Nstone Thesis[1]

8/22/2019 Nstone Thesis[1]

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CRANFIELD UNIVERSITY

NICHOLAS STONE

MODELLING NARROW GROOVE PIPE WELDING OF X100

PIPELINE STEEL

SCHOOL OF APPLIED SCIENCES

MSc Thesis


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CRANFIELD UNIVERSITY

SCHOOL OF APPLIED SCIENCES

MSc Thesis

Academic Year 2006 2007

Nicholas Stone

Supervisors: D Yapp, P Colgrove

Sept 2007

This thesis is submitted in partial fulfilment of the requirements for the

degree of Master of Science

Cranfield University 2007. All rights reserved. No part of thispublication may be reproduced without permission of the copyright owner.


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Abstract

Knowledge of temperature distribution patterns is useful in any welding process to

predict microstructure and distortion. I n the current work a model has been

developed to predict the thermal cycles during welding of a narrow groove joint of

X100 pipeline steel. The model was developed in the COMSOL Finite Element

package and considered a tandem arc welding power source, including temperature

dependent material properties. In addition the work looked to evaluate the process

efficiency using liquid nitrogen calorimetry. Results show a good comparison

between model and experimental results, although further work is needed to more

closely match temperature profiles close to the heat source.


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List of Contents

Abstract ...................................................................................................................... 3List of Contents......................................................................................................... 4List of Figures........................................................................................................... 6List of Tables........................................................................................................... 101. Introduction ....................................................................................................... 11

Project Aims and Objectives ............................................................................. 112. L iterature Review ............................................................................................. 12

Introduction ......................................................................................................... 12X100 Steels used for Pipelines.......................................................................... 13Tandem Pulsed Gas Metal Arc Welding of X100 Steel................................. 17Modelling the Welding Process ........................................................................ 19Numerical Methods............................................................................................ 21Heat Source Models............................................................................................ 22Microstructure Modelling.................................................................................. 26Thermal Material Properties for Welding Simulation ................................. 28Heat Source Efficiency Measurement ............................................................. 31

3. Modelling the Welding Process........................................................................ 36Modelling the Geometry .................................................................................... 37Heat Source Modelling....................................................................................... 40Model Subdomain & Boundary Conditions.................................................... 46

Mesh Size............................................................................................................. 50Material Properties ............................................................................................ 51

4. Model Validation through Experiment........................................................... 79Introduction ......................................................................................................... 79Materials .............................................................................................................. 80Welding Equipment............................................................................................ 80Recording Equipment ........................................................................................ 83Metallographic Examination ............................................................................ 84Calorimeter Measurements .............................................................................. 85Experimental Procedure.................................................................................... 86

Welding Tests...................................................................................................... 86Set up of Welding Rig......................................................................................... 86Welding Test 1: Flat Plate Test 3 Thermocouples ........................................ 87Welding Test 2: Flat Plate Test 4 Thermocouples ........................................ 89Welding Test 3: Bead on Plate Welds for Weld Wool Measurement .......... 90Welding Test 4: Multipass Groove Weld with Multiple Thermocouples ... 91Thermal Efficiency Measurements.................................................................. 94

5. Experimental Results..................................................................................... 100Welding Tests 1&2: Bead on Plate Tests...................................................... 100Weld Test 3: Weld Pool Measurement .......................................................... 103

Weld Test 4: Multipass Groove Weld............................................................ 104


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Process Efficiency Tests................................................................................... 1116.Discussion of experimental results................................................................ 115

Weld Test 1........................................................................................................ 115Weld Test 2........................................................................................................ 115

Weld Pool Measurement.................................................................................. 116Weld Test 4: Multipass Groove Weld ............................................................ 117Welding Efficiency Calorimeter Tests........................................................... 119

7. Incorporation and comparison of Experimental Results ........................... 122Weld Test 1........................................................................................................ 122Weld Test 2........................................................................................................ 126Weld Test 4: Multipass Groove Weld ............................................................ 128

8. Discussion of Model results ............................................................................ 1419. Conclusions and Further Work ...................................................................... 14510. References........................................................................................................ 147


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List of Figures

Figure 1: Comparison of weld and base metal areas with FeC phase diagram[6]....................................................................................................................... 16

Figure 2: Variation of hardness profiles in HAZ of TCMP steel welded withvaried heat input [6]....................................................................................... 17

Figure 3: Diagram showing Rosenthal model description [7]......................... 20Figure 4: Goldak Double Ellipsoidal heat source.............................................. 23Figure 5: Comparison of normal Gaussian heat source and spread heat

source [25]........................................................................................................ 25Figure 6: Thermal cycle comparision between heat treatment and welding

[6]....................................................................................................................... 26Figure 7: Effect of peak temperature on CCT diagram [6].............................. 27Figure 8: Typical temperature dependent properties for mild steel [8] ........ 29Figure 9: More common form of temperature-dependent data for welding

simulation [31] ................................................................................................ 30Figure 10: Heat source efficiencies for various processes [7] .......................... 32Figure 11: Typical measurement of arc efficiency by Kou [7] ......................... 32Figure 12: Typical groove geometry .................................................................... 37Figure 13: Model geometry dimensions .............................................................. 39Figure 14: Heat source dimensions ..................................................................... 41Figure 15: Distributed heat flux of Goldak heat source................................... 43Figure 16: Distributed heat flux of modified heat source ................................ 43Figure 17: Heat source shape comparison.......................................................... 44Figure 18: Heat source located in the groove..................................................... 45Figure 19: Heat source applied to top of deposited weld.................................. 46Figure 20: Prescribed temperature boundary condition

Figure 21: Top surface heat loss boundary condition 48Figure 22: Bottom surface heat loss boundary condition

Figure 23: Thermal insulation & symmetry boundary condition ........... 48Figure 24: Convective flux boundary condition ................................................. 49Figure 25: Example of meshed geometry ........................................................... 50

Figure 26: Refined mesh around heat source.................................................... 52Figure 27: Temperature dependent thermal conductivity models................. 53Figure 28: Thermal conductivity variation 0mm .............................................. 54Figure 29: Thermal conductivity variation 4mm .............................................. 54Figure 30: Thermal conductivity variation 8mm .............................................. 55Figure 31: Thermal conductivity variation 11.51mm....................................... 55Figure 32: Thermal conductivity variation 21.32mm....................................... 56Figure 33: Thermal conductivity variation 31.8mm......................................... 56Figure 34: Specific heat capacity models............................................................ 58Figure 35: Specific Heat variation 0mm............................................................. 59

Figure 36: Specific Heat variation 4mm............................................................. 59


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Figure 37: Specific Heat variation 8mm............................................................. 60Figure 38: Specific Heat variation 11.51mm ..................................................... 60Figure 39: Specific Heat variation 21.32mm ..................................................... 61Figure 40: Specific Heat variation 31.8mm........................................................ 61

Figure 41: Density and Emissivity models......................................................... 62Figure 42: Density variation 0mm....................................................................... 63Figure 43: Density variation 4mm....................................................................... 63Figure 44: Density variation 8mm....................................................................... 64Figure 45: Density variation 11.51mm............................................................... 64Figure 46: Density variation 21.32mm............................................................... 65Figure 47: Density variation 31.8mm................................................................. 65Figure 48: Emissivity variation 0mm ................................................................. 66Figure 49: Emissivity variation 4mm ................................................................. 66Figure 50: Emissivity variation 8mm ................................................................. 67

