effect of coefficient of friction in finite element modeling_sanjeev n k
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8112019 Effect of Coefficient of Friction in Finite Element Modeling_SANJEEV N K
httpslidepdfcomreaderfulleffect-of-coefficient-of-friction-in-finite-element-modelingsanjeev-n-k 18
Int Journal of Applied Sciences and Engineering Research Vol 3 No 4 2014 wwwijasercom
copy Copyright 2011 - Integrated Publishing Association editorialijasercom
Research article ISSN 2277 ndash 8442
991252 991252 991252 991252 991252 991252 991252 991252 991252 991252 991252 991252 991252
755
Corresponding author (e-mail sanjeevkumaraswamygmailcom)
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 NK1 Vinayak Malik 2 H Suresh Hebbar1
1Department of Mechanical Engineering National Institute of Technology Karnataka Surathkal India
2Department of Mechanical Engineering Indian Institute of Science Bangalore India
DOI 106088ijaser030400001
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 theapplicability of FSW by simulating the process for better understanding The success of modeling of FSW
depends on selection of suitable techniques and modelslaws 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 (eg
Al 7xxx) and those regarded as difficult to weld by fusion processes (eg 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 ie 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)
8112019 Effect of Coefficient of Friction in Finite Element Modeling_SANJEEV N K
httpslidepdfcomreaderfulleffect-of-coefficient-of-friction-in-finite-element-modelingsanjeev-n-k 28
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
bull
Isotropic and anisotropic Coulomb friction model In its general form allows the COF to bedefined 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)
bull
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
8112019 Effect of Coefficient of Friction in Finite Element Modeling_SANJEEV N K
httpslidepdfcomreaderfulleffect-of-coefficient-of-friction-in-finite-element-modelingsanjeev-n-k 38
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
757
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
fric p micro τ = (1)
where fricτ is the friction shear stress micro 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 (ie 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 fric shear sτ τ σ = = (2)
Whereshear
τ is the flow shear stress calculated from the equivalent flow stresss
σ (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
8112019 Effect of Coefficient of Friction in Finite Element Modeling_SANJEEV N K
httpslidepdfcomreaderfulleffect-of-coefficient-of-friction-in-finite-element-modelingsanjeev-n-k 48
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
758
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 (micro) 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 04 05 and 06 under 100 mmmin transverse
speed and 900 rpm rotational speed According to investigations made by Kumar et al (2009) the COFand temperatures do have a synergic influence on each other The COF in FSW condition was found to be
as high as 12 to 14 in temperature range of 400-450degC Therefore simulations were performed by varying
the COF values from 01-20 to see the effects on results and to choose the right value
3 FE modeling details
FE model is developed in the commercial code ABAQUSExplicit using the Coupled Eulerian-Lagrangian
Formulation the Johnson-Cook material law and Coulombrsquos 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 mmmin Dwell Time of 10 sec Welding speed of 60
mmmin Plunge depth is 02 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 1 micro lt
resulted in unrealistic prediction of results Also considering 12 micro gt lead to over softening of material
8112019 Effect of Coefficient of Friction in Finite Element Modeling_SANJEEV N K
httpslidepdfcomreaderfulleffect-of-coefficient-of-friction-in-finite-element-modelingsanjeev-n-k 58
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 (micro) on void size (Top view) (a) micro = 02 (b) micro = 04 (c) micro = 06
(d) micro = 08 (e) micro = 1
Figure 5 Effect of high COF (Top view) (a) micro = 14 (b) micro = 16
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 micro=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
8112019 Effect of Coefficient of Friction in Finite Element Modeling_SANJEEV N K
httpslidepdfcomreaderfulleffect-of-coefficient-of-friction-in-finite-element-modelingsanjeev-n-k 68
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
760
40436degC recorded by thermo-couple during the experiment The resulted simulation temperature at micro=1 is
in close agreement with thermocouple reading with an error of 646 (which is of acceptable range) The
error could be because of considering tool as a discrete rigid body Considering micro=1 and Johnson-Cook
