modeling weld process

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Maritime Engineering and Technology Guedes Soares et al. 2012 Taylor & Francis Group, London, ISBN 978-0-415-62146-5

Numerical investigations to study the effect of weld parameters on the

temperature-time history in steel plates

B.Q. Chen, M. Adak & C. Guedes SoaresCentre for Marine Technology and Engineering (CENTEC), Instituto Superior Tcnico,

Technical University of Lisbon, Portugal

ABSTRACT: Numericalinvestigations arecarried outto study theeffect of weldparameters on thetemperature-time history in a butt-joint weld steel plate. A mathematical model of transient thermal process in welding isestablishedto simulate the transient thermal analysis with moving heat sourcemodel (Gaussian function) by usingfinite element method. Results are compared to numerical and experimental results obtained from a previous

study. Parametric studies based on numerical results are carried out for different weld parameters includingwelding speed, plate thickness, heat input, heat source type and finite element mesh.

1 INTRODUCTION

1.1 Introduction to welding

Welding is a complex industrial process that oftenrequires several trials before it can be done right. Thewelding processes are carried out by skilled work-ers, but in the past few years automated machinesand robots are introduced in shipyards. To obtain the

expected productivity through mechanization, highprecision of parts to be assembled must be kept.Therefore in the shipbuilding industry dimensionalpredictability is important. In order to produce a high-quality product, the accuracy control should be keptthrough the whole assembly line. The concept of accu-racy control should be incorporated in the structuraldesign, so that the designer can produce a better designaccounting for the geometric inaccuracy.

Generally, welding can be defined as any process inwhich two or more pieces of metal are joined togetherby the application of heat, pressure, or a combination

of both. Most of the processes may be grouped into twomain categories. pressure welding, in which the weldis achieved by pressure; and heat welding, in whichthe weld is achieved by heat. Heat welding is the mostcommon welding used today.

During the welding process, a liquid weld poolis created through the interaction of an intense heatsource and the substrates being joined (see Figure 1).Melting on the front side of the weld pool eliminatesthe interface between the materials, while solidifi-cation on the back side of the weld pool fuses thesubstrates together to create a solid joined part. Sur-

rounding the fusionzone is a heat-affected zone, wherethe substrate is heated to temperatures up to the melt-ing point of the metal being joined. Solidification inthe fusion zone and solid-state phase transformationsin the heat-affected zone are responsible for dramatic

Figure 1. Illustration of a fusion weld.

changes in the microstructure and properties of thewelding joint.

1.2 Arc welding

Arc welding, which is heat-type welding, is one ofthe most important manufacturing operations for thejoining of structural elements for a wide range ofapplications, including guide way for ships, bridges,trains, building structures, automobiles, and nuclearreactors, to name a few. It requires a continuous supplyof either direct or alternating electric current, whichcreates an electric arc to generate enough heat to meltthe metal and form a weld.

The arc welding process is a remarkably com-plex operation involving extremely high temperatures,which produce severe distortions and high levels of

residual stresses. These extreme phenomena tend toreduce the strength of a structure, which becomesvulnerable to fracture, buckling, corrosion and othertype of failures. The most widely used arc weldingprocesses are shielded metal arc welding (SMAW),

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gas tungsten arc welding (GTAW), gas metal arcwelding (GMAW), and submerged metal arc welding(SMAW).

2 THEORY OF THE WELDING PROCESS

2.1 Heat transfer during welding process

Welding is a process with sharply local heating tohigh temperature and rapid cooling afterwards, dur-ing which the temperature highly depends on the timeand location, while the mechanical properties of thematerial varies with the temperature, and melting,phase changing and latent heat exist. To sum up, theweld induced temperature field analysis is a typicalnonlinear transient heat transfer issue.

During theweldingprocess, the temperaturesof dif-ferent parts of the weldment vary immensely due to thelocal heating. Consequently, heat transfer occurs bothinside the weldment and between the weldment and

surrounding.Heat transfer mechanisms can be grouped into three

broad categories.

1) Conduction. Regions with greater molecularkinetic energy will pass their thermal energy toregions with less molecular energy through directmolecular collisions, a process known as con-duction. In metals, a significant portion of thetransported thermal energy is also carried byconduction-band electrons.

