is taken from in site measurements Step 6: Excess Air required for the complete combustion was calculated by comparing the theoretical CO2 and Actual CO2 Step 7: After calculating the Excess Air Required for different combinations of theoretical CO2 and Actual CO2for different grades of coal, a neural network was trained to predict the values of excess air required. A. ANN for Prediction of Excess Air Requirement A feed forward neural network trained with back propagation is used for this prediction. The steps followed for creating the Artificial Neural Network is as follows: Step 1: Theoretical CO2 from different grades of coal and their Measured Actual CO2 where given as Input vectors. Step 2: Corresponding Excess air Requirement calculated were assigned as the target values for their input vectors. Step 3: The 2 layer feed forward Neural Network was created with 3 neurons in each hidden layer. Step 4: TheNetwork was trained and created with the Data samples Step 5: Weight values and the biasing is adjusted iteratively to improve the network performance function. Step 6: Mean square error between the network outputs and the target outputs is the performance function Step 7: Trained network can be applied to simulate output corresponding to any new set of input data

Boiler Efficiency = [100 – (L1+ L2+ L3+ L4+ L5+ L6+ L7+ L8)] III. ALGORITHM & RESULT ANALYSIS

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Excess Air Percentage

TABLE V RESULTS OF INDIRECT METHOD USED FOR TRAINING NETWORK IN ANN

50 CO2_Actual

Excess Air

CO2Theoretical %

CO2 Actual %

Excess air % by Indirect method

22.32

15.6

43.81

21.5

15.83

36.04

20.67

47.44

18.25

15.76

15.27

15.5

51.42

10 0 1

3 5 7 9 11 13 15 17 19 21 CO2 _Actual in Percentage

Fig. 1 Excess Air Requirement for Different CO2 actual measurements of coal using indirect method

Neural Network Training data is shown in Table 5. The CO2 actual is taken from in site measurements for different grades of pulverized coal with different compositions. The training algorithm used in neural network is Levenberg -Marquardt algorithm which works better on function fitting problems with small networks [3]. CO2theoretical is derived from the details of ultimate analysis of the coal [4-5]. The performance function for the feed forward network is its mean square error between the network output and targets. The resulting graph with test data, validation data and training is shown in Fig 2.

TABLE VI RESULTS OF SIMULATION FROM ANN

CO2Theoretical %

CO2 Actual %

Excess Air % from ANN

Excess air % by Indirect method

Error %

20.5

15.2

39.68

34.69

14.38

14.8

44.55

41.89

6.3

13.6

71.53

62.55

14.3

22.5

15.8

42.2

43.23

2.5

42.38

44.88

5.5

IV. CONCLUSIONS The Excess air requirement predicted by the ANN is in good understanding with the values using indirect method. As the CO2 actual from the flue gas reduces, the excess air Requirement is increasing. The Errors can be minimized in this prediction if more training dataâ&#x20AC;&#x2122;s are added for training. This Prediction method can be incorporated with the control mechanism of primary and secondary induced/Forced draft fans to give excessair control in boilers which in turn will increase the combustion efficiency as well as the boiler efficiency. ACKNOWLEDGMENT We acknowledge our friends and colleagues of Shinas College of Technology who helped in collecting information to finish this paper. We here by showing our gratitude towards our college management for their constant support and encouragement.

Fig 2 Training plot showing Mean Square Error (MSE) of the network

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REFERENCES [1]

[2]

[3]

Henry CopeteLópez and Santiago Sánchez Acevedo., An Approach to Optimal Control of the Combustion System in a Reverberatory Furnace, RevistaTecnologicas No. 23, December 2009. Yoshitaka and Akihiro Murata., Optimum Combustion control by TDLS200 Tunable Diode Laser Gas Analyser, Yokogawa Technical Report English Edition, Vol.53, No.1, 2010. Mark Hudson Beale, Martin T Hagan and Howard B Demuth., Neural Network Tool BoxTM –User’s Guide, R2013b.

