Ncair newsletter 4 1 by NCAIR

Elevons FEATURED ARTICLE 6

PHASE FIELD MODELLING: FOR MICROSTRUCTURAL EVOLUTION IN MANUFACTURING PROCESSES CONTRIBUTED ARTICLE 12

Influence of duplex heat treatment on the micro-structure of Ti-6Al-4V alloy TECHNOLOGY UPDATES 38

Resins - Types and Applications (Part I)

April 2014 . Newsletter . Volume 4 . Issue 1

CONTENTS Editorial, NCAIR News Updates 2 Important Announcements 5 FEATURED ARTICLE Phase field modelling: for microstructural evolution in manufacturing processes â&#x20AC;&#x201C; M.P.Gururajan and Arijit Roy

CONTRIBUTED ARTICLE Influence of duplex heat treatment on the micro-structure of Ti-6Al-4V alloy â&#x20AC;&#x201C; Dr. Akhilesh Kumar Swarnakar

R&D UPDATES Machinability of Ti-6Al-4V at different feed rates in orthogonal machining 21 Modelling of drilling forces along chisel edge

Multi-gate resin infusion simulation in liquid composite molding process

TECHNOLOGY UPDATES Resins : Types and applications- Part 1

NEWS UPDATES Huge Employment Potential in India's Aerospace Sector

Aerospace Industry-Academia Conclave

Global Aerospace Composites business to reach $4.7 billion by 2019

Acknowledgement We extend our sincere gratitude to the faculty members of IIT-Bombay for their support. We are also thankful to the students and staff of NCAIR, for their valuable articles and other support. Editors : Prof. Suhas Joshi and Prof. Asim Tewari Asst. Editors : Dr. Sarbani Banerjee Belur Ms. Vani K. Sreedhara Contact details : admin@ncair.in Articles that fall under the purview of NCAIR Newsletter are always welcome.

EDITORIAL Welcome to the first issue of the NCAIR â&#x20AC;&#x2DC;Elevonsâ&#x20AC;&#x2122; newsletter for the year 2014.

The NCAIR newsletter is an outcome-based quarterly report of the centre and its various activities. Research is the prime focus of this centre. It is through the newsletter that we draw attention to the various ongoing and completed R&D activities in the arena of aerospace manufacturing.

The important aim of this newsletter is to keep the readers informed of the ongoing developments, and innovations in research being a part of NCAIR. The newsletter is a collection of various review and contributed articles from academia, industry NCAIR Ph.D./M.Tech. students and staff. Apart from the various research articles, the newsletter also serves the purpose of being a notice board where important announcements related to NCAIR are put up. Various training programs, workshops, events and seminars slated for being held in the coming months have been covered in this newsletter.

In this issue of the newsletter, we present some interesting contributions related to aerospace applications and manufacturing processes. The featured article of this issue discusses phase modelling for microstructural evolution in manufacturing processes. In the present times, the cycle of designing a new alloy and deploying the same in industrial applications takes enormously large amount of time and money. The Integrated Computational Materials Engineering (ICME) for aerospace industry in particular studies the microstructure models and tools. These microstructure models and tools play a crucial role of connecting properties of the final product/ component to the processing route. Phase modelling is an ideal computational tool for the study of microstructural evolution. The present issue of the newsletter carries a contributed article pertaining to the domain of aerospace manufacturing. This article is on the influence of duplex heat treatment on the microstructure of Ti-6Al-4V alloy.

Research and development is an important aspect of NCAIR. This is reflected in the R&D updates, which has articles on theoretical model to estimate drilling forces along chisel edge, multi-gate resin infusion simulation in liquid composite molding process and influence of feed rate on chip segmentation in Ti-6Al-4V. The technology update section focuses on recent technological advancements in the arena of aerospace manufacturing globally. In this issue, we present a review on resins, their types and applications. The newsletter also carries important business updates in the aerospace domain.

Hope you will find this newsletter interesting. Please feel free to provide us with any feedback, including things that you would like to see being featured in the forthcoming editions through email: admin@ncair.in This newsletter is also available online at www.ncair.in. Happy Reading !!!!! Kind Regards, Suhas S. Joshi & Asim Tewari Editors

NCAIR NEWS UPDATES Aerospace Material Programme A three-day workshop on ‘Aerospace Materials and Processes’ was held during December 16-18, 2013 at Victor Menezes Convention Centre (Hall No. 22), IITBombay.

Workshop Highlights The inauguration of the workshop was done by the chief guest Mr. Kishore Jayaraman, President, Rolls Royce India. In his inaugural address, he appreciated the efforts of NCAIR and also mentioned the need for technological developments in the area of aerospace manufacturing domain in India. There were keynote talks by eminent international professors Dr. Shiv Kapoor, from University of Illinois – Urbana Champaign and Dr. Shreyas Melkote, from Georgia Institute of Technology. The talks were on recent and future research developments of aerospace manufacturing processes.

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There were other talks by the experts from various industries like NAL, Boeing, General Motors, GE Global Research, Sandvik Asia Pvt. Ltd., ESI India and others. These talks also elaborated on the recent trends of the aerospace materials like titanium, composites and their application in aerospace domain. The presentations touched upon the use of modelling and simulation techniques in the manufacturing industry. The fundamental understandings on aerospace worthy materials and process were delivered by the experts from IIT-Bombay from various departments like Mechanical Engineering, Metallurgy and Material Science and Department of Aerospace Engineering.

The workshop being a three day workshop, each day concluded with panel discussions where the participants elaborately talked about their apprehensions and sought experts' opinion.

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1.1 - Inauguration of Workshop on Aerospace Materials and Processes. Dec 16-18, 2013. Venue: VMCC, IIT-Bombay 1.2 - Workshop on Aerospace Materials and Processes. Dec 16-18, 2013. Venue: VMCC, IITBombay 1.3 - Panel Discussion at workshop on Aerospace Materials and Processes: Left to Right: Dr. Shreyas Melkote, Dr. Bhaskar Patham, Mr. S. M. Vaidya, Dr. Shiv Kapoor, Mr. Kanchan Biswas, and Dr. Rajesh Raghavan

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1.4 - Workshop on Aerospace Materials and Processes. Prof. Naik, IIT-Bombay

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1.5 - Workshop on Aerospace Materials and Processes. Prof. Shiv Kapoor, University of Illinois-Urbana Champaign, USA

Formal inauguration of the NCAIR ‘Elevons’ newsletter NCAIR newsletter ‘Elevons’ new design was released at the Aerospace Materials Program held during December 16-18, 2013 at Victor Menezes Convention Centre (Hall No. 22), IIT-Bombay. The inauguration was done by the chief guest Mr. Kishore Jayaraman. 2

2 - Release of the design of Elevons, NCAIR Newsletter. Left to Right: Prof. Devang Khakhar, Director IIT-Bombay, Mr. Kishore Jayaraman, President, Rolls‐Royce South Asia

3 - Boeing visit to NCAIR, IIT Bombay Left to Right: Prof. Suhas Joshi, Dr. Pratyush Kumar, Dr. Bala Bharadwaj, Prof. Asim Tewari, Mr. Avik Bhattacharya

Boeing visit on March 20, 2014 to NCAIR, IIT-Bombay Dr. Pratyush Kumar, President, Boeing India visited NCAIR, IIT-Bombay along with his colleagues Dr. Bala Bharadwaj and Mr. Avik Bhattacharya. They had several discussions with the various professors at IIT-Bombay who are directly working for the NCAIR generic projects. 3.

Participation in Conferences by NCAIR students and project engineers

Workshop conducted by Central Library, IIT Bombay

The P.H.D. students of NCAIR Shashikant Joshi, Ashish Saxena, Vivek Kumar Barnwal, Sagar Telrandhe and Harsh Kumar Narula participated in IMTEX-2014, held between 23-28 January, 2014 at Bangalore. The posters on the overview of NCAIR and the glimpse of few processes and technology developed at NCAIR, IIT-Bombay were showcased in the Academic/R&D pavilion.

A workshop was conducted by the Central Library, IIT Bombay on January 29, 2014. The workshop involved demonstration and training session on various library services of IIT Bombay. These included e-databases, referencing tools, plagiarism check. As part of this workshop, there were demonstrations and discussions on three softwares used primarily in IIT Bombay by the faculty as well as the students. They were the following:

The posters were presented to the visitors and were well received by them too. Also, NCAIR students were awarded first consolation prize for their presented efforts. http://www.imtex.in/pdf/Round%20up%20 report%20IMTEX%202014.pdf The poster displayed some of the technology development work at NCAIR. (See page No. 6-7 for the poster). Some of the technology development work which was presented are as follows: • Microstructure changes during machining of titanium alloys. (Student- Shashikant Joshi, Investigator- Prof. Asim Tewari and Prof. Suhas S. Joshi) • Microstructural and texture evolution of deformation of Ti6Al4V alloy. (Student- Ashish Saxena, Investigator- Prof. Prita Pant and Prof. Asim Tewari)

• Development of single point incremental sheet forming for light weight materials (Student- Vivek Kumar Barnwal, Investigator- Prof. Asim Tewari)

• Improvement of machinability through subsurface modification (Student- Sagar Telrandhe, Investigator- Prof. Sushil Mishra) • An Algorithm for Generating Montage of Multiple SEM images (Student- Harsh Kumar Narula, Investigator- Prof. Asim Tewari)

Talk on iMachining There was an interactive talk by Mr. Michael Berman on SolidCAM iMachining at NCAIR, IIT Bombay on 29 January, 2014. Mr. Berman is a Chief Scientist and Lead inventor of SolidCAM iMachining. He is a veteran in the field of CAM with over 40 years of experience.

TURNITIN (Plagiarism Prevention Software)

SCOPUS, which is one of the largest abstract and citation database of peer-reviewed literature.

REAXYS (Chemistry Workflow Solution Designed to help you find essential, relevant and actionable chemical data)

MENDELEY (a free reference manager and academic social network that can help organize research, collaborate with others online, and discover the latest research).

New Colleagues at NCAIR Nakul Vaid

He has completed his Bachelor of Technology in Mechanical Engineering from Arni University, Kangra (Himachal Pradesh). He has joined NCAIR as a project staff. Abdul Arif He completed his Master's degree in Mechanical Engineering (Design) from Motilal Nehru National Institute of Technology (MNNIT), Allahabad, Uttar Pradesh, India. He has joined NCAIR as a Project Research Associate.