2) Convection. When heat conducts into a static fluidit leads to a local volumetric expansion. As aresult of gravity-induced pressure gradients, theexpanded fluid parcel becomes buoyant and dis-places, thereby transporting heat by fluid motion(i.e. convection) in addition to conduction. Suchheat-induced fluid motion in initially static fluidsis known as free convection.

3) Radiation. All materials radiate thermal energy inamounts determined by their temperature, wherethe energy is carried by photons of light in theinfrared and visible portions of the electromag-netic spectrum. When temperatures are uniform,the radioactive flux between objects is in equi-

librium and no net thermal energy is exchanged.The balance is upset when temperatures are notuniform, and thermal energy is transported fromsurfaces of higher to surfaces of lower temperature.

Understanding of the theory of heat flow is essen-tial in order to study the welding process analytically,numerically or experimentally.

2.2 Development in prediction of welding

The problem of welding distortion during large steelfabrications leads to dimensional inaccuracies and

misalignments of structural members, which canresult in corrective tasks or reworkwhen tolerance lim-its are exceeded. This in turn, increases the cost of pro-duction and leads to delays. In fabrication and designindustries, for example, expenses for rework such as

straightening could cost millions of dollars. Therefore,the problems of distortion and residual stresses arealways of great concern in welding industry.

In order to deal with this problem, it is necessaryto predict the amount of distortion resulting from thewelding operations. One way to predict the distortionand shrinkage of steel welding is through numericalanalysis such as finite element analysis (FEA). Oncethe techniques to predict the distortion and shrink-age are identified, then the problems can be controlledaccordingly.

Within the welding procedures, there are many fac-tors such as welding process type, welding processparameters, welding sequence, preheat patterns, levelof constraint and joint details that contribute to thedistortion of the welded structure. Knowing whichparameters have an effect on the quality of the weldand which parameters give the most significant effecton the weld quality are the main issues in weldingindustry.

Welds are made at the junction of various piecesthat make up the weldment. The junctions of parts, orjoints, are defined as the location where two or moremembers are to be joined. Parts being joined to pro-duce the weldment may be in the form of rolled plate,sheet, pipes, castings, forgings, or billets.

2.3 Mathematic model of heat source

The research activity in welding simulation starteddecades ago. Rosenthal (1941) was among the firstresearchers to develop an analytical solution of heat

flow during welding based on conduction heat trans-fer for predicting the shape of the weld pool for twoand three-dimensional welds. Using the Fourier par-tial differential equation (PDE) of heat conduction,he introduced the movingcoordinate system to developsolutionsfor thepoint andline heat sources andappliedthis successfully to address a wide range of weldingproblems. His analytical solutions of the heat flowmade possible for the first time the analysis of theprocess from a consideration of the welding parame-ters namely the current, voltage, welding speed, andweld geometry.

His analytical solution (Rosenthal 1946) is basedon theconcentration heat source, butit didnot considerthe changes of material properties with temperature,the phase change and latent heat. Hence, the resultdeviation in the heat affect zone is relatively big.Nevertheless, owing to its acceptable accuracy in thelow temperature zone and its simplicity, it has beenwidely used in engineering applications.

Since the pioneering work of Rosenthal, Friedman(1975) proposed to apply the Gaussian Distributedheat source to approximately express the heat flux inheating spot, as shown in Figure 2.

The heat fluxq(r), with a distance rfrom the heat

source center, can be expressed as:

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Figure 2. Gaussian distributed heat source.

Figure 3. Double-ellipsoidal distributed heat source.

whereqmax is the maximum heat flux in the center ofthe heat source; Q= IU is the heat flux of the arc;andR is the radius of the heating spot.

For the normal welding process, such as GTAW and

SMAW, the Gaussian distributed heat source modal isproved to provide precise enough results.

However, for the welding process in which themomentum effect of arc is considerably large, thedisadvantage of the Gaussian distribution model inresult accuracy appears due to neglecting the effectof the arc stiffness.

To solve this problem, Goldak et al. (1985) initiallyproposed a semi-ellipsoidal heat source in which heatflux is distributed in a Gaussian manner throughoutthe heat sources volume.

