Numerical simulation of temperature distribution and residual stress in TIG welding of stainless-steel single-pass flange butt joint using finite element analysis

Hitesh Arora; Rajeev Kumar; Piyush Gulati; Shubham Sharma; Shashi Prakash Dwivedi; Ambuj Saxena; Abhinav Kumar; Kuldeep Sharma; Dražan Kozak; Anica Hunjet; Mohamed Abbas

doi:10.1515/htmp-2024-0015

Article Open Access

Numerical simulation of temperature distribution and residual stress in TIG welding of stainless-steel single-pass flange butt joint using finite element analysis

Hitesh Arora , Rajeev Kumar , Piyush Gulati , Shubham Sharma , Shashi Prakash Dwivedi , Ambuj Saxena , Abhinav Kumar , Kuldeep Sharma , Dražan Kozak , Anica Hunjet and Mohamed Abbas

Published/Copyright: November 28, 2024

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From the journal High Temperature Materials and Processes Volume 43 Issue 1

Abstract

Controlling defects such as deformation in the weld joint and the residual or superfluous stresses due to tungsten inert gas (TIG) welding or arc welding is a major concern for many industries like aeronautical, automobiles, nuclear or atomic power plants, crude oil or fossil fuel industries where pipes are in use and circumferential welding is done. Arc welding is a metal joining process, and TIG welding is applied to many industrial sectors that require high-quality welding. Simulation has been done on single-pass TIG welding on the Flange pipe of SS316 to evaluate transient temperature, residual stresses, and distortion. First, a 3D model is developed and assembled in SolidWorks. Second, in an MSC Patran, preprocessing of the FE model is done. Finally, in MSC Marc, thermal and mechanical simulation is performed. Based on this simulation, the accuracy of welding of the flange–butt joint made of SS316 is validated. In this study, the information regarding simulation of temperature dispensation and residual or superfluous stresses is done on the flange–butt joint, and it found the stresses are compressive at the weld bead area, and along the transverse direction, stresses changed to the tensile. The experimental data show that the steep curve at 0.00 mm represents a maximum temperature near the weld path at approximately 2,352°C, and the slant curve shows the far away points from the weld path. Comparing it with FE analysis, the maximum temperature attained was around 2,539°C. An approximate deviation of 7.365% was observed. The results of the study will provide experimental and simulation analyses for the welding of pipes of stainless steel for the transportation of oil and gases in the petroleum industries.

Keywords: finite element; temperature fields; numerical simulation; welding residual stresses

1 Introduction

Welding is a very well-known fabrication process in which two or multiple parts of metals are joined or fused by using heat, pressure, or both, forming a weld joint when the welded parts are cooled. Mostly, it is used to weld metals of the same type or may be different, but it can be done on both wood and thermoplastics. Welding is an efficient metal joining process, which makes it one of the most reliable joining processes and is also used in various industries. In industries, pipelines are also known as the arteries of industries, and through these arteries, various substances flow, like solids, liquids, semi-fluids, vapor, and gases, in the required direction or place as guided by the controller. Sometimes, these pipes used in industries have to go through intense stresses that are produced by many parameters, such as sudden changes in pressure, temperature, flow, or maybe a combination of different processes. These stresses cause significant damage to the pipes, mostly in distorted areas caused by corrosion, erosion, and it also affects the region of the welded area having low strength because the residual stress is produced while welding the pipes. Welding residual stresses, as well as welding the distortion left in the metal after welding, play an important role in the dependable design of the welded component and junctions or joints [1].

The butt–weld joint having a circumferential structure is a very usual type of link found in SS piping systems used in atomic power plants [2]. In these types of systems where piping is involved, the butt–weld joint is mainly constructed with various weld passes because of the relatively larger wall thickness. While performing the welding process, the regions that are present very close to the weld path undergo many thermal cycles. These thermal cycles create irregular heating and cooling effects inside the material, which generate strain, which always induces permanent distortion as well as superfluous stresses in the weldment during the heating phase. While assessing the risk for growth of defects such as surface flaws in piping systems, the welding residual stress may give a larger contribution to the total stress field than the stress caused by design loads [3], which makes the residual stress a major concern area in the welding industry and nowadays it becomes the major foreboding of the welding industry. The residual or superfluous stresses present in the metal can also be harmful to the welded product’s performance. Tensile superfluous stresses present in metals are detrimental. It can increase the chance of a weld to stress corrosion, rupture, cleave, cracking, fatigue damage, and fracture [4]. To quantify the degradation of mechanical properties of the weld material, thermal and structural analyses were carried out using the numerical method, and it was found that maintaining low but sufficient high welding power helps to minimize excessive temperature rise in the base metal and improves stress distribution along the welding line, which in turn mitigates the degradation of tensile strength and other mechanical properties.

