a study on material flow pattern in friction stir welding using

Original Article

Proc IMechE Part B:J Engineering Manufacture227(10) 1453–1466� IMechE 2013Reprints and permissions:sagepub.co.uk/journalsPermissions.navDOI: 10.1177/0954405413485952pib.sagepub.com

A study on material flow pattern infriction stir welding using finiteelement method

Hamed Pashazadeh, Abolfazl Masoumi and Jamal Teimournezhad

AbstractIn this article, numerical modelling of friction stir welding of copper plates is presented. The aim of this study is to imple-ment DEFORM-3D for developing the numerical simulation. Material flow patterns are extracted using point trackingmethod, and mechanical/metallurgical properties of workpiece are analysed. Simulation results suggest that material par-ticles in front of the tool pin tend to pass and settle behind the pin from the retreating side. Based on the results, a newclassification of distinctive zones in the stirred zone is presented. The stir zone shape in friction stir welding is dividedinto five distinctive zones. In friction stir welding of copper metals, the stir zone does not lean completely towards anysides of the welding line, which was found to compare favourably with experimental observations.

KeywordsFinite element modelling, friction stir welding, material flow pattern, stir zone, Zener–Hollomon parameter

Date received: 4 December 2012; accepted: 18 March 2013

Introduction

Welding of copper is often difficult by conventionalfusion welding techniques due to high thermal diffusiv-ity, high melting point and good thermal conductivityof copper, which is 10–100 times higher than that ofsteels and other alloys. Therefore, higher heat input isrequired for welding of copper compared to steel oraluminium. In friction stir welding (FSW), parts aremated together, rigidly fixed and joined in solid stateby forcing a rotating tool into the joint and traversingthat tool along the joint. This process creates weld withproperties comparable to those of the base metal and inmost cases are superior to properties that are achievedwith traditional fusion welding techniques. FSW of alu-minium alloys and steel has been reported in manystudies, but few studies have been done for the weldingof copper and its alloys.

The Swedish Nuclear Fuel and Waste ManagementCompany (SKB) is responsible for managing and dis-posing all radioactive waste from Swedish nuclearpower plants in such a way to secure maximum safetyfor human beings and the environment. The coppercanisters are placed in crystalline basement rock at adepth of about 500 m, embedded in bentonite clay. Thecanisters are nearly 5 m long and over 1 m in diameter.They weigh between 25 and 27 ton when filled with

spent nuclear fuel. The outer casing is a 50-mm-thicklayer of copper to protect against corrosion. The canis-ter is designed to withstand corrosion and any mechan-ical forces caused by movements in the rock,earthquakes and future ice ages. In 1997, SKB decidedto investigate the potential of FSW on 50-mm-thickcopper. The development program showed that 50-mm-thick copper plates and 50-mm-thick copper ringscut from tubes could be joined with FSW, and a weld-ing tool was developed that could last a full weld cycle.However, during longer weld cycles, the developedwelding procedure with constant input parameterscould not keep the process within its process window.1

When it comes to copper and its alloys, only oneindustrial FSW application is documented. HitachiCable Ltd and Hitachi Copper Products Ltd appliedFSW to water-cooled copper backing plates in Japandue to the low distortion and excellent mechanical

School of Mechanical Engineering, College of Engineering, University of

Tehran, Tehran, Iran

Corresponding author:

Hamed Pashazadeh, School of Mechanical Engineering, College of

Engineering, University of Tehran, North Kargar at Jalal-Exp Way, Tehran

5166816354, Iran.