model the Figure 6 shows the capability of model in accurate simulation of FSW process
Table 1 Simulation temperature with respect to COF
COF (micro) Temperature (degC)
[Simulation]
Error ()
02 14086 -6128
04 18062 -5203
06 26054 -3345
08 36746 -858
1 43214 646
12 46057 1307
14 47023 1532
16 47515 1646
18 47748 1700
2 47834 1720
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 10 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
(micro=1) and Johnson-Cook material model in ABAQUSExplicit environment the proposed modelis capable of predicting right processing parameters
8112019 Effect of Coefficient of Friction in Finite Element Modeling_SANJEEV N K
httpslidepdfcomreaderfulleffect-of-coefficient-of-friction-in-finite-element-modelingsanjeev-n-k 78
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 WeldingmdashExperimental and
Numerical Studies Journal of Manufacturing Science and Engineering 125(1) pp 1384 Deplus i K (2014) ALUWELD Innovative welding of aluminium alloys ndash 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 244 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 andTechnology 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
8112019 Effect of Coefficient of Friction in Finite Element Modeling_SANJEEV N K
httpslidepdfcomreaderfulleffect-of-coefficient-of-friction-in-finite-element-modelingsanjeev-n-k 88
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
762
friction spot stir welding of aluminium 6060-T5 alloys Materials amp Design 31(6) pp 3023-3028
15
Mishra R S and Ma Z Y (2005) Friction stir welding and processing Materials Science and
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 maximumtemperature 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
welding Modelling and Simulation in Materials Science and Engineering 12(1) pp 143-157
20
Steen R V D (2007) Tyreroad friction modeling Literature survey Eindhoven University of
Technology Department of Mechanical Engineering Dynamics and Control group
21
Tutunchilar S Haghpanahi M Besharati Givi M K Asadi P and Bahemmat P (2012)
Simulation of material flow in friction stir processing of a cast AlndashSi alloy Materials amp Design 40
pp 415-426
22
Uyyuru R K and Kailas S V (2006) Numerical Analysis of Friction Stir Welding Process
Journal of Materials Engineering and Performance 15 pp 505-518
23 Zhang Z and Chen J T (2007) The simulation of material behaviors in friction stir welding
process by using rate-dependent constitutive model Journal of Materials Science 43(1) pp
222-232
8112019 Effect of Coefficient of Friction in Finite Element Modeling_SANJEEV N K
httpslidepdfcomreaderfulleffect-of-coefficient-of-friction-in-finite-element-modelingsanjeev-n-k 28
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
bull
Isotropic and anisotropic Coulomb friction model In its general form allows the COF to bedefined 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)
bull
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
8112019 Effect of Coefficient of Friction in Finite Element Modeling_SANJEEV N K
httpslidepdfcomreaderfulleffect-of-coefficient-of-friction-in-finite-element-modelingsanjeev-n-k 38
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
757
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
fric p micro τ = (1)
where fricτ is the friction shear stress micro 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 (ie 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 fric shear sτ τ σ = = (2)
Whereshear
τ is the flow shear stress calculated from the equivalent flow stresss
σ (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
8112019 Effect of Coefficient of Friction in Finite Element Modeling_SANJEEV N K
httpslidepdfcomreaderfulleffect-of-coefficient-of-friction-in-finite-element-modelingsanjeev-n-k 48
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
758
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 (micro) 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 04 05 and 06 under 100 mmmin transverse
speed and 900 rpm rotational speed According to investigations made by Kumar et al (2009) the COFand temperatures do have a synergic influence on each other The COF in FSW condition was found to be
as high as 12 to 14 in temperature range of 400-450degC Therefore simulations were performed by varying
the COF values from 01-20 to see the effects on results and to choose the right value
3 FE modeling details
FE model is developed in the commercial code ABAQUSExplicit using the Coupled Eulerian-Lagrangian
Formulation the Johnson-Cook material law and Coulombrsquos 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 mmmin Dwell Time of 10 sec Welding speed of 60
mmmin Plunge depth is 02 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 1 micro lt