Figure 51: Emissivity variation 11.51mm.......................................................... 67Figure 52: Emissivity variation 21.32mm.......................................................... 68Figure 53: Emissivity variation 31.8mm............................................................ 68Figure 54: Heat-transfer coefficient variation 0mm......................................... 69Figure 55: Heat-transfer coefficient variation 4mm......................................... 70Figure 56: Heat-transfer coefficient variation 8mm......................................... 70Figure 57: Heat-transfer coefficient variation 11.51mm ................................. 71Figure 58: Heat-transfer coefficient variation 21.32mm ................................. 71Figure 59: Heat-transfer coefficient variation 31.8mm.................................... 72Figure 60: Thermal efficiency variation 0mm................................................... 73

Figure 61: Thermal efficiency variation 4mm................................................... 73

Figure 62: Thermal efficiency variation 8mm................................................... 74Figure 63: Thermal efficiency variation 11.51mm............................................ 74Figure 64: Thermal efficiency variation 21.32mm............................................ 75Figure 65: Thermal efficiency variation 31.8mm.............................................. 75Figure 66: Travel speed variation 0mm.............................................................. 76Figure 67: Travel speed variation 4mm.............................................................. 76Figure 68: Travel speed variation 8mm.............................................................. 77Figure 69: Travel speed variation 11.51mm...................................................... 77Figure 70: Travel speed variation 21.32mm...................................................... 78Figure 71: Travel speed variation 31.8mm........................................................ 78

Figure 72: Twin contact tip tandem torch.......................................................... 82Figure 73: Groove plate sample secured onto the welding rig........................ 82Figure 74: Welding rig with table motion control box...................................... 83Figure 75: Calorimeter experimental setup....................................................... 85Figure 76: Welding table travel speed calibration ............................................ 87Figure 77: Test 1 thermocouple locations........................................................... 88Figure 78: Test 1 thermocouple distances from the weld line......................... 89Figure 79: Test 2 thermocouple locations........................................................... 90Figure 80: Bottom and top drill hole positions for thermocouples ................. 92Figure 81: Test 4 multipass weld thermocouples locations............................. 92

Figure 82: Groove geometry dimensions ............................................................ 93


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Figure 83: Welded 1000g sample......................................................................... 95Figure 84: Sample with added clamping feature.............................................. 96Figure 85: Groove sample with added clamping feature ................................. 96Figure 86: Welding energy composition.............................................................. 98

Figure 87: Oscilloscope data for Test 1............................................................. 100Figure 88: Oscilloscope data for Test 2............................................................. 101Figure 89: Oscilloscope data for Test 3............................................................. 101Figure 90: Weld Test 1 thermocouple data ...................................................... 102Figure 91: Weld Test 2 Thermocouple data ..................................................... 102Figure 92: Weld pool size dimensions, 0.617 m/min above, 0.793 m/min

below ............................................................................................................... 103Figure 93: Bead on plate weld dimensions....................................................... 103Figure 94: Bead on plate with torch oscillation weld dimensions ................ 104Figure 95: Pass 1 thermocouple......................................................................... 105

Figure 96: Pass 2 thermocouple data................................................................ 105Figure 97: Pass 3 thermocouple data................................................................ 106Figure 98: Pass 4 thermocouple data................................................................ 106Figure 99: Pass 5 thermocouple data................................................................ 107Figure 100: Pass 6 thermocouple data.............................................................. 107Figure 101: Cap pass thermocouple data ......................................................... 108Figure 102: Macro of multipass groove weld.................................................... 108Figure 103: Multipass weld location of thermocouple 4................................. 109Figure 104: Multipass weld location of thermocouple 5................................. 109Figure 105: Multipass weld location of thermocouples 1,2,3 & 6 ................. 110

Figure 106: Multipass weld location of thermocouple 8................................. 110

Figure 107: Liquid nitrogen normal evapouration rate................................. 112Figure 108: Calorimeter tests example weight loss profile........................... 113Figure 109: Calorimeter test data showing variation with temperature.... 113Figure 110: Calorimeter test data showing variation with weight .............. 114Figure 111: Weld test 1 model data comparison dataset 1............................ 123Figure 112: Weld test 1 model data comparison dataset 2............................ 124Figure 113: Weld test 1 model data comparison dataset 3............................ 125Figure 114: Heat Affected Zone model size for 5 mm heat model depth ..... 125Figure 115: Heat Affected Zone model size for 2 mm heat model depth ..... 126Figure 116: Weld test 2 model data comparison dataset 1............................ 127

Figure 117: Weld test 2 model data comparison dataset 2............................ 128Figure 118: Multipass weld test 4 model data comparison dataset 1, pass 1

......................................................................................................................... 129

Figure 119: Multipass weld test 4 model data comparison dataset 1, pass 1......................................................................................................................... 130



Figure 122: Multipass weld test 4 model data comparison dataset 1, pass 3

......................................................................................................................... 131


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Figure 130: Multipass weld test 4 model data comparison dataset 2, pass 2......................................................................................................................... 136Figure 131: Multipass weld test 4 model data comparison dataset 2, pass 2

......................................................................................................................... 136




Figure 135: Multipass weld test 4 model data comparison dataset 2, pass 4

......................................................................................................................... 138Figure 136: Multipass weld test 4 model data comparison dataset 2, pass 5

......................................................................................................................... 139


Figure 138: Heat Affected Zone size with width of 7.9 mm........................... 140Figure 139: Heat Affected Zone size with width of 10 mm............................ 140


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List of Tables

Table 1: Typical composition and properties of X100 steel [3]........................ 14Table 2: Equation based material properties [21]............................................. 31Table 3: Welding parameters for bead on plate tests ..................................... 100Table 4: Multipass groove weld input parameters and weld deposition ..... 104Table 5: Mutipass weld power input results.................................................... 104Table 6: Multipass weld thermocouple location summary ............................ 111Table 7: Calorimeter test calibration summary .............................................. 111

Table 8: Welding efficiency results.................................................................... 112Table 9: Model input data for Weld Test 4....................................................... 128


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1. Introduction

Project Aims and Objectives

The main aim of this project has been to develop an accurate model that predicts

the thermal cycles present in a narrow groove pipe weld, utilising the Tandem

Pulsed Gas Metal Arc Welding (Tandem GMAW-P) process. The prediction of these

thermal cycles, due to each successive welding pass, allows an understanding of the

microstructure that will develop upon cooling of the weld, which in turn provides

estimates of mechanical properties of such welds.

The complete task of modelling the problem was broken down into smaller areas,

both theoretical and experimental. Therefore the overall project aims became:

Understanding of the fundamentals of the Tandem GMAW-P process and

how narrow groove welds are typically welded.

Knowledge of welding X100 pipeline steel, detailing welding parameters for

the process that are suitable to create defect-free welds.

Understanding how to model a welding process, involving characterisation

of welding heat sources and typical model properties and boundary

conditions.

Validation of the model using conventional narrow groove Tandem GMAW-

P and subsequent measurement of thermal cycles and weld properties.

An in depth study into the efficiency of the Tandem GMAW-P process in

order to utilise a sensible and accurate value in the developed model.

Another objective of this project has been to develop typical project working and

report writing skills, known as soft skills. Therefore the main soft skills that have

been tested and improved during the project have been:

Time management, developing skills for scheduling experiment and working

to deadlines.