IMPORTANT ANNOUNCEMENTS Forthcoming NCAIR programmes

• Joint seminar with Sandvik Asia Pvt Ltd., regarding recent trends in aerospace manufacturing processes - At Bangalore during May 2014. Exact date and venue to be announced shortly. • Advanced Application Training - Hard Part Turning at Sandvik Asia Pvt. Ltd., Pune, during April 10-11, 2014. • Advanced Application Training - Milling at Sandvik Asia Pvt. Ltd., Pune, during April 14-15, 2014.

For nominations and further details contact: admin@ncair.in Technical Writing workshop, ‘Capable Communicative Engineers’ This is a two-day workshop as part of the induction training programme of students and staff at NCAIR. The workshop is going to be held on 5-6 April, 2014 at NCAIR, IIT Bombay. This workshop aims at enabling students develop better communication and critical thinking skills. The communication skills focus on understanding and demonstrating the writing and speaking processes, appropriate selection of communication for specific audience/reader. Through this workshop, students will also learn to collate, evaluate and synthesize information collected from various sources having diverse view points. Students will use the communication skills to use their authority, point-of-view and individual voice and style in their technical writing and presentation.

Results :-

0.45 0.4 0.35

Major Strain (%)

Sheet

Tool

Mg2Si

Fig.1: Setup of SPIF

Strain distribution in conical shape

Top and bottom plate

Fig.2: Conical shape formed using SPIF

Objective:To establish and develop an alternate sheet forming process for customized and small batch production Setup :Approach :-

Development of single point incremental sheet forming for light weight materials (Student- Vivek Kumar Barnwal, Investigator- Prof. Asim Tewari)

Region of high dislocation density

Microstructure changes during machining of titanium alloys (Student- Shashikant Joshi, Investigator- Prof. Asim Tewari and Prof. Suhas S. Joshi)

Temp

Time

Furnace Cooling

825C, 6hr, FC

Hold

950C, Air Cooled

950C, Water Quenched

Results:1hr

2hr

Microstructural and Texture changes during Ti6Al4V Deformation

825C, 8hr, FC

825C, 24hr, FC

Heat Treatment to develop microstructures

Heat Treatment

Strain Rate

Temperature

Strain Path

Twin Activity

Effect on Mechanical Behavior

2-1-10

10-10

2-1-10

0001

2-1-10

10-10

2-1-10

10-10

Tracking of same grains in interrupted compression

Texture Modeling of PS Compression

0001

10-10

Objective :To understand the relationship between microstructure and texture on the mechanical behaviour of Ti6Al4V alloy under varying loading and temperature conditions Approach:Slip activity

Microstructural and texture evolution of deformation of Ti6Al4V alloy (Student- Ashish Saxena, Investigator- Prof. Prita Pant and Prof. Asim Tewari)

NCAIR GENERIC R&D PROJECTS

Strain

Distance (mm)

100

Fig.4: Major and minor strain distribution

Minor Strain (%)

150

Fig.5: Optical microstructure of Al-6061

Fig.6: FEM modeling in Pamstamp-2G

As received, extruded rod

Orthogonal cutting

Results: Simulation and EBSD scans

Approach:

Heated at 825ºC, FC

Oblique cutting

2-D Set up for turning:

Graphical User Interface:- Developed on MATLAB®

Objective:To develop an algorithm & software for Montaging of SEM Images to facilitate more accurate stereological analysis Algorithm :- Random Search followed by Steepest Descent

An Algorithm for Generating Montage of Multiple SEM images (Student- Harsh Kumar Narula, Investigator- Prof. Asim Tewari)

Modeling Polycrystalline Deformation

[Ɛgrain]= a[ƐB1] +b[ƐB2] +c[ƐB3] +d[ƐP1] +e[ƐP2] + f[ƐP3]

Machined sample after annealing at 825ºC, Contact Details: NCAIR, IIT Bombay, Email: admin@ncair.in, Ph. 022.25764945/4946, www.ncair.in FC

Objective:To establish an methodology and techniques to improve machinability through subsurface modification and texture analysis

Improvement of machinability through subsurface modification (Student- Sagar Telrandhe, Investigator- Prof. Sushil Mishra)

Fig.3: Strain measurement using DIC

0.3 0.25 0.2 0.15 0.1 0.05 0 -0.05 0 -0.1

NCAIR students were awarded first consolation prize for the presented poster.

FEATURED ARTICLE

Phase field modelling: for microstructural evolution in manufacturing processes M. P. Gururajan and Arijit Roy, Department of Metallurgical Engineering and Materials Science (MEMS), IIT Bombay. The dream of every physical metallurgist is to design alloys with given properties [1]. At present, a cycle of designing a new alloy and deploying it, in industrial applications takes enormously large amount of time and may not be cost effective. Hence, Integrated Computational Materials Engineering (ICME) approaches are being developed to reduce the costs associated with the development of new materials, their manufacturing processes and deployment; aerospace industry is one in which ICME based approaches have already resulted in huge financial savings as well as deployment of new alloys within a time frame of two years instead of the traditional six years [2]. One of the important components of ICME for any industry in general, and, aerospace industry in particular, are the microstructure models and tools. These microstructure models and tools play the crucial role of connecting the properties of the final product/component to the processing route [2]. Developing models that can predict the formation and evolution of microstructures and benchmarking these models and their implementation is thus very crucial for successful implementation of ICME. For the purpose of this article, microstructures can be thought of as the sizes, shapes and distributions of different interfaces at the micro- and meso-scale. For example, the grain boundaries, the precipitate-matrix interfaces, twin boundaries and stacking faults are all important microstructural features. The sizes, shapes and distributions of these different interfaces can be (and are) modified through thermo-mechanical processing routes. Thus, the problem of modelling microstructural evolution is one of relating the thermo-mechanical processes to the development of microstructures.

Phase field modelling is an ideal computational tool for the study of microstructural evolution. In this technique, the interfaces are not tracked; interface related effects (such as the Gibbs-Thomson effect) are automatically

accounted for; topological singularities such as splitting and disappearance of interfaces are naturally taken care of; and, the models are, in general, thermodynamically consistent.

Phase field models are also known as diffuse interface models. The idea behind the models, as the name itself indicates, is to assume that the interfaces are diffuse; that is to assume that they have a finite width, and that the thermodynamic properties of the system determine this width. Thus, any continuum model in which interfaces are assumed to have finite width can be thought of as a phase field model. A generic process for formulating phase field models is as follows: Description of the microstructure In phase field models, we use field variables (that is, variables with specific values at all points of a domain for all times) to describe the microstructure or topology of the domain; these field variables are also known as order parameters and are assumed to be continuous and differentiable. Composition in a two phase binary alloy is an example of a field variable; similarly, crystal orientations in a poly-crystalline microstructure are also field variables. While composition is a conserved order parameter, the grain orientations are examples of non-conserved order parameters. Thermodynamics Once we have a description of microstructures in terms of order parameters, the next step is to describe the thermodynamics of the system in terms of order parameters and their gradients. The inclusion of gradients in the thermodynamic description is the key feature of the phase field models; the gradients in order parameters describe regions of interfaces and hence, by including them in the free energy or entropy functionals, we incorporate the effect of interfaces in the evolution of the microstructure.

Kinetics The thermodynamic functionals, once given, can be extremised to identify the equilibrium microstructure. However, in majority of the practical cases, the microstructure that is formed is either metastable or unstable and continues to evolve under service conditions. Hence, the kinetics in the phase field model is described by the constitutive law, namely, that the time evolution of the order parameter is driven by the Euler-Lagrange equation of the thermodynamic functional that is being extremised. Thus, this is also the step which ensures thermodynamic consistency of phase field models. In the next two sections, we describe two classical phase field models: one based on the conserved order parameter, namely composition to study spinodal decomposition, and the second based on the non-conserved order parameter, namely chemical order to study ordering. The formulation of these phase field models results in partial differential equations (PDEs). These PDEs can be solved numerically; in this article, we will show the (numerical) solutions (that is, microstructures) of these partial differential equations (PDEs) obtained using Fast Fourier Transforms (FFT).

Phase field models use field variables to describe the microstructure or the topology of the domain. These field variables are also known as order parameters and are assumed to be continuous and differentiable. Two classical phase field models are described: one based on the conserved order parameter and the second based on the nonconserved order parameter.

Cahn-Hilliard equation and spinodal decomposition The Cahn-Hilliard equation is one of the earliest phase field models to be written down for the study of microstructural evolution. To better understand the origins of this equation, let us start with a classical diffusion equation – the so-called Fick’s second law: (1)

In this equation, c is the composition, t is the time, ∇ is the gradient operator, and D is a positive constant known as diffusivity (assumed to be a constant here). Since ∇2c indicates the curvature of the composition profile, this equation indicates that the rate of change of composition at any point is directly proportional to the curvature of the composition profile at that point; composition at regions with positive curvatures increases while that at regions with negative curvatures decreases. This means a sinusoidal profile as shown in Figure 1 will get flattened out after a long time. In other words, this equation indicates that diffusional flux is from regions richer in A (B) to regions poorer in A (B). Such a diffusion is known as downhill diffusion. Let us now consider a phase diagram as shown in the schematic (Fig. 2) and an alloy of composition c0 quenched

Composition, c

∂c = D∇ 2 c ∂t

Initial sinusoidal profile Final equilibrium profile

Position, x Fig. 1: Schematic composition profile change in a system in which diffusion is described by classical diffusion equation: Fick’s second law.

from the temperature T1 to T2 and maintained at T2 subsequently. In such systems, sometimes, the diffusional flux is observed to be up-hill; that is, regions rich in A (B) become richer in A (B). This phenomenon is known as spinodal decomposition and the sinusoidal composition profile gets enhanced with time as shown in Figure 2.

Final equilibrium profile

Composition, c

Temperature

α' + α ''

T2 c ' α

c 0 Composition

c α''

Fig. 2: Schematic phase diagram of a system that undergoes spindoal phase separation at low temperatures and the evolution of composition profile as a function of time when a system undergoes spinodal phase separation.

Initial sinusoidal profile

Position, x

Cahn and Hilliard, in their classic papers [3, 4] showed how to model the spinodal phase separation by modifying the classical diffusion equation. This modified diffusion equation is known as the Cahn-Hilliard equation:

∂c  ∂f (c )  = ∇M∇  0 − 2κ∇ 2 c  ∂t   ∂c

(2)

where M is the mobility, ƒ0(c) is the double well potential, which can be assumed for simplicity’s sake a polynomial of the form Ac2(1−c)2 with A being a constant; and, κ is a constant known as the gradient energy coefficient. For the assumed ƒ0(c), and assuming that the mobility is a constant, one obtains (3)

In physical terms, the modification Cahn and Hilliard has done to the classical diffusion equation is two-fold: (a) the diffusivity changes its sign (which is related to the curvature of free energy and mobility); and, (b) the effect of interfaces, especially, incipient interfaces is accounted for.

