1. Introduction
Electron Beam Welding (EBW) is a fusion welding process that utilizes a concentrated beam of high velocity electrons over a narrow area of the joining materials. The kinetic energy of the electrons is converted to thermal energy upon striking the joining surfaces, causing the materials to melt and then solidify to form a weld joint1). Due to high energy density, EBW requires a lower volume of molten metal for joining components, resulting in lower energy input and higher velocity. The low energy input of EBW also reduces the heat-affected zone (HAZ) and distortions compared to high heat input processes like arc welding1). EBW is conducted in a vacuum environment, which provides protection against oxidation, porosity, and other contaminations2). This method sets a benchmark for achieving superior quality and efficiency in joining components or materials commonly found in engineering sectors.
This welding technique has become essential in various engineering industries, including aeronautical, aerospace, nuclear, and petrochemical sectors, due to its ability to produce high-quality, precise, and efficient welds2-5). Most of the engineering components in nuclear power plants are thick sections in the form of pipes, where safety is a prime concern. The fabrication of these critical nuclear components requires full penetration weld joints with minimal distortion and residual stresses. These weld joints are of paramount importance as they directly impact equipment safety. Therefore, optimizing welding parameters is necessary to achieve full penetration weld joints with minimal weld pool size, residual stresses, and HAZ.
In thick pipe EBW, a high-power density electron beam is produced, which causes material vaporization and creates a keyhole through the specimen thickness. The molten material flow around the electron beam then closes the gap in the welding joint6). Currently, suitable welding parameters are often defined based on experience and testing trials on actual or similar materials/components. Numerical simulations of the weld joint can help reduce testing trials, thereby saving time and costs. These simulations also aid in understanding and predicting the evolution of residual stresses and distortions in thick pipe weld joints. Moreover, they facilitate the optimization of weld parameters, further reducing the time and cost associated with welding. However, the numerical simulations of thick pipe EBW encounter several challenges due to the complex physics involved in the welding process.
Numerous studies have employed Finite Element (FE) analysis techniques to characterize the distribution of residual stresses, HAZ, and distortion in welded joints. For example, Lacki et al.7) performed a theoretical and experimental analysis of thermo-mechanical phenomena during the EBW process. Akbari et al.8) used FE techniques to predict the residual stresses in dissimilar pipes made of A240-TP304 stainless steel and A-106-B carbon steel welded by the arc welding process. Wang et al.9) simulated the shielded metal arc welding of pipes and studied the behavior of residual stresses in the pipe. These studies show that the axial residual stresses at the weld center are tensile on the inner surface and compressive on the outer surface of the pipe. The hoop and axial residual stresses are tensile at the weld center, transitioning to compressive and then zero as one moves away from the weld center on the pipe’s inner surface. Conversely, the axial residual stresses are compressive at the weld center, changing to tensile and then zero as one moves away from the weld center on the pipe’s outer surface7-9). All these studies focused on the FE simulations of weld joints prepared by conventional welding techniques, comparing the results with experiments, and predicting the distribution of residual stresses and HAZ. Additionally, the author is not aware of any previous research that has conducted a comparative analysis of EB welding processes for thick pipe joints or optimized the electron beam welding for 13.5 mm thick pipes made of stainless-steel SA312 TP 304L.
In the present study, experimental and numerical analyses were carried out to develop optimal welding parameters for joining 13.5 mm thick pipes made of SA312 TP304L stainless steel using the EBW process. The pipe weld joint was prepared using EBW parameters selected based on experience and literature, followed by measurements of deformation and weld pool geometry. The pipe weld joint was then numerically simulated and analyzed. Predicted weld pool geometry and deformations from the numerical analysis were compared with experimental measurements. The reasonable matching of experimental and numerical results confirms the validity of the numerical analysis procedure and results.