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[4]

[5] [6]

JigishaParikha, S.A. Channiwalab and G.K. Ghosalc., A correlation for calculating HHV from proximate analysis of solid fuels, Science Direct, Fuel84, pp. 487-494, 2005. James G. Speight., Hand Book of Coal Analysis, John Wiley & Sons, Inc. Publications, Hoboken, New Jersey, 2005. Viktor Placek, Cyril Oswald and Jan Hrdlicka., Optimal Combustion Conditions for a Small-scale Biomass Boiler, ActaPolytechnica, Vol. 52, No. 3, 2012.

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Study of Microwave Radiation on Transesterification of Jatropha Oil in Presence of Alkali Catalyst Nadira Hassan Mohammed Al Balushi#1, Priy Brat Dwivedi*2 1

Student, 2Project Guide, Mechanical & Industrial Engineering Department Caledonian College of Engineering, Muscat, Oman Corresponding author: nadraalbalushi@hotmail.com

Abstract— The objectives of this study is to produce biodiesel from Jatropha oil using microwave radiation in presence of alkali catalyst and designing suitable batch reactor for lab scale production. Cost effectiveness of the project is also being studied. This paper outlines studies done to find the optimal method for converting Jatropha oil to useable biodiesel using microwave irradiation. The amount of acid catalyst is 0.4w % and ratio of methanol to oil is 6:1 w/w for the optimal trans-esterification. Keywords: Jatropha oil, Biodiesel, Catalyst, Microwave radiation, Trans-esterification

I. INTRODUCTION Oil is running out. In the short term it will continue to go up in price and in the middle distant future it will be too expensive to burn. As the world energy demand and consumption increases every day, we need to focus on the use of biofuels that will help extend the lifetime of our oil supply, but eventually we will need to replace oil. Whatever that replacement is it needs to be sustainable. By 2030, global energy consumption is projected to grow by 36% [1] and, in our view; demand for liquid transport fuels will rise by some 16 million barrels more a day. With the world’s population projected to reach 8.3 billion by then, an additional 1.3 billion people will need energy. To meet this demand a diverse energy mix is needed. This is where biofuels can help; in the next two decades, biofuels is expected to provide some 20% (by energy) of the growth in fuel for road transport [2]. The possibility of deriving bioduesel from locally grown sources and using them as alternatives to petro diesel products is attractive for many countries, including the

Sultanate of Oman, that currently depend largely on fossil fuels. Biodiesel is fuel that is similar to diesel fuel and is derived from usually vegetable sources. Biodiesel refers to a vegetable oil- or animal fat-based diesel fuel consisting of long-chain alkyl (methyl, ethyl, or propyl) esters. Biodiesel is typically made by chemically reacting lipids (e.g., vegetable oil, animal fat (tallow) with an alcohol producing fatty acid esters (FAE). Biodiesel helps reduce greenhouse gas emissions (GHGs) because it comes from animal or plant biomass with a lifecycle of a few years. On the other hand, petro diesel is a fossil fuel that releases into the atmosphere carbon that has been tied up for hundreds of millions of years, and all of it adds to GHGs. Fossil fuels also release more tailpipe emissions than does biodiesel. Biodiesel is a liquid which varies in color between golden and dark brown depending on the production feedstock. It is slightly miscible with water, has a high boiling point and low vapor pressure. The flash point of biodiesel (>130 °C, >266 °F) is significantly higher than that of petroleum diesel (64 °C, 147 °F) or gasoline (−45 °C, -52 °F). Biodiesel has a density of ~ 0.88 g/cm³, higher than petrodiesel (~ 0.85 g/cm³). Most diesel engines are warranted to run on anywhere between B5 (5% biodiesel) to B20 (20% biodiesel). [3] Have discussed few chemical and physical properties of jatropha oil. (Table 1). Kapilan [5] has used microwave radiation for two step transesterification in his work and reported successful production of biodiesel from jatropha oil grown in Indian soil. Antony Raja, et al. [6] reported that Jatropha oil is converted into jatropha oil methyl ester known as (biodiesel) prepared in the presence of homogeneous acid catalyst. The same characteristics study was also carried out for the diesel fuel for obtaining the base line data for analysis.