Email: [email protected]; [email protected]

at PENNSYLVANIA STATE UNIV on May 10, 2016pib.sagepub.comDownloaded from

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properties from the welding process. Grooves aremachined in up to 70-mm-thick copper plates, andthese water channels are covered with copper sheet thatare friction stir welded to the plate.2

Most problems governed by differential equationscan be solved by approximating the problem with anumerical method and formulating a solution based onthat method. Simplistically, numerical modelling is thedivision of a geometrical domain into a finite numberof nodal points and elemental volumes, the approxima-tion of the governing boundary physics affecting eachnodal point and its neighbourhood points and the solu-tion of the system of equations resulting from thisapproximation. The FSW process incorporates a chal-lenging set of physical phenomena. These phenomenainclude very large non-linear material deformations,highly temperature-dependent material properties andthermal heating from coupled frictional and mechani-cal shear deformation. Therefore, a careful study ofnumerical modelling approaches must be conducted toproperly select the appropriate method of analysis.Some researchers made efforts to develop numericalcodes for FSW process.

Previous FSW researchers have applied variouscombinations of the finite element, finite difference andfinite volume approaches to model the FSW process.These approaches have been implemented inLagrangian, Eulerian and arbitrary Lagrangian–Eulerian (ALE) formulation, each with strengths andweaknesses. Several researchers developed the processwith a fully three-dimensional (3D) domain, while oth-ers have elected focusing on a two-dimensional simplifi-cation of the geometry. Each of these modellingattempts incorporates simple assumptions for the weldmaterial, the frictional contact interface and the geome-try. Therefore, the principal motivation for thisresearch was to capture the FSW process as accuratelyas possible by reducing the number of simple assump-tions utilized in the modelling process.

Bendzsak et al.3 modelled the FSW process in threedimensions; however, they assumed that the material tobe a fluid with a viscosity equal to that of the materialat the eutectic temperature. This viscosity was experi-mentally determined by equating input spindle torquethrough several experimental tests. Ulysee,4 similar tothe Bendzsak model, utilized a fluid material represen-tation in the 3D FSW model. Each of these approachesattempted to tackle the fundamental challenge of FSWmodelling: the 3D nature of the process. However,assumptions were implemented in each of these models,such as fluid material models, and frictional boundaryassumptions left room for improvement.

Several authors have modelled the tool as a non-mechanical moving heat source in an effort to removethe thermo-mechanical and weld material modellingchallenges. These authors tended to focus on capturingresidual stresses and exploited the weld line as a symme-try boundary. Khandkar and Kahn5 assumed that 98%

of the heat generation takes place at the shoulder–weldmaterial interface and modelled the tool as a movingheat source. The study of Khandkar et al.6 is anotherexample of this symmetric weld-line approach, whichmodels the FSW process with a non-mechanical movingheat source. All these researchers focused their effortson non-mechanical models, seeking a fundamentalunderstanding of the microstructure and the accompa-nying post-weld residual stresses. The removal of thethermo-mechanical effects of the FSW tooling doeseffectively remove the high material deformation chal-lenge, which exists in modelling of the FSW process,but in doing so, the analyst must sacrifice the insightone would gain with a fully thermo-mechanical numeri-cal model.

The reduction of the FSW problem to a two-dimensional plane has allowed the industry to funda-mentally understand the FSW process. For example,Seidel and Reynolds7 modelled a two-dimensional slice,perpendicular to the tool, far below the shoulder of theFSW tool. Although these models effectively study theplanar flow of the material, they lack the ability to cap-ture the 3D nature of the friction stir welded material.

Fully transient models of the FSW process are few.The challenge of these studies is capturing the weld for-mation and the weld process, and the extraction is a potof gold for the industry. Approximations of the fric-tional boundary, the material flow properties and theheat flow characteristics make these models difficult toproduce. Song and Kovacevic8 also modelled the transi-ent FSW process in three dimensions, assuming the heatgeneration input equal to experimentally determinedvalues. Assumptions utilized in this model effectivelyreduce the complexity of the problem and the accuracyof the solution.

Frigaard et al.9 modelled the FSW process with thepurpose of examining the resulting microstructure.Heurtier et al.10 focused on the optimization of thefinal microstructure in the FSW joint. We reviewed theresults of each of these studies to fundamentally under-stand the challenges of FSW modelling.

Recently, Tutunchilar et al.11 developed models toinvestigate material flow mechanism using the pointtracking method, and their results showed that materialon the advancing side (AS) experiences more plasticstrain than that of the retreating side (RS).