Heat flux reaches the maximum value in the cen-

ter of heat source, whose distribution is given by thefollowing equation.

whereA,B, Care the heatflow distribution coefficient.However, their experience with this heat source

showed that the predicted temperature gradients infront of the arc were less steep than experimentallyobserved ones and gradients behind the arc weresteeper than those measured. To overcome this, theycombinedtwo semi-ellipsoidsand proposed a newheat

source called double ellipsoidal heat source, as shownin Figure 3.

Since two different semi-ellipsoids are combinedto give the new heat source, the heat flux within eachsemi-ellipsoid are described by different equations.

For a point within the first semi-ellipsoid locatedin front of the welding arc, the heat flux equation isdescribed as:

wherefris the heat input proportion in the rear part.For points (x,y,z) within the second semi-ellipsoid,

covering the rear section of the arc, the heat fluxequation is described as:

In the past twenty years, considerable interest in thethermal aspects of welding was expressed by manyresearchers, such as Michaleris and DeBiccari (1997),Wahab et al. (1998), and Gery et al. (2005).

3 FINITE ELEMENT ANALYSIS AND RESULTS

3.1 Considerations

Generally speaking, severely physical and chemicalreactions occur during the welding process, betweenthe base metal and the melted pool, which includesthe thermodynamics and heat transfer, the interactionbetween the heat source and metal, solidification in thewelding line, the phase transformations in the weldingjoint, and so on. To focus on the temperature f ield ofthe welding structure, some factors that have a smalleffect on it are supposed to deserve low weight inconsideration or sometimes even be neglected. Hence,several simplifications have been considered duringthe simulation.

First of all, the chemical reactions and agitation

and convection phenomena, and the phase change arenot taken into consideration.

Secondly, the heat transfer between the base metaland the experiment table are neglected, assuming thatthere is only convection heat transfer between theedges of the work piece and the air, without radiationheat transfer.

Thirdly, assume that the welding rod is of the samematerial as the substrate.

Finally, assuming that the welding process is con-ducted with the constant heating speed V; the heatsource is complied with the Gaussian model.

3.2 Material properties

The material properties of metal, for instance, the spe-cific heat, thermal conductivity, modulus of elasticity

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Table 1. Material Properties for Steel 25 (Biswas et al. 2001).

Temperature (C) 0 100 300 450 550 600 720 800 1450

Thermal conductivity 51.9 51.1 46.1 41.1 37.5 35.6 30.6 26.0 29.5

(W m1 C1)Specific heat capacity 450 499 566 631 706 773 1080 931 438

(J kg1 C1)

Poissons ratio () 0.28 0.31 0.33 0.34 0.36 0.37 0.37 0.42 0.47Thermal expansion coefficient 10 11 12 13 14 14 14 14 15

(106 C1)Modulus of elasticity (GPa) 200 200 200 150 110 88 20 20 2

Film coefficient (W m2 C1) 1.0 6.5 7.5 7.3 7.2 7.2 7.1 7.1 7.0

and yield stress, vary with the change of tempera-ture. The average values can be used in calculationsif the temperature does not vary too much. Whilein the welding process, the temperature of weldmentvaries shapely. In this case, to neglect the material

properties differences by temperature will result in bigdeviations. Consequently, the temperature-dependentmaterial properties are supposed to be taken intoconsideration in welding process simulation.

In this analysis, eight-node three-dimensional brickthermal element, Solid 70, is used. The Solid 70element has a three-dimensional thermal conductioncapability. It has eight nodes with a single degree offreedom, temperature, at each node andis applicable toa three-dimensional, steady-state or transient thermalanalysis. The element also can compensate for masstransport heat flow from a constant velocity field. If

the model containing the conducting solid element isalso to be analyzed structurally, the element should bereplaced by an equivalent structural element (such asSolid 45 or Solid 185).

The C-Mn steel whose temperature-dependentmaterial properties are listed in Table 1 was used.

3.3 FE modeling

In this work, the butt welding process has been sim-ulated in Ansys. The dimensions of the work pieceare 300*260*6 mm3, as shownin Figure 4 inwhich the

arc center is moving along the x+ direction in line KI.Furthermore, for the sake of saving computational

time and reducing computer configurations require-ment, a half model has been taken in the simulation,with symmetric boundary condition setting in thesymmetry plane, since the model is symmetric alongthe X-Z plane.