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International Journal of Students’ Research in Technology & Management Vol 2 (04), June-July 2014, ISSN 2321-2543, pg 153-156 TABLE I CHEMICAL AND PHYSICAL PROPERTIES [4]

Parameter % FFA as oleic acid

Value 2.23±0.02

Iodine value

103.62±0.07

Saponification value

193.55±0.61

Peroxide value

1.93±0.012

Percentage oil content (kernel)

63.16±0.35

Density at 20° C (g/ml)

0.90317

Viscosity at room temperature (cp)

42.88

Physical state at room temperatur

Liquid

A Value is mean ± standard deviation of triplicate determinations. Marchetti, et al. [7] concluded that there are different ways of production, with different kinds of raw materials: refine, crude or frying oils. Also with different types of catalyst, basic ones such as sodium or potassium hydroxides, acids such as sulfuric acid and ion exchange resins. One of the advantages of this fuel is that the raw materials used to produce it are natural and renewable. Also of this process, the free fatty acid will be changed completely in to esters. Bojan, et al. [8] carried out his work to produce biodiesel from crude Jatropha Curcas oil (CJCO) with a having high free fatty acid (HFFA) contents (6.85%) and also the crude Jatropha Curcas oil was processed in two steps. During the first step the free fatty acid content of crude Jatropha Curcas oil was reduced to 1.12% in one hour at 60°C using 9:1 methanol to oil molar ratio. The second step was alkali catalyzed transesterification using methanol to oil molar ratio of 5.41:1 to produce biodiesel from the product of the first step at 60°C.The maximum yield of biodiesel was 93% v/v of crude Jatropha Curcas oil which was more than the biodiesel yield (80.5%) from the one step alkali catalyzed transesterification process. Temu, et al. [9] reported that the quality of biodiesel is influenced by the nature of feedstock and the production processes employed. The physico-chemical properties of jatropha and castor oils were assessed for their potential in biodiesel. The properties of jatropha and castor oils were compared with those of palm from literature while that of biodiesel were compared with petro-diesel. Results showed that high amounts of FFA in oils produced low quality biodiesel while neutralized oils with low amounts of FFA produced high quality biodiesel.

considered are methanol, ethanol, biogas and vegetable oils. Vegetable oils have certain features that make them attractive as substitute for Diesel fuels. Vegetable oil has the characteristics compatible with the CI engine systems. Vegetable oils are also miscible with diesel fuel in any proportion and can be used as extenders. Ronnie, et al. [11] concluded that the benefits of jatropha as biodiesel include the reduction of greenhouse gas emissions, as well as the country’s oil imports. Local production of jatropha is also practical because as a non-food crop, it will not compete with food supply demands. It can also grow on marginal degraded land, leaving prime agricultural lots for food crops while at the same time restoring the marginal and degraded land’s fertility. All of these benefits can possibly be achieved by the presence of this locally fabricated high efficiency jatropha oil extractor equipment. This mixture was heated in LG make domestic microwave oven with occasional shaking for 60 seconds. Power level was set at 160 W. This pretreatment was done with every set before mixture was set for transesterification. This pre-treated jatropha oil was used in base catalysed second-step transesterification. In the second step, transesterification was carried out at with various methanol-to- oil ratio, at various catalyst strength, and various time duration. In this step also power supply 160 W. Results of variations are summarized in table 2. After the reaction, the excess methanol was removed by vacuum distillation and then the trans-esterification products were poured into a separating funnel for phase separation. After phase separation, the top layer (biodiesel), was separated and washed with distilled water in order to remove the impurities. Then the biodiesel was heated above 1000C, to remove the moisture.

In current study locally grown jatropha oil was taken as feed stock and two step transesterification was done by microwave radiation. Antony, et al. [10] reported that all countries are at present heavily dependent on petroleum fuels for transportation and agricultural machinery. The fact that a few nations together produce the bulk of petroleum has led to high price fluctuation and uncertainties in supply for the consuming nations. This in turn has led them to look for alternative fuels that they themselves can produce. Among the alternatives being

Fig 1: Conventional Heating

II. MATERIALS For current study, Jatropha oil was purchased from local market in Salalah, Oman. This oil was filtered and then used