“Sometimes the transportation of materials like crude oil or natural gas has to be continuous for very far distances example, for thousands of miles across the countries, which is only possible by pipelines (Ernest Holmes et al. 1973)” [5]. Also, these pipelines have to pass through various toxic conditions or environments while carrying different types of materials like acids, alkalis, etc., which can be harmful. If leakage occurs, it can produce diverse problems that can cause hygiene or health issues, heat and cold losses, etc. For many years, the industries and the governments of various countries have increasingly shown their concern about the safety of pipes or the protection of pipelines [6].

However, the major problems in welded structures are the non-uniform heating and residual stresses generated due to welding, which can result in cracks, fatigue, and even failure of the whole flange-pipe butt joint assembly. These are major reasons why the management of residual stresses is necessary for the arc (tungsten inert gas [TIG]) welding process [7,8]. Internal residual stresses induced on welded joints can be determined by experiments as well as by simulation or numerical methods [9]. The experimental methods need proper welding equipment with proper voltage, current, and necessary safety, along with sufficient time to execute the experiments. In contrast to the experimental procedure, simulation developed upon the finite element (FE) technique performed in MSC Marc or any numerical simulation environment is well-executed and tested several times for faultless or precise temperature distribution; the welding residual stresses in welding mechanization are also economically efficient [10].

This article discusses the challenges faced while welding aluminum alloys fused using GTA and GMA weldings, as well as their solutions. Aluminum alloy has more welding issues than other materials due to its superior heat conductivity, solidification shrinkage, oxide development, and thermal expansion coefficient. The link between welding parameters, the quality of the weld, and the mechanical properties of the joint is complex and non-linear [11]. Examples of such factors include the welding current, welding voltage, shield gas flow rate, welding speed, and torch placement. Pulsing the current, post-weld heat treatment, proportionate mixing of the shielding gases, quick shielding gas injection, and many more methods are recommended for better weld quality and joint strength. GMA and GTA welding of different aluminum alloys present greater challenges since different materials have different chemical and thermal properties [12]. A UHS single-pass butt-welded joint with filler wire of ER307Si was fabricated, and thermal cycles at specific points were measured by thermocouples. After welding, relevant measurements of residual stress, deformation, microstructures, and hardness were carried out [13]. A butt-welded joint between the P92 ferritic steel and SUS304 austenitic stainless steel was fabricated with a nickel-based filler material [14].

A combination of experimental and numerical simulations was used to examine the temperature and weld residual stress distribution in the repair zone under various welding repair procedures in order to determine the most appropriate weld cladding repair process parameters. The findings show that the blade and shroud’s temperature and welding residual stress distributions are not symmetrical, the blade side has a quicker rate of temperature conduction, and the high-stress zone is primarily contained inside the weld and its surrounding region. The maximal value of welding residual stress reaches a minimum of 796.29 MPa at preheating temperatures of up to 150°C. The distribution trend of welding residual stresses can be altered by the welding sequence [15].

Pertaining to the fusion welding of aluminum alloys using GTA and GMA welding, the study identified a research gap. This study examines the various challenges that are commonly associated with aluminum alloys, including but not limited to heat conductivity, solidification shrinkage, oxide formation, and thermal expansion coefficient. In addition to emphasizing the need for effective solutions to these challenges, the complexity of the relationship between welding parameters and weld quality is emphasized. Determining the optimal parameters for the weld cladding repair process is the objective of this research. The findings demonstrate an asymmetry in the distributions of temperature and stress, which has significant consequences for the optimization of the repair process. The scientific contributions of the article have been elucidated.