resulted in unrealistic prediction of results Also considering 12 micro gt lead to over softening of material
8112019 Effect of Coefficient of Friction in Finite Element Modeling_SANJEEV N K
httpslidepdfcomreaderfulleffect-of-coefficient-of-friction-in-finite-element-modelingsanjeev-n-k 58
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 (micro) on void size (Top view) (a) micro = 02 (b) micro = 04 (c) micro = 06
(d) micro = 08 (e) micro = 1
Figure 5 Effect of high COF (Top view) (a) micro = 14 (b) micro = 16
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 micro=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
8112019 Effect of Coefficient of Friction in Finite Element Modeling_SANJEEV N K
httpslidepdfcomreaderfulleffect-of-coefficient-of-friction-in-finite-element-modelingsanjeev-n-k 68
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
760
40436degC recorded by thermo-couple during the experiment The resulted simulation temperature at micro=1 is
in close agreement with thermocouple reading with an error of 646 (which is of acceptable range) The
error could be because of considering tool as a discrete rigid body Considering micro=1 and Johnson-Cook
model the Figure 6 shows the capability of model in accurate simulation of FSW process
Table 1 Simulation temperature with respect to COF
COF (micro) Temperature (degC)
[Simulation]
Error ()
02 14086 -6128
04 18062 -5203
06 26054 -3345
08 36746 -858
1 43214 646
12 46057 1307
14 47023 1532
16 47515 1646
18 47748 1700
2 47834 1720
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 10 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
(micro=1) and Johnson-Cook material model in ABAQUSExplicit environment the proposed modelis capable of predicting right processing parameters
8112019 Effect of Coefficient of Friction in Finite Element Modeling_SANJEEV N K
httpslidepdfcomreaderfulleffect-of-coefficient-of-friction-in-finite-element-modelingsanjeev-n-k 78
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 WeldingmdashExperimental and
Numerical Studies Journal of Manufacturing Science and Engineering 125(1) pp 1384 Deplus i K (2014) ALUWELD Innovative welding of aluminium alloys ndash 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 244 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 andTechnology 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
8112019 Effect of Coefficient of Friction in Finite Element Modeling_SANJEEV N K
httpslidepdfcomreaderfulleffect-of-coefficient-of-friction-in-finite-element-modelingsanjeev-n-k 88
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
762
friction spot stir welding of aluminium 6060-T5 alloys Materials amp Design 31(6) pp 3023-3028
15
Mishra R S and Ma Z Y (2005) Friction stir welding and processing Materials Science and
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 maximumtemperature 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
welding Modelling and Simulation in Materials Science and Engineering 12(1) pp 143-157
20
Steen R V D (2007) Tyreroad friction modeling Literature survey Eindhoven University of
Technology Department of Mechanical Engineering Dynamics and Control group
21
Tutunchilar S Haghpanahi M Besharati Givi M K Asadi P and Bahemmat P (2012)
Simulation of material flow in friction stir processing of a cast AlndashSi alloy Materials amp Design 40
pp 415-426
22
Uyyuru R K and Kailas S V (2006) Numerical Analysis of Friction Stir Welding Process
Journal of Materials Engineering and Performance 15 pp 505-518
23 Zhang Z and Chen J T (2007) The simulation of material behaviors in friction stir welding
process by using rate-dependent constitutive model Journal of Materials Science 43(1) pp
222-232
8112019 Effect of Coefficient of Friction in Finite Element Modeling_SANJEEV N K
httpslidepdfcomreaderfulleffect-of-coefficient-of-friction-in-finite-element-modelingsanjeev-n-k 38
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
757
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
fric p micro τ = (1)
where fricτ is the friction shear stress micro 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 (ie 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 fric shear sτ τ σ = = (2)
Whereshear
τ is the flow shear stress calculated from the equivalent flow stresss
σ (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
8112019 Effect of Coefficient of Friction in Finite Element Modeling_SANJEEV N K
httpslidepdfcomreaderfulleffect-of-coefficient-of-friction-in-finite-element-modelingsanjeev-n-k 48
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
758
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 (micro) 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 04 05 and 06 under 100 mmmin transverse