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for the production of biodiesel. Sulphric acid (H2SO4) is used as acid catalyst in first step and KOH was used as catalyst in second step. In our study we used Methanol for transesterification. Because methanol is cheaper and has better physical and chemical properties (polar and shortest chain alcohol). Potassium hydroxide, methanol and sulphuric acid were purchased from Schalau, Chemie S.A, Spain. All the chemicals used for transesterification were of analytical reagent grade. Study was done in LG domestic microwave oven at 160 W power levels.

effect of time was also studied and results are summarized in table 2 (entries number 7, 8, and 9). Yield of biodiesel was found to be increasing with time. But to avoid bumping and overheating, no study was done after 200 seconds. Biodiesel production by microwave irradiation was due to direct adsorption of the radiation by the polar group (OH group) of methanol. It is speculated that the OH group is directly excited by microwave radiation, and the local temperature around the OH group would be very much higher than its environment. Hence, microwave assisted transesterification is a way of reducing the reaction time, the electrical energy and labor costs as compared to the conventional method. TABLE II SUMMARY OF MICROWAVE HEATING VARIATION

Fig 2: Microwave-assisted biodiesel production units.

No.

Oil(g)

1 2 3 4 5 6 7 8 9

5g 5g 5g 5g 5g 5g 5g 5g 5g

Methanol (g) 30g 40g 50g 40g 40g 40g 50g 50g 50g

Catalyst (g) 0.02g 0.02g 0.02g 0.01g 0.02g 0.04g 0.02g 0.02g 0.02g

Time(s)

Yield (g) 4.8 4.68 3.97 4.06 4.10 4.21 3.9 4.18 4.26

80s 80s 80s 140s 140s 140s 80s 140s 200s

After variation, biodiesel properties were tested as per ASTM D 6751, for various parameters as given in table 3. TABLE III FUEL PROPERTIES

III. BIODIESEL PRODUCTION Acid value of Jatropha oil was determined by standard method and it was found as 9 mg KOH per g of oil. Since acid value is higher than 1 mg KOH, acid catalyzed transesterification is necessary in first step. Acid catalyzed transesterification is good if oil is having high free fatty acid content. It avoids possibility of soap formation like in case of alkali catalyst. In this pretreatment, methanol-to-oil ratio was taken as 4:1 w/w and 0.4 w% of H2SO4 was IV. RESULTS AND DISCUSSION Conventional heating set was also studied (Figure 1) with 5g of jatropha oil, 40 ml methanol and 5 hrs of refluxing. Biodiesel yield was 3.09g. From table 2 it is clear that microwave radiation is one of the best tools for transesterification of Jatropha oil. During experiment various ratios of methanol to jatropha oil was tested. Results are summarized in table 2 (entries 1, 2 and 3). Optimum yield was found when methanol to oil ratio was 6:1. Later yield was decreasing with increasing the amount of methanol. More study is required in this area to find the reasons behind this observation. In case of alkali catalyst variation, (entries 4, 5 and 6 in table 2) biodiesel yield was increasing with increase in alkali catalyst concentration. But due to of possibility of soap formation and difficulty in product separation, catalyst ratio was not studied beyond 0.8 w%. During this study,

Property Flash point (◦C) Pour point (◦C) Calorific Value (MJ/kg) Viscosity at 40 ◦C (mm2/sec) Density at 15 ◦C (kg/m3) Water content (mg/kg) Acid number (mg KOH/g) Copper strip corrosion Ash Content (%)

ASTM D6751 > 130

Biodiesel 128

Diesel 68

–7 39.9

−15 42.71

1.9–6

4.20

2.28

–

901

846

< 500

102

< 0.50

0.80

0.34

>No. 3

< 0.02

0.01

Table III compares the properties of jatropha biodiesel produced in this study with the properties of diesel. The flash point of biodiesel satisfies the fuel standards and is better than the flashpoint diesel. This is an important safety consideration when handling and storing flammable materials. The important cold flow properties of biodiesel are the cloud and pour point.

