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Int. Journal of Applied Sciences and Engineering Research, Vol. 3, No. 4, 2014 www.ijaser.com 
© Copyright 2011 - Integrated Publishing Association editorial@ijaser.com 
Research article ISSN 2277 – 8442 
Effect of Coefficient of Friction in Finite Element Modeling 
of Friction Stir Welding and its Importance in 
Manufacturing Process Modeling Applications 
Sanjeev N.K*1, Vinayak Malik2, H. Suresh Hebbar1 
1Department of Mechanical Engineering, National Institute of Technology Karnataka, Surathkal, India 
2Department of Mechanical Engineering, Indian Institute of Science, Bangalore, India 
Abstract: Friction Stir Welding (FSW) is a relatively new joining process which is gaining significance in 
many joining applications. The development in Finite element (FE) modeling is also aiding in widening the 
applicability of FSW by simulating the process for better understanding. The success of modeling of FSW 
depends on selection of suitable techniques and models/laws irrespective of FE package used for 
simulation. The principal equations that govern modeling of FSW are the material model and the friction 
model. This paper aims at discussing the effect of variation in Coefficient of Friction (COF) on simulation 
outputs. It also highlights the modification required in friction model to get the realistic results from FSW 
simulations using ABAQUS. 
Key words: FE modeling; FSW; Coefficient of friction; Coupled Eulerian Lagrangian; ABAQUS 
1. Introduction 
Friction stir welding (FSW) is a relatively new joining process invented at The Welding Institute 
(Cambridge, UK) in 1991. It involves the joining of metals without fusion or filler materials. It was 
initially applied to aluminum alloys. Since then FSW has rapidly evolved and has opened up multiple 
research channels. It is being touted as the most significant development in metal joining in the last decade 
(Mishra and Ma, 2005, Mishra and Mahoney, 2007). Many alloys, including most aerospace Al alloys (e.g., 
Al 7xxx) and those regarded as difficult to weld by fusion processes (e.g., Al 2xxx), may be welded by 
FSW (Uyyuru and Kailas, 2006, Kumar et al., 2008). The basic process of FSW is that, a rotating 
cylindrical tool is plunged into the plates to be welded and moved along joint line as illustrated in Figure 1. 
During the welding, heat is generated by contact friction between the tool and workpiece due to which the 
material gets plasticized within a narrow zone while transporting metal from the leading face of the pin to 
its trailing edge. The processed zone cools without solidification, as there is no liquid. Hence, a defect-free 
re-crystallized fine grain microstructure is formed and welding is achieved between plates. Since FSW is 
solid state joining process, i.e., without melting, high quality weld can generally be fabricated with absence 
of solidification cracking, porosity, oxidation, and other defects typical to traditional fusion welding 
(Prasanna et al., 2010). The significant advantage of FSW is that it is an environment friendly process, 
which does not make use of flux and consumable electrodes thereby minimizing and avoids the generation 
of fumes, formation of slag and ultra-violet radiation thus minimizing the level of health hazards 
(Kandasamy et al., 2011). 
————————————— 
755 
DOI: 10.6088/ijaser.030400001 
*Corresponding author (e-mail: sanjeevkumaraswamy@gmail.com) 
Received on Jun. 16, 2014; Accepted on Jun. 20, 2014; Published on August 2014
Effect of Coefficient of Friction in Finite Element Modeling of Friction Stir Welding and its Importance in 
Manufacturing Process Modeling Applications 
Sanjeev N K et al., 
Int. Journal of Applied Sciences and Engineering Research, Vol. 3, No. 4, 2014 
756 
Figure 1: Schematic of friction stir welding process (Deplus, 2014) 
Use of Finite Element (FE) simulations is adding the FSW process to a better understanding of its physics, 
observing the influence of input parameters on the obtained joints, and optimizing the overall process for a 
large range of tools, process conditions and materials and also in lowering development costs (Assidi et al., 
2010). Simulations require the modeling of friction, mechanical and thermal behavior and kinematics to 
solve all field equations (Lorrain et al., 2009). However, the difficulty arises when one needs to implement 
accurate friction characteristics (Contact condition) using a particular FE formulation. In this study, a 
Coupled Eulerian Lagrangian finite element formulation is used to simulate FSW of 2024-T3 aluminium 
alloy. The effects of using various tool-work interface contact conditions on the simulations are 
investigated. Experimentally measured temperature in the work piece, force on the tool and macro 
structural findings for defects are utilized in investigation and evaluation of the results for the friction 
models (different values of variables in models are also checked). The results depict that the use of various 
tool-work interface friction models and COF has appreciable influence in predicting temperature, force and 
mainly defect formation. 