speed and 900 rpm rotational speed According to investigations made by Kumar et al (2009) the COFand temperatures do have a synergic influence on each other The COF in FSW condition was found to be
as high as 12 to 14 in temperature range of 400-450degC Therefore simulations were performed by varying
the COF values from 01-20 to see the effects on results and to choose the right value
3 FE modeling details
FE model is developed in the commercial code ABAQUSExplicit using the Coupled Eulerian-Lagrangian
Formulation the Johnson-Cook material law and Coulombrsquos 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 mmmin Dwell Time of 10 sec Welding speed of 60
mmmin Plunge depth is 02 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 1 micro lt
resulted in unrealistic prediction of results Also considering 12 micro gt lead to over softening of material
8112019 Effect of Coefficient of Friction in Finite Element Modeling_SANJEEV N K
httpslidepdfcomreaderfulleffect-of-coefficient-of-friction-in-finite-element-modelingsanjeev-n-k 58
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 (micro) on void size (Top view) (a) micro = 02 (b) micro = 04 (c) micro = 06
(d) micro = 08 (e) micro = 1
Figure 5 Effect of high COF (Top view) (a) micro = 14 (b) micro = 16
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 micro=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
8112019 Effect of Coefficient of Friction in Finite Element Modeling_SANJEEV N K
httpslidepdfcomreaderfulleffect-of-coefficient-of-friction-in-finite-element-modelingsanjeev-n-k 68
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
760
40436degC recorded by thermo-couple during the experiment The resulted simulation temperature at micro=1 is
in close agreement with thermocouple reading with an error of 646 (which is of acceptable range) The
error could be because of considering tool as a discrete rigid body Considering micro=1 and Johnson-Cook
model the Figure 6 shows the capability of model in accurate simulation of FSW process
Table 1 Simulation temperature with respect to COF
COF (micro) Temperature (degC)
[Simulation]
Error ()
02 14086 -6128
04 18062 -5203
06 26054 -3345
08 36746 -858
1 43214 646
12 46057 1307
14 47023 1532
16 47515 1646
18 47748 1700
2 47834 1720
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 10 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
(micro=1) and Johnson-Cook material model in ABAQUSExplicit environment the proposed modelis capable of predicting right processing parameters
8112019 Effect of Coefficient of Friction in Finite Element Modeling_SANJEEV N K
httpslidepdfcomreaderfulleffect-of-coefficient-of-friction-in-finite-element-modelingsanjeev-n-k 78
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 WeldingmdashExperimental and
Numerical Studies Journal of Manufacturing Science and Engineering 125(1) pp 1384 Deplus i K (2014) ALUWELD Innovative welding of aluminium alloys ndash 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 244 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 andTechnology 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
8112019 Effect of Coefficient of Friction in Finite Element Modeling_SANJEEV N K
httpslidepdfcomreaderfulleffect-of-coefficient-of-friction-in-finite-element-modelingsanjeev-n-k 88
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
762
friction spot stir welding of aluminium 6060-T5 alloys Materials amp Design 31(6) pp 3023-3028
15
Mishra R S and Ma Z Y (2005) Friction stir welding and processing Materials Science and
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 maximumtemperature 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
welding Modelling and Simulation in Materials Science and Engineering 12(1) pp 143-157
20
Steen R V D (2007) Tyreroad friction modeling Literature survey Eindhoven University of
Technology Department of Mechanical Engineering Dynamics and Control group
21
Tutunchilar S Haghpanahi M Besharati Givi M K Asadi P and Bahemmat P (2012)
Simulation of material flow in friction stir processing of a cast AlndashSi alloy Materials amp Design 40
pp 415-426
22
Uyyuru R K and Kailas S V (2006) Numerical Analysis of Friction Stir Welding Process
Journal of Materials Engineering and Performance 15 pp 505-518
23 Zhang Z and Chen J T (2007) The simulation of material behaviors in friction stir welding
process by using rate-dependent constitutive model Journal of Materials Science 43(1) pp
222-232
8112019 Effect of Coefficient of Friction in Finite Element Modeling_SANJEEV N K
httpslidepdfcomreaderfulleffect-of-coefficient-of-friction-in-finite-element-modelingsanjeev-n-k 48
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
758
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 (micro) 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 04 05 and 06 under 100 mmmin transverse