Figure 5 displays the element mesh of the geometricmodel to be solved. 2 mm element size is used in thewelding zone, while 8 mm element size is used in thearea far away from the heat affected zone (FAZ). Freemesh is performed in the middle zone.

Meanwhile, a finer mesh was carried on, to studythe effect of the mesh style on the result. In this case,four different element sizes, 1.25 mm, 2.5 mm, 5 mm,and 10 mm are modeled. And all the elements arehexahedrons (see Figure 6).

Figure 4. Dimensions of work piece.

Figure 5. Element mesh.

Figure 6. Finer element mesh.

FE results demonstrates that the temperature distri-

bution of the node located in the center of the weldingline are almost identical since the maximum deviationin all time steps are only 0.21%, which means the rel-atively coarser model is satisfied to be utilized in thesimple butt welding process.

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Figure 7. Comparison with Biswass result.

Figure 8. Temperature distribution in time= 1 s.

3.4 Verification

As presented by several researchers, finite elementmethod (FEM) has been successfully used to evalu-ate thermal response of the complex welding process.

In the present work, the finite element (FE) packageANSYShas been used to simulate the arc weldingprocess.

Quite a few researchers have addressed this topic,Tsai & Eagar (1983), Guedes Soares et al. (1998) andBiswas et al. (2007), to name a few.

In Figure 7, a finite element simulation of a lineheating process was verified using the work of Biswaset al. (2007). To do this, the same geometry andmaterial properties as Biswass model were using,the heating process with total heat input 5350 Wattsand heating speed 6 mm/sec was simulated usingANSYScodes.

From Figure 4, it shows that the temperature historyresult of present work is in a good agreement with theexperimental result obtained by Biswas et al. (2007).

3.5 Results and discussion

Figure 8 to Figure 12 display the temperature fielddistributions in the heating process, in the finer meshcase. It is obvious that the temperatures increaserapidly in the beginning, from room temperature toover 350C within one second. After that, the tem-

perature field tends to be stable, which means thetemperature of a certain point is varied by time, butthe certain temperature is moving with the heat source,meanwhile, thepeak temperature is retainingof a valueof approximately 547C.

Figure 9. Temperature distribution in time=

10s.

Figure 10. Temperature distribution in time= 20s.




During this period, the contour in the front of theheat source is quite dense. On the contrary, in the rearpart, the temperature distribution gradient is compar-atively small. Generally speaking, the shapes of thecontours are close to ellipsoids.

The cooling process in the finer mesh case isdescribed in the following four figures, from Figure13 to Figure 15. After removing the heat source, thepeak temperatures drop to about 350C in 50 seconds.However, the changing rate is relatively lower compar-

ing with the heating process. In the cooling stage, thecontours enlarge by time (see Figure 14). After 6000seconds, the peak temperature becomes less than 70C(see Figure 15) and eventually the temperatures in allnodes are tending to the room temperature.

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Figure 16. Simulation results in different meshes.

Figure 17. Nodes in the welding line (Group 1).

Figure 16 demonstrates that the peak temperatures

of the node located in the center of the welding line,in the coarser and finer mesh, are 1308C and 1126Crespectively.

To obtain more detailed information of the tem-perature field, several groups of nodes are selected.

Figure 18. Temperatures of nodes group 1.

Figure 19. Nodes Group 2 (parallel to Group 1).

Firstly 7 nodes in the welding line with uniform dis-tance are chosen (see Figure 17), and the temperaturesof these 7 points are plotted in Figure 18, which indi-cates that, after reaching a stable state, the curve of thetemperature of each node is of the same tendency, andfor a certain node, the temperature shapely increaseswhen it is subject to heat input, and then fall downwith a relatively lower speed after achieving the peaktemperature. The first node and the last one are withlower/higher temperature than the other nodes, whichis due to the less/more heat affected time.

Another 7 points are selected in Figure 19, whosetemperature distributions are similar to the previousones, expect the peak temperatures are much lowersince they are a little far from the heat source, and thedecrements of temperatures are slower (see Figure 20).

In the Z direction, 3 more nodes are taken asFigure 21. Figure 22 shows their temperatures distri-butions. The temperature reduces with the incrementof distance from the heating surface but the effect isnot so significant.