Refinement of report writing skills, presenting concisely and eloquently the

details of our project.


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2. Literature Review

Introduction

Demand for high strength steel pipelines is increasing, with recent studies showing

there will be a doubling in demand by 2030. This is due to continuing increased

demand for energy across the globe. Products such as oil and gas need to be

transported across large distances which can be done in a very cost effective way

with pipelines. Oil products can also be transported by tanker across the sea and

stored locally. This is a more economical alternative and one that is receiving a

large investment by oil and gas majors. Until recently sea tanker was not a viable

option for the transportation of Natural Gas, and so pipelines have been the main

method employed. The Liquified Natural Gas product has allowed a similar

technique of transportation to that of oil products, by way of tanker, but as

Aristotelle [1] states this is not yet economically feasible. There is some debate as

to whether this is the case, owing to a large number of LNG terminals that are

being built around Europe to store the natural gas produced from Russia.

Whatever the final outcome the near future holds a requirement for continued

pipeline construction both on and offshore.

I t has been stated [1] that the speed of laying a pipeline, and the quality of the in-

field welded joints during construction, is fundamental to the feasibility of such a

project. I f too many repairs must be made during construction, the cost of the

project increases. To avoid this problem robust welding technology and procedures

are required. In essence the outcome of welding such steels in the correct

configurations must be known before the project is started. In order to have

confidence in a particular welding procedure or method the usual technique is to

carry out a set of trial and error tests, to quantify the welding variables associated

with the method. In fact this is a requirement of all of the welding standards

currently employed. This is due mainly to the fact that welding is a complex science

and it is difficult to predict the integrity of a joint by specifying merely input


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variables. Such procedure qualification tests are time consuming and expensive to

perform as they expend manpower and welding consumables.

Mathematical modelling has obvious economic advantages in that, given a

workable model, much of the procedure development could be computationally

based. Computational work is far cheaper than experimental welding trials and so

would offer considerable cost savings. Mathematical models have been employed

for all aspects of welding, with varying degrees of success. The fact that welding

procedure specification and qualification is still experimentally based shows that

welding model performance is limited. The main reason mathematical models are

limited in performance is due to complexity of the input variables that must be

adequately accounted for to characterise a specific welding process.

The project undertaken will develop a model to characterise and predict the

thermal cycle of a typical narrow groove geometry used for welding pipeline steel in

service. The model has to take into account an appropriate heat source model to

represent the weld heat input, in addition to the correct geometry of joint. The aim

of the project is to predict with accuracy the thermal cycle in the Heat Affected

Zone (HAZ) and therefore allow prediction of microstructural changes that will

occur due to the imposed thermal cycle. This literature review will first discuss the

X100 thermomechanically produced steel, that is increasingly used for modern

pipeline installations. The manufacturing procedure and original microstructure of

such steels is important to understand before it is possible to consider the added

effect of welding thermal cycles. Typical welding procedures will be discussed in

relation to the heat input used and the effect on the base metal, especially the

HAZ. The review will then concentrate on the modelling of welding in general,

discussing the various models that have been historically used.

X100 Steels used for Pipelines

The relatively new X100 material has a specified minimum yield strength of

690MPa. Use of increased strength steels for pipelines allow either the operating

pressure to be increased, allowing more carrying capacity, or the thickness of the


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pipe to be decreased. Either way there are distinct economic advantages. X100 is

part of the wider S690 family of steels that have this minimum specified yield

strength. These steels can show a large difference in their overall properties due to

their diverse manufacturing procedures and chemical composition. Various

standards exist for these steels such as: ASTM A543 Class2, API 5XL X100 or

MIL-S-12616 HY100 [2].

The previous generation of pipeline steels were produced by quenching and

tempering. Quenching of the steel is done after the material reaches the

austenising temperature of about 900 C. Quenching of the steel involves rapid

cooling that prevents formation of soft microstructural components such as ferrite.

Instead the hard micro-constituent of martensite is formed. Pure martensite is far

too brittle for structural purposes and so it must be tempered. The tempering

process reduces the super-saturation of the matrix by forming carbides, and causes

some annealing which also reduces the dislocation. Quench and tempered steels

display a combination of good tensile and toughness properties. In order that high

strength steels can be produced in such a manner, the ideal carbon level is between

0.12% - 0.18% to facilitate the martensite formation for such steels [2]. The

thickness of such materials poses a problem as it is difficult to achieve the required

cooling rate for martensite formation in the centre of thick section steels. This

problem may be rectified by adding alloying elements that increase the materials

hardenability, or the ability to form martensite. The carbon equivalent for such a

material is often used as a measure for the weldability of such steels. High carbon

equivalent steels are difficult to weld due to the high hardenability that may cause

cracking during cooling. It is not possible to produce very thick quench and

tempered steels with low carbon equivalent, and hence they are difficult to weld.

Table 1: Typical composition and properties of X100 steel [3]


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To overcome these problems, thermomechanically produced steels have been

developed which take advantage of thermomechanical rolling followed by

accelerated cooling. The rolling improves the grain refinement and dislocation

density. Most strengthening mechanisms produce an increase in strength at the

expense of a fall in material toughness. This is not so with grain refinement and it

is the principle reason why steels such as X100 are sought after. I t is a feature of

the very fine ferrite and second phase structure present [6]. A fine ferr ite structure

is achieved before the austenite-ferrite transformation with microalloying additions

such as niobium, vanadium and titanium. These combine with carbon, oxygen or

nitrogen to pin the grain boundary movement and prevent growth [6, 2]. Work

hardening of the material is done after the material has been transformed to

acicular ferrite, which further increases the strength of the material. The major

advantage of this material is the much lower carbon content, which makes it more

a weldable steel due to a higher resistance to hydrogen cracking.

X100 is a type of thermomechanically produced steel, whose thickness is limited to

about 20 mm due to production methods. There are a number of different

approaches to producing X100 steel. The manufacturer can choose which

composition and manufacturing process is used provided the material meets the

required strength and impact toughness. Experience has shown the an optimised

two-stage rolling process allows the use of a low carbon content but quite a high

carbon equivalent [3].

Welding of such material means the strength due to work hardening and grain

refinement is lost in the HAZ. Figure 2 shows the coarse grains of heat affected

zone material produced by grain growth which reduces the strength of the welded

steel. I n addition high peak temperatures dissolve the precipitates that pin the

grains and prevent growth, leading to coarser grains [6]. Welding of X100 steel

poses similar problems to those of thick gauge X80 steel [3]. The use of precipitates

that will not easily dissolve, such as titanium nitride, TiN, is a solution to the

problem [6]. The representation of welding thermal cycles using an equilibrium

phase diagram, as in figure 2, is not however appropriate as welding produces far

from equilibrium conditions. The remedy to this is discussed further in the

literature review regarding microstructural models in welding.


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Figure 1: Comparison of weld and base metal areas with FeC phase diagram [6]

A number of studies have been carried out to evaluate the effect of various weldingprocedures on the final properties of welded pipeline girth welds [4, 5]. Welds are

designed to act as crack arresters that essentially prevent a crack from propagating

the length of a pipe, causing catastrophic failure. For this reason the weld metal is

usually designed to have a higher strength than the base metal. This is known as

overmatching. The selection of welding electrode is where this is put into practise

and there are a number of choices with regards to electrode composition. Laratzis

[5] and Hudson [4] have both performed extensive tests regarding suitable welding

electrodes. The advanced nature of welding procedure specification is not relevant

to this project. The important aspect to focus on with respect to modelling such

procedures is the heat input of the process and welding geometry. Finally an

appreciation of the final weld strength or hardness is important.