Many studies have been done by researchers in theinvestigation of FSW of aluminium alloys and steels.However, the studies of FSW on copper are few, and sofar, no simulation was performed for FSW of copper.Therefore, the purpose of this study was to investigatecopper welding by modelling approach. For this, a 3DLagrangian thermo-mechanical coupled incrementalfinite element simulation of the FSW was developed.Material flow patterns were extracted using the pointtracking capability of software. The stir zone shape pre-dicted by simulation corresponds with macrostructuralphotography.

1454 Proc IMechE Part B: J Engineering Manufacture 227(10)



Governing equations

First thermal model is used to successfully predicttrends in temperature history and thermal profiles. Inthe second step of the analysis, the thermal historiespredicted by the thermal model is used as an input fora mechanical model that ignores all other forces apartfrom those arising out of thermal expansion. In the cur-rent model, however, no mechanical forces are consid-ered, and only the forces arising out of the volumetricthermal expansion are taken into account. As a result,it is only the thermal strain increment that contributesto the residual stresses. This thermal stress, however,can constitute both elastic and plastic components.Since the current mechanical model deals only withresidual thermal stresses, the only forces consideredwere those caused by the thermal expansion of theworkpiece material plus the downward force exerted bythe tool shoulder.

Mechanical model

Neglecting inertia and body forces, the equilibriumequations in a volume V of material with a boundary∂V may be written as follows12

rs =0 ð1Þ

where s is the stress tensor. Tractions C0i may be pre-

scribed on a portion of boundary Vt, while velocitycomponents v0i may be specified on the remaining sur-face Vu

snð Þ � ei =C0i on Vci, i=1, 2, . . . ð2Þ

v � ei = v0i on Vvi, i=1, 2, . . . ð3Þ

where _0V= _0Vi + _0Vt, n denotes outward unit normalon the boundary _0V, ei the unit vectors of a 3D rectan-gular Cartesian coordinate system and v the velocityvector. The strain rate tensor relates with velocity fieldspatial derivatives by the following relation

E=rvc +rvð Þ

2ð4Þ

Continuity equation satisfies everywhere in V

r � v=0 ð5Þ

The deviatoric stress tensor F relates to strain ratetensor E by the following relation.

F=2mE, F=s � pI ð6Þ

m=se

3 _eeð7Þ

where m is the effective viscosity of the material, p thehydrostatic pressure, se stress and _ee strain rate. Theycan be written as

s2e =

3

2F � F ð8Þ

_e2e =3

2E � E ð9Þ

In this study, a rigid-viscoplastic material wasassumed; it is represented by an inverse sine–hyperbolicrelation as follows

se =1

asinh�1

Z

A

� �1=n" #

ð10Þ

Z= _e expQ

RT

� �ð11Þ

where a, Q, A and n are material constants; R the uni-versal constant and T the absolute temperature. a, Q, Aand n can be determined by compression tests.

Thermal model

Energy balance is expressed here as the conductive–con-vective, steady-state equation12

rcu � rT=r � krTð Þ+ _Q ð12Þ

where r is the density, c the specific heat, u the velocityvector, k the conductivity, T the temperature and _Q theinternal heat generation rate. The heat generation rateterm is expressed by product of the effective stress andeffective strain rate.

Fluxes q0 may be prescribed on a portion of bound-ary Vq, while the temperature T0 may be specified onthe remaining surface VT

krT � n= q0 on Vq ð13ÞT=T0 on VT ð14Þ_0V= _0Vq + _0VT ð15Þ

Numerical model details

FSW process was simulated with the ALE formulation.Also, we assumed the following: (1) the tool is rigid, (2)the friction factor is constant and (3) the thermal char-acteristics of the workpiece and tool are constant. Allthe free surfaces are surrounded by atmosphere at theambient temperature. The workpiece was fixed in thebottom surface from all directions. Furthermore, simu-lation was done based on the following assumptionsand conditions.