10.

From the equation (Eq. 3), it is clear that Cahn-Hilliard equation is a modified diffusion equation; it contains a ∇4c term in addition to the usual ∇2c term. This equation

FEATURED ARTICLE can be linearized and solved in 1-D. It can also be solved numerically. For example, in Fig. 3, we show the evolution of microstructure in a system undergoing spinodal decomposition starting from an initially homogeneous (albeit with a small noise) composition profile: these simulations were carried out on a 1024 × 1024 system (with ∇x = ∇y = 1.0 and ∇t = 0.1). The constants A, κ and M take a (non-dimensional) value of 1.0. As is clear from the last figure, the microstructure also coarsens at the later stage and this interfacial energy driven process is also captured by the phase field model.

Allen-Cahn equation and ordering In crystalline alloys, in which there is a chemical ordering over, and above the crystalline ordering, the atoms prefer to occupy specific lattice positions (so called sublattices). For example, in B2 NiAl, the Ni atoms prefer to occupy the body centre positions while the Al atoms prefer to occupy the cube corners or vice versa. Thus, there are two ordered domains and the interface between these two ordered domains is known as an antiphase boundary. Let us assume that the ordered microstructure is described in terms of the order parameter ϕ.

(a) �=0

(b) �=100

In this case, since there is no conservation principle involved for the order parameter, the evolution equation (known as Allen-Cahn equation) becomes:

 ∂f (φ )  ∂φ = −L 0 − 2κ∇ 2φ  ∂t  ∂φ 

(4)

where L is the relaxation parameter, κ is the gradient energy coefficient, and f0(ϕ) is a double well potential as above (that is, f0(ϕ) = Aϕ2(1 − ϕ)2 , where A is a constant) .

From the equation (Eq. 4), it is clear that Allen- Cahn equation is also a modified diffusion equation; it contains a non-linear source term in addition to the usual ∇2ϕ term. This equation can be linearized and solved in 1-D. It can also be solved numerically. For example in Fig. 4, we show the evolution of microstructure in a system undergoing ordering starting from an initially random ordered domain structure: these simulations were carried out on a 1024 × 1024 system (with ∇x = ∇y = 1.0 and ∇t = 0.1). The constants A, κ and L take a (nondimensional) value of 1.0. As is clear from the last figure, the microstructure also coarsens at the later stage and this interfacial energy driven process is also captured by the phase field model.

(d) �=5000 Fig. 3: Spinodal decomposition. The initial homogeneous composition profile (albeit with a small noise) spontaneously phase separates and then the microstructure coarsens. The microstructures correspond to the non-dimensional time units of 0, 100, 1000, and 5000. At t=100, the phase separation has set in. At t=1000, the phase separation is nearly complete. At t=5000, the microstructure has visibly coarsened.

11.

Implications for industry It is possible to build many different phase field models using the above two canonical phase field models as the basic models. This will enable studying different aspects of microstructural evolution that are of relevance to the manufacturing processes. (a) �=0

(b) �=400

(d) �=5700

Fig. 4: Ordering. The initial random microstructure evolves to give rise to two different ordered domains and then the microstructure coarsens. From the top, the microstructures correspond to the non-dimensional time units of 0, 400, 1700, and 5700. At t=400, the microstructure is in the process of developing ordered domains with antiphase boundaries separating the same. At t=1700, the ordering is nearly complete. At t=5700, the microstructure has visibly coarsened.

12.

In the heat affected zones of weldings, grain growth becomes an important microstructural phenomenon; similarly, in many precipitation hardenable alloys, studies on the rate of growth of precipitates are crucial. Both grain and precipitate growth kinetics are amenable to be treated using phase field models. The models of grain growth involve an (unconserved) order parameter defined for each grain orientation (see, for example [5]) while the models for precipitate growth kinetics combine Cahn-Hilliard and Allen-Cahn equations (see, for example [6]).

Microstructures that form during solidification is another important area of practical importance as well as fundamental interest. Combination of Cahn-Hilliard and Allen-Cahn like phase field equations are used quite successfully to study microstructures that develop in alloys during solidification. Complex phase field models are in the process of being developed to study issues such as eutectic solidification and effect of convection.

In Ni-base superalloys (which are used as single crystal turbine blade materials in jet engines), during service conditions, the precipitates which give the required strength to the material, preferentially coarsen either parallel or perpendicular to the direction of applied stress. This phenomenon, known as rafting, is very crucial, since the appropriate type of rafting can harden the material during service conditions. The origin of rafting is the interaction between the applied stress, and the mismatch in lattice parameters and elastic moduli of the precipitate and matrix phases in these superalloys. By including this stress related physics in the phase field model, the Cahn-Hilliard equation can be modified to study rafting - see, for example [7, 8]. There are several reviews which discuss the phase field models and their applications in great detail. We refer the interested readers to these reviews: [9, 10, 11, 12, 13, 14, 15], and we believe that the time spent on learning phase field models will be very useful in ICME studies in general, and in studies on microstructural evolution in particular. As indicated in some of these reviews, by integrating the phase field models with thermodynamics

FEATURED ARTICLE and kinetic databases, one can study many important microstructural phenomena which play a crucial role during the manufacturing processes.

Acknowledgements We thank Prof. Suhas S Joshi and Dr. Sarbani Banerjee Belur for their inputs in making this article accessible to a wider audience. REFERENCES

[1] General Chemistry, Linus Pauling, Dover Publications, Inc, 1970. [2] Integrated Computational Materials Engineering (ICME):

Implementing ICME in the Aerospace, Automotive, and Maritime

Industries, TMS. Report available for download at

http://www.tms.org/icmestudy/ [3] J. W. Cahn and J. E. Hilliard, The Journal of Chemical Physics, Vol.

28, No. 2, pp. 258-267, 1958.

[4] J. W. Cahn and J. E. Hilliard, and The Journal of Chemical Physics,

Vol. 31, No. 3, pp. 688-699, 1959.

It is possible to build many different phase field models using Cahn-Hilliard and AllenCahn canonical phase field models as the basic models. This will enable studying different aspects of microstructural evolution that are of relevance to the manufacturing processes.

[5] D. Fan and L. Q Chen, Acta Materialia, Vol. 45, No. 2, pp. 611-622, 1997. [6] R. Mukherjee, T. A. Abinandanan, and M. P. Gururajan, Acta

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15, pp. 5015-5026, 2007.

[8] A. Gaubert, Y. Le Bouar, and A. Finel, Vol. 90, Nos. 1-4, pp. 375-404, 2010. [9] L. Q Chen, Annual Review of Materials Research, Vol. 32, pp. 113-

140, 2002.

[10] W. J. Boettinger et. al., Annual Review of Materials Research, Vol.

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[11] K. Thornton, J. Agren, and P. W. Voorhees, Acta materialia , Vol. 51,

No. 19, pp. 5675-5710, 2003.

[12] I. Steinbach, Annual Review of Materials Research, Vol. 43, pp. 89-

107, 2013.

[13] N. Moelans, B. Blanpain, and P. Wollants, CALPHAD â&#x20AC;&#x201C; Computer

Coupling of Phase Diagrams and Thermochemistry, Vol. 32, pp.

268-294, 2008.

[14] R. S. Qin and H. K. D. H. Bhadeshia, Current opinion in solid state

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[15] B. Nestler and A. Choudhury, Current opinion in solid state and

materials science, Vol. 15, No. 3, pp. 93-105, 2011.

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CONTRIBUTED ARTICLE

Dr. AKHILESH K. SWARNAKAR Assistant Professor, Department of Metallurgical Engineering, National Institute of Technology (NIT), Raipur, Raipur (C.G), Pin – 492010, Email – akswarn.met@nitrr.ac.in Phone - +91 9406397570

Influence of duplex heat treatment on the micro-structure of Ti-6Al-4V alloy Abstract Present day extensive application of Ti-6Al-4V alloy in aeronautical applications is mainly due to their excellent strength-to-weight ratio. Tailoring the microstructures by different heat treatments have been a profound industrial and research interest to achieve desired mechanical and thermal properties for specific applications. In the present article, the influence of duplex heat treatment on the microstructures of Ti-6Al-4V alloy has been investigated to further enrich the knowledge about the thermal processing of the material. The duplex heat treatment consisted of solution treatment at 950°C for 30 s, 60 s and 30 mins and subsequent water-quenching followed by an aging treatment at 500/550°C for 40 s. These duplex heat treatments result in the formation of α‘ martensite phase formation and precipitation of fine α phase in the retained β phase during the short-time aging.

Machining of Ti-alloys is one of the crucial steps for aerospace industries. The microstructural investigation of these alloys retains special interest from the application point of view due to their sensitivity towards thermal treatment, which influences their final microstructure.

Introduction Titanium alloys are widely used in aeronautical applications due to their excellent strength-to-weight ratio1 and in prostheses due to their superior biocompatibility, low elastic modulus and enhanced corrosion resistance2. Machining of Ti-alloys is one of the crucial steps for aerospace industries. The microstructural investigation of these alloys retains special interest from the application point of view due to their sensitivity towards thermal treatment, which influences their final microstructure1,2. Therefore, various studies have been performed on these alloys to understand the microstructural changes and their effects on mechanical properties 3, 4, 5. Furthermore, many metal forming processes such as closed-die forging, superplastic sheet forming, etc. require a uniform, fine grain size microstructure, which is obtained from hot working of α/β titanium alloys after breaking down the colony or basket weave microstructures6. Hence, such fine microstructures with desired phases can be obtained by tailoring the microstructures using different heat treatments7,8,9. One of the known heat treatments for Ti-alloys involves solution treatment and quenching plus aging. With these heat treatments, β phase transforms to α’ martensite phase and it further decomposes to fine α and β phases, which subsequently increases the mechanical properties of Ti–6Al–4V alloy 3,4. In the present work, duplex heat treatments were performed on Ti-6Al-4V alloy. This heat treatment consisted of solution treatment at 950°C for 30 s, 60 s and 30 mins and subsequent water-quenching plus aging at 500°C/550°C for 40 s. The effect of duplex heat treatments was studied on microstructural

14.

Influence of duplex heat treatment on the micro-structure of Ti-6Al-4V alloy

development. The XRD and hardness testing were performed on each specimen to study the phase changes and hardness variation after the heat treatment.