From scientific contributions and in terms of the analysis and simulation of TIG welding on flange pipe, a finite element analysis (FEA) is employed to validate a three-dimensional model of the SS316 flange pipe. In order to determine the transient temperature, residual stresses, and distortion during single-pass TIG welding, MSC Patran and MSC Marc are utilized to conduct thermal and mechanical simulations. To determine temperature distribution and history, the simulation incorporates transient thermal analysis. Weld-induced stresses and deformations are examined by the implementation of structural analysis.

In comparison with the experimental data, the characteristics and temperature profiles of the welded structure are determined by the collection of experimental data. A comprehensive evaluation of the simulation’s accuracy is obtained through a comparative analysis of experimental data and FEA. The analysis demonstrates that there is a transition from compressive stresses in the vicinity of the weld bead to tensile stresses in the transverse direction.

To enhance the quality of welds and the strength of joints when welding aluminum alloys, this study proposes a range of techniques. It is advisable to employ post-weld thermal treatment, pulse the current, and proportionally mix shielding gases. Particular investigations are detailed, including the use of nickel-based filler material for dissimilar metal joints and butt–welding joints incorporating ER307Si filler wires.

By determining the deformation and stresses, compressive stresses are identified in the vicinity of the weld bead and transformed into tensile stresses in the transverse direction, as residual stresses in the welded flange–butt joint are examined. With regard to the material’s expansion and contraction during and after the welding process, deformation and stresses are described.

In accordance with the implementation in the petroleum sectors, the findings of this research will enhance comprehension regarding the use of stainless steel welding pipes in the petroleum and gas transportation sectors.

Thus, the findings of this study are intended to offer significant insights that can be used to enhance the welding method, thus ensuring the structural integrity and functionality of rigorous industrial applications.

2 FE method

The FE simulation of the flange–butt joint for an FE model that is thermo-mechanical is performed. MSC Patran and MSC Marc were used to generate thermal and mechanical analysis and models have been designed in SolidWorks [16].

Node, messing, and pre-processing, along with defining metal properties, have been performed in the MSC Patran post model and have been imported from SolidWorks. The transient thermal cycle and temperature profile are calculated by the transient thermal analysis method. The results of the thermal analysis are used as the thermal loads, and weld-induced stresses are analyzed by structural analysis.

2.1 FE model

For the flange pipe, single-pass circumferential welding performed on the FE model of the flange pipe is designed as shown in Figure 1.

Figure 1

FE model of the pipe with meshing.

The metal used to design the flange and pipe in the model is SS 316. The flange has an internal diameter of 80 mm, an external diameter of 104 mm, and a length of 100 mm. The length of one part of the pipe, which is similar to the other, is 97.50 mm with an internal diameter of 80 mm and an external diameter of 84 mm, resulting in the thickness of the pipe throughout being 2 mm. Quadrilateral 4 with one degree of freedom (DOF) – temperature – is the type of element used in the thermal analysis, and Quadrilateral 4 with three DOF – translation in the x, y, and z directions – is the type of element used in structural analysis. The element size is 0.25 mm in the transverse direction to the weld bead in the area of the weld bead and the HAZ. This will give precise data but will take some time as there are more nodes and elements with smaller elements [17].

The analysis overall consists of two steps: the first is transient thermal analysis considering the temperature distribution and its history, and the second step is the thermal load used for structural analysis in the residual stresses field. The element size varies with decreasing size as one comes closer to the weld path.

The thermostructural properties of SS-316, which is both a weld metal and flange pipe base metal, are listed in Table 1, with the yield strength of 1,490 MPa of the material.

Table 1

Mechanical and thermophysical properties of SS316 [17]