2. Contact condition 
When modeling the FSW, the contact condition between workpiece and tool is a critical part of the FE 
model. In FE packages the contact conditions are defined using available friction laws or with user defined 
laws. The friction models available in ABAQUS are: 
• Isotropic and anisotropic Coulomb friction model: In its general form allows the COF to be 
defined in terms of slip rate, contact pressure, average surface temperature at the contact point and 
field variables. It also provides the option to define a static and a kinetic COF with a smooth 
transition zone defined by an exponential curve (Steen, 2007). 
• Softened interface model for sticking (no slip) friction (modified Coulomb friction model): Here, 
the shear stress is a function of elastic slip, which can be implemented with a stiffness (penalty) 
method, a kinematic method or a Lagrange multiplier method depending on the contact algorithm 
used (Steen, 2007). 
Sticking condition: The matrix surface will stick to the moving tool surface segment, if the friction shear 
stress exceeds the yield shear stress of the underlying matrix. In this case, the matrix segment will 
accelerate along the tool surface, until equilibrium state is established between the contact shear stress and 
the internal matrix shear stress. At this point, the stationary full sticking condition is fulfilled (Schmidt et
Effect of Coefficient of Friction in Finite Element Modeling of Friction Stir Welding and its Importance in 
Manufacturing Process Modeling Applications 
al., 2004). In ABAQUS, friction law used in solid mechanics and that suite for FSW modeling is modified 
Coulomb friction law (Lorrain et al., 2009, Schmidt et al., 2004). According to Coulomb friction law, the 
shear stress of the contacting interface is expressed as: 
t = μ p (1) 
t fric t shear s s = = (2) 
Sanjeev N K et al., 
Int. Journal of Applied Sciences and Engineering Research, Vol. 3, No. 4, 2014 
757 
fric 
where fric t is the friction shear stress,μ the COF and p the normal contact pressure (Li et al., 2012). 
Figure 2: Modified Coulomb law (Zhang and Chen, 2007) 
The COF could be a variable dependent on the interface temperature, relative slipping rate between the two 
surfaces and normal pressure. However, for FSW, the conventional Coulomb friction law will be only 
applied at the very beginning of welding when interface temperature is relatively low. As the interface 
plasticized material is formed in larger volumes at elevated temperatures, the friction behavior will be 
dominated by viscoplastic friction. Therefore, heat generation is dependent on intense plastic deformation 
of the thin shear layer at the interface (i.e. all heat generated in the whole FSW process is attributed solely 
to the significant plastic deformation in the shear layer of certain thickness (Li et al., 2011)). A modified 
Coulomb friction law is then applied (Figure 2), where the equivalent flow stress of the material is used as 
follows: 
3 
Where shear t is the flow shear stress calculated from the equivalent flow stress s s (Li et al., 2012). 
Hatzenbichler et al. (2009) have stated that the COF which is true for one software package cannot be 
transferred directly into another one. So, COF has to be calibrated for each process and software package 
used for simulation by the user. This is because contact in conjunction with plastic material behavior leads 
to highly nonlinear equations in the FEM algorithms, which may cause problems in numerical convergence. 
Some FEM software providers handle this problem by automatic contact damping or similar algorithms. 
However, the user has mostly no detailed information about adjustments and prediction accuracy. The only 
possibility for the user to have an impact on the contact behavior is to set a COF and to choose a friction 
model appropriate to the investigated process and model availability in software package. Friction factors
Effect of Coefficient of Friction in Finite Element Modeling of Friction Stir Welding and its Importance in 
Manufacturing Process Modeling Applications 
are often measured by standard tests like the ring compression test which should be valid for all used 
software packages (Hatzenbichler et al., 2009). The COF (μ) between tool and work-piece is an input 
parameter in FE model and used in heat generation formulations. Different values of COF have been used 
in literature. Tutunchilar et al. (2012) used COF values of 0.4, 0.5, and 0.6, under 100 mm/min transverse 
speed and 900 rpm rotational speed. According to investigations made by Kumar et al. (2009), the COF 
and temperatures do have a synergic influence on each other. The COF in FSW condition was found to be 
as high as 1.2 to 1.4 in temperature range of 400-450°C. Therefore, simulations were performed by varying 
the COF values from 0.1-2.0 to see the effects on results and to choose the right value. 