In the present work, duplex heat treatments were performed on Ti-6Al-4V alloy. This heat treatment consisted of solution treatment at 950°C for 30 s, 60 s and 30 mins and subsequent water-quenching plus aging at 500°C/550°C for 40 s. The effect of duplex heat treatments was studied on microstructural development.

Experimental method The starting material Ti-6Al-4V (Grade 5) was hot forged and mill annealed, received in the form of a half-moon cut from a rod with a diameter of 10 cm. The chemical compositions of the material are listed in Table 1. The samples were cut in the longitudinal axis from the as-received material in the form of rectangular shapes for the duplex heat treatment. The heat treatment cycles are summarized in Table 2 for each specimen and schematics are represented in Fig.1. These specimens were solution treated at 950°C for 30 s, 60 s and 30 mins in air and water quenched. After quenching, an aging treatment was performed to each specimen at 550°C and 500°C for 40 s (Fig. 1) followed by air cooling. After the heat treatment, the specimens were cut across to study the microstructure of each specimen. After mechanical polishing, each sample was polished through a series of diamond abrasives ranging from 6 µm down to 1 µm; in the last step, further polishing was done using colloidal silica. The specimens were etched by Kroll’s reagent applied for 10 s for microstructural investigations. The microstructures were observed using optical microscope (Zeiss Axio Vert.A1 Inverted Microscope, Germany). The room temperature X-ray diffraction (XRD) patterns were recorded on an X’pert Powder, X-ray diffractometer from PANalytical (The Nederland) using Cu Kα radiation for phase analysis. The Vickers hardness (HV), was measured (Model FV-700, Future-Tech Corp., Tokyo, Japan) across the cross section with an indentation load of 2.95N.

Table 1: Chemical Composition of Ti-6Al-4V alloy as received % w/w

Other elements

0.05

0.10

0.0125

0.20

0.30

5.50-6.75

3.50-4.5

Bal

0.40 T

Table 2: Specimens code and their experimental conditions S.No. Specimen code

Solution treatment temperature/time (step 1)

Aging temperature/Time (step 2)

S1 (as received sample)

950°C/30s

550°C/40s

950°C/60s

500°C/40s

950°C/30mins

500°C/40s

15.

Influence of duplex heat treatment on the micro-structure of Ti-6Al-4V alloy

Fig.1: Schematic of heat treatment profile for different specimens

Results and discussions Microstructure analysis Optical microscopy was used on the specimens etched by Kroll’s reagent to study the microstructure of each specimen as shown in Fig. 2. Fig. 2a shows the dark and bright phases that correspond to β and α phase respectively. Whereas in Fig. 2(c-d), the dark phase disappeared after the heat treatment.

(a) S1 [As received]

Fig. 2: The Illustration of Ti-6Al-4V alloy after different duplex heat treatments (a) S1 (as received), (b) S2 solution treated at 950°C/30s followed by aging at 550°C/40s (c) S3 solution treated at 950°C/60s followed by aging at 500°C/40s and (d) S4 Solution treated at 950°C/30mins followed by aging at 500°C/40s]

16.

(b) S2 [Solution treated at 950°C/30s followed by aging at 550°C/40s]

(d) S4 [Solution treated at 950°C/30mins followed by aging at 500°C/40s]

CONTRIBUTED ARTICLE

Fig. 3: The backscattered SEM images of (a) S1 (as received) and S4 specimen (Solution treated at 950°C/30mins followed by aging at 500°C/40s)

Duplex annealing alters the shapes, sizes and distribution of phases to improve the specific properties, which include creep resistance or fracture toughness. In general, during first anneal near the β transus, globularizes the deformed α, and also minimizes its volume fraction. This is followed by a second, lower-temperature aging, precipitated the new lenticular (acicular) α’ between the globular α particles.

The microstructure of S1 and S4 specimens were also investigated by scanning electron microscopy (SEM, FEI XL30FEG) of polished cross sections (Fig. 3), where back-scattered electron (BSE) imaging with very high contrast allows discerning directly the α and β phases omitting artefacts from etching.

(a)

(b)

The SEM microstructure of as-receivedTi-6Al-4V (specimen S1) comprises of α phase (grey) and β phase (white) showing a duplex α-β microstructure where the β phase is segregated at grain boundaries of α-phase (Fig. 3a). The solution treated samples at 950°C with different aging time followed by water quenching and aging at 500/550°C for 40 s produced a microstructure which consist of transformed β phase (α' martensite) and acicular α phase (Fig. 2c-d). Increasing the annealing time from 30 s to 60 s during solution treatment at 950°C and decreasing the aging temperature from 550°C to 500°C for 40s, did not show significant changes in the phase morphologies (Fig. 2b and 2c). However, extending the annealing time for 30 mins during solution treatment at 950°C showed more equiaxed grains distribution (S4) compared with specimen S2 and S3. Duplex annealing alters the shapes, sizes and distribution of phases to improve the specific properties, which include creep resistance or fracture toughness. In general, during first anneal near the β transus, globularizes the deformed α, and also minimizes its volume fraction. This is followed by a second, lower-temperature aging, precipitated the new lenticular (acicular) α’ between the globular α particles9. Fig. 3b shows similar microstructure, where the transformed β-phase (α' martensite) contains needle like structure, are precipitated between the globular α phases. X-Ray diffraction analysis The X-ray diffraction (XRD) patterns were recorded on an X’pert Powder, X-ray diffractometer from PANalytical using Cu Kα radiation. The XRD patterns for as received material, solution treated/water quenched and subsequently aging specimens are shown in Fig. 4. After the heat treatment, the β phase peak disappeared from the XRD. This was expected because of the interplanars pacing in the two structures (α’ and β) are nearly the same and cannot be differentiated for retained β phase by X-ray diffraction measurements. Similar observation was also reported by Morita et al.3 and Imam et al.10.

17.

Influence of duplex heat treatment on the micro-structure of Ti-6Al-4V alloy

Fig. 4: XRD pattern of specimen S1 (as received), S2, S3 and S4 specimens

Hardness profile The Vickers microhardness tests were carried out on polished cross sections of as-received, heat treated specimens by applying a weight of 300g (HV0.3). Similar to the microstructure, the microhardness changes after the heat treatment. As received specimen showed the Vickers hardness of about 339, that increased 30-40 (HV) after the heat treatment (Table 3). Apparently, the material undergoes hardening throughout the specimens due to the heat treatment (Fig. 5). It is clear from the specimen S2 and S3 hardness data that the aging temperature at step two has minor effect on the hardness value. Their average hardness value is comparable and under the error limits. Similar hardness values were reported for Ti-6Al-4V alloy after solution treatment at 930°C for 60 s and water quenching with subsequently aging treatment at 527°C for 40 s in air3. The increase in hardness value of Ti-6Al4V alloy can be associated with martensitic phase (α’) formation after the duplex heat treatment.

18.

CONTRIBUTED ARTICLE Table 3: : Micro-hardness at room temperature for each specimen (i) average hardness across the surface and (ii) in the center Hardness (HV0.3) Reference Material (S1) Average hardness

339± 7

Centre 346

Specimen S2

Specimen S3

Specimen S4 2)

379 ± 17

369 ± 9

388 ± 15

404

382

381

Fig. 5: Micro-hardness at profile measured on the polished surface for each specimen

Conclusions In the present work, the microstructural analysis was performed on Ti-6Al-4V alloy to understand the effect of treatment parameters (time and temperature) on the properties of the material. A duplex heat treatment schedule consisting of two step annealing was designed to study the microstructure, phase formation and hardness variation. After the duplex heat treatments, the microstructure of Ti-6Al-4V consists of transformed β-phase (α' martensite) precipitated between the globular α phases. The annealing time at solution treatment temperature was recognized as a governing parameter for causing significant microstructural changes compared to the aging temperature at the second step of duplex heat treatment. The XRD studies on heat treatment specimens were unable to distinguish between retained β and martensite (α’) phases due to similar interplanner spacing. These duplex heat treatment caused strengthening of these alloys as a result of martensite (α‘) phase formation with quenching after the short-time solution treatment followed by the short-time aging. 19.

Influence of duplex heat treatment on the micro-structure of Ti-6Al-4V alloy

Acknowledgments This research was performed at NIT Raipur at the Department of Metallurgical Engineering as a framework of B Tech project. We are thankful to Mr. Kapil Kumar from M/S Bharat Aerospace Metals, Mumbai for supplying the material for this project. I would like to acknowledge my students O.V.S Narayana, Manish Kumar and Vivek Kumar Sahu (B. Tech. final year students) for sample preparation by heat treatment experiments at the department. REFERENCES [1] E. W. Collings, The Physical Metallurgy of Titanium Alloys. 1984: American Society for Metals. [2] ASM, Http://products.asminternational.org/hbk/do/highlight/content/V02/D01/A25/ S0026726.html [3] T. Morita, K. Hatsuoka, T. Iizuka and K. Kawasaki, Strengthening of Ti–6Al–4V Alloy by Short- [4]

Time Duplex Heat Treatment, Materials Transactions, Vol. 46, No. 7 (2005) pp. 1681 - 1686 G. Lutjering, Inﬂuence of processing on microstructure and mechanical properties of (α-b)

titanium alloys, Materials Science and Engineering A243 (1998), pp. 32–45

[5] S. L. Semiatin, V. Seetharaman, and I. Weiss, The thermomechanical processing of alpha/beta

titanium alloys, JOM, 49 (6) (1997), pp. 33-39

[6] H. M. Flower, Microstructural Development in Relation to Hot Working of Titanium Alloys,

Mater. Sci. Technol., 6 (11), (1990), pp. 1082–1092

[7] T. Ahmed, H. J. Rack, Phase transformations during cooling intitanium alloys, Materials

Science and Engineering A243 (1998), pp. 206 – 211

[8] B. D. Venkatesh, D. L. Chen, S. D. Bhole, Effect of heat treatment on mechanical properties of

Ti–6Al–4V ELI alloy, Materials Science and Engineering: A, 506 (1–2) (2009) pp. 117-124

[9] N. Stefansson, S. L. Semiatin, and D. Eylon, The Kinetics of Static Globularization of Ti-6Al-4V,

Metallurgical and Materials Transactions A, 33A (2002) pp. 3527-3534

[10] M. A. Imam and C. M. Gilmore, Fatigue and microstructural properties of quenched Ti-6Al-4V,

20.