Temperature ( K )	Specific heat (J·(kg·K)⁻¹)	Conductivity (J·(s·cm·°C)⁻¹)	Density (kg·m⁻³)	Thermal expansion coefficient ( ° C ‒ 1 )	Young’s modulus (MPa)	Poisson’s ratio
298	442	0.154	787,000	1.62 × 10⁻⁵	205,600	0.29535
373	473	0.166	783,000	1.65 × 10⁻⁵	199,400	0.29928
473	501	0.179	797,000	1.68 × 10⁻⁵	192,700	0.30364
673	559	0.205	771,000	1.73 × 10⁻⁵	177,800	0.31236
773	597	0.218	767,000	1.75 × 10⁻⁵	168,500	0.31671
873	648	0.230	763,000	1.78 × 10⁻⁵	158,400	0.32107
1073	621	0.256	756,000	1.81 × 10⁻⁵	134,700	0.33261
1273	634	0.281	746,000	1.84 × 10⁻⁵	117,400	0.34203
1473	711	0.307	735,000	1.90 × 10⁻⁵	100,500	0.35087
1773	863	0.342	725,000	2.05 × 10⁻⁵	57,300	0.36021
3273	863	0.342	725,000	2.05 × 10⁻⁵	57,300	0.36021

2.2 Thermal analysis

The 3D flange-pipe FE model is shown in Figure 1, with 56,720 bricks and 71,600 nodes. Missing near and on the weld path or weld center is comparatively constricted with respect to an area elsewhere or apart from the weld path (Figure 2).

Figure 2

Weld path.

The temperature around the welding must be within limits to manage metallographic changes, distortion of the structure and stresses produced, which are the outcome of circumferential welding done on the flange pipe. During welding, large changes in the temperature field are observed, resulting in the form of locked-in stresses in the form of a hoop, radial, and axial are generated in the welded flange-pipe structure.

Conduction of heat is the key element for the traveling of heat into the welded structure and is given by the heat flow equation as follows [17]:

(1) ρ c d T d t = d q x d x + d q y d x + d q z d x − ρ c V x d T d x + V y d T d y + V z d T d z + Q ,

(2) q i = k d T d i ,

where i are the coordinates of x, y, and z, and they can be replaced with the respective values of x, y, and z. Replacing Fourier’s law (equation (2)) in equation (1) gives the new heat transfer relation as [18]

(3) ρ c d T d t = d d x k d T d x + d d y k d T d y + d d z k d T d z − ρ c V x d T d x + V y d T d y + V z d T d z + Q .

A double-ellipsoidal (Table 2) is expressed by the given equations for the front and rear quadrants after measuring the dimension of the tack weld bead, equations (4) and (5), respectively, in the form of x, y, and z, which can also be termed the cartesian coordinate system:

(4) q f ( x , y , z ) = 6 √ 3 f f Q ab c f π √ π e − 3 x 2 / a 2 e − 3 y 2 / b 2 e − 3 z 2 / c 2 ,

(5) q f ( x , y , z ) = 6 √ 3 f r Q ab c r π √ π e − 3 x 2 / a 2 e − 3 y 2 / b 2 e − 3 z 2 / c 2 .

Table 2

Heat source values

Parameters	Values (mm)
Depth	2
Width	5
Ellipsoidal length front	5
Ellipsoidal length rear	11.5

In equations (4) and (5), Q = η V I is the input power of source heat for welding for flange pipe circumferential welding. Q is the product of η (arc efficiency) with V (voltage) and I (current) defined as the power of the heat source for TIG welding.

Assuming the efficiency η of the arc welding process(TIG) is 70%, the other losses can be encountered with a power of 1,200 W:

(6) Q = η VI ,

where f _f is the fraction of the total heat and f _r is the total heat in the front and rear quadrants, respectively, and f _f + f _r = 2.0. Here, a and b hold similar values for both front and rear quadrants, but c has somewhat different values for both front and rear ellipsoidal c _f and c _r, respectively.

Heat losses occur in both radiation and heat transfer on welded surfaces in a significant manner. The overall temperature-dependent coefficient of heat transfer is given by the following equation [19]

(7) h = = 0.68 T × 10 − 8 W mm 2 0 < T < 500 o C = 0.231 T − 82.1 × 10 − 6 W mm 2 > 500 o C ,

(8) Q ( loss ) = q ( convection ) + q ( radiation ) .

Every element along the belt centerline must come in contact with the welding arc. The load step selection minimum criteria are given as follows [20]:

(9) Load s tep = t otal time of welding / no . o f elements on the circumference of the weld .

The welding process parameters are listed in Table 3.

Table 3

Welding process parameters

Welding parameters	Values
Current	90 A
Voltage	20 V
TIG welding efficiency	70%
Welding speed	2.5 mm·s⁻¹

2.3 Structural or mechanical analysis

The flange pipe FE model used in the thermal analysis is used again, and the thermal profile is the temperature history in making a key element, and the welding stresses are used as the thermal load.