Both experimental and numerical results for the pipe weld joint showed overpenetration of the weld pool. This overpenetration resulted in a larger weld area, which generated a higher HAZ, increased residual stresses, and greater shrinkage in the pipe. To mitigate the overpenetration of the electron beam, efforts were made to optimize the welding parameters using numerical analysis. The optimized weld parameters were then used to predict the weld pool size, deformation, HAZ, and residual stresses in the weld joint through numerical simulations. These predictions were compared with experimental data, and the comparison validates the optimization of the pipe welding process. Through this approach, the optimal EBW input power was determined to be 600 J/mm for achieving full penetration in a perfect butt weld of 13.5 mm thick pipes made of 304L stainless steel, with minimal residual stress and HAZ.
2. Experimental Details
2.1 Pipe weld configuration
Pipe of outer diameter of 168.50 mm and a thickness of 13.50 mm made of austenitic stainless-steel Type 304L have been used for carrying out welding. The chemical compositions of the plate and pipe materials are given in Table 1. The edges of the pipes have been machined with accuracy of 0.05mm, ensuring that the cross-sections were parallel to each other with no gap. The inner diameter of the matting surface of joint was supported by a backup ring with a thickness of 10.50 mm and a width of 17.00 mm, which was tacked using gas tungsten arc welding (GTAW) at four locations. Back plate has been used to take care of over penetration and good surface finish of the joint. The sketch of the joint with fit-up has been shown in Fig. 1. During the assembly process, foreign materials such as oil and oxide scales were removed from the joint, ensuring that the plates were closely matched with an assembly clearance of 0.05 mm. One end of the assembled pipe was fixed in the EBW machine chuck, while the other end was free to move. Eight points (A1, B1, C1, D1 on ring-1 outer surface and A2, B2, C2, D2 on ring-2 outer surface) were marked at 90-degree intervals along the circumference for measurement of shrinkage, as illustrated in Fig. 1 (a and b).
Table 1
Chemical composition of pipe materials (in wt. %)10)
| C | Mn | Mo | S | P | Si | N | Cr | Ni | Fe |
|---|---|---|---|---|---|---|---|---|---|
| 0.036 | 1.79 | 0.152 | 0.015 | 0.042 | 0.363 | 0.1 | 18.06 | 8.062 | Bal. |
2.2 Welding of pipes
Welding of pipes have been carried out using the EBW process. Two set of pipe weld joints have been manufactured with two different beam power. The weld joints have been referred as pipe weld joint-1 and pipe weld joint-2. The welding input parameters for each joint are provided in Table 2. The electron beam is well-focused on the pipe weld joint by optimizing the focusing current. During the welding of stainless steel, gun chamber vacuum was set to 10-6 mbar and welding chamber vacuum was set to 10-5 mbar for maintaining the quality and stability of the electron beam. The actual pipe weld joints are shown in Fig. 2.
2.3 Pipe weld pool geometry
The sample pieces from the welded pipes were cut across the thickness and subjected to chemical etching using a mixture of distilled water, nitric acid, and hydrochloric acid. This process allowed the weld pool profile to be differentiated from the base metal. The weld pool profiles after chemical etching are shown in Fig. 3 (a and b).
The measured dimensions of the weld pool size for pipe weld joints-1 and 2 are presented in Fig. 3 (a and b) and zoomed view of weld pool dimensions are shown in Fig. 10 (a and b). Observations from the weld pool shape reveal that the width of the weld pool vary with increase in the depth. Areas near the surface of the weld pool exhibit a teardrop shape, while the weld width at the top portion of the weld pool is higher and gradually transitions into a conical shape. (This conical shape is due to the intense energy of the EBW process, which causes some of the material at the point of impact to vaporize. This vaporization creates a keyhole effect, where the electron beam drills into the material, forming a conical cavity). Proper fusion of the pipes’ mating surfaces across the thickness was achieved. The weld pool width for pipe joint-1 is 1.49 mm at the root of the pipe joint. The higher width is due to the over penetration of the beam in the backup ring. This indicates that the higher beam power has been used in the welding of pipes.