Metallurgical Transaction A, Vol. 14A, (1983), pp. 233-240

R & D UPDATES

SHASHIKANT JOSHI ASIM TEWARI SUHAS S. JOSHI

Machinability of Ti-6Al-4V at different feed rates in orthogonal machining Titanium alloys have poor thermal conductivity. Therefore, heat gets concentrated at the shear zone which forms adiabatic shear bands [1] in their chips during machining. Formation of shear bands represents a localizationof deformation which leads to formation of segmented chips. The localization of deformation causes a non-uniform material deformation during machining and causes fluctuations in machining forces [2].

In this article, an influence of different feed rate on the machinability of titanium alloys has been presented. Orthogonal turning experiments were performed on Ti-6Al-4V pipe of Ď&#x2022;93 mm diameter and 1 mm thickness. Three cutting speed of 24, 30 and 60 m/min and three feed rates of 0.11, 0.22 and 0.33 mm/rev were used during machining process.

An increase in the cutting speed causes an increase in the strain rate of deformation during machining and corresponding increase in the heat generated during machining process [3]. However, increasing feed rate does not increase the strain rate of material deformation [4]. Therefore, heat generated during machining process does not increase similar to that with an increase in the cutting speed. Therefore, with an increase in the feed rate, mass of material deformed during machining increases. This leads to a decrease in heat generated per unit mass of the material. Thus, the material machined at a higher feed rate has lower temperature during deformation.

In this article, an influence of different feed rate on the machinability of titanium alloys has been presented. Orthogonal turning experiments were performed on Ti6Al4V pipe of Ď&#x2022;93 mm diameter and 1 mm thickness. Three cutting speed of 24, 30 and 60 m/min and three feed rates of 0.11, 0.22 and 0.33 mm/rev were used during the machining process. Machining forces were measured using kistler dynamometer. Chips were collected during turning operation on CNC lathe. Scanning electron microscopy was performed on chips. Measurements of chip length and segment dimensions were carried out using image J software. The parameters considered to evaluate the machinability of titanium alloys are chip morphology, segmentation frequency and dynamic shear strength. Chip morphology can be analysed by observing segment shape, spacing between the segments and relative length of attached and separated part of the chip segment from each other. During machining, the chip segments are formed by two mechanisms viz. plastic strain and fracture process. In the segment formed by a plastic strain, adjoining segments slide over each other due to formation of shear bands between them. Therefore, attached part of the segment indicates deformation due to plastic strain. On the other hand, the separated length of segment from each other indicates that they are formed by a fracture from the parent material. Another next parameter, segmentation frequency, represents the number of segments formed per second during machining process. The segmentation

21.

Machinability of Ti-6Al-4V at different feed rates in orthogonal machining

frequency also represents frequency of fluctuation in the cutting forces [5]. The segmentation frequency is obtained by the following expression-

ƒ= V⁄w

(1)

where, ƒ= frequency of segmentation in Hz, V= cutting speed in m/s, w = average width of the segment which represents the distance between the two consecutive shear bands in meter. It is obtained by measuring the number of segments for 1 mm chip length. The average segment width is obtained by dividing chip length with the number of segments formed. The third parameter, dynamic shear strength of the material represents material resistance during machining. Higher material resistance causes higher cutting forces and subsequently higher energy consumption. Dynamic shear strength is obtained by the following expression-

k.f.d = (Fc .cosØ–Ft .sinØ).sinØ

(2)

where, k = dynamic shear strength of material in MPa, ƒ= feed rate in mm/ rev = 0.11 mm/rev, d = depth of cut in mm = 1, Fc and Ft= cutting and thrust forces (N) measured using Kistler dynamometer , ∅ = shear angle measured from SEM image of chip as shown in Fig. 1a.

Chip morphology In these experiments, chip morphology was observed at different feed rates. Fig. 1a-c, shows SEM images of chips obtained at a cutting speed of 60 m/min and at three different feed rates of 0.11, 0.22, 0.33 mm/min. At a feed rate of 0.11 mm/min, the segments are joined together over a part of shear plane length and are separated from each other over the other part of the shear plane length. Thus, the segments are formed by a combination of plastic strain and fracture. Also, the segments are trapezoidal in shape. With an increase in the feed rate to 0.22 mm/min, the segments remain joined together over a part of the shear plane length and are separated from each other over the remaining part of the shear plane length. However, the fraction of shear plane length over which segments separate from each other increases by 30%. This indicates an increase in fracture part in segment formation over plastic strain. Also, the segments of trapezoidal shape are formed.

With an increase in the feed rate to 0.33 mm/min, chip segments get separated from each other over a whole length of shear plane. Thus, segments are formed by a fracture process. Also, segments shape changes from trapezoidal at 0.22 mm/rev to semi-circular at 0.33 mm/rev. At a high feed rate of 0.33 mm/rev, the material compresses along the shear plane before fracture. This changes the segment shape to a semi-circular one. Thus, semi-circular segment shape at a higher feed rate represent plastic deformation of the material. It may be noted that the plastic deformation during machining process is undesired as it indicates energy utilised in deforming the material and not in cutting. At a lower feed rate, heat generated per unit mass of the material increases. 22.

Machinability of Ti-6Al-4V at different feed rates in orthogonal machining

a. at 0.11 mm/min

Generation of higher heat per unit mass of material causes formation of the shear bands. On the other hand, at a higher feed rate, heat generated per unit mass of material decreases. Therefore, higher material strength causes it to fracture instead of allowing formation of shear bands. Also, due to higher material strength, the material deforms more along the shear plane length before the fracture.

b. at 0.22 mm/min

c. at 0.33 mm/min

Fig.1 a-c: Chip morphology at a cutting speed of 60 m/min and at feed rate of a. 0.11 mm/rev b. 0.22 mm/rev c. 0.33 mm/rev

23.

Machinability of Ti-6Al-4V at different feed rates in orthogonal machining

The above described changes are illustrated further by drawing conceptual models of segment shape and size. This model is prepared by drawing an outline over the segments and arranging them in a orthogonal turning set up, see Fig. 2a,b. From the model, it is observed that with an increase in the feed rate, the length of segment dimensions opposite to shear plane length decreases. This length indicates a reduction in sliding of one segment over the other and corresponding plastic strain in the segment formation. Also, a large segment at high feed rate as shown in Fig. 2b indicates a large material deformation during the machining [6]. This may be due to a reduction in the plastic strain in segment formation. It is observed that at a higher feed rate of 0.22 and 0.33 mm/rev, segments become semi-circular in shape. Also, two segments separate by crack in between the segment. Thus, shear bands do not form between the segments at a higher feed rate.

Fig. 2a, b : Model showing chip segment at different feed rate at a cutting speed of a.30 m/min b. 60 m/min

a. at 30m/min

b. at 60m/min

Segmentation frequency Segmentation frequency indicates frequency of fluctuation in the cutting forces during machining. The influence of feed rate on segmentation frequency at a cutting speed of 60 m/min at the three feed rates is as shown in Fig.3. At a higher feed rate, the number of segments formed decreases. This increases the segmentation frequency. Also, with a decrease in the feed rate, the segmentation frequency increases. Thus, with an increase in the feed rate, the frequency of fluctuation in the cutting forces decreases and vice versa.

Dynamic shear strength To evaluate dynamic shear strength of material, cutting forces were measured using dynamometers. A plot of cutting and thrust forces at different feed rates at a cutting speed of 60 m/min is as shown in Fig. 4a. Cutting forces increase with the feed rate. However, feed forces do not increase with the increase in the feed rate. Feed forces depend on friction between work-tool [3]. This shows that no significant change in work-tool friction is observed with an increase in the feed rates. 24.

Segmentation frequency (KHz)

Machinability of Ti-6Al-4V at different feed rates in orthogonal machining

Fig. 3: Variation in segmentation frequency at different feed rate

Cutting speed (m/min)

Fig. 4a, b: Influence of feed rate on a. machining forces b. dynamic shear strength of material

Dynamic shear strength (MPa)

Machining forces (N)

Dynamic shear strength of material with an increase in the feed rate has been evaluated using eq. (2). The dynamic strength represents the material resistance during machining. With an increase in material resistance, the cutting forces increase and there is a corresponding increase in cutting energy. Therefore, a higher dynamic shear strength indicates, a reduction in the cutting efficiency and vice versa. At a low feed rate, dynamic shear strength of material is low, see Fig.4b. With an increase in the feed rate, the dynamic shear strength of the material increases (Fig.4b).

Feed rate (mm/rev)

25.

Machinability of Ti-6Al-4V at different feed rates in orthogonal machining

This shows that machining at a higher feed rate increases the resistance of the material. It may be noted that with an increase in the feed rate, the heat generated per unit mass of the material decreases. Therefore, the heat generated during machining does not help in reducing the material strength. On the other hand, at a lower feed rate, quantity of heat generated per unit mass of the material is relatively higher. This helps in reducing the material strength. Therefore, at a low feed rate, a lower material resistance reduces the cutting forces and a corresponding improvement in the cutting efficiency of material is realized. This can further be confirmed from the semi-circular segment shape at a higher feed rate, which represents a large plastic deformation during the machining process. This is due to higher material strength. Thus, with an increase in the feed rate, the energy consumption per unit metal removed increases and thus causes a reduction in the processing economy.

Conclusions • Feed rate changes the segment forming mechanism in machining of titanium alloys. With an increase in the feed rate, segments are formed more by fracture than by plastic strain. • With an increase in feed rate, segment shape changes from trapezoidal to a semi-circular one. This indicates an increase in the plastic deformation of material during the machining process. • A higher feed rate during machining reduces the segmentation frequency and causes a corresponding reduction in the fluctuation in the cutting forces. • At a lower feed rate, heat generated during machining process helps reduce the material resistance. This assists in reducing the cutting forces and causes a corresponding increase in the cutting efficiency. On the other hand, at a higher feed rate, a higher material resistance decreases the cutting efficiency. • An increasing feed rate does not influence the feed forces indicating no significant influence on friction between work-tool interface. Acknowledgement We gratefully acknowledge the partial support provided for this work by NCAIR, IIT-Bombay, DST – GoI, The Boeing Co. and IIT Bombay Collaboration. REFERENCES [1] J. Bonney, E. O. Ezugwu, "An overview of the machinability of aeroengine alloys," Journal of Materials Processing Technology, vol. 134, pp.

233–253, 2003.

[2] M. Brandt, M.S. Dargush, S. Sun, "Characteristics of cutting forces and chip formation in machining," International Journal of Machine Tools

and Manufacture , vol. 49, pp. 561–568, 2009.

[3] Winston A. Knight, Geoffrey Boothroyds, Fundamental of Machining and Machine Tool. New york: Marcel Dekker Inc., 1989. [4] Kroneberg M., Machining Science and Application., 1966.