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According to ASTM standard D 6751, no limit is given for pour point and suggested “report” in the fuel standard. The calorific value is an important property of biodiesel that determines its suitability as an alternative to diesel. As per European standard, EN 14214, the approved calorific value for biodiesel is 35 MJ per kg. The table shows that the calorific value of jatropha biodiesel is close to that of diesel. According to the ASTM standards, the acceptable viscosity range for biodiesel is between 1.9–6.0 mm2/s at 400C, and jatropha biodiesel satisfies the biodiesel standard. The density of jatropha biodiesel is close to that of diesel and satisfies the ASTM standard. ASTM standard approves a maximum acid value for biodiesel of 0.5 mg KOH/g, but jatropha biodiesel produced in this study has acid value 0.80 mg. The degree of tarnish on the corroded copper strip correlates to the overall corrosiveness of the fuel sample. The copper strip corrosion property of jatropha biodiesel is within the specifications of ASTM. Another important factor of biodiesel is the ash content estimation. The ash content of jatropha biodiesel satisfies the ASTM standard. V. CONCLUSIONS In this work, biodiesel was produced from jatropha oil using microwave radiation and with the help of two-step transesterfication. It was observed that microwave radiation helps the synthesis of methyl esters (biodiesel) from nonedible oil, and higher biodiesel conversion can be obtained within a few minutes, whereas the conventional heating process takes more than 5 hrs. In the current investigation, it has confirmed that Jatropha oil may be used as resource to obtain biodiesel. The experimental result shows that alkali catalyzed transesterification is a promising area of research for the production of biodiesel in large scale. Effects of different parameters such as time, reactant ratio and catalyst concentration on the biodiesel yield were analyzed. The best combination of the parameters was found as 6:1 w/w ratio of Methanol to oil, 0.8 w% of KOH as catalyst and 200 seconds of reaction time. The viscosity of Jatropha oil reduces substantially after transesterification and is comparable to diesel. Biodiesel characteristics like density, viscosity, flash point, and pour point were studied and are found as comparable to diesel.

ACKNOWLEDGEMENT Authors are thankful to Caledonian College of Engineering, Muscat, for supporting this work.

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(2013) Annual Energy Outlook 2013 website. [Online]. Available: http://www.eia.gov/forecasts/aeo/IF_all.cfm. [2] (2013) BP Outlook 2030 website. [Online]. Available: http://www.bp.com/sectiongenericarticle.do?categoryId =9030039&contentId=7055156. [3] (2014) The wikipedia website. [Online]. Available: http://en.wikipedia.org/wiki/Biodiesel. [4] E. Akbar, Z. Yaakob, S. K. Kamarudin, M. Ismail and J. Salimon, “Characteristic and Composition of Jatropha Curcas Oil Seed from Malaysia and its Potential as Biodiesel Feedstock, ” European Journal of Scientific Research., vol. 29, pp. 396-403, Nov. 2009. [5] N. Kapilan, “Production of Biodiesel from Vegetable Oil Using Microware Irradiation,” Acta Polytechnica., vol. 52, pp. 46-50, Nov. 2010.,” Research Journal of Chemical Science., vol. 1, pp. 81-87, Nov. 2011. [6] S. Antony, D.S. Robinson and C. Lee, “Biodiesel production from jatropha oil and its characterization Oil by A Two Step Method- An Indian Case Study, ” Journal of Sustainable Energy & Environment., vol. 3, pp. 63-66, Dec. 2012. [7] J.M. Marchetti, V.U. Miguel and A.F. Errazu, “Possible methods for biodiesel production,” Renewable and Sustainable Energy Reviews., vol. 11, pp. 1300-1311, Nov. 2007. [8] S.G. Bojan and S.K. Durairaj, “Producing Biodiesel from High Free Fatty Acid Jatropha Curcas Oil by A Two Step Method- An Indian Case Study, ” Journal of Sustainable Energy & Environment., vol. 3, pp. 63-66, Nov. 2012. [9] A. Okullo, T. Ogwok and J.W. Ntalikwa, “PhysicoChemical Properties of Biodiesel from Jatropha and Castor Oils, ” International Journal of Renewable Energy Research., vol. 2, pp. 47-52, Nov. 2012. [10] S. Antony, D. Robinson and C. Robert, “Biodiesel production from jatropha oil and its characterization, ” Research Journal of Chemical Sciences., vol. 1, pp. 8187, Apr. 2011. [11] P. Ronnie, D. Robinson and C. Robert, “Jatropha Oil Extractor Equipment, ” Research Journal of Chemical Sciences., vol. 3, pp. 238-243, Apr. 2010.

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