Sanjeev N K et al., 
Int. Journal of Applied Sciences and Engineering Research, Vol. 3, No. 4, 2014 
758 
3. FE modeling details 
FE model is developed in the commercial code ABAQUS/Explicit using the Coupled Eulerian-Lagrangian 
Formulation, the Johnson-Cook material law, and Coulomb’s law of friction. 
Figure 3: Geometry of tool employed (Malik et al., 2014) 
The tool with shoulder, frustum shaped pin made of material of Hot die steel (HDS) is considered. The 
Figure 3 shows schematic representation of tool geometry. The work-piece of 200X100 mm area and 
thickness of 5 mm is considered in simulation. In FE model the Eulerian domain is meshed with 
multi-material thermally coupled 8-node (EC3D8RT) Eulerian elements (Merzoug et al., 2010, Al-Badour 
et al., 2013) and the void region thickness is taken as 1 mm. The simulation and experimental welding 
conditions considered are; Plunge velocity of 10 mm/min, Dwell Time of 10 sec, Welding speed of 60 
mm/min, Plunge depth is 0.2 mm, tool tilt angle of zero degree and varying the rotational speed. 
4. Results and discussion 
Initially model was developed referring to results of temperature and macrographs obtained from 
experiment conducted on aluminium 2024-T3 alloy. Further by changing the workpiece material, 
validation of model was carried out using temperature results and macrographs published by Merzoug et al. 
(2010) and Hirasawa et al. (2010). Here the effects of COF on material AA2024-T3 are discussed in detail. 
The simulation results show that the COF has a major effect on void formation. The lower the COF is 
applied, larger is the void formed. The Figure 4 shows the effect of COF on void size at a tool rotational 
speed of 950 rpm. As the friction between tool and the workpiece increased the formation of void and 
moment of material was closer to that of experimental conditions. It can be seen that any value of μ <1 
resulted in unrealistic prediction of results. Also considering μ >1.2 lead to over softening of material,
Effect of Coefficient of Friction in Finite Element Modeling of Friction Stir Welding and its Importance in 
Manufacturing Process Modeling Applications 
Sanjeev N K et al., 
Int. Journal of Applied Sciences and Engineering Research, Vol. 3, No. 4, 2014 
759 
which in turn showed the defect as shown in Figure 5. 
Figure 4: Effect of COF (μ) on void size (Top view): (a) μ = 0.2, (b) μ = 0.4, (c) μ = 0.6, 
(d) μ = 0.8, (e) μ = 1 
Figure 5: Effect of high COF (Top view): (a) μ = 1.4, (b) μ = 1.6 
For a sound weld, it is found from literature that the working temperature in FSW should be in the range 
of 80 to 90% of melting temperature (Tmelt) of the welding material (Qian et al., 2013, Chao et al., 2003). 
Table 1 indicates that with μ=1, the maximum temperature predicted in simulation is in the 80 to 90% of 
Tmelt range. Here, the percentage of error is calculated by considering the maximum temperature of
Effect of Coefficient of Friction in Finite Element Modeling of Friction Stir Welding and its Importance in 
Manufacturing Process Modeling Applications 
404.36°C, recorded by thermo-couple during the experiment. The resulted simulation temperature at μ=1 is 
in close agreement with thermocouple reading with an error of 6.46% (which is of acceptable range). The 
error could be because of considering tool as a discrete rigid body. Considering μ=1 and Johnson-Cook 
model, the Figure 6 shows the capability of model in accurate simulation of FSW process. 
Sanjeev N K et al., 
Int. Journal of Applied Sciences and Engineering Research, Vol. 3, No. 4, 2014 
760 
Table 1: Simulation temperature with respect to COF 
COF (μ) Temperature (°C) 
[Simulation] 
Error (%) 
0.2 140.86 -61.28 
0.4 180.62 -52.03 
0.6 260.54 -33.45 
0.8 367.46 -8.58 
1 432.14 6.46 
1.2 460.57 13.07 
14 470.23 15.32 
1.6 475.15 16.46 
1.8 477.48 17.00 
2 478.34 17.20 
Figure 6: Comparison of (i) experimental and (ii) FE model simulated FSW process 
(After retracting tool) 
5. Conclusions 
Based on the analysis carried out and the results obtained, following conclusions can be made: 
(1) A COF of 1.0 has to be considered with sticking condition while using Columbus law of friction in 
modeling of FSW and its variants. 
(2) Based on the comparison of the simulation and experimental results, under the no slip condition 
(μ=1) and Johnson-Cook material model in ABAQUS/Explicit environment, the proposed model 
is capable of predicting right processing parameters.