[5] K. Necib, B. Haddag, M. Nouari, S. Kouadri, "Quantification of the chip segmentation in metal machining: Application to machining the

aeronautical aluminium alloy AA2024-T351 with cemented carbide tools WC-Co," International Journal of Machine Tools and Manufacture ,

Headline Group, 2000.

vol. 64, pp. 102-113, 2013.

[6] Katsuhiro Maekawa, Toshiyuki Obikawa, Yasuo Yamane, Thomas Childs, Metal Machining Theory and Applications. London: Arnold Hodder 26.

R & D UPDATES

ANKIT RANA SUHAS S. JOSHI

Modelling of drilling forces along chisel edge Introduction Drilling is among the principal machining processes and is used widely in aerospace industry. In recent times, high material removal rate is a growing priority along with quality and reliability. Thus, it is important to accurately model the drilling process. Important parameters of the drilling process such as cutting forces, power required, temperatures, chip morphology, strains and stresses, tool life can be calculated before actually any cutting is performed. During drilling of titanium alloys, major heat is absorbed by the tool. This results in the work piece becoming harder due to rapid work hardening tendency of Ti alloys. The tool thus becomes softer due to heat generation and accumulation near the cutting zone. This results in a rapid decrease in tool life, poor surface quality and poor dimensional accuracy.

In recent times, high material removal rate is a growing priority along with quality and reliability. Thus, it is important to accurately model the drilling process. Important parameters of the drilling process such as cutting forces, power required, temperatures, chip morphology, strains and stresses, tool life can be calculated before actually any cutting is performed.

Modelling as such reduces the trial and error approach thus reducing efforts, time and cost. Although validation of the model is required, modelling significantly reduces the experimental work. The drilling process in some respects can be compared with turning and milling but because of the complex geometry of the drill, it is difficult to model the cutting mechanics in drilling. In modelling the drilling process, one needs to take into account several variables. The variation of work and tool properties along with the interaction of cutting parameters like feed rate, cutting velocity, depth of cut and geometrical features of the drill make it challenging to accurately model the drilling process. In drilling with conventional twist drills, the chisel edge can contribute to more than 60% of the total thrust force even though the total length of the chisel edge is 0.1-0.2 times the diameter of the drill.

Model approach and formulation The chisel edge removes material in two different ways. Near the axis of the drill, in the region where the clearance angle is negative, the chisel edge acts as an indentation wedge beyond which material removal analysis is done using the principle of orthogonal cutting. This region is called as the secondary cutting zone. The cutting process over the lips can be modelled using principles of oblique cutting. The indentation zone accounts for about 2- 4% of the thrust forces due to chisel edge. The cutting velocity is very low at the center of the drill and therefore can be assumed to be perpendicular to the cutting edge. The normal rake angle is constant, half-wedge angle, and the uncut chip thickness are independent of the point angle since the chisel edge is assumed to be in the plane perpendicular to the axis of the drill. Also, the cutting edge intersects with axis of the drill resulting in zero inclination angle on the chisel edge. Thus, application of

27.

Modelling of drilling forces along chisel edge

orthogonal cutting is a fair assumption to model the cutting process over the chisel edge [2].

The focus of modelling any machining process is to accurately determine cutting forces, temperature and the kind of chips produced. Industry is now focusing on high speed machining and is environmentally conscious trying to reduce the use of coolants. An analytical model can determine the output parameters, through equations and material properties without relying on experimental data.

As shown in Fig. 1, the input parameters to the model are cutting conditions, drill geometry and material properties. Forces and torque in drilling are calculated by applying the principle of orthogonal cutting to model cutting by chisel edge. The shear forces are estimated using the material flow stress and the shear area. The temperature profile is estimated by modelling temperature rise in shear zone and at tool-chip interface [3]. Based on the temperature profile, the forces and torque in drilling are calculated to account for the changes in material properties due to temperature variation. Fig. 1: Model methodology

Feed rate

Cutting parameters Cutting speed

Chisel edge length

Shear force

Drill diameter

Cutting force Drill geometry

Point angle

Thrust force

Helix angle

Torque

Mechanical properties

Temperature distribution

Material properties Thermal properties Iterate

28.

Modelling of drilling forces along chisel edge

The total thrust force is given by the expression

The total torque is given by

where, f = k s = β n = �e = φn = � =

(1)

(2)

feed flow-stess normal friction angle effective rake angle shear angle resultant cutting velocity angle

Based on the work of Agapiou and DeVries [3], the rise on temperature in the shear zone is calculated as (3)

where, A s = Vs = �w = Sw = Kw = Vs =

Shear area shear velocity density of work material specific heat of work material thermal conductivity of work material shear velocity

The heat generated due to friction is distributed between the tool and the chip. The temperature at the chip-tool interface is given by the expression [4]: (4) where, q" Kt �t St lc t

= = = = = =

heat generation flux over tool-chip interface thermal conductivity of tool material density of the tool material specific heat of the tool material tool-chip contact length time duration the heat flux is applied

Results and Model analysis The model results show that the drill temperature increases and becomes maximum at the chisel edge corner. The temperature increases with an increase in the spindle speed as shown in Fig. 2.

29.

Modelling of drilling forces along chisel edge

Fig. 2: Variation of temperature along the chisel edge

The thrust force due to chisel edge secondary cutting region increases with an increase in the diameter and chisel edge length as shown in Fig. 3. For the same web ratio, an increase in chisel edge angle increases the length of the chisel edge resulting in an increase in the thrust force. The thrust force increases with an increase in feed as shown in Fig. 4. The torque variation is similar to thrust force variation. The torque increases with an increase in diameter and feed. Both thrust force and torque decrease with an increase in spindle speed. An increase in cutting speed increases the temperature which reduces the flow stress of the material. This in turn reduces the forces in drilling.

Fig. 3: Variation of thrust force with drill diameter

Fig. 4: Variation of thrust force with feed

30.

Modelling of drilling forces along chisel edge

Summary Both, the thrust and torque, increase with an increase in chisel edge length, feed and chisel edge angle. Thrust force and torque decrease with an increase in spindle speed, as an increase in spindle speed results in an increase in temperature. At elevated temperature, the material softens. The maximum temperature is obtained at the corner of the chisel edge. Along the chisel edge, away from the axis of the drill, the friction force and cutting speed increases gradually. This results in a higher rate of heat generation over tool-chip contact length. The average temperature of the plastic deformation zone also rises along the chisel edge length. A combination of increased heat flux due to friction and temperature rise in shear zone leads to an increase in average temperature at the tool-chip interface. The analysis presented here is for the chisel edge of the drill. The methodology can be adopted over the cutting lips to estimate the total force and torque in drilling. Acknowledgement The authors acknowledge the support of National Centre for Aerospace Innovation and Research (NCAIR), IIT Bombay. REFERENCES [1] E. S. Costa, M. B. d. Silva and A. R, “Burr produced on the drilling process as a function of tool

wear and lubricant-coolant conditions,” J. Braz. Soc. Mech. Sci. & Eng, 2009.

[2] J. R. Flachs, “Force modeling in drilling with application to burr minimization,” 2011. [3] J. S. Agapiou and M. F. DeVries, “On the determination of thermal phenomena during

drilling - Part I. Analytical models of twist drill temperature distributions,” Int. J, Mach. Tools

Manufact., vol. 30, no. 2, pp. 203-215, 1990. [4] M. Bono and J. Ni, “A model for predicting the heat flow into the workpiece in dry drilling,”

Journal of Manufacturing Science and Engineering, vol. 124, pp. 773-777, 2002.

[5] M. Bono and J. Ni, “The location of the maximum temperature on the cutting edges of a drill,” International Journal of Machine Tools & Manufacture, vol. 46, pp. 901-907, 2006.

31.

R & D UPDATES

Multi-Gate Resin Infusion Simulation in Liquid Composite Molding Process

JAINIL BHATT ASIM TEWARI

Introduction Many processes exist for the production of composites with a high content of oriented fiber reinforcements. Out of these, Liquid Composite Molding (LCM) process is a cost effective option to produce high performance composite parts. LCM process consists of impregnation of dry reinforcement material (e.g. carbon fiber fabric) with a liquid matrix (e.g. Epoxy Resin). It is essential to study the resin flow behavior in order to minimize or eliminate the possibilities of voids formation and uneven resin distribution. It is equally important from the production point of view to optimize the injection pressures and mold filling times. The major concern for mapping the resin flow behavior is to understand the variation in resin properties with temperature and time. Resin viscosity and cure fraction keeps varying throughout the injection period. In this paper, a model for simulating the resin flow while taking into account the variations in properties is presented. Background Several methods have been used for simulation of the mold filling process in LCM. The table displays the investigations of various modeling techniques in brief.

Table 1: Considerable developments in various modeling techniques No. Author(s)

Study/Findings

Coulter et al.,1988 [1]

Resin impregnation using FDM with boundary fitted co-ordinates.

Chang and Hwang,1992 [2]

Modelling of resin flow in axisymmetric parts using FEM with moving grids.

3. Souza et al.,2008 [3]

Resin infiltration using CVFEM for a porous medium with a heterogeneous permeability tensor.

Analysis of multiple gate resin injection using CVFEM.

Kang et al.,2000 [4]

5. Luz et al.,2012 [5]

CVFEM is widely used due to its ease of computing and fixed mesh. However, VoF method is found to be more suitable for the purpose due to its capability of precisely mapping the air-resin interface.

Sadeh and Khodadadi, 2013 [6]

VoF method to identify the interface behavior and void formation during resin infiltration in porous media.

Gerlach et al.,2006 [7]

Surface tension dominant two-phase flows using VoF method.

32.

Multi-Gate Resin Infusion Simulation in Liquid Composite Molding Process

NUMERICAL MODELLING Resin flow is primarily affected by the permeability and porosity of the media. High fiber volume fraction would result in more reduction in flow velocity. The resin viscosity keeps varying throughout the injection process due to the effect of gelation and temperature variations if any. The table below indicates the physics and equations used to formulate the numerical model. Table 2: Physics and modules being used in the numerical model No. Physics/Module

Governing Equations

Flow through Porous Media: Darcy's Law

for isotropic permeability

for anisotropic permeability tensor

: flow velocity, đ?&#x153;&#x2021;: viscosity, â&#x2C6;&#x2020;đ?&#x2018;&#x192;: pressure differential. đ??ž: permeability 2.

Volume of Fluid Method

Continuity and volume fraction equations:

Ď : average density and f : volume fraction of resin. Average properties of density and viscosity:

Cure-kinetics

Îą : degree of cure, m, n, E1, E2, A1, and A2 are empirical constants. 4.