Workpiece and tool models

Two copper plates, 220 mm long, 75 mm wide and 4mm thickness, were butt-welded along the rolling direc-tion in a flat position. As shown in Figure 1, the smal-lest elements were placed in the tool pin, and whenaway from the pin mesh, the size becomes larger, andthe minimum mesh size is 0.5 mm. The sheets weremeshed with ;42,000 tetrahedral elements. The smal-lest mesh was considered to be 0.8 mm, which is located

Pashazadeh et al. 1455



under the tool shoulder, and by increasing the distancefrom this region, the size of the elements becomeslarger. To prevent element distortion, automatic localremeshing was taken into account for the workpieceelements.

Material properties and welding parameters

Flow stress of the pure copper at different strain ratesand temperatures was interpolated in logarithmic spaceof strain and strain rate and linear space of tempera-ture. The relationship between flow stress and strainfor material at temperatures of 500 �C, 800 �C and 900�C and strain rates of 0.001–100 s21 is illustrated inFigure 2.13 Workpiece, tool and backing plate thermalproperties were considered constant, and their valuesare specified in Table 1. Heat exchange between ambi-ent air (with the temperature of 20 �C) and free surfacesof the workpiece and tool was taken into account (seeTable 1). Simulation parameters (welding parameterssuch as rotational speed, traverse speed, tilt angle andplunge depth of shoulder) are given in Table 2.

Results and discussion

Temperature and strain distribution

In this section, temperature result of FSW process fromfinite element method (FEM) has been compared usingthe experimental data of Hwang et al.14 To maintainconsistency, the dimensions of the workpiece, materialproperties, welding conditions and boundary condi-tions used were the same as those used in the study byHwang et al.14 A comparison between measured tem-perature data of weld nugget from Hwang et al.’s study

Figure 1. Schematic illustration of tool.

Table 1. Thermal characteristics of workpiece, tool and backing plate.

Property Cu FSW tool (H13) Back plate

Heat capacity (N mm22�C21) 4.42 3.24 –Emissivity 0.64 0.7 –Conductivity (N s21�C21) 371 24.5 –Heat transfer coefficient between tool and billet (N mm21 s21�C21) 11 11 –Heat transfer coefficient between backing plate and billet (N mm21 s21�C21) 1 – 1Heat transfer coefficient between tool/workpiece and air (N mm21 s21�C21) 0.02 0.02 –

FSW: friction stir welding.

Table 2. Process parameters used in the simulation.

Tool rotational speed (r min21) 630, 700Tool traverse speed (mm min21) 40, 63Tilt angle 1.5Plunge depth (mm) 0.3Tool shoulder diameter (mm) 17.8Tool pin diameter (mm) 6.5Tool pin length (mm) 3.5




and the calculated results from FEM simulation isshown in Figure 3. These curves show thermal historiesof the point with 6 mm distance from welding line. Thecalculated temperatures are then verified using theexperimental data.

Figure 4 shows the temperature contours of weldwith different parameters. These counters were achievedat x = 30 mm. As seen in Figure 5, temperature distri-bution is not symmetric around the tool. Maximumtemperatures of welds 1 and 3 are almost the same, buttheir difference with maximum temperature of weld 2 isabout 35 �C.

Figure 6 illustrates the effective plastic strain con-tours. Effective strain distribution around welding line

Figure 2. Flow stress–strain curves of base metal under different conditions: (a) T=500 �C, (b) T= 800 �C and (c) T= 900 �C.13

0

100

200

300

400

500

600

0 20 40 60 80 100 120 140

Tem

pera

ture

(°C)

Time (s)

Numerical

Experimental14

Figure 3. Temperature history derived from simulation andexperiment14 at 6 mm from the welding line.




is non-symmetric. This non-homogeneity in the straindistribution is the cause of asymmetric material flow.

Microstructural investigation

In thermo-mechanical processes such as FSW/frictionstir processing (FSP), there is an effective connectionbetween the grain size and temperature, strain andstrain rate. According to the Zener–Hollomon para-meter (equations (10) and (11)), the variations in tem-perature and strain rate display reverse influence on thegrain size. In other words, an increase in strain rate ora decrease in temperature will increase Z value andsubsequently resulting in a finer microstructure.

