effect of coefficient of friction in finite element modeling_sanjeev n k

8112019 Effect of Coefficient of Friction in Finite Element Modeling_SANJEEV N K

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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

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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)



Effect of Coefficient of Friction in Finite Element Modeling of Friction Stir Welding and its Importance in


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





Sanjeev N K et al


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





Sanjeev N K et al


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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





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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





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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





Sanjeev N K et al


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





Sanjeev N K et al


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





Sanjeev N K et al


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





Sanjeev N K et al


757















follows


Whereshear


σ (Li et al 2012)













Sanjeev N K et al


758

































Sanjeev N K et al


759













Sanjeev N K et al


760







[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


5 Conclusions




(2)







Sanjeev N K et al


761

Acknowledgements



and encouragement

6 References



213(8) pp 1433-1439

2




3




5





6




7



206-215

8



9



438-445



11




12




13









Sanjeev N K et al


762


15




17





68(3-4) pp 175-178

19



20



21



pp 415-426

22





222-232





Sanjeev N K et al


757















follows


Whereshear


σ (Li et al 2012)













Sanjeev N K et al


758

































Sanjeev N K et al


759













Sanjeev N K et al


760







[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


5 Conclusions




(2)







Sanjeev N K et al


761

Acknowledgements



and encouragement

6 References



213(8) pp 1433-1439

2




3




5





6




7



206-215

8



9



438-445



11




12




13









Sanjeev N K et al


762


15




17





68(3-4) pp 175-178

19



20



21



pp 415-426

22





222-232





Sanjeev N K et al


758

































Sanjeev N K et al


759













Sanjeev N K et al


760







[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


5 Conclusions




(2)







Sanjeev N K et al


761

Acknowledgements



and encouragement

6 References



213(8) pp 1433-1439

2




3




5





6




7



206-215

8



9



438-445



11




12




13









Sanjeev N K et al


762


15




17





68(3-4) pp 175-178

19



20



21



pp 415-426

22





222-232





Sanjeev N K et al


759













Sanjeev N K et al


760







[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


5 Conclusions




(2)







Sanjeev N K et al


761

Acknowledgements



and encouragement

6 References



213(8) pp 1433-1439

2




3




5





6




7



206-215

8



9



438-445



11




12




13









Sanjeev N K et al


762


15




17





68(3-4) pp 175-178

19



20



21



pp 415-426

22





222-232





Sanjeev N K et al


760







[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


5 Conclusions




(2)







Sanjeev N K et al


761

Acknowledgements



and encouragement

6 References



213(8) pp 1433-1439

2




3




5





6




7



206-215

8



9



438-445



11




12




13









Sanjeev N K et al


762


15




17





68(3-4) pp 175-178

19



20



21



pp 415-426

22





222-232





Sanjeev N K et al


761

Acknowledgements



and encouragement

6 References



213(8) pp 1433-1439

2




3




5





6




7



206-215

8



9



438-445



11




12




13









Sanjeev N K et al


762


15




17





68(3-4) pp 175-178

19



20



21



pp 415-426

22





222-232





Sanjeev N K et al


762


15




17





68(3-4) pp 175-178

19



20



21



pp 415-426

22





222-232

effect of coefficient of friction in finite element modeling_sanjeev n k

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