Structural boundary conditions are shown in Figure 3, in which both the edges of the pipe are fixed, and the condition displacement in x, y, and z is 0. The number of nodes and elements taken during thermal analysis is tripled for the case of structural analysis. Solid-state phase change does not occur in the SS316 base metal of the flange pipe and the welding metal.

Figure 3

Flange-pipe with structural boundary conditions and the weld path.

The overall strain can be written by splitting its three components into elastic ( ε e ̇ ), plastic ( ε p ̇ ), and thermal ( ε th ̇ ) strain as

(10) ε ̇ = ε e ̇ + ε p ̇ + ε th ̇ .

The Young’s modulus and Poisson’s ratio of the metal are shown in Table 1. The yielding criteria for the thermal–structural material details are given by the following equation [21]:

(11) σ v = 1 / 2 [ ( σ x − σ y ) 2 + ( σ y − σ z ) 2 + ( σ z − σ x ) 2 ] .

3 Experiment

Two lengths of identical pipes with the same outside diameter (OD), internal diameter (ID), and thickness are the materials used in this experiment. The pipe was made of stainless steel 304. The SS 304 pipe(Figure 1) has an OD of 84 mm, an ID of 80 mm, and a thickness of 2 mm. ER 304 SS was the filler metal used in this experiment.

On the rotating jig-prepared configuration, pipes were placed perpendicular to the welding flame. The weld line’s center was where the torch was held. In this experiment, argon was used as the shielding gas. In this experiment, a rotational jig was employed to hold and rotate the pipe while performing customized orbital welding, as shown in Figure 4(a) and (b) shows the welded pipe. The welding machine was linked to the rotary jig. A motor with 900 rpm and 0.5 hp was used to turn the jig. By connecting this motor to the control unit, one can regulate the motor’s speed and obtain a minimum speed of 10 rpm. Following is how the welding heat input was calculated:

(12) Heat in put = VI 1,000 × S .

Figure 4

(a) Welding setup. (b) SS 304 thin pipe sample welded.

4 Results and discussion

4.1 Thermal analysis

With the increase in time, the temperature profiles are shown in Figures 5–9 at time intervals of t = 10.048, 30.144, 60.288, 90.432, 105.504 s, respectively. From Figures 5–9, it is very clear that on the weld path, different nodes have different temperatures with the movement of the arc. Arc makes an angle of 90° with the circumference of the flange pipe. Asymmetry in the temperature profile can be noticed with the welding axis [22,23,24,25]. The maximum temperature achieved for delivery in welding is near 2,352°C.

Figure 5

Temperature profile at 10.048 s.

Figure 6

Temperature profile at 30.144 s.

Figure 7

Temperature profile at 60.288 s.

Figure 8

Temperature profile at 90.432 s.

Figure 9

Temperature profile at 105.504 s.

As shown in Figure 10(a), the experimental data show that the steep curve at 0.00 mm represents the maximum temperature near the weld path, approximately at 2,352°C, and the slant curve shows the far away points from the weld path. Compared with FEA, the maximum temperature attained was around 2,539°C. The approximate deviation was observed at 7.365%.

Figure 10

(a) Transient thermal cycle from the point of start of welding (in mm) during the experiments. (b) Transient thermal cycle from the point of start of welding (in mm) in FEA.

Temperature profiles after cooling at 150.504 and 300.504 s are shown in Figures 11 and 12. Cooling begins just after welding is completed at 105.557 s. At the maximal temperature of 2352.82°C at 105.557 s, cooling is observed at temperatures as low as 25.1136°C at 150.504 s, with the weld path temperatures at 595.891°C and 32.3144°C at 300.504°C, with the weld path temperature at 208.132°C.

Figure 11

The temperature profile after cooling at 150.504 s.

Figure 12

The temperature profile after cooling at 300.504 s.

4.2 Mechanical or structural analysis

On the surface of the flange pipe, both inner and external types of stresses have been observed as compressive and tensile. This led to various temperature profiles at the length of the flange pipe surface on both the internal and external sides.