Hudson showed that 100 C preheat was required to produce good welds with Gas

Metal Arc Welding (GMAW) and Shielded Metal Arc Welding (SMAW) welding

procedures on X100 [4]. Typical hardness values were 281 HV10 for the HAZ of the

base metal and 299 HV10 for the weld metal using SMAW electrodes. Hudson


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limited the amount of heat input into the joint to 1.5kJ /mm to reduce the likelihood

of mechanical strength reduction. Laratzis also found that high heat input was not

acceptable. Submerged Arc Welding (SAW) of joints failed due to a high heat input

of 2.5KJ /mm. Dual tandem GMAW trials proved more successful employing a lower

heat input of 0.5kJ /mm.

Figure 2: Variation of hardness profiles in HAZ of TCMP steel welded with variedheat input [6]

Figure 3 shows how the heat input of the welding process affects the hardness in

the HAZ of a typical Thermo-Mechanical-Controlled-Process (TCMP) steel. High

heat inputs reduce the hardness and, in consequence, the strength of the HAZ.

Hudson states that the pipe wall thickness, bevel angle and welding process have a

major impact on the HAZ dimensions and hardness levels. I t is therefore essential

that these aspects are modelled correctly to allow accurate prediction of the

thermal cycle and hence final weld composition.

Tandem Pulsed Gas Metal Arc Welding of X100 Steel

Welding of gas pipelines has become an automated process as automation provides

more stability during welding and hence a higher quality weld. Arc stability, for


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example, is far more constant when the welding torch is mounted on to a purpose-

built pipe jig than when used by hand for manual operation. The Tandem Pulsed

Gas Metal Arc Welding (Tandem GMAW-P) is a welding process that has been

developed for welding pipeline steel and is an area for which much research has

been done at Cranfield University. The major advantage of the process is the high

production rate, due to use of two welding electrodes to feed one weld pool.

Improved positional welding around the pipe is also possible due to a fast freezing

weld pool with pulsed power supply used.

Gas Metal Arc Welding (GMAW) is probably the most widely used process to join

ferrous materials. The process creates a welding arc between a continuously fed

wire electrode and the work surface with additional gas shielding present to

displace the natural atmosphere. The arc melts the wire electrode creating a weld

bead. The GMAW process is mostly used with the Direct Current Electrode

Positive (DCEP) power configuration, meaning that DC voltage is used and the

electrode represents the positive terminal of the supply, with the work piece the

negative terminal. GMAW is mostly a constant voltage process, whereby the

current is regulated by the wire-feed speed of the electrode wire [6]. This allows a

constant arc length to be maintained even if the welding torch is moved away from

the work piece. The transfer of metal droplets from the electrode tip to the work

piece is achieved by globular transfer below a certain welding current. Globular

transfer is characterised by large metal droplets that fall from the electrode tip due

to their own weight. Above a certain current, known as the Transition Current, the

transfer of metal becomes more ordered with smaller droplets and is known as

Spray Transfer. The advantage of spray transfer is that, as the droplets are

accelerated across the arc with electromagnetic force, there is greater possibility to

weld in positions other than down-hand or directly on top of a plate. This has

obvious advantage for pipe welding where the entire pipe must be welded at all

angles. The spray transfer mode is also less susceptible to spatter.

The high current required to produce spray transfer is associated with a high heat

input for the process. It has already been shown that materials can be sensitive to

high heat input processes with associated loss of mechanical strength. A

compromise to this is the Pulsed Current process. This has an overall low heat

input but can be used for greater positional work. The GMAW-P process utilises


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finite periods of high current, above the transition current, with an overall low base

level of current to maintain the welding arc. To define a pulsed current waveform

requires selecting the peak current and time in addition to the base current and a

frequency of pulsing. The magnitude of the pulse waveform affects the molten

metal detachment from the electrode. Trial and error tests are often performed to

determine the correct set of parameters to produce satisfactory welds [30].

The Narrow gap groove geometry is used in conjunction with the GMAW-P or the

tandem version of the process. The advantage of the narrow gap configuration is

that a smaller amount of material is required to weld the joint, thereby increasing

productivity. I n addition the heat input into the material is less due to reduced

welding time. The narrow groove profile does require accurate electrode positioning

and for this reason the automated process is always used.

Modelling the Welding Process

Mathematical modelling of welding phenomena has become extremely popular in

academia as researchers look to predict processes performance. The proposed

advantages of modelling are mostly due to cost. Welding simulation is, however,

not readily used in industry where a pragmatic approach to welding stilldominates. The applications that have found use have been in the aerospace and

nuclear industries, where safety plays and important role in the production of

components [10].

Looking only at temperature field prediction due to welding, there are a number of

general approaches that can be used. Experimental methods, both full and small

scale allow evaluation of the permeating welding temperature fields. Often, due to

component complexity, this is the only realistic method of obtaining useful,

workable data. To obtain this experimental data, however, is time consuming and

expensive. Extrapolation of data obtained from experimental methods may not

characterise the welding process effectively and may not be useful for purposes

outside of which the original test was designed. Analytical and numerical

modelling offer the advantage of characterising a wider area of welding

phenomenon, although the complexity of the science has severely limited the

application of reliable models.


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Analytical models quantify a phenomenon using mathematical equations or

relationships. These relationships look to characterise behaviour by simplifying the

problem greatly. Rosenthal was the first to create a useful mathematical model for

welding, based on Fouriers heat flow equations [7]. He used an infinitely small

point heat source to represent the arc heating. In addition the line heat source is

often used for analytical models. Rosenthal postulated that, given a heat source

moving with a constant speed, on a constant plate thickness the analysis could be

done as quasi-stationary. Quasi-stationary means that the temperature locally

around the heat source remains constant. This is one major simplification which is

very useful for all welding models. I n addition to the point heat source analytical

models use the assumptions that no convection occurs in the weld pool, there are

no convection or radiation heat losses and there is negligible heat of fusion. The

models are designed for heavily simplified geometries to further aid analysis.

Another major simplification, used with all analytical methods, is to presume that

the thermal properties of the material are not temperature dependent. In fact, due

to the complexity of inclusion, no analytical model accounts for temperature

dependent material properties or latent heat effects. The Rosenthal model is

highlighted in figure 3.

Figure 3: Diagram showing Rosenthal model description [7]

The diagram shows the temperature evaluated at a point from the heat source,

characterised by the equation:

( )00

2exp

2 2

s rT T kg V V

KQ

=

(1) [7]


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Where T is temperature, T0 is workpiece temperature, k is thermal conductivity, g

material thickness, Q is heat input, V is travel speed, is thermal diffusivity, r is

radial distance from the heat source and K0 is a modified Bessel function of second

kind.

Basic geometries are characterised by the semi-infinitely extended solid, infinitely

extended plate and the indefinitely extended rod [26]. Choice of geometry is based

on the heat flow analysis that is of interest.