The point tracking option of software was chosen toextract the variation of Z parameter according to thewelding time, as shown in Figure 7. Welding parametersare shown in Table 3. The three graphs in Figure 7 arecomposed of two main parts, namely, part A and partB, which are related to the stirring and forging phasesof FSW, respectively. Weld No. 2 has higher rotationalspeed than that of weld No. 1, which results in highertemperature and strain rate. Besides, according to theZener–Hollomon equation, the temperature variationshave a greater effect than the strain rate variations onZ. Therefore, the Z parameter of weld No. 1 is greater

Figure 4. Temperature distribution at different welding parameters: (a) v = 40 mm min21, w = 630 r min21; (b) v = 40 mm min21,w = 710 r min21 and (c) v = 63 mm min21, w = 710 r min21.

Figure 5. Temperature distribution around tool (v = 40 mmmin21, w = 630 r min21).




than that of weld No. 2. For weld No. 3, the tempera-ture was lower when compared with the other twowelds, and strain rate of the weld No. 3 is nearly equal

to the weld No. 2, which results in higher Z parameter.As previously mentioned, increase in the Z parameterleads to a finer microstructure. Microscopic images ofthe microstructure of three welds, as presented inFigure 8, correspond with obtained Z parameter, whichindicate that the increasing of the Z parameter resultsin grain size reduction.

Material flow behaviour

The material flow during FSW is complicated anddirectly influences the properties of friction stir weldedworkpiece. It is of vital importance to understand thedeformation process and basic physics of the materialflow for optimal tool design. To visualize the materialflow phenomenon, tracer particle set was defined alongthe welding line to track the material movement. Eighttracer particles, numbered 1–8, were used, as illustrated

Figure 6. Effective plastic strain distribution at different welding parameters.

Figure 7. Variation of the Zener–Hollomon parameter fordifferent welding conditions.




Figure 8. Micrographs of the base metal and the weld nuggets for three different parameters of welding, specified in Table 3.

Figure 9. Initial position of the particles on the welding line that has been selected for material flow pattern.

Table 3. Processing parameters for FSW.

FSW ID Rotational speed (r min21) Traverse speed (mm min2) Plunge depth (mm) Tilt angle (�)

No. 1 630 40 0.3 1.5No. 2 710 40 0.3 1.5No. 3 710 63 0.3 1.5

FSW: friction stir welding.




Figure 10. Continued.




in Figure 9. Points P1–P8 at their initial position arelocated on the weld centre line with 0.5-mm incrementin depth from the top surface.

Figure 10 shows the material flow pattern on thecentre of weld. Figure 10(a)–(d) shows the position ofthose points as the time elapses. Figure 11 shows the

Figure 10. Material flow pattern on the centre line with tool advancing.AS: advancing side; RS: retreating side.

Figure 11. Final position of centre line points.

Figure 12. Initial position of the particles on the AS that has been selected for material flow pattern.




Figure 13. Continued.




final position of the particles. Particle 1 starts to movearound the pin with tool simultaneously towards RS.At initial stages of the process, it rotates in a zone withdiameter more than that of pin, due to high stress andstrain rate and severe deformation in the region exactlybelow the tool shoulder. However, as the process pro-ceeds, it moves finally to a zone with a size equal to thepin diameter behind the tool pin. This behaviour is

almost the same for particle 2, which was at firstexpelled from the region with size equal to the pin dia-meter, but finally, it resides in the same zone. It is inter-esting that these points reside finally behind the pin onthe welding line and not behind the AS, which wasreported in previous studies.11 In fact, these particlesenter the shoulder–workpiece interface, in a period oftime and then are pushed into the zone with a diameter

Figure 13. Material flow pattern on the AS with tool advancing.




equal to the pin diameter. The lower particles includingNo. 3–No. 8 showed partially the same flow behaviour;however, these particles always move near/inside thezone with a diameter equal to that of pin. These pointsreside behind the pin, near joint line, and form anasymmetric flow pattern with other points. The inter-esting point is point No. 6, which showed a completelyrandom flow manner. Also, this point is the only pointthat resides on the AS. The complicated material flowbehaviour in FSW process is the reason for this case.Another important observation is that the height of theparticles does not change considerably.