Once the arc passes through the circumferential weld path on the flange pipe high-temperature increase can be seen, leading it to expand along the weld path, and once the arc passes by, there is a sudden decrease in temperature, leading to a contraction in the weld path. This expansion and contraction results in tensile and compressive stresses as well [22,23].

Stresses along the three directions of the flange pipe or σ _x, i.e., the axial stresses contour plot is shown in Figure 13. The radial stresses (σ _y) contour plot is shown in Figure 14. The hoop residual (σ _z) stresses contour plot is shown in Figure 15.

Figure 13

σ _x axial stresses.

Figure 14

σ _y radial stresses.

Figure 15

σ _z hoop stresses.

The profile generated in the external surface of the weld due to σ _x, i.e., axial stresses, is presented in Figure 16, σ _y, i.e., radial stresses are presented in Figure 17, and σ _z, i.e., hoop residual stresses [24,25] are presented in Figure 18. The stresses are compressive at the weld bead area, and along the transverse direction, stresses changed to tensile. The most harmful residual stresses are σ _x axial stresses, which are utmost 350 MPa.

Figure 16

σ _x axial stresses on the external surface of the welded pipe.

Figure 17

σ _z radial stresses on the external surface of the welded pipe.

Figure 18

σ _y hoop residual stresses on the external surface of the welded pipe.

Experimental and numerical simulation analyses were performed in this study in order to understand the deformation and welding behavior of a flange pipe experiencing TIG welding. The following is a summary of the primary evidence and findings for welding deformation:

Experimental verification for welding deformation:

Model development and simulation: Solidworks was employed to develop a three-dimensional model of the SS316 flange pipe.

For the preprocessing of the FE model, MSC Patran was used.

Thermal and mechanical simulations were conducted using MSC Marc.
Temperature and stress distribution: This study is focused on the analysis of transient temperature, residual stresses, and distortion, which occurred throughout the process of single-pass TIG welding.

Experimental investigations revealed that the highest recorded temperature in the vicinity of the weld path was around 2,352°C.

A maximal temperature of 2,539°C was observed when the experimental data were compared with FEA, which revealed a deviation of approximately 7.365%.
Stress analysis: The analysis of stresses revealed the presence of compressive stresses in the vicinity of the weld bead, which transitioned to tensile stresses in the transverse direction.

At the outer surface of the welded pipe, the highest axial stresses (σ _x) were observed to be 350 MPa.

The investigation yielded valuable knowledge regarding the radial (σ _y) and hoop (σ _z) residual stresses.
Concluding the experimental phase: The validity of the FE model was established by comparing the temperature distributions of the simulation and the experiment.

In the vicinity of the weld path, compressive stresses were observed in addition to tensile stresses along the flange-pipe butt joint.

It is anticipated that the outcomes will aid in developing an understanding of the welding process utilized in the transportation of oil and gases through stainless steel pipelines.

Furthermore, in accordance with the comparative analysis from the prior studies, Sampath and Haribalaji aimed to optimize the welding parameters to achieve a balance between the “mechanical characteristics” and the “heat-affected zone (HAZ)” width [26]. The authors used an L27 orthogonal array of the Taguchi method to plan the experiments and used the MOORA technique to evaluate the “optimal welding factors.” The findings indicated that the optimal welding factors for the cryogenic FSW of AA2014 and AZ31B alloys were a rotational speed of 1,000 rpm, a traverse speed of 25 mm·min⁻¹, a tilt angle of 3°, and a tool offset of 0.4 mm. The authors concluded that cryogenic FSW could significantly enhance the physicomechanical characteristics and reduce the HAZ width of welded joints [26].

Das and Chakraborty compared the performance of different optimization techniques for the FSW of AA6061-T6 aluminum alloy [27]. The authors used the Taguchi method, response surface methodology (RSM), and hybrid-Taguchi methods to optimize the welding factors. The study aimed to identify the optimal welding parameters that would result in a high joint strength and a low porosity level. They used the signal-to-noise ratio to determine the quality characteristics. The results showed that the hybrid-Taguchi method outperformed the Taguchi method and RSM in terms of quality characteristics. The optimal welding parameters obtained using the hybrid-Taguchi method were a rotational speed of 1,000 rpm, a traverse speed of 50 mm·min⁻¹, a tilt angle of 2.5°, and a shoulder diameter of 20 mm. The authors concluded that the hybrid-Taguchi method could effectively optimize the FSW parameters and improve the quality of the welded joints [27].