Even though the original Rosenthal model has great simplifications and was

developed in the 1940s it is still a very quick and accurate way of determining the

thermal cycles due to welding on simple geometries such as flat plates. One well

known problem with the Rosenthal model is that, by use of the point heat source,

the accuracy of temperature prediction is not good near the welding arc. In fact the

predicted temperature tends to infinity. Adams [6] accounted for the peak

temperature with another model to predict the temperature at any distance from

the fusion line. The Adams model is:

0 0

4.131 1g

p m

VY C

T T Q T T

= +

(2) [6]

Analytical models give quick solutions, where simplifications to the problem are

sufficient, but complex structures using these models are difficult to analyse.

Ramirez [29] states that Rosenthals analytical heat flow models used for bead on

plate welding are not adequate for representing multipass welding of medium thick

plates. The major field of work is now focussed on numerical analyses.

Numerical Methods

Since the 1970s the work of computational analysis in welding engineering has

increased [8]. The advantage of using computers for analysis is calculation speed.

Numerical models are often used where a closed form of analytical solution is not

available. In welding, as previously discussed, the closed form solution of thermal

cycle models grossly simplifies the actual welding setup. Therefore numerical

models allow better prediction of the real weld properties. Numerical models can be

based on different methodologies such as Finite Difference, Finite Element and


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Computational Fluid Dynamics. All of these methods involve solution of partial

differential equations which describe the problem over a mesh created from the

geometry. The method of solving these equations, however, is different for each

method. Given the nature of heat flow and stress analysis the primary methods

used for computational welding simulations are either Finite Difference or Finite

Element techniques. The finite difference technique was more popular before

computational power allowed Finite Element methods to improve.

There have been a number of reviews already done of the vast amount of numerical

models used for welding simulation [8,9]. These models have different objectives in

that some wish to predict weld thermal cycles, others are trying to quantify the

amount of distortion using complex thermo-mechanical coupling relationships. As

this project is focused on evaluating thermal cycles, alluding to prediction of effects

on the base metal, the review has not looked in depth into distortion and stress

analysis models. Although it must be pointed out that all welding simulation

models have to ascertain the thermal cycle due to welding and so they all become

relevant to the current work.

L indgren [9], Komanduri [9] and Goldak [10] have all done extensive reviews of

many welding models from both the analytical and numerical perspective. Common

goals of simulation have been to quantify the effects of weld thermal cycle on

structure or thermal expansion and volume change due to phase transformations.

This is known as thermal dilatation. Multipass welding and diverse geometries has

also been a constant area of model development. I t has been shown by Wahab [12]

that the heat source model has a very influential effect on the validity of the entire

welding model. For this reason the main analysis of the literature review is

focussed on the various heat source models and their applicability to different

welding applications.

Heat Source Models

The original point heat source model was, as previous described, the Rosenthal

solution. L indgren points out that the original method of Rosenthal was enhanced

by Christensen [9], in order to make the analysis dimensionless. This allowed

many different welding processes to be compared easily. Eager and Tsai [11] stated


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that the heat source due to welding should be defined as a distributed source over

the surface of the material. They developed the 2D Gaussian distributed heat

source. Similar to Rosenthal the model did not include convective or radiative heat

flow. The model also used constant thermal properties due to the analytical nature

and was applicable only to quasi-steady-state analysis. The model did provide a

comparison between actual welding inputs, such as current, voltage and travel

speed, and the dimensions of the weld pool. By far the most widely used heat

source model for numerical models of welding is that of Goldak [10]. Goldak states

that the analyst requires a heat source model that accurately predicts the

temperature field in the weldment. This argument is that the heat source is not

purely surface based but has an associated volume due to the weld pool

dimensions. The Double Ellipsoidal heat source model, proposed by Goldak, allows

the volumetric nature of actual welding arcs to be taken into account. The model

can be shown to be of general form, with the other distributed models of Pavel and

Paley [10] to be special cases. The model is highlighted in figure 4.

Figure 4: Goldak Double Ellipsoidal heat source


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The coefficients ofa, b, c1and c2 shown are used to specify the boundary of the

fusion zone. The following equation is used to characterise the heat source in front

of the arc:

( )22 2

11

6 3, , exp 3 3 3

fR Q x y z

q x y z a b cabc

=

(3) [10]

and the following for behind the arc:

( )

22 2

22

6 3, , exp 3 3 3b

R Q x y zq x y z

a b cabc

=

(4) [10]

where x, y, zare spatial coordinates, Q is the total heat input in the process, and R

is a balancing factor between the front and back equations whereby both the sumof the integral of both ellipsoids should equal the total heat input Q.

The advantage of the model is that a variety of different welding processes, such as

arc or laser for example, can be specified by using different multiplication factors

for the above equations. The problem exists as to how to determine these model

coefficients and it has been shown by Gery et al. [13] that correct heat source model

parameters are vital in producing an accurate prediction of the fusion zone and

heat affected zone size. Moore, Bibby and Goldak [14] state that setting the values

to 10% smaller than those of the weld pool gives good results. Alternatively the

width of the weld pool can be used by way of standard multiplication factors to

characterise the heat source. With this technique the front of the heat source

parameter, c1, is set to half the bead width, a. The distance behind the heat source,

c2, is set to twice the bead width, four times a. The problem still exists as to how

the weld pool dimensions can be measured. The typical method is to produce bead

on plate samples with a known set of welding parameters. The width and depthcan then be used for the model input values. The weld pool length still poses a

problem using this technique if the bead profile is very smooth. A novel approach

was proposed by Wahab et al. [12]. An apparatus was designed to eject molten

metal, by workpeice acceleration, from the welded material during welding. The

crater that is left can be measured and gives an accurate measure of the weld pool

geometry for a given set of welding parameters. The authors found that welding

speed and current had the greatest influence on weld pool length. Increased heat

input values produced an increase in all of the weld pool dimensions [12]. Gery et


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al point out that this is not a linear relationship [13]. The crater method is feasible

but using it would require some time and experience to develop. Thermal boundary

measurement is another method of characterising the heat source. This requires

expensive thermal imaging equipment and only gives surface weld pool

measurements.

Without doubt the largest difficulty in using a mathematical model for a

distributed heat source is ascertaining the correct input parameters. Gery showed

that the peak temperatures and distributions are extremely sensitive to small

changes in the heat source model [13].

An added complication to the heat source model is due to the weaving or oscillating

nature of the arc when performing narrow groove welding of pipelines. The

movement of the heat source could be programmed as oscillating from side to side

but Sabapathy [25] used a widened version of the Goldak heat source model. The

advantage of this method is that the path of the arc can remain linear along the

length of the weld. Sabapathy modified the Goldak model, quoted previously, to:

( )1 2 3

, , exp 3 3 3

n n n

f

x y zq x y z Q

a b c

=

(5) [25]

The value ofn2allows a broadening of the heat source as shown in figure 5 below.Although this solves the problem of an oscillating source it does complicate model

input parameters.

Figure 5: Comparison of normal Gaussian heat source and spread heat source [25]


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Microstructure Modelling

The high thermal gradients caused during welding produce far from equilibrium

cooling conditions, as previously discussed. In order to ascertain the effect of a weld

thermal cycle on a particular ferritic steel it is not possible to use methods that

may be applicable to other heat treatments. The figure below shows the difference

between a typical heat treatment, on the left, and a welding thermal cycle, on the

right, at various points in the weldment. Heat treatments involve a soak time at a

specified temperature, usually around theAc3temperature, followed by a constant

cooling period. The graph on the right of the figure shows that the peak

temperature during welding varies with distance from the weld centreline, and the

accompanying cooling rate is not constant. Continuous Cooling Curves or CCT

diagrams are often used to predict final cooled microstructures of metals. These are

produced with a single peak temperature and so cannot easily be applied to

welding. The rate of heating and peak austenising temperature highly affect the

phase transformation upon cooling.