Material flow pattern on the AS is shown in Figures12 and 13(a)–(f). Figure 12 illustrates the initial posi-tion of eight particles in the AS with 0.5-mm incrementin depth from the top surface, and Figure 13(a)–(f)illustrates the position of the particles as the timeelapses. Motion of the particles near the surface (P1and P2) is mostly affected by tool shoulder and that of

lower particles is mainly affected by tool pin. In fact,the force generated by shoulder is the key factor formaterial flow pattern in the zones near the surface, andthe force generated by tool pin is the key factor formaterial flow pattern in the lower zones. Similar to thecentre line particle flow mechanism, the particles nearthe surface (P1 and P2) move swiftly with shoulder(especially P1), as shown in Figure 13(a)–(c). Thus,they rotate along with the shoulder, and as tool pro-ceeds, they speed down (Figure 13(d) and (e)) andfinally reside behind the pin on the RS. Their motion inz-direction is very negligible. The lower particles startto rotate slightly, and as the tool moves forwards, theirup-and-down motions occur. Behind the pin, theyrotate from RS towards AS and finally reside near thejoint line on the AS. The material flow mechanism onthe AS has some difference with that of the centre lineparticles. First, some upper particles (P1) finally residein a zone larger than the zone with size equal to the pin

Figure 14. Initial position of the particles on the RS that has been selected for material flow pattern.

Figure 15. Final position of the particles on the RS that has been selected for material flow pattern.




diameter. Second, they move upwards and downwards.Figures 14 and 15 show the initial and final positionsof the particles, which were selected from the RS. Allparticles finally reside on the RS. An important obser-vation from material flow mechanism on the centre,AS and RS is that all materials finally reside in a zonenear the welding line. This illustrates that in FSW ofcopper, the stirred zone does not lean towards any sidesof the welding line. This is in agreement with experi-mental macro photography of stirred zone in FSW ofcopper, which is illustrated in Figure 16, whereas it iscompletely different for Al alloys, in which the stirredzone leans towards the AS.11 Based on the materialflow mechanism characterized earlier, the stir zone inFSW can be classified into five distinctive zones, asshown in Table 4.

Conclusions

This study deals with numerical investigation on mate-rial flow pattern in FSW of a copper alloy. The mainhighlights are the following:

1. Temperature and strain distributions are not sym-metric around the welding line.

2. Increase in the Zener–Hollomon parameter leadsto a finer microstructure.

3. In FSW of copper, the stirred zone does not leantowards any sides of the welding line completely.This case is completely different for Al alloys.

4. Based on the material flow mechanism, the stirredzone in FSW can be classified into five distinctivezones.

Declaration of conflicting interests

The authors declare that there is no conflict of interest.

Funding

This research received no specific grant from any fund-ing agency in the public, commercial or not-for-profitsectors.

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Figure 16. Macrostructural photography of fiction stir weldedcopper.

Table 4. Distinctive zones of weld area.

Zone 1 Materials originally come from the front andedges of shoulder and behind the tool, movefrom RS towards AS. They seem to be in theform of thin layers

Zone 2 Materials first move outside the stir zone due totool forward motion and then after somerotation under shoulder move inside the stirzone (under surface and flow arm zonematerials)

Zone 3 Materials come from ahead of the pin, AS andRS. They rotate from RS towards AS and fill thecavity located behind the pin

Zone 4 These materials are originally from AS. Inside thestirred zone, they have random upward anddownward motion and stretch from RS to AS.These materials form the lowest part of thestirred zone

Zone 5 This zone completely contributes to TMAZ

AS: advancing side; RS: retreating side.




a study on material flow pattern in friction stir welding using

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