Viscosity

Îźâ&#x2C6;&#x17E;, â&#x2C6;&#x2020;EÎź, and k are model constants to be determined experimentally.

33.

Multi-Gate Resin Infusion Simulation in Liquid Composite Molding Process

Simulations A 2-D geometry as shown in figure-1 was done to obtain variations in the filling time due to changes in gate positions and orthotropic permeability. The medium is considered to be rigid, i.e. there is no relative movement between any points in the structure and contraction within the porous media is considered to be negligible. Resin density was taken to be 1200 Kg/m3 . COMSOL Multiphysics solver was used to solve the numerical model and run the simulations. The values of empirical and experimental constants used are as displayed in the table. All dimensions are in cm

Fig. 1: Part Geometry and Dimensions

Table 3: Experimental Constants used for Simulations Parameter (Unit)

Value

R (J/mol*K)

8.314

K (m2)

2.4×10–10

A2(1/s)

3.8231×105

A1(1/s) E1(J/mol)

2.7321×105 7.2776×104

E_2 (J/mol)

6.6934×104

2.43

m_∞ (Pa*s) ∆Eμ (K) R

1.07

5.419×10–6 3636.45 26.89

1. Mold Temperature Variations Due to variation in mold temperature, changes occur in degree of cure and viscosity of resin. The infusion process is simulated for six different mold temperatures while keeping injection parameters same. The temperatures are 298K, 323K, 373K, 423K, 453K, and 473K. One case is taken to be 453K, as it is generally taken as the curing temperature for resin during post filling steps. 34.

Multi-Gate Resin Infusion Simulation in Liquid Composite Molding Process

Fig. 2: Resin Impregnation at various times during the Simulations (Scheme 1, T 298 K)

2. Changes in Permeability Tensor Permeability is a measure of the resistance to fluid flow in a porous material, which can be obtained experimentally, or through analytical predictions [12]. Three cases are simulated here. One with isotropic permeability, where K xx=Kyy=K; second with fiber orientation in X-direction, i.e. K xx/Kyy=6; and the third one with fiber orientation in Y-direction resulting into Kyy/K xx=6.

3. Changes in Gate Position Three different injection schemes are compared in these simulations. In the first and second scheme, the inlet gate is provided at the extreme ends of the geometry. At the top-left corner in the first scheme while at the bottom-right corner in the other. In the third scheme, the gate is provided at the center and two outlet vents are given at both the extreme edges.

4. Multi-Gate Injection An injection scheme with two inlet gate is investigated in these simulations. One gate is provided at the top-left corner with inlet pressure of 100kPa and the other at central corner with inlet pressure of 50kPa. Difference in the inlet pressures is maintained to minimize the air entrapment which would result in void formation. Simulations are done to map the effect of temperature variations and permeability variations during multi-gate injection.

Results and discussion The penetration of resin according to time is plotted in the following figures, the first being effect of variation in mold temperature for similar injection parameters.

35.

Multi-Gate Resin Infusion Simulation in Liquid Composite Molding Process

1. Effect of Temperature Variations The results show that with an increase in temperature, initially the resin viscosity decreases resulting in a faster flow. This is found to be in argreement with the results of Garschke et al. [13]. However, above the range of 100째 C, the viscosity tends to reduce due to the increased effect of curing. So, as seen in the graph below, the injection process takes longer to fill the mold when mold temperatures are 373 K and 423 K. For 453 K and above, the resin flow was observed to be ceased due to very high degree of cure. The time consumed for mold filling process for 298 K, 323 K, 373 K and 423 K was 302s, 258s, 491s and 930s, respectively.

Fig. 3: Time vs Filled Distance for Various Mold Temperatures

2. Effect of Change in Permeability Tensor The effect of orthotropic permeability is displayed in the following figure. It was observed that the mold filling process takes more time with variable permeability values along X and Y directions as compared to isotropic permeability. Flow velocity was seen to reduce more where the fiber orientation is perpendicular to the flow direction.

Fig. 4: Time vs Filled Distance for Isotropic and Orthotropic Permeability

36.

Multi-Gate Resin Infusion Simulation in Liquid Composite Molding Process

Mold filling took 302 s, 499 s, and 443 s, respectively for isotropic permeability, orientation along X direction and orientation along Y direction.

The flow front tends to attain an elliptical shape in the case of orthotropic permeability, the major axis of ellipse being along the fiber orientation, which is similar to the results discussed by Lam et al. [14].

3. Effect of Change in Gate Position In the figure below, the first and second injection schemes took 302 s and 300 s, respectively as they are almost similar. The central injection resulted in a mold filling time of 199 s and multigate injection further reduced the filling time to 128 s.

Fig. 5: Time vs Filled Distance for Various Inlet Gate Schemes

In single gate injection, selection of the inlet gate position can be a very important aspect to obtain faster and uniform filling. These results also demonstrate the drastic time savings obtained through multi gate injection schemes even at lower injection pressures as compared to a single gate injection.

4. Effect of Multi-Gate Injection Similar effects of temperature and curing were observed in a single gate and two gate injections. The flow front slows down for higher temperatures. The time taken for mold filling was 128 s and 243 s for 298 K and 423 K, respectively. The simulations illustrate that the effect of orthotropic permeability can be minimized by implementation of multi gate injection. The flow was found to have more uniform behavior compared to single gate injections with orthotropic permeability. As shown in the chart above, the time taken by isotropic media was 128 s, while it was 144 s and 155 s for fibers running along X direction and Y directions, respectively.

Conclusions Behavior of resin flow through the porous media can be predicted using

37.

Multi-Gate Resin Infusion Simulation in Liquid Composite Molding Process

Fig. 6: Time vs Filled Distance for Multi gate Injection for two different Mold Temperatures

Fig. 7: Time vs Filled Distance for Multi gate Injection for Isotropic & Orthotropic Permeability

the presented model thus it can aid in the optimization of the process with a reduced filling time in the LCM processes. The resin viscosity tends to reduce with an increase in temperature within a range, above which it increases due to the enhanced effect of curing. Multi gate injection can function better even with the lesser injection pressures and brings huge reduction in mold filling times. Multi gate injection reduces the effect of anisotropic permeability on the flow front. However, the experimental assessment of the above mentioned simulations remain to be investigated in future studies.

Acknowledgement The authors gratefully acknowledge the partial support provided for this work by National Centre for Aerospace Innovation and Research, IIT-Bombay, a Department of Science and Technology - Government of India, The Boeing Company and IIT Bombay Collaboration. The authors also acknowledge Hindustan Aeronautics Limited and National Aerospace Laboratories for their technical support. 38.

Multi-Gate Resin Infusion Simulation in Liquid Composite Molding Process

REFERENCES [1] Coulter J P, Smith B F, Guceri SI. (1988), "Experimental and Numerical Analysis of Resin

Impregnation During the Manufacturing of Composite Materials" Proc Amer Soc Comp,

Second Tech Conf, pp. 209– 17.

[2] Chan A W, Hwang S T. (1992), "Modelling Resin Transfer Moulding of Axisymmetric

Composite Parts", Journal of Materials Processing and Manufacturing Science, 1, pp. 105–18.

[3] Souza J A, Nava M J A, Rocha L A O, Amico S C. (2008), "Two-Dimensional Control Volume

Modeling of the Resin Infiltration of a Porous Medium with a Heterogeneous Permeability

Tensor", Materials Research, 11(3), pp. 261-268. [4] Kang M K, Jung J J, Lee W I. (2000), "Analysis of Resin Transfer Moulding Process with

Controlled Multiple Gates Resin Injection", Composites: Part A, 31(5), pp. 407–422

[5] Luz F F, Amico S C, Souza J A, Barbosa E S, Barbosa de Lima A G. "Numerical Analysis of Heat

and Mass Transfer in Porous Media", Springer-Verlag, Berlin, 2012, Chapter-5, pp. 121-148.

[6] Sedeh M M, Khodadadi J M. Interface (2013), "Behavior and Void Formation during

Infiltration of Liquids into Porous Structures", International Journal of Multiphase Flow, 57, pp.

49–65 [7] Gerlach D, Tomar G, Biswas G, Durst F. (2006), "Comparison of Volume-of-Fluid Methods for

Surface Tension-Dominant Two-Phase Flows", International Journal of Heat and Mass

Transfer, 49, pp. 740–754 [8] Kang M K, Lee W I. (1999), "A Flow-front Refinement Technique for the Numerical Simulation

of the Resin-Transfer Molding process", Composites Science and Technology, 59, pp. 1663-

1674 [9] Srinivasan V, Salazar A J, Saito K. (2001), "Modeling the Disintegration of Modulated Liquid

Jets Using Volume-of-Fluid (VOF) Methodology", Applied Mathematical Modelling, 35,

pp.3710–30. [10] Kamal M R, Sorour S. (1973), "Kinetics and Thermal Characterization of Thermosetting Resin",

Polymer Engineering and Science, 13, pp. 356–69.

[11] Stolin A M, Merzhanov A G, Malkin A Y. (1979), "Non-Isothermal Phenomena in Polymer

Engineering and Science, A Review, Part II: Non-Isothermal Phenomena in Polymer

Deformation", Polymer Engineering and Science, 19, pp. 1074–80. [12] Ye X, Qiu J, Zhang C, Liang R, Wang B. (2009), "A Finite Element-Based Heuristic Estimation

of Local Perform Permeability for Resin Transfer Molding", Transport in Porous Media, 76, pp.

247–263. [13] Lam Y C, Joshi S C, Liu X L. (2000), "Numerical Simulation of the Mould-Filling Process in

Resin-Transfer Moulding", Composites Science and Technology, 60, pp. 845-855.

[14] Garschke C, Parlevliet P P, Weimer C, Fox B L. (2013), "Cure Kinetics and Viscosity Modelling of

a High-Performance Epoxy Resin Film", Polymer Testing. 32, pp. 150–157.

39.

TECHNOLOGY UPDATES

Resins - Types and Applications (Part I)

SWETHA MANIAN Research Assistant NCAIRTM, IIT-Bombay

What are resins? Resins are a sticky flammable substance. They are either, natural and organic, exuded by some trees and other plants or synthetic and used as the basis of plastics, adhesives, varnishes, and other products. Types of resin Based on their characteristics, resins can be broadly categorized as thermosetting and thermoplastic (see Fig. 1); they find their use in various applications. Recently, the aerospace industry has seen a rise in the use of composites which are a material system comprising of dissimilar constituents. Resins form the basis of such composite matrix, and have hence gained importance with respect to their properties, processability and profitability.