speed and 900 rpm rotational speed According to investigations made by Kumar et al (2009) the COFand temperatures do have a synergic influence on each other The COF in FSW condition was found to be
as high as 12 to 14 in temperature range of 400-450degC Therefore simulations were performed by varying
the COF values from 01-20 to see the effects on results and to choose the right value
3 FE modeling details
FE model is developed in the commercial code ABAQUSExplicit using the Coupled Eulerian-Lagrangian
Formulation the Johnson-Cook material law and Coulombrsquos 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 mmmin Dwell Time of 10 sec Welding speed of 60
mmmin Plunge depth is 02 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 1 micro lt
resulted in unrealistic prediction of results Also considering 12 micro gt lead to over softening of material
8112019 Effect of Coefficient of Friction in Finite Element Modeling_SANJEEV N K
httpslidepdfcomreaderfulleffect-of-coefficient-of-friction-in-finite-element-modelingsanjeev-n-k 58
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 (micro) on void size (Top view) (a) micro = 02 (b) micro = 04 (c) micro = 06
(d) micro = 08 (e) micro = 1
Figure 5 Effect of high COF (Top view) (a) micro = 14 (b) micro = 16
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 micro=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
8112019 Effect of Coefficient of Friction in Finite Element Modeling_SANJEEV N K
httpslidepdfcomreaderfulleffect-of-coefficient-of-friction-in-finite-element-modelingsanjeev-n-k 68
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
760
40436degC recorded by thermo-couple during the experiment The resulted simulation temperature at micro=1 is
in close agreement with thermocouple reading with an error of 646 (which is of acceptable range) The
error could be because of considering tool as a discrete rigid body Considering micro=1 and Johnson-Cook
model the Figure 6 shows the capability of model in accurate simulation of FSW process
Table 1 Simulation temperature with respect to COF
COF (micro) Temperature (degC)
[Simulation]
Error ()
02 14086 -6128
04 18062 -5203
06 26054 -3345
08 36746 -858
1 43214 646
12 46057 1307
14 47023 1532
16 47515 1646
18 47748 1700
2 47834 1720
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 10 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
(micro=1) and Johnson-Cook material model in ABAQUSExplicit environment the proposed modelis capable of predicting right processing parameters
8112019 Effect of Coefficient of Friction in Finite Element Modeling_SANJEEV N K
httpslidepdfcomreaderfulleffect-of-coefficient-of-friction-in-finite-element-modelingsanjeev-n-k 78
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 WeldingmdashExperimental and
Numerical Studies Journal of Manufacturing Science and Engineering 125(1) pp 1384 Deplus i K (2014) ALUWELD Innovative welding of aluminium alloys ndash 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 244 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 andTechnology 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
8112019 Effect of Coefficient of Friction in Finite Element Modeling_SANJEEV N K
httpslidepdfcomreaderfulleffect-of-coefficient-of-friction-in-finite-element-modelingsanjeev-n-k 88
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
762
friction spot stir welding of aluminium 6060-T5 alloys Materials amp Design 31(6) pp 3023-3028
15
Mishra R S and Ma Z Y (2005) Friction stir welding and processing Materials Science and
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 maximumtemperature 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
welding Modelling and Simulation in Materials Science and Engineering 12(1) pp 143-157
20
Steen R V D (2007) Tyreroad friction modeling Literature survey Eindhoven University of
Technology Department of Mechanical Engineering Dynamics and Control group
21
Tutunchilar S Haghpanahi M Besharati Givi M K Asadi P and Bahemmat P (2012)
Simulation of material flow in friction stir processing of a cast AlndashSi alloy Materials amp Design 40
pp 415-426
22
Uyyuru R K and Kailas S V (2006) Numerical Analysis of Friction Stir Welding Process
Journal of Materials Engineering and Performance 15 pp 505-518
23 Zhang Z and Chen J T (2007) The simulation of material behaviors in friction stir welding
process by using rate-dependent constitutive model Journal of Materials Science 43(1) pp
222-232
8112019 Effect of Coefficient of Friction in Finite Element Modeling_SANJEEV N K
httpslidepdfcomreaderfulleffect-of-coefficient-of-friction-in-finite-element-modelingsanjeev-n-k 58
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 (micro) on void size (Top view) (a) micro = 02 (b) micro = 04 (c) micro = 06
(d) micro = 08 (e) micro = 1
Figure 5 Effect of high COF (Top view) (a) micro = 14 (b) micro = 16