Figure 6: Thermal cycle comparision between heat treatment and welding [6]

The figure below shows that the effect of increased peak temperature is to shift the

CCT curve to the right. The larger austenite grain size increases the hardenability

of the steel, allowing more time for the harder martensite structure to form [6].


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Figure 7: Effect of peak temperature on CCT diagram [6]

For the prediction of final microstructure the important cooling time from 800 C to

500 C is used. This time interval directly determines the hardenability of the

weldment as it is during this time that austenite decomposes to bainite or

martensite [15][14]. Various microstructure prediction models are based on the

T8/5 time. Yurioka, for example, has developed a number of equations to

characterise the HAZ hardness, tensile strength and weld metal toughness, based

on a modified Rosenthal model by predicting peak temperature and thermal

profiles [17,18]. In addition theT15/1 time, that is the time for cooling from 1500 C

to 100 C, is also considered as this dictates the time for hydrogen to escape the

HAZ and prevents cold cracking [14].

The problems associated with using a CCT diagram for welding purposes has not

prevented most work on microstructure prediction from utilising them. Often adatabase of CCT diagrams for different peak temperatures and various material

chemical compositions is employed. Okada et al [16] used an estimated thermal

cycle in combination with the CCT diagram database. This is obviously difficult to

achieve without the necessary data to support it.

Odanovic simulated the microstructure in the HAZ of quench and tempered HY-

100 steel. The study used only two CCT diagrams, one for the Course-Grained HAZ

and another for the Grain-Refined HAZ. The prediction of HAZ dimensions was

within 13% of the experimental values. The hardness prediction was not very


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accurate using this method which was thought to be primary due to the inaccurate

thermal cycle analysis.

Thermal Material Properties for Welding Simulation

Welding produces a large temperature gradient in the base material being welded.

Materials do not exhibit constant thermal properties, but instead vary with

temperature and the relationships are not necessary simple. For analytical

solutions there exists the problem of whether to use room temperature, maximum

temperature or average temperature properties. Komanduri [8] suggests that

average temperature values should offer the most logical choice for analytical

models. Moore [14] shows that if a very low value of 25 W/mC for thermal

conductivity is used, as a constant value for analytical methods, the final thermal

analysis and HAZ structure can be well compared. It is thought that the low value

of thermal conductivity compensates for neglecting the effect of latent heat or the

effect of keeping other quantities constant that are actually temperature

dependent. I t was pointed out that these results may have been specific to the case

at hand.The choice of whether to use constant or temperature dependent material

properties has been solved by the introduction of Finite Element techniques for

analysis with added computational functionality. In fact Lindgren states that there

is no longer a need for analytical methods for thermal analysis due to the ease of

FE analyses [9]. The new computational methods can accommodate quantities that

vary with temperature and the argument for their inclusion is too strong to ignore.

The problem of a suitable source of data does, however, still exist. Ideally material

data would be available for all material types to allow good input data for

simulations. Instead most studies use a set of density, thermal conductivity,

specific heat and latent heat of fusion for mild steel, with the presumption that the

data does not vary significantly with chemical composition. Figures 8 and 9 show

the variance of data gathered from two different sources. I t should be noted that

the relationships are far from linear. Zhu [24] points out that the thermal

conductivity has the most effect of the all material properties on the simulation

results, due mainly to the fact that conduction is the primary mode of heat


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transfer. The plot in figure 9 shows that there is a jump in the specific heat plots

due to the latent heat of transformation which may be difficult to incorporate into a

model. Goldak [10] suggests that the simplest way to include latent heat is to

compute specific heat from the enthalpy, with the specific heat being the derivative

of enthalpy.

Figure 8: Typical temperature dependent properties for mild steel [8]


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Temperature Variable Material Properties

0

10

20

30

40

50

60

0 500 1000 1500 2000 2500 3000

Temperature DegC

ThermalConcductivity(W/mK)

0

200

400

600

800

1000

1200

1400

1600

SpecificHeat(J/kgm3)

Conductivity

Specific Heat

Temperature Variable Material Properties

0

1000

2000

3000

4000

5000

6000

7000

8000

9000

0 500 1000 1500 2000 2500 3000

Temperature DegC

Density(kg/m3)

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

Emissivity

Density

Emissivity

Figure 9: More common form of temperature-dependent data for weldingsimulation [31]


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Table 2: Equation based material properties [21]

Heat Source Efficiency Measurement

Given the primary input into the distributed heat source is the overall heat from

the welding arc, it is clear that an accurate evaluation of arc heating is required.

Not all of the electrical input power of the welding arc is converted to useable heat

in the process. Heat losses due to convection and radiation to the environment are

also present. The ratio of actual heat input to power input for the process gives the

overall process efficiency. The process efficiency for GMAW is quoted at between

62% - 85% [21]. Such a spread is difficult to incorporate into an accurate heatsource model. The typical efficiencies of various welding processes are shown in

figure 10, where LBW is Laser Beam Welding, showing the lowest efficiency,

although this is dependent on the surface reflectivity. PAW in the diagram is

Plasma Arc Welding, GTAW is Gas Tungsten Arc Welding, SMAW is Shielded

Metal Arc Welding, GMAW is Gas Metal Arc Welding, SAW is Submerged Arc

Welding and EBW is Electron Beam Welding, with the higher heat source

efficiency. These thermal efficiencies quoted are a combination of three calorimeter

measurements estimating heat transfer from the arc, filler metal drops and

cathode heating [7] and therefore represent quite a detailed interpretation of

efficiency.


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Figure 10: Heat source efficiencies for various processes [7]

The process used in the project will be Tandem GMAW-P which will also have itsown associated process efficiency and must be investigated experimentally to

determine the value.

A number of approaches can be used to estimate the process efficiency. Goncalves

et al [20] point to two main methods, the cooled anode technique and

measurements from actual weldments. The cooled anode approach is also

highlighted by Kou [7].

Figure 11: Typical measurement of arc efficiency by Kou [7]

The figure above highlights how the temperature change in cooling water passing

through a welded section can account for the energy input into the system. The

integral of the thermal cycle, given by equation 7, can be used to calculate heat


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input. The power input will be known based on the current and voltage measured

during the trial and equation 6 can then be used to obtain a value for efficiency.

weld

weld

Qt Q

EIt EI = = (6) [7]

( ) ( )0 0

weld out in out inQt WC T T dt WC WC T T dt

= = (7) [7]

The technique of Tandem Pulsed GMAW (GMAW-P), to be modelled in this project,

has a complex power waveform where the average current of the process remains

below the spray transition temperature for fast cooling, but pulses of current above

the transition temperature create spray transfer for improved positional welding.The method of assessing process efficiency of GMAW-P is complicated by the fact

that, due to the very rapid variations of the pulsed voltage and currents, it is not

possible to use the simple relationship given in equation 6 as the input process

power. In addition it has been stated that efficiency is function of voltage and

current of the arc [10].