Abd Elnabi et al. optimized the FSW process factors for dissimilar aluminum alloys using different Taguchi arrays [28]. The study aimed to optimize the welding parameters to achieve a high “joint strength” and a low “porosity level.” The authors used a Taguchi method to plan the experiments and used the “signal-to-noise ratio” to evaluate the “quality characteristics.” The findings showed that the “rotational speed” and “axial force” had the most substantial effect on the quality characteristics. The optimal welding parameters for the dissimilar aluminum alloys were a rotational speed of 800 rpm, a traverse speed of 80 mm·min⁻¹, and an axial force of 6 kN. The authors concluded that the Taguchi method could effectively optimize the FSW parameters and improve the quality of the welded joints. The results showed that the “axial force” had the most substantial impact on the weld strength. The optimal process parameters were found to be a tool rotational speed of 1,100 rpm, a welding speed of 30 mm·min⁻¹, and an axial force of 3.5 kN. The study concluded that the Taguchi method was effective in optimizing the FSW process factors for dissimilar Al alloys [28].

Nadikudi aimed to optimize the welding parameters to achieve high joint strength and a low HAZ width [29]. The authors used the Taguchi approach to plan the experiments and used the “signal-to-noise ratio” to evaluate the quality characteristics. The findings indicated that the “rotational speed” and “tool-traverse speed” had the most substantial influence on the quality characteristics. The results showed that the optimal process parameters were a rotational speed of 1,000 rpm tool, a welding speed of 200 mm·min⁻¹, and an axial force of 20 kN. The study concluded that the proposed approach was an efficient manner to optimize the process parameters of the FSW process for dissimilar materials [29].

Asadi et al. conducted experiments on aluminum alloy plates using the FSW method [30]. The welding parameters were varied to create different welding conditions, and the physicomechanical and microstructural characteristics of the welded joints were measured using various testing techniques.

The study used a multivariate optimization approach to find the optimal welding factors that can produce welded joints with the desired physicomechanical and microstructural characteristics. The optimization approach involved using a mathematical model to relate the welding parameters to the physicomechanical and microstructural characteristics of the welded joints [31–33].

The results showed that the multivariate optimization approach can successfully report the optimal welding factors that can produce welded joints with the desired physicomechanical and microstructural characteristics. The study also showed that the FSW method can produce welded joints with superior mechanical and microstructural properties compared to traditional welding methods.

Asadi et al. conducted experiments on AZ91 magnesium alloy plates using the FSW process [31]. The welding parameters were varied using the Taguchi method, which involves creating an orthogonal array of experiments that allows for the simultaneous optimization of multiple parameters [34–36].

The study used various testing techniques to determine the characteristics of the welded joints, including visual inspection, microstructural analysis, and tensile testing. The findings concluded that the Taguchi method can successfully optimize the welding parameters to produce high-quality welded joints with minimal defects [37–39].

The study found that the optimal welding parameters depend on the specific welding conditions, with different combinations of rotational speed, traverse speed, and axial force being optimal for different welding conditions [40,41]. The study also found that the Taguchi method can significantly reduce the number of experiments needed to find the optimal welding parameters, which can save time and resources in the optimization process [42–44].

Akbari et al. investigated the influences of process parameters on the “material-flow behavior” during welding [32]. The experimental work was conducted on dissimilar lap joints of aluminum and brass using a tool made of tungsten carbide. The process parameters were varied to create different welding conditions, and the “material-flow behavior” was observed using a high-speed camera [45,46].

The coupled Eulerian and Lagrangian methods were used to simulate the material flow behavior during welding. The method involves dividing the welding zone into two regions: an Eulerian region, where the material is treated as a continuum, and a Lagrangian region, where the material is treated as discrete particles. The two regions are coupled using a moving boundary interface [47–49].

The simulation results exhibited that the “material-flow behavior” during welding is affected by the process parameters, with higher rotational speeds leading to a more vigorous stirring of the material. The results also showed that the coupled Eulerian and Lagrangian methods can accurately predict the material flow behavior during welding [50–52].