In theY direction, 7 nodes are marked in Figure 23,with the distances away from the center line of 2, 4,

6, 8, 14 and 26 mm respectively. The more distancesaway from the heating line, the lower temperaturesproduced (see Figure 24). Figure 25 illustrates therelationship between the peak temperatures and thedistances from the welding line.

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Figure 21. Nodes Group 3 (in z direction).


3.6 Parametric effect study

For the sake of finding out the effects of weldingprocess parameters (welding speed and heat input)and geometricparameter (thickness of the metal plate),series of calculations with different parameters have

been performed.Figure 26 explains the temperature distributions of

the node located in the middle of the welding line,in 5 cases of variant welding speeds, 4 mm/s, 6 mm/s,8 mm/s, 10 mm/s and 12 mm/s. It can be concluded

Figure 23. Nodes Group 4 (in y direction).


Figure 25. Temperature-distance curve.

that the lower the speed is, the higher temperature gotin the result.

The heat input in the previous calculation is 5350 W.Keeping the fixed welding speed 6 mm/s, and chang-ing the heat input to 3000 W, 6500 W and 7950 W,then the corresponding temperature distributions are

plotted in Figure 27. There is no doubt that the higherheat input results in higher temperature.

To study the effect of the plate thickness on the tem-perature field result, 5 cases are conducted in whichthe welding speeds are fixed to 6 mm/s, the heat inputs

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Figure 26. The effect of welding speed.

Figure 27. The effect of heat input.

Figure 28. The effect of plate thickness.

are set as 5350W, but the plate thickness changesas 4 mm, 6 mm, 8 mm, 10 mm and 12 mm. It can beproved in Figure 28 that the thinner the plate, the higher

temperature is obtained.

4 CONCLUSIONS

The model of transient thermal process in weldingwhich is a material nonlinear procedure is describedin the present work, to simulate the moving of theheat source, and to predict the temperature field ofthe entire weldment. The function of Gauss was cho-sen as heat source model, and was used as functioncommand to apply load of moving heat source.

The effects of welding speed, plate thickness andheat input, heat source type and finite element meshon temperature field distribution were discussed. Ithas been proved that all these three parameters playan essential role in affecting the final temperaturedistribution.

ACKNOWLEDGEMENTS

This work has been performed in a EU funded

project Network of Excellence in Marine Struc-tures (MARSTRUCT) under contract TNE3-CT-2003-506141.

REFERENCES

ANSYS. 2007. Release 11.0 Documentation for ANSYS.United States of America. ANSYS Inc.

Biswas, P., Mandal, N.R.& Sha,O.P. 2007. Threedimensionalfinite element prediction of transient thermal historyand residual deformation due to line heating. Journal ofEngineering for the Maritime Environment, Part M 221:

1730.Friedman, E. 1975. Thermomechanical analysis of the

welding process using the finite element method. Trans.A.S.M.E. J. Pressure Vessel Tech973.3: 206213.

Gery, D., Long, H. & Maropoulos, P. 2005. Effects of weld-ing speed, energy input and heat source distribution ontemperature variations in butt joint welding. J. MaterialsProcessing Technology1672-3.2-3: 393401.

Goldak, J.A., Chakravarti, A. & Bibby, M.J. 1985. A doubleellipsoid finite element model for welding and heatsources. IIW Doc-212-603-85.

Guedes Soares, C., Gordo, J.M. & Teixeira,A.P. 1998. Elasto-plastic behavior of plates subjected to heat loads.Journalof Constructional Steel Research452.2: 179198.

Michaleris, P. & DeBiccari, A. 1997. Prediction of weldingdistortion. Welding Res. Suppl 76: 172181.

Rosenthal, D. 1941. Mathematical theory of heat distributionduring welding and cutting. Welding J205.5: 220s234s.

Rosenthal, D. 1946. The theory of moving sources of heatand its application to metal treatments. Trans. A.S.M.E:849866.

Tsai, N.S. & Eagar, T.W. 1983. Temperature fields pro-duced by traveling distributed heat sources. WeldingJ 62:346s355s.

Wahab, M.A., Painter, M.J. & Davies, M.H. 1998. The pre-diction of the temperature distribution and weld poolgeometry in the gas metal arc welding process. J. Mater.

Process. Technol 77: 233239.

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