J oseph et al [21] gave a review of the various methods of assessing power input

into the GMAW-P process. The studies focussed on the three ways of accounting for

power input:

Root Mean Squared measurement of pulsed voltage and current waveforms

o2

1

2

1

.RMS RMS RMS

ni

RMS

i

ni

RMS

i

P I V

II

n

VV

n

=

=

=

=

=

(8) [21]

o where I is welding current, V is welding voltage and n is the number

of points in the waveform

Average values of voltage and current


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o 1

1

.AV AV AVn

i

iAV

n

i

iAV

P I V

I

I

n

V

Vn

=

=

=

=

=

(9) [21]

Instantaneous Averages of voltage and current

o1

.n i iinst

i

I EP

n== (10) [21]

The study concludes that Root Mean Squared or RMS values should only be takenfor non-pulsed waveforms where there may be a slight ripple present on the power

supply. The Average value method takes the average of the voltage or current over

a complete cycle, while the Instantaneous Average method calculates the power by

multiplication of the voltage and current at each point in the cycle. The advantage

of the instantaneous method is that it can account for any spikes in the power

supply that may occur during welding.

The studies point out the process efficiency measured by RMS values give 10%

higher than instantaneous measurement, while the average method gives

efficiencies of 12% lower [21]. Therefore the study concludes that the instantaneous

power should be used when calculating power input for process efficiency

measurements of pulsed power supplies.

In addition to the power input review the study of J oseph et al also highlights the

use of liquid nitrogen to measure the heat input during GMAW-P. In effect a small

welded coupon is placed into a dewar containing liquid nitrogen, the initial andfinal weight of which can be used to calculate the heat input into the coupon. If the

process is done quickly the losses to the environment are minimal. A more detailed

description of the process is given in the Experimental Procedure section of this

report.

The literature study showed that some researchers have investigated the variation

of welding process efficiency when different geometries are welded. Rykalin [29]

proposes a correction factor for the heat input of the process based on the joint


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geometry of a V bevel groove weld. Ramirez states that Rykalins model implies

that arc energy losses to the surrounding environment are greater than the losses

when welds are made within a groove geometry. The experimental study of process

efficiency in this project should prove whether this is the case.


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3. Modelling the Welding Process

The Finite Element Method was chosen to model the process of multipass pipewelding. The literature review has highlighted the fact that computational

methods are far more adaptable to complex welding cases and it is for this reason

the FEM solution was chosen. FEM obtains approximate solutions of engineering

problems by cutting the structure in elements and finds solutions for a number of

connected elements.

The software package chosen for modelling during the project was COMSOL

Multiphysics, formerly FEMLAB. COMSOL is an FEM analysis and solver package

that has many modules for different engineering applications [27]. Very often,

when using FEM packages, a very in-depth knowledge of cell structures and types

must be known before correct characterisation of the process can be achieved.

COMSOL allows modelling of physical problems without great knowledge of

required solution structures. The package allows standard construction of the

domain geometry, independent of the problem type, from heat transfer to fluid

flow. COMSOL also has the ability to combine various physical phenomena, for

example coupled problems such as thermal cycles and associated residual stress.This would be an ideal application for welding analysis.

The Heat Transfer Module was used in COMSOL to create a model that combined

conduction, convection and radiation.

A thermal problem is setup by specification of the domain, material parameters,

initial conditions and boundary conditions. Solution to the problem is temperature

at all points in the domain.

The field equation for heat conduction in a 3-dimensional solid of dimensions x, y

and z is given as:

2 2 2

2 2 2

1 vQT T T T

t c x y z c t

= + + +

(11) [32]

where the parameter T is temperature, t is time, is the thermal conductivity, c

the mass-specific heat capacity and the density. Q is the heat energy released per

unit volume.

By adding a convective term and simplifying the 3-dimensional notation this

becomes:


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( ). .T

c T Q c u T t

+ =

(12) [27]

where u is the velocity vector.

The aim of the project was to correctly model the typical geometry of a narrow

groove pipeweld. Additional suitable boundary conditions were then set to allow

evaluation of thermal cycles due to an applied heat source. Figure 12shows the

dimensions of the joint that was modelled. The bevel angle was 5.

Figure 12: Typical groove geometry

The actual weld is completed in a number of separate weld passes. Therefore it was

decided that a separated model would be setup for each weld pass. Each model

would have different groove height and width dimensions, due to the amount of

weld deposited in the groove, in addition to different heat input and travel speeds.

The boundary conditions would be identical for all of the models. The model wouldsimplify the welded components by not considering weld metal and base metal

separately. Instead the entire volume would be considered as one homogeneous

volume with the same material properties.

Modelling the Geometry

I t was decided from the outset that the best way to model the geometry in

COMSOL was to use a scripting language. The COMSOL script is a language that

5.00

9.00

22.8 All measurements in mm


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allows the user to write code to be implemented in COMSOL . Using a COMSOL

script the user can actually specify the complete model, from the geometry to the

visualisation parameters of the solution.

The advantage of using a script to build the geometry is that, should the user wish

to change the dimensions of a model, it can be done by merely changing a pre-

defined variable in the script. Without a script the complete model must be rebuilt

from scratch for each change in geometry. The time to write the script was,

therefore, easily less than the time to make any changes to model geometries

further down the line.

The model geometry is defined in terms of plate size (length, width and thickness)

in addition to the groove dimensions. The dimensions of the groove are shown in

figure 13. The input variables for the model geometry are:

plate_t - Plate thickness in metresplate_l - Plate length in metres (actually width in model)plate_w - Plate width in metres (actually length in model)back_t - From groove base to bottom of the model inmetresbevel_deg - Bevel anglegrve_botdim - Width of the groove at the lowest point

The script uses the above input parameters to calculate the other geometrydimensions as follows:

grve_ht = plate_t - back_t; - Groove heightbevel_rad = bevel_deg*(pi/180); - Bevel angle in radiansgrve_topdim = (grve_ht*tan(bevel_rad))+grve_botdim; - Groove topdimension

The calculated variables are used as coordinates to specify the geometry

automatically once the COMSOL script is executed. Due to symmetry only half of

the groove geometry needs to be created, as the other half would be redundant.

This also means less computation is required to solve the model.

I t should be noted the zero reference height, or zero position on the Z axis, is

always the bottom of the groove. The zero position therefore moves as the height of

the groove is varied. This was done to aid positioning of the heat source model to a

simple reference plane.


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Figure 13: Model geometry dimensions


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For characterisation of the multipass weld 5 models were developed, each to model

a single pass. Accurate dimensions of the groove geometry could not be specified

until experimental results had been collected from actual weld tests.

Model length was varied depending on the temperature profile time required. To

obtain a time from the point of heating, the distance from the heat source was used

in conjunction with the travel speed.

The COMSOL script file that creates the mesh not only specifies the grooved

sample dimensions but also defines a region in the groove where the heat source is

situated and is used to simulate insulation of the weld pool from heat losses to the

atmosphere. The setting of the boundary conditions is described in more detail in a

subsequent section. To create this geometry two semi-ellipse shapes were modelled

in COMSOL and applied to the groove geometry. The COMSOL model file can be

used vary the size of this insulation shape by varying the size of the input

variables.

Heat Source Modelling

The literature review showed that correct characterisation of the heat source

influences greatly the final accuracy of the welding model. For arc welding the

most common form of heat source model is the Goldak Double-Ellipsoidal model.

The model is made up from two semi-ellipsoids, one at the front and one at the

rear. Figure 14 shows the configuration of the standard heat source model.