Effect of Coefficient of Friction in Finite Element Modeling of Friction Stir Welding and its Importance in 
Manufacturing Process Modeling Applications 
Sanjeev N K et al., 
Int. Journal of Applied Sciences and Engineering Research, Vol. 3, No. 4, 2014 
761 
Acknowledgements 
Authors wish to thank Department of Mechanical Engineering, Indian Institute of Science, Bangalore, for 
providing research facilities and National Institute of Technology Karnataka, Surathkal, for constant help 
and encouragement. 
6. References 
1. Al-Badour, F., Merah, N., Shuaib, A. and Bazoune, A. (2013) 'Coupled Eulerian Lagrangian finite 
element modeling of friction stir welding processes', Journal of Materials Processing Technology, 
213(8), pp. 1433-1439. 
2. Assidi, M., Fourment, L., Guerdoux, S. and Nelson, T. (2010) 'Friction model for friction stir 
welding process simulation: Calibrations from welding experiments', International Journal of 
Machine Tools and Manufacture, 50(2), pp. 143-155. 
3. Chao, Y. J., Qi, X. and Tang, W. (2003) 'Heat Transfer in Friction Stir Welding—Experimental and 
Numerical Studies', Journal of Manufacturing Science and Engineering, 125(1), pp. 138. 
4. Deplus, i. K. (2014) ALUWELD : Innovative welding of aluminium alloys – Hybrid Laser Welding 
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5. Hatzenbichler, T., Harrer, O., Buchmayr, B. and Planitzer, F. (2009) 'Effect of different contact 
formulations used in commercial FEM software packages on the results of hot forging simulations', 
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Grado, organized by AIM. 
6. Hirasawa, S., Badarinarayan, H., Okamoto, K., Tomimura, T. and Kawanami, T. (2010) 'Analysis of 
effect of tool geometry on plastic flow during friction stir spot welding using particle method', 
Journal of Materials Processing Technology, 210(11), pp. 1455-1463. 
7. Kandasamy, K., Kailas, S. V. and Srivatsan, T. S. (2011) 'The Extrinsic Influence of Tool Plunge 
Depth on Friction Stir Welding of an Aluminum Alloy', Advanced Materials Research, 410, pp. 
206-215. 
8. Kumar, K., Kailas, S. V. and Srivatsan, T. S. (2008) 'Influence of Tool Geometry in Friction Stir 
Welding', Materials and Manufacturing Processes, 23(2), pp. 188-194. 
9. Kumar, K., Kalyan, C., Kailas, S. V. and Srivatsan, T. S. (2009) 'An Investigation of Friction during 
Friction Stir Welding of Metallic Materials', Materials and Manufacturing Processes, 24:4, pp. 
438-445. 
10. Li, W., Shi, S., Wang, F., Zhang, Z., Ma, T. and Li, J. (2012) 'Numerical Simulation of Friction 
Welding Processes Based on ABAQUS Environment', Journal of Engineering Science and 
Technology Review 5 (3) (2012) 5(3), pp. 10-19. 
11. Li, W., Zhang, Z., Li, J. and Chao, Y. J. (2011) 'Numerical Analysis of Joint Temperature Evolution 
During Friction Stir Welding Based on Sticking Contact', Journal of Materials Engineering and 
Performance, 21(9), pp. 1849-1856. 
12. Lorrain, O., Serri, J., Favier, V., Zahrouni, H. and Hadrouz, M. E. (2009) 'A Contribution To A 
Critical Review Of Friction Stir Welding Numerical Simulation', Journal Of Mechanics Of 
Materials And Structures, 4(2), pp. 351-370. 
13. Malik, V., K, S. N., Hebbar, H. S. and Kailas, S. V. 'Time Efficient Simulations of Plunge and Dwell 
Phase of FSW and its Significance in FSSW '. International Conference on Advances in 
Manufacturing and Materials Engineering, NITK, Surathkal: Procedia Material Science. 
14. Merzoug, M., Mazari, M., Berrahal, L. and Imad, A. (2010) 'Parametric studies of the process of
Effect of Coefficient of Friction in Finite Element Modeling of Friction Stir Welding and its Importance in 
Manufacturing Process Modeling Applications 
friction spot stir welding of aluminium 6060-T5 alloys', Materials & Design, 31(6), pp. 3023-3028. 
15. Mishra, R. S. and Ma, Z. Y. (2005) 'Friction stir welding and processing', Materials Science and 
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Engineering: R: Reports, 50(1-2), pp. 1-78. 