To address the overpenetration and excessive weld pool area, second pipe weld joint was prepared with a lower beam power input, referred to as pipe weld joint-2. The welding parameters for pipe weld joint-2 are detailed in Table 2. The weld pool profile of pipe weld joint 2 after etching is shown in Fig. 3(b). Observations from pipe weld joint-2 indicate proper fusion of the pipes mating surfaces. The weld pool geometry shows a reduced weld width of 1.18 mm at the root compared to 1.49 mm in pipe weld joint-1. The higher width is due to the over penetration of the beam in the backup ring. This also indicates that beam power is still higher in the pipe weld joint-2. This calls for optimization or minimization of beam power input during welding of stainless-steel pipes. These two pipe weld joints have been numerically simulated, and their analyses are detailed in subsequent section 3.0.
2.4 Deformation/Shrinkage measurements
Deformation/shrinkage occur during welding of pipes. This is due to the contraction of weld pool during solidification of the molten material. The distance between points A1-A2, B1-B2, C1-C2 and D1-D2 were measured before and after welding to assess axial shrinkage. These points are indicated in Fig. 1 (a and b). The measurements of axial shrinkage are presented in Table 3 for both pipe weld joint-1 and pipe weld joint-2.
Table 3
Axial deformation results in pipe joints
The mean axial shrinkage was found to be -0.425 mm and -0.3125 mm for pipe weld joints-1 and 2, respectively. Here, the negative sign indicates that the axial length of the pipes reduced after welding. The lower axial shrinkage in pipe weld joint-2 compared to pipe weld joint-1 is due to the use of lower beam power during welding.
3. Finite Element Modelling
This section offers insight into the theory and methodology employed in finite element modeling for the electron beam welding process of pipe butt weld joints. Finite element analysis of weld joints entails solving a coupled thermal, microstructural, and mechanical problem. The welding simulations were conducted using FE-based software11).
3.1 Geometry/Meshing
Finite element simulations have been carried out using linear 3D quadratic elements to model the pipe weld joint. These elements were selected for their robust performance in nonlinear finite element simulations. In the weld region, a very fine mesh with a size of 0.4 mm was employed, while elements farther from the welds were coarser. The total mesh consisted of 150,242 nodes and 146,670 3D elements. The finite element model of the pipe, with dimensions of 170 mm outer diameter and 13.5 mm thickness, along with a backup ring of 10.5 mm thickness, is shown in Fig. 4. One-fourth of the pipe was simulated to reduce computation time.
The entire model has been divided into several subparts and collectors. Collectors included base metal elements, filler elements, weld trajectory, and a reference line for heat source movement. Additionally, 2-D skin elements have been extracted from the 3-D surface mesh for applying convection and radiation boundary conditions, as shown in Fig. 5. The nodes at the pipe ends have been assigned to a separate collector, where mechanical boundary conditions were applied.
The elements have been modelled using an element birth and death technique. Initially, all elements of the bead were active. Element deactivation, or “element death,” occurred as the temperature of the element reached the melting point temperature of the material12). This comprehensive modelling approach enables an accurate representation of residual stresses in welding processes.
3.2 Material properties
Temperature-dependent thermo-physical properties of pipe material (SS304L) and its weld have been used in the analysis. Fig. 6 illustrates the variation of thermo-physical properties such as specific heat, thermal conductivity, and density with temperature11). Additionally, Fig. 7 and Fig. 8 shows the variation of mechanical properties, such as Young’s Modulus, Yield Strength, Coefficient of Thermal Expansion, and true stress-strain curves with temperature11). An isotropic hardening material model has been used for the mechanical analysis.
The melting temperature of stainless steel has been considered as an average between the solidus (1400°C) and liquidus temperatures (1455°C), set at 1428°C. The latent heat of fusion for stainless steel is 268 kJ/kg13).