Dimensions of the model in figure 14 correspond to the geometric coefficients in the

following equations:

( )

2 2 26 3

, , exp 3 3 3f

ff

R Q x y zq x y z

c a babc

= (13) for the front

( )

2 2 26 3

, , exp 3 3 3b

bb

R Q x y zq x y z

c a babc

=

(14) for the rear


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where Q is the total heat input from the welding arc. The two equations must be

balanced by the quantity R so that R f+ Rb = 2

The project aim is to model Tandem Pulsed Gas Metal Arc Welding, which had

some big implications on the choice of heat source model. I t has previously been

shown that there is not a great deal of published literature available with regards

to modelling the tandem arc process. Even though there are two arcs present in the

process, the choice was made to create a model with only one Goldak type heat

source. The reasoning was that the main input variables for such a model are

based on weld pool dimensions, and the tandem process has one weld pool even

though two electrodes feed the same weld pool.

The pulsed nature of the process was not seen to influence the heat source model in

terms of the concept used, but merely affect the heat input in the model and

therefore possibly the weld pool dimensions.

Figure 14: Heat source dimensions

Narrow groove welding is an automated process. Part of the automation of the

process is utilisation of torch oscillation. The oscillation of the torch allows the weld

to be completed in less pass,s as more weld metal can be deposited for each pass.

A transient model could be setup in COMSOL whereby the heat source would


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follow a designated path. This path could be a straight line, or it could be a sine

wave along the length of the groove geometry. This type of analysis would certainly

be interesting to run, but due to the complex nature would take a long time to

produce a solution. The chosen steady-state model could not produce a heat source

that moves in such a way. To simplify the model, therefore the approach used was

to adopt a modified heat source model that takes into account the torch oscillation.

The model proposed by Sabapathy (25), documented in the literature review, was

investigated. The model is a modification of the Goldak heat source model, with the

power of the width component varied to spread the heat source in the direction of

oscillation. The general form of the model:

( )1 2 3

, , exp 3 3 3

n n n

fx y zq x y z Qa b c

=

(15) [25]

Which was modified to:

( )

2 10 2

, , exp 3 3 3f

f

EIr x y zq x y z

R c a b

= (16)

for the front of the heat source model and

( )

2 10 2

, , exp 3 3 3b

b

x y zEIrq x y z R c a b

= (17)

for the rear of the model.

The value of 10 for the power of y dimension was chosen as it produced a

satisfactory shape that approximated an ellipse with a degree of oscillation.

Figures 15-16 show the comparison of heat flux distribution between the original

Goldak heat source model and the new proposed model.


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Figure 15: Distributed heat flux of Goldak heat source

Figure 16: Distributed heat flux of modified heat source

Figure 17 shows how the shape of the model is affected as the y dimension power is

changed from its original value of n=2 to n=10. The width and height of the model


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is also increased from 4 to 6 in the diagram to further highlight the difference

between the two models. I t can be seen that the proposed model could be used to

characterise a heat source that is being oscillated in the y axis direction.

Figure 17: Heat source shape comparison

Equations 16-17 contain the term

EIr

R

(18)

where is the thermal efficiency of the process, E is the welding voltage, I is the

welding current, r is the balance variable between front and back sources and R is

the reduction factor.

The total heat input due to welding is equal to EI , whereby the power input is

reduced due to thermal inefficiencies of the welding arc. These inefficiencies

manifest themselves in heat losses to the surroundings during welding. The factor

of R must be determined depending on the size of the heat source model and

effectively modifies the expression in the model so that the heat input is no more

than the available power input from the welding power supply. In order to set this

correction factor the integral of both expressions 16 & 17 must be taken over the

volume of the heat source that is contained within the plate geometry. The value of

R must be changed until the integral of the expression, which represents the total

heat input, matches the value ofEI .


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The placement of the heat source is on the zero line of the model. This puts the

heat source at the centre of the groove geometry. F igure 18 shows the groove

geometry with the heat source applied to the edge of the groove face.

Figure 18: Heat source located in the groove

The COMSOL script file defines the size of the heat source using the following

variables:

gold_a = grve_botdim+0.001; - Heat source widthgold_b = - Heat source depthgold_cf = - Heat source front lengthgold_cb = - Heat source rear lengthgold_bt = - Heat source insulation height

The width of the heat source was defined as the width of the groove +1mm. This

means that the heat source protrudes into the side of the groove, thought to better

characterise the effect of arc oscillation during welding.


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Figure 19: Heat source applied to top of deposited weld

Figure 19 shows that for each weld pass the heat source model was defined as

having maximum heat flux at the upper edge of the groove geometry. This

corresponds to top of the weld metal deposited during the pass being modelled and

may be unrealistic in terms of actual heat input and metal deposition during

welding. The heat source model also has heat flux above the reference in addition

to below the reference plane (the top surface of the aforementioned weld). This

allows a heat source boundary to be produced as it is shown in the diagram. It is

thought this is quite satisfactory for characterising the actual flow during narrow

gap welding.

Model Subdomain & Boundary Conditions

The subdomain settings are those that describe the properties of the created

geometry. The heat equation that describes the subdomain used is:

( ). .pk T Q C u T = (19) [27]

where k is thermal conductivity, is density, Cp is specific heat capacity, Q is heat

input and u is speed.

These properties are mainly material properties, which will be discussed in

greater detail in a separate section. The Q term is where the heat input can be

expressed and is in the form of an expression of volumetric heat flux distributed


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through the volume of x, y and z. The exact equation used for the heat source is

discussed in a previous section.

The travel speed, u, was defined depending on the welding test or pass number in

the mutlipass weld. The initial temperature for the subdomain was set to ambient

temperature of 293 degrees Kelvin.

Boundary conditions are a compromise between an accurate definition of the

problem and many simplifications to create a workable model. The weld pool

dynamics, for example, are a very complex set of interactions. Modelling such

behaviour for the purposes of thermal profiles would be extremely difficult. I t is

obviously extremely important, however, to use correct boundary conditions where

possible.

Given that the model is essentially a homogenous solid the boundary conditions are

external boundary conditions only. The model uses 5 different boundary conditions

applied to the 11 boundary faces of the geometry.

Prescribed temperaturewas set for the front face of the model, shown in figure 20.

This boundary condition sets the boundary to a known temperature, which in this

case is the ambient temperature of the sample 293K.

Insulation or symmetry specifies where the domain is well insulated, or can reduce

model size due to symmetry.

( ). 0pn k T C uT + = (20) [27]where n is the normal vector to the direction of heat flow.

The above equation shows that there is no heat transfer across the specified

boundary. This condition was set for the surfaces shown in figure 23. The surface

at the origin of the axes is only there due to a reduction in size of the model due to

symmetry. For that reason symmetry or insulation boundary condition was

applied. The far surface in figure 23, furthest from the origin, has the insulation

boundary condition also. Strictly speaking this may not be correct, but was set due

to the large size of sample to be modelled. As the welding direction is parallel to

this face, and the heat flux does not reach that face, the effect of this boundary

condition is highly limited.


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Figure 20: Prescribed temperature boundary condition Figure 21: Top surface heat loss boundary condition

Figure 22: Bottom surface heat loss boundary condition Figure 23: Thermal insulation & symmetry boundary condition


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Figure 24: Convective flux boundary condition

Thermal insulation was also set for the two faces covering the location of the heat

source. This was done so that no heat losses could exist at the position of the heat

source. In reality the intense nature of the welding arc would preve

Nstone Thesis[1]

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Transcript of Nstone Thesis[1]