16. Mishra, R. S. and Mahoney, M. W. (2007) Friction Stir Welding and Processing. ASM International. 
17. Prasanna, P., Rao, B. S. and Rao, G. K. M. (2010) 'Finite element modeling for maximum 
temperature in friction stir welding and its validation', The International Journal of Advanced 
Manufacturing Technology, 51(9-12), pp. 925-933. 
18. Qian, J., Li, J., Sun, F., Xiong, J., Zhang, F. and Lin, X. (2013) 'An analytical model to optimize 
rotation speed and travel speed of friction stir welding for defect-free joints', Scripta Materialia, 
68(3-4), pp. 175-178. 
19. Schmidt, H., Hattel, J. and Wert, J. (2004) 'An analytical model for the heat generation in friction stir 
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'Simulation of material flow in friction stir processing of a cast Al–Si alloy', Materials & Design, 40, 
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23. Zhang, Z. and Chen, J. T. (2007) 'The simulation of material behaviors in friction stir welding 
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222-232.

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Effect of coefficient of friction in finite element modeling sanjeev n k

  • 1. Int. Journal of Applied Sciences and Engineering Research, Vol. 3, No. 4, 2014 www.ijaser.com © Copyright 2011 - Integrated Publishing Association editorial@ijaser.com Research article ISSN 2277 – 8442 Effect of Coefficient of Friction in Finite Element Modeling of Friction Stir Welding and its Importance in Manufacturing Process Modeling Applications Sanjeev N.K*1, Vinayak Malik2, H. Suresh Hebbar1 1Department of Mechanical Engineering, National Institute of Technology Karnataka, Surathkal, India 2Department of Mechanical Engineering, Indian Institute of Science, Bangalore, India Abstract: Friction Stir Welding (FSW) is a relatively new joining process which is gaining significance in many joining applications. The development in Finite element (FE) modeling is also aiding in widening the applicability of FSW by simulating the process for better understanding. The success of modeling of FSW depends on selection of suitable techniques and models/laws irrespective of FE package used for simulation. The principal equations that govern modeling of FSW are the material model and the friction model. This paper aims at discussing the effect of variation in Coefficient of Friction (COF) on simulation outputs. It also highlights the modification required in friction model to get the realistic results from FSW simulations using ABAQUS. Key words: FE modeling; FSW; Coefficient of friction; Coupled Eulerian Lagrangian; ABAQUS 1. Introduction Friction stir welding (FSW) is a relatively new joining process invented at The Welding Institute (Cambridge, UK) in 1991. It involves the joining of metals without fusion or filler materials. It was initially applied to aluminum alloys. Since then FSW has rapidly evolved and has opened up multiple research channels. It is being touted as the most significant development in metal joining in the last decade (Mishra and Ma, 2005, Mishra and Mahoney, 2007). Many alloys, including most aerospace Al alloys (e.g., Al 7xxx) and those regarded as difficult to weld by fusion processes (e.g., Al 2xxx), may be welded by FSW (Uyyuru and Kailas, 2006, Kumar et al., 2008). The basic process of FSW is that, a rotating cylindrical tool is plunged into the plates to be welded and moved along joint line as illustrated in Figure 1. During the welding, heat is generated by contact friction between the tool and workpiece due to which the material gets plasticized within a narrow zone while transporting metal from the leading face of the pin to its trailing edge. The processed zone cools without solidification, as there is no liquid. Hence, a defect-free re-crystallized fine grain microstructure is formed and welding is achieved between plates. Since FSW is solid state joining process, i.e., without melting, high quality weld can generally be fabricated with absence of solidification cracking, porosity, oxidation, and other defects typical to traditional fusion welding (Prasanna et al., 2010). The significant advantage of FSW is that it is an environment friendly process, which does not make use of flux and consumable electrodes thereby minimizing and avoids the generation of fumes, formation of slag and ultra-violet radiation thus minimizing the level of health hazards (Kandasamy et al., 2011). ————————————— 755 DOI: 10.6088/ijaser.030400001 *Corresponding author (e-mail: sanjeevkumaraswamy@gmail.com) Received on Jun. 16, 2014; Accepted on Jun. 20, 2014; Published on August 2014