Fig. 1: Categories of resins

Reisins

Thermosetting

Thermoplastic

Epoxy

Polyetherimide (PEI)

Bismileimide

Polyphenylene sulfide (PPS)

Cyanate Ester

Polyetherketone ketone (PEKK)

Benzoxazine

Polyether etherketone (PEEK)

Of the different types of resins, the epoxy resins have been extensively used in the specialty composite applications because of the combination of its properties. In general, epoxy resin can be thought of as a molecule containing a three-membered ring, consisting of one oxygen and two carbon atoms (Fig. 2).

40.

Resins - Types and Applications (Part I)

O C

C Fig. 2: Epoxy resin molecule

The primary crosslinking in an epoxy resin occurs due to the presence of an epoxide group which attaches to a wide variety of molecular bases to yield various classes of epoxy resins. One such class is formed by the reaction of a synthetic compound, Bisphenol A, commonly referred to as BPA with epichlorohydrin to yield an epoxy resin as shown in Fig. 3. CH3

CH2

H2 C CH 2

CH3

Epichlorohydrin

Bisphenol-A

Epichlorohydrin

Bisphenol-A

CH 3

CH 2

CH2

CH 3

CH 3 Epoxy Resin

Fig. 3: Epoxy polymer formed by the reaction of bisphenol A and epichlorohydrin

Epoxy Resin

The thermal stability and flammability of epoxy resins depend on the structure of the monomer, the structure of the curing agent and its crosslink density. Diglycidyl ether of BPA (DGEBA) is the most commonly used epoxy resin. However, after curing with conventional curing agents, this resin gives inadequate dimensional stability, high water uptake, low glass transition temperature and unacceptable dielectric properties for advanced material applications. Newer polymer matrixes have been developed with phenolic resins. A phenol molecule consists of a phenyl-group (-C6H5) bonded to a hydroxyl-group (-OH) and is represented as shown in Fig. 4. Today, various grades of phenol formaldehyde resins are available from multiple suppliers where phenol reacts with formaldehyde (HCHO) to form hydroxymethyl phenol (Fig. 5). Phenolic resins used widely in industrial materials also have recently found their applications in the aerospace industry for the interior components in aerospace applications. This is due to their high heat and chemical resistance and electrical insulation capacity.

HOC6H5 Fig. 4: Phenol Fig. 5: Phenol formaldehyde reaction

CH2O â&#x2020;&#x2019;

HOC6H4CH2OH

41.

Resins - Types and Applications (Part I)

Various other polymer resins like bismaleimide and cyanate esters are being researched to be used in high temperature components, like aeroengines. Bismaleimides, a younger class of thermoset resins, albeit expensive, display good mechanical properties like high tensile strength and modulus and has good resistance to corrosion. It displays good chemical, thermal and electrical and ease in processability. Their attribute of use in high service temperature has lead to its increased use in composite matrix for various applications. Yet another polymer resin that has attracted significant attention in the recent years is the benzoxazine-based family of phenolic resins prepared by reacting phenol, primary amines, and formaldehyde as shown in Fig. 6. R'

2HCHO

Fig. 6: Phenol, primary amine, and formaldehyde reaction to form benzoxazine

H2NR'

Fig. 6 Phenol, primary amine, and formaldehyde reaction to form benzoxazine

Benzoxazines have shown to overcome many shortcomings associated with the conventional phenolic resins. These include the release of condensation byproducts and the use of strong acids as catalysts, while maintaining the thermal properties and flame retardance of phenolics. One of the features of benzoxazines is their strong resistance to corrosion and erosion due to its relatively low glass transition temperature (Tg). This is an important indicator of the mechanical behavior and transition of the polymer under various temperature conditions. The benzoxazines have far better fire fighting capability and flame retardance than epoxy resins. Not only do they have excellent mechanical properties, they have also shown to undergo near-zero volumetric changes or expansion polymerization.

How resins are used in the making of composite parts? Resin are mixed with a hardener at the manufacturing stage, and then impregnated into a dry reinforcement fabric to make a ‘prepreg’ reinforcement. The most common method of making a composite part from a prepreg is to layer the uncured prepreg into a mould, vacuum bag the mould, and then cure it in an autoclave or an oven. Curing prepregs in an oven, known as ‘outof-autoclave’ or ‘oven-only’ curing, is a very effective and accessible way to use prepreg technology that almost anyone can use. However, maintaining and caring for the prepregs is a big challenge in itself. While the shelf-life and out-life is most certainly to be taken into account, handling the prepregs is also very crucial. The resin begin to react and cure properly only at elevated temperatures, known as the cure temperature.

The search is always on for superior resin performance in terms of damage tolerance and the prepreg processability i.e. its flow, shelf life, out-life, etc. A proper flow of the resin through a fiber network dictates the wet-out of 42.

Resins - Types and Applications (Part I)

the fiber and is also crucial for the production of void-free parts. Hence resin properties, their flow and cure characteristics, are crucial for the aerospace industry. These properties and a more detailed comparison of the resins will be presented in the next part of this article.

Conclusion As the aerospace industry grows, the need for composites with better properties will continue to be of utmost importance. As resins represent a significant part of the aerospace composite industry, research in the field of polymer science is always ongoing to find resins with superior properties, excellent processability and profitability. Even as the aircraft structure properties need to be tailored for ultimate performance, it must meet stringent regulations while being cost effective at all times. BIBLIOGRAPHY

[1]

J. R. Fried, Polymer Science and Technology. Prentice Hall of India Private Limited, 2000.

[2]

A. C. Loos and G. S. Springer, “Epoxy Matrix Composites of,” vol. 17, no. March, pp. 135–169, 1983.

[3]

S. V Levchik and E. D. Weil, “Thermal decomposition, combustion and flame-retardancy of epoxy resins - a review of

the recent literature,” Polym. Int., vol. 53, no. 12, pp. 1901–1929, Dec. 2004.

[4] H. Kimura, “Curing reaction of bisphenol-A based benzoxazine with cyanate ester resin and the properties of the

cured thermosetting resin,” Express Polym. Lett., vol. 5, no. 12, pp. 1113–1122, Oct. 2011.

[5] R. Jain, A. K. Narula, and V. Choudhary, “Studies on curing and thermal behavior of diglycidyl ether of bisphenol-A and

benzoxazine mixtures.,” J. Appl. Polym. Sci., vol. 106, no. 5, pp. 3327–3334, 2007.

[6] Huntsman, N. America, “High Performance Components.”

http://www.huntsman.com/portal/page/portal/advanced_materials/Media%20Library/global/files/US%20High%20

Performance%20Components%20Sel%20Guide.pdf [7] Maureen A. Boyle, C. J. Martin, “Epoxy Resins.pdf.” Hexcel Corporation.

http://home.engineering.iastate.edu/~mkessler/MatE454/Constituent%20Materials%20Chapters%20from%20

ASM%20Handbook/%284%29%20Epoxy%20Resins.pdf

43.

NEWS UPDATES Huge Employment Potential in India's Aerospace Sector The first aerospace HR Round Table Conference with the theme "Challenges and Opportunities for Talent Management in the Aerospace Industry" was held in Bangalore recently. Delivering his keynote address, Dr. R. K. Tyagi, Chairman of HAL, said that in the coming decade, the Indian aerospace industry will transform into a huge revenue and employment generator. To tap this opportunity, the country requires better training and education, and a dedicated policy-industry-academia ecosystem, he added. â&#x20AC;&#x153;We need to ensure quality-oriented specialized training of international standards and requirements, backed by university affiliation and aviation industry, not just mushrooming of training institutions. India is yet to get its first aviation university whereas some countries have more than six aviation universitiesâ&#x20AC;?, Dr. Tyagi said. Statistics shows that, a mere 2% of India's population is vocationally skilled, compared to 75% in Germany, 80% in Japan and 68% in the UK. In addition to filling the void, the young talent needs to be extensively trained to match the high aerospace standards. Periodic skill up-gradation, specific entry-level education which would cater to the aerospace life-cycle, leadership development for mid-level management were some of the HR challenges outlined by him. Source: http://www.hal-india.com/HugeEmploymentPotentialin AerospaceIndustry.asp

Aerospace Industry-Academia Conclave Aimed at creating an ecosystem for enhancing the capabilities in the aerospace sector in India, an Aerospace Industry-Academia Conclave was organized at HAL on February 17, 2014. The event was chaired by Prof. S. G. Dhande, former Director of IIT Kanpur, and was attended by Senior executives of HAL and distinguished academicians. In his key-note address, Prof. Dhande said, "manpower challenge is a phenomena faced by the entire aerospace industry because of globalization". Further, he added that a synergy must be established between the Indian academia and the aerospace industries. Shri B. K. Chaturvedi, who heads the expert group at HAL, recommended that an Aerospace University must be established or a collaboration of universities for expanding the capabilities of the aviation sector. The discussions 44.

covered various issues such as review of domain specific curriculum, dedicated aeronautical courses to meet the man-power requirements of the industry. Source: http://www.hal-india.com/Aerospace_IndustryAcademia Conclave.asp

Global Aerospace Composites business to reach $4.7 billion by 2019 The global aerospace industry's demand for composites have significantly increased in the recent times owing to the ramp up of existing and new commercial aircraft production. There has also been a similar increase in the civil helicopters and business jet market. A published report (Composite Insights) forecasts, that the overall demand for composite materials is likely to grow to $4.7 billion in 2019. With new generation aircrafts being introduced, the aerospace industry will utilize a greater proportion of composite materials. Further, as order backlogs increase, commercial aircraft deliveries are set to go up again this year and beyond as a result of ramping up of the production rates by the airframe manufactures. New aircraft programs which are nearing the end of their development phase by the end of the decade, will also contribute toward the growing demand for composites materials in civil aerospace. Source: http://www.compositeinsights.com global_aerospace_composites.aspx

45.

ELEVONS are aircraft control surfaces that combine the functions of the elevator (used for pitch control) and the aileron (used for roll control), hence the name.

All postal/courier correspondences to NCAIRTM should be made on the adjacent postal address:

National Centre for Aerospace Innovation and Research (NCAIR), 2nd Floor, Pre-engineered building, Opp. Power house, IIT-Bombay, Powai, Mumbai-400076

Disclaimer: The views and opinions expressed in this newsletter are those of the respective authors. The content of this newsletter is solely for the purpose of dissemination of knowledge and not for any commercial purposes. The articles in this newsletter should not be utilized in real-world analytic products, as they are based only on very limited and open source information, without the prior consent of the authors.

46.