3.3 Heat source and boundary conditions
In welding processes, the generation of heat input is governed by intricate physical phenomena. Modelling of the heat input source is crucial for accurately predicting temperature, residual stresses and distortions in pipe weld joint. Finite element-based welding simulations utilize weld heat input models to accurately depict heat generation using simplified mathematical models. These models define the heat input through analytical input power distribution models, denoted as q (x, y, z, t) (W/m3). Here, x, y, and z represent coordinates within a Cartesian coordinate system, and t denotes time. The total analytical power input can be described by the equation (1).
Where, Ω is the heat source region.
Here, a three-dimensional moving conical heat source with Gaussian radial distribution and linear axial distribution has been modelled to simulate the EBW process. The mathematical model of the power distribution is given by the equations (2) and (3).
Q0 represents the source intensity (W/m3), ro(m) and ri(m) are the radii of the cone at its upper and lower end, respectively, while H (m) represents the height of the cone. The radius of the cone at any intermediate location z is denoted by r(z). These values are schematically represented in Fig. 9.
Q0 is related to input power P by equation (4) as:
Where, η represents the efficiency of power conversion. In the case of EB welding, η accounts for the loss of energy of electrons due to emissions of backscattered electrons (reflected), secondary electrons, and X-rays during the interaction of the electron beam with the electrons of the material14). The efficiency of power conversion typically ranges between 80-95% for electron-beam-based devices15-17). In this study, a calibrated value of 90% is used.
Thus, numerical simulations of the EB welding process require estimation of the following heat source parameters: input power (P), upper and lower radius of the heat source - (ri, r0), depth of the conical heat source (H). In addition, welding speed (VW) is required as it affects the heat input per unit length. The estimation of heat source parameters is explained in Section (3.4).
In the welding process, the heat input by the electron beam primarily contributes to melting the material. Some of this heat is conducted away from the welding location through metal conduction, while the rest dissipates into the environment through convection and radiation. This study takes into account all these heat transfer mechanisms comprehensively. The ambient environment temperature is assumed to be 30°C, and the heat loss to the environment is simulated through thermal analysis until the temperature of the weld region reaches 30°C. The temperature-dependent effective heat transfer coefficients for convection and radiation, heff , were calculated using equation (5).
Where,
ε = Emissivity of material (taken as ε =0.8 for stainless-steel11)).
σ = Stefan’s Boltzmann’s Constant.
T = Actual temperature of element (K)
T∞ = Ambient Temperature (K)
h = heat transfer coefficient of convection (0.01 W/m2k for vacuum environment)
The nodal temperature profiles obtained through thermal analysis provide temperature-time histories for each node. These profiles serve as inputs for the mechanical analysis, enabling the determination of residual stresses and distortion resulting from the welding process. In the mechanical analysis, rigid body motions were constrained by fixing the nodes at one end surface of the pipe, while the other end of the pipe was allowed to move freely in the axial direction. Symmetric thermal and mechanical boundary conditions were applied to the side surface of the pipe since only one-fourth of the pipe was simulated.
3.4 Estimation of heat source parameters
In this section, the process for estimating various parameters required for the conical heat source model used to simulate EBW is elucidated. In EBW, the input power (P) is calculated using the equation (6).
Where, Vacc and Ib represent the accelerating voltage and the beam current, respectively. This input power P is associated with the heat input per unit length q and the welding velocity VW through the equation (7).
A moderate welding velocity (VW) of 600 mm/min has been used in present analysis. Based on the energy balance in the melting zone, Zuev18) provided analytical correlation for calculating the beam current necessary to achieve the desired depth of penetration in continuous welding. The correlation is given by equation (8).
In equation (8), d represents beam spot diameter (m); d = 2r0(upper radius of the conical heat source); ηt represents thermal efficiency, indicating the proportion of input heat energy used in melting of the material. For SS304L material, the thermal efficiency varies from 46% to 63% for a weld penetration of 10 mm17,19). Here, an average value of 55% has been used.
Sm represents the heat capacity (J/m3) corresponding to the melting temperature, calculated by the equation (9