  • 2. Effect of Coefficient of Friction in Finite Element Modeling of Friction Stir Welding and its Importance in Manufacturing Process Modeling Applications Sanjeev N K et al., Int. Journal of Applied Sciences and Engineering Research, Vol. 3, No. 4, 2014 756 Figure 1: Schematic of friction stir welding process (Deplus, 2014) Use of Finite Element (FE) simulations is adding the FSW process to a better understanding of its physics, observing the influence of input parameters on the obtained joints, and optimizing the overall process for a large range of tools, process conditions and materials and also in lowering development costs (Assidi et al., 2010). Simulations require the modeling of friction, mechanical and thermal behavior and kinematics to solve all field equations (Lorrain et al., 2009). However, the difficulty arises when one needs to implement accurate friction characteristics (Contact condition) using a particular FE formulation. In this study, a Coupled Eulerian Lagrangian finite element formulation is used to simulate FSW of 2024-T3 aluminium alloy. The effects of using various tool-work interface contact conditions on the simulations are investigated. Experimentally measured temperature in the work piece, force on the tool and macro structural findings for defects are utilized in investigation and evaluation of the results for the friction models (different values of variables in models are also checked). The results depict that the use of various tool-work interface friction models and COF has appreciable influence in predicting temperature, force and mainly defect formation. 2. Contact condition When modeling the FSW, the contact condition between workpiece and tool is a critical part of the FE model. In FE packages the contact conditions are defined using available friction laws or with user defined laws. The friction models available in ABAQUS are: • Isotropic and anisotropic Coulomb friction model: In its general form allows the COF to be defined in terms of slip rate, contact pressure, average surface temperature at the contact point and field variables. It also provides the option to define a static and a kinetic COF with a smooth transition zone defined by an exponential curve (Steen, 2007). • Softened interface model for sticking (no slip) friction (modified Coulomb friction model): Here, the shear stress is a function of elastic slip, which can be implemented with a stiffness (penalty) method, a kinematic method or a Lagrange multiplier method depending on the contact algorithm used (Steen, 2007). Sticking condition: The matrix surface will stick to the moving tool surface segment, if the friction shear stress exceeds the yield shear stress of the underlying matrix. In this case, the matrix segment will accelerate along the tool surface, until equilibrium state is established between the contact shear stress and the internal matrix shear stress. At this point, the stationary full sticking condition is fulfilled (Schmidt et
  • 3. Effect of Coefficient of Friction in Finite Element Modeling of Friction Stir Welding and its Importance in Manufacturing Process Modeling Applications al., 2004). In ABAQUS, friction law used in solid mechanics and that suite for FSW modeling is modified Coulomb friction law (Lorrain et al., 2009, Schmidt et al., 2004). According to Coulomb friction law, the shear stress of the contacting interface is expressed as: t = μ p (1) t fric t shear s s = = (2) Sanjeev N K et al., Int. Journal of Applied Sciences and Engineering Research, Vol. 3, No. 4, 2014 757 fric where fric t is the friction shear stress,μ the COF and p the normal contact pressure (Li et al., 2012). Figure 2: Modified Coulomb law (Zhang and Chen, 2007) The COF could be a variable dependent on the interface temperature, relative slipping rate between the two surfaces and normal pressure. However, for FSW, the conventional Coulomb friction law will be only applied at the very beginning of welding when interface temperature is relatively low. As the interface plasticized material is formed in larger volumes at elevated temperatures, the friction behavior will be dominated by viscoplastic friction. Therefore, heat generation is dependent on intense plastic deformation of the thin shear layer at the interface (i.e. all heat generated in the whole FSW process is attributed solely to the significant plastic deformation in the shear layer of certain thickness (Li et al., 2011)). A modified Coulomb friction law is then applied (Figure 2), where the equivalent flow stress of the material is used as follows: 3 Where shear t is the flow shear stress calculated from the equivalent flow stress s s (Li et al., 2012). Hatzenbichler et al. (2009) have stated that the COF which is true for one software package cannot be transferred directly into another one. So, COF has to be calibrated for each process and software package used for simulation by the user. This is because contact in conjunction with plastic material behavior leads to highly nonlinear equations in the FEM algorithms, which may cause problems in numerical convergence. Some FEM software providers handle this problem by automatic contact damping or similar algorithms. However, the user has mostly no detailed information about adjustments and prediction accuracy. The only possibility for the user to have an impact on the contact behavior is to set a COF and to choose a friction model appropriate to the investigated process and model availability in software package. Friction factors