Asadi et al. aimed to optimize the welding parameters to minimize the “residual stress” in the welded joints [33]. The experimental work was conducted on steel pipes of different materials, with varying levels of preheating and different numbers of weld passes. The residual stresses in the welded joints were measured using an “X-ray diffraction method.”

The results revealed that the “residual stress” in the welded joints is affected by the material type, preheating, and the number of weld passes. The study also found that increasing the preheating temperature and reducing the number of weld passes can reduce the “residual stress” in the welded joints.

Overall, these studies provide valuable insights into the parametric optimization of the FSW process for various materials and applications [53–55]. The findings exhibited that optimizing process variables like “tool rotational speed,” “welding speed,” and “axial force” can have considerable implications on the “weld strength and quality” [56–58]. The research gaps in the domain of FSW optimization include the need for further investigation into the influences of other process parameters like “tool design,” “material thickness,” and “tool offset” on the “weld strength and quality” [59,60]. The findings and results of these studies can be applied in various sectors like “the aerospace,” “automotive,” and “marine industries,” where the use of lightweight and higher-strength materials is crucial [61–63].

Hence, the summary has covered different aspects of the welding process, including modeling the material flow during welding, optimizing welding parameters to minimize residual stress and defects, and finding the optimal welding parameters to produce welded joints with desired mechanical and microstructural properties [64,65]. The studies demonstrate the importance of understanding the complex interactions between welding parameters and the resulting material properties [66,67]. In addition, there is a need for sophisticated modeling and optimization techniques to achieve optimal welding results [68].

5 Conclusions

In this study, a flange pipe 3D model is developed in Solidworks, keeping the metal as SS316, and the same model is prepared in MSC Patran and analyzed in MSC Marc for the thermal as well as mechanical behavior of the model while going through TIG welding. As per the outcomes of the analysis and results, we concluded the following.

The FE model is validated with the experiment. The validation was done by comparing the temperature distribution in the experiment and the FE model. The experimental data show the steep curve at 0.00 mm represents the maximum temperature near the weld path approximately at 2,352°C, and the slant curve shows the far away points from the weld path. While compared with FEA, the maximum temperature attained was around 2,539°C. The approximate deviation was observed at 7.365%. The rapid decrease in the value of temperature is seen in just a few seconds of welding on the weld path and near it, but contrary to that, a gradual or slower rate of temperature change is observed while we move elsewhere or apart from the weld path applicable at 10 mm onward. Tensile as well as compressive stresses are observed on the flange-pipe butt joint. Compressive stresses are present near the weld path, and while we move elsewhere or apart from the weld path tensile stresses are there. The results of the study provide experimental and simulation analysis for the welding of pipes of stainless steel for the transportation of oil and gases in the petroleum industries.

shubhamsharmacsirclri@gmail.com

Acknowledgments

The authors extend their appreciation to University Higher Education Fund for funding this research work under Research Support Program for Central labs at King Khalid University through the project number CL/CO/A/4.

Funding information: The authors extend their appreciation to University Higher Education Fund for funding this research work under Research Support Program for Central labs at King Khalid University through the project number CL/CO/A/4.
Author contributions: Conceptualization, HA, RK, PG, SS; methodology, HA, RK, PG, SS; formal analysis, HA, RK, PG, SS; investigation, HA, RK, PG, SS; writing – original draft preparation, HA, RK, PG, SS; writing – review and editing, SS, SPD, AS, AK, KS, DK, AC, MA; supervision, SS, SPD, AS, AK, KS, DK, AC, MA; project administration, SS, SPD, AS, AK, KS, DK, AC, MA; funding acquisition, SS, SPD, AS, AK, KS, DK, AC, MA. All authors have read and agreed to the published version of the manuscript.
Conflict of interest: The authors state no conflict of interest.
Data availability statement: All the data that were used to support this study are available in this manuscript.

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Received: 2023-08-28

Revised: 2024-02-07

Accepted: 2024-04-28

Published Online: 2024-11-28

This work is licensed under the Creative Commons Attribution 4.0 International License.

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https://doi.org/10.1515/htmp-2024-0015

Keywords for this article

finite element; temperature fields; numerical simulation; welding residual stresses

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