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 micro=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
8112019 Effect of Coefficient of Friction in Finite Element Modeling_SANJEEV N K
httpslidepdfcomreaderfulleffect-of-coefficient-of-friction-in-finite-element-modelingsanjeev-n-k 68
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
760
40436degC recorded by thermo-couple during the experiment The resulted simulation temperature at micro=1 is
in close agreement with thermocouple reading with an error of 646 (which is of acceptable range) The
error could be because of considering tool as a discrete rigid body Considering micro=1 and Johnson-Cook
model the Figure 6 shows the capability of model in accurate simulation of FSW process
Table 1 Simulation temperature with respect to COF
COF (micro) Temperature (degC)
[Simulation]
Error ()
02 14086 -6128
04 18062 -5203
06 26054 -3345
08 36746 -858
1 43214 646
12 46057 1307
14 47023 1532
16 47515 1646
18 47748 1700
2 47834 1720
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 10 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
(micro=1) and Johnson-Cook material model in ABAQUSExplicit environment the proposed modelis capable of predicting right processing parameters
8112019 Effect of Coefficient of Friction in Finite Element Modeling_SANJEEV N K
httpslidepdfcomreaderfulleffect-of-coefficient-of-friction-in-finite-element-modelingsanjeev-n-k 78
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 WeldingmdashExperimental and
Numerical Studies Journal of Manufacturing Science and Engineering 125(1) pp 1384 Deplus i K (2014) ALUWELD Innovative welding of aluminium alloys ndash 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 244 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 andTechnology 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
8112019 Effect of Coefficient of Friction in Finite Element Modeling_SANJEEV N K
httpslidepdfcomreaderfulleffect-of-coefficient-of-friction-in-finite-element-modelingsanjeev-n-k 88
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
762
friction spot stir welding of aluminium 6060-T5 alloys Materials amp Design 31(6) pp 3023-3028
15
Mishra R S and Ma Z Y (2005) Friction stir welding and processing Materials Science and
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 maximumtemperature 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
welding Modelling and Simulation in Materials Science and Engineering 12(1) pp 143-157
20
Steen R V D (2007) Tyreroad friction modeling Literature survey Eindhoven University of
Technology Department of Mechanical Engineering Dynamics and Control group
21
Tutunchilar S Haghpanahi M Besharati Givi M K Asadi P and Bahemmat P (2012)
Simulation of material flow in friction stir processing of a cast AlndashSi alloy Materials amp Design 40
pp 415-426
22
Uyyuru R K and Kailas S V (2006) Numerical Analysis of Friction Stir Welding Process
Journal of Materials Engineering and Performance 15 pp 505-518
23 Zhang Z and Chen J T (2007) The simulation of material behaviors in friction stir welding
process by using rate-dependent constitutive model Journal of Materials Science 43(1) pp
222-232
8112019 Effect of Coefficient of Friction in Finite Element Modeling_SANJEEV N K
httpslidepdfcomreaderfulleffect-of-coefficient-of-friction-in-finite-element-modelingsanjeev-n-k 68
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
760
40436degC recorded by thermo-couple during the experiment The resulted simulation temperature at micro=1 is
in close agreement with thermocouple reading with an error of 646 (which is of acceptable range) The
error could be because of considering tool as a discrete rigid body Considering micro=1 and Johnson-Cook
model the Figure 6 shows the capability of model in accurate simulation of FSW process
Table 1 Simulation temperature with respect to COF
COF (micro) Temperature (degC)
[Simulation]
Error ()
02 14086 -6128
04 18062 -5203
06 26054 -3345
08 36746 -858
1 43214 646
12 46057 1307
14 47023 1532
16 47515 1646
18 47748 1700
2 47834 1720
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 10 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
(micro=1) and Johnson-Cook material model in ABAQUSExplicit environment the proposed modelis capable of predicting right processing parameters
8112019 Effect of Coefficient of Friction in Finite Element Modeling_SANJEEV N K
httpslidepdfcomreaderfulleffect-of-coefficient-of-friction-in-finite-element-modelingsanjeev-n-k 78
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 WeldingmdashExperimental and
Numerical Studies Journal of Manufacturing Science and Engineering 125(1) pp 1384 Deplus i K (2014) ALUWELD Innovative welding of aluminium alloys ndash 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 244 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 andTechnology 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