  • 4. Effect of Coefficient of Friction in Finite Element Modeling of Friction Stir Welding and its Importance in Manufacturing Process Modeling Applications are often measured by standard tests like the ring compression test which should be valid for all used software packages (Hatzenbichler et al., 2009). The COF (μ) between tool and work-piece is an input parameter in FE model and used in heat generation formulations. Different values of COF have been used in literature. Tutunchilar et al. (2012) used COF values of 0.4, 0.5, and 0.6, under 100 mm/min transverse speed and 900 rpm rotational speed. According to investigations made by Kumar et al. (2009), the COF and temperatures do have a synergic influence on each other. The COF in FSW condition was found to be as high as 1.2 to 1.4 in temperature range of 400-450°C. Therefore, simulations were performed by varying the COF values from 0.1-2.0 to see the effects on results and to choose the right value. Sanjeev N K et al., Int. Journal of Applied Sciences and Engineering Research, Vol. 3, No. 4, 2014 758 3. FE modeling details FE model is developed in the commercial code ABAQUS/Explicit using the Coupled Eulerian-Lagrangian Formulation, the Johnson-Cook material law, and Coulomb’s law of friction. Figure 3: Geometry of tool employed (Malik et al., 2014) The tool with shoulder, frustum shaped pin made of material of Hot die steel (HDS) is considered. The Figure 3 shows schematic representation of tool geometry. The work-piece of 200X100 mm area and thickness of 5 mm is considered in simulation. In FE model the Eulerian domain is meshed with multi-material thermally coupled 8-node (EC3D8RT) Eulerian elements (Merzoug et al., 2010, Al-Badour et al., 2013) and the void region thickness is taken as 1 mm. The simulation and experimental welding conditions considered are; Plunge velocity of 10 mm/min, Dwell Time of 10 sec, Welding speed of 60 mm/min, Plunge depth is 0.2 mm, tool tilt angle of zero degree and varying the rotational speed. 4. Results and discussion Initially model was developed referring to results of temperature and macrographs obtained from experiment conducted on aluminium 2024-T3 alloy. Further by changing the workpiece material, validation of model was carried out using temperature results and macrographs published by Merzoug et al. (2010) and Hirasawa et al. (2010). Here the effects of COF on material AA2024-T3 are discussed in detail. The simulation results show that the COF has a major effect on void formation. The lower the COF is applied, larger is the void formed. The Figure 4 shows the effect of COF on void size at a tool rotational speed of 950 rpm. As the friction between tool and the workpiece increased the formation of void and moment of material was closer to that of experimental conditions. It can be seen that any value of μ <1 resulted in unrealistic prediction of results. Also considering μ >1.2 lead to over softening of material,
  • 5. Effect of Coefficient of Friction in Finite Element Modeling of Friction Stir Welding and its Importance in Manufacturing Process Modeling Applications Sanjeev N K et al., Int. Journal of Applied Sciences and Engineering Research, Vol. 3, No. 4, 2014 759 which in turn showed the defect as shown in Figure 5. Figure 4: Effect of COF (μ) on void size (Top view): (a) μ = 0.2, (b) μ = 0.4, (c) μ = 0.6, (d) μ = 0.8, (e) μ = 1 Figure 5: Effect of high COF (Top view): (a) μ = 1.4, (b) μ = 1.6 For a sound weld, it is found from literature that the working temperature in FSW should be in the range of 80 to 90% of melting temperature (Tmelt) of the welding material (Qian et al., 2013, Chao et al., 2003). Table 1 indicates that with μ=1, the maximum temperature predicted in simulation is in the 80 to 90% of Tmelt range. Here, the percentage of error is calculated by considering the maximum temperature of
  • 6. Effect of Coefficient of Friction in Finite Element Modeling of Friction Stir Welding and its Importance in Manufacturing Process Modeling Applications 404.36°C, recorded by thermo-couple during the experiment. The resulted simulation temperature at μ=1 is in close agreement with thermocouple reading with an error of 6.46% (which is of acceptable range). The error could be because of considering tool as a discrete rigid body. Considering μ=1 and Johnson-Cook model, the Figure 6 shows the capability of model in accurate simulation of FSW process. Sanjeev N K et al., Int. Journal of Applied Sciences and Engineering Research, Vol. 3, No. 4, 2014 760 Table 1: Simulation temperature with respect to COF COF (μ) Temperature (°C) [Simulation] Error (%) 0.2 140.86 -61.28 0.4 180.62 -52.03 0.6 260.54 -33.45 0.8 367.46 -8.58 1 432.14 6.46 1.2 460.57 13.07 14 470.23 15.32 1.6 475.15 16.46 1.8 477.48 17.00 2 478.34 17.20 Figure 6: Comparison of (i) experimental and (ii) FE model simulated FSW process (After retracting tool) 5. Conclusions Based on the analysis carried out and the results obtained, following conclusions can be made: (1) A COF of 1.0 has to be considered with sticking condition while using Columbus law of friction in modeling of FSW and its variants. (2) Based on the comparison of the simulation and experimental results, under the no slip condition (μ=1) and Johnson-Cook material model in ABAQUS/Explicit environment, the proposed model is capable of predicting right processing parameters.
  • 7. Effect of Coefficient of Friction in Finite Element Modeling of Friction Stir Welding and its Importance in Manufacturing Process Modeling Applications Sanjeev N K et al., Int. Journal of Applied Sciences and Engineering Research, Vol. 3, No. 4, 2014 761 Acknowledgements Authors wish to thank Department of Mechanical Engineering, Indian Institute of Science, Bangalore, for providing research facilities and National Institute of Technology Karnataka, Surathkal, for constant help and encouragement. 6. References 1. Al-Badour, F., Merah, N., Shuaib, A. and Bazoune, A. (2013) 'Coupled Eulerian Lagrangian finite element modeling of friction stir welding processes', Journal of Materials Processing Technology, 213(8), pp. 1433-1439. 2. Assidi, M., Fourment, L., Guerdoux, S. and Nelson, T. (2010) 'Friction model for friction stir welding process simulation: Calibrations from welding experiments', International Journal of Machine Tools and Manufacture, 50(2), pp. 143-155. 3. Chao, Y. J., Qi, X. and Tang, W. (2003) 'Heat Transfer in Friction Stir Welding—Experimental and Numerical Studies', Journal of Manufacturing Science and Engineering, 125(1), pp. 138. 4. Deplus, i. K. (2014) ALUWELD : Innovative welding of aluminium alloys – Hybrid Laser Welding and Friction Stir Welding: The Belgian Welding Institute Non-Profit Organisation. 5. Hatzenbichler, T., Harrer, O., Buchmayr, B. and Planitzer, F. (2009) 'Effect of different contact formulations used in commercial FEM software packages on the results of hot forging simulations', Paper presented at the International Conference Hot Forming of Steels And Products Properties, Grado, organized by AIM. 6. Hirasawa, S., Badarinarayan, H., Okamoto, K., Tomimura, T. and Kawanami, T. (2010) 'Analysis of effect of tool geometry on plastic flow during friction stir spot welding using particle method', Journal of Materials Processing Technology, 210(11), pp. 1455-1463. 7. Kandasamy, K., Kailas, S. V. and Srivatsan, T. S. (2011) 'The Extrinsic Influence of Tool Plunge Depth on Friction Stir Welding of an Aluminum Alloy', Advanced Materials Research, 410, pp. 206-215. 8. Kumar, K., Kailas, S. V. and Srivatsan, T. S. (2008) 'Influence of Tool Geometry in Friction Stir Welding', Materials and Manufacturing Processes, 23(2), pp. 188-194. 9. Kumar, K., Kalyan, C., Kailas, S. V. and Srivatsan, T. S. (2009) 'An Investigation of Friction during Friction Stir Welding of Metallic Materials', Materials and Manufacturing Processes, 24:4, pp. 438-445. 10. Li, W., Shi, S., Wang, F., Zhang, Z., Ma, T. and Li, J. (2012) 'Numerical Simulation of Friction Welding Processes Based on ABAQUS Environment', Journal of Engineering Science and Technology Review 5 (3) (2012) 5(3), pp. 10-19. 11. Li, W., Zhang, Z., Li, J. and Chao, Y. J. (2011) 'Numerical Analysis of Joint Temperature Evolution During Friction Stir Welding Based on Sticking Contact', Journal of Materials Engineering and Performance, 21(9), pp. 1849-1856. 12. Lorrain, O., Serri, J., Favier, V., Zahrouni, H. and Hadrouz, M. E. (2009) 'A Contribution To A Critical Review Of Friction Stir Welding Numerical Simulation', Journal Of Mechanics Of Materials And Structures, 4(2), pp. 351-370. 13. Malik, V., K, S. N., Hebbar, H. S. and Kailas, S. V. 'Time Efficient Simulations of Plunge and Dwell Phase of FSW and its Significance in FSSW '. International Conference on Advances in Manufacturing and Materials Engineering, NITK, Surathkal: Procedia Material Science. 14. Merzoug, M., Mazari, M., Berrahal, L. and Imad, A. (2010) 'Parametric studies of the process of
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