8112019 Effect of Coefficient of Friction in Finite Element Modeling_SANJEEV N K
httpslidepdfcomreaderfulleffect-of-coefficient-of-friction-in-finite-element-modelingsanjeev-n-k 88
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
762
friction spot stir welding of aluminium 6060-T5 alloys Materials amp Design 31(6) pp 3023-3028
15
Mishra R S and Ma Z Y (2005) Friction stir welding and processing Materials Science and
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 maximumtemperature 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
welding Modelling and Simulation in Materials Science and Engineering 12(1) pp 143-157
20
Steen R V D (2007) Tyreroad friction modeling Literature survey Eindhoven University of
Technology Department of Mechanical Engineering Dynamics and Control group
21
Tutunchilar S Haghpanahi M Besharati Givi M K Asadi P and Bahemmat P (2012)
Simulation of material flow in friction stir processing of a cast AlndashSi alloy Materials amp Design 40
pp 415-426
22
Uyyuru R K and Kailas S V (2006) Numerical Analysis of Friction Stir Welding Process
Journal of Materials Engineering and Performance 15 pp 505-518
23 Zhang Z and Chen J T (2007) The simulation of material behaviors in friction stir welding
process by using rate-dependent constitutive model Journal of Materials Science 43(1) pp
222-232
8112019 Effect of Coefficient of Friction in Finite Element Modeling_SANJEEV N K
httpslidepdfcomreaderfulleffect-of-coefficient-of-friction-in-finite-element-modelingsanjeev-n-k 78
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 WeldingmdashExperimental and
Numerical Studies Journal of Manufacturing Science and Engineering 125(1) pp 1384 Deplus i K (2014) ALUWELD Innovative welding of aluminium alloys ndash 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 244 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 andTechnology 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
8112019 Effect of Coefficient of Friction in Finite Element Modeling_SANJEEV N K
httpslidepdfcomreaderfulleffect-of-coefficient-of-friction-in-finite-element-modelingsanjeev-n-k 88
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
762
friction spot stir welding of aluminium 6060-T5 alloys Materials amp Design 31(6) pp 3023-3028
15
Mishra R S and Ma Z Y (2005) Friction stir welding and processing Materials Science and
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 maximumtemperature 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
welding Modelling and Simulation in Materials Science and Engineering 12(1) pp 143-157
20
Steen R V D (2007) Tyreroad friction modeling Literature survey Eindhoven University of
Technology Department of Mechanical Engineering Dynamics and Control group
21
Tutunchilar S Haghpanahi M Besharati Givi M K Asadi P and Bahemmat P (2012)
Simulation of material flow in friction stir processing of a cast AlndashSi alloy Materials amp Design 40
pp 415-426
22
Uyyuru R K and Kailas S V (2006) Numerical Analysis of Friction Stir Welding Process
Journal of Materials Engineering and Performance 15 pp 505-518
23 Zhang Z and Chen J T (2007) The simulation of material behaviors in friction stir welding
process by using rate-dependent constitutive model Journal of Materials Science 43(1) pp
222-232
8112019 Effect of Coefficient of Friction in Finite Element Modeling_SANJEEV N K
httpslidepdfcomreaderfulleffect-of-coefficient-of-friction-in-finite-element-modelingsanjeev-n-k 88
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
762
friction spot stir welding of aluminium 6060-T5 alloys Materials amp Design 31(6) pp 3023-3028
15
Mishra R S and Ma Z Y (2005) Friction stir welding and processing Materials Science and
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 maximumtemperature 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
welding Modelling and Simulation in Materials Science and Engineering 12(1) pp 143-157
20
Steen R V D (2007) Tyreroad friction modeling Literature survey Eindhoven University of
Technology Department of Mechanical Engineering Dynamics and Control group
21
Tutunchilar S Haghpanahi M Besharati Givi M K Asadi P and Bahemmat P (2012)
Simulation of material flow in friction stir processing of a cast AlndashSi alloy Materials amp Design 40
pp 415-426
22
Uyyuru R K and Kailas S V (2006) Numerical Analysis of Friction Stir Welding Process
Journal of Materials Engineering and Performance 15 pp 505-518
23 Zhang Z and Chen J T (2007) The simulation of material behaviors in friction stir welding
process by using rate-dependent constitutive model Journal of Materials Science 43(1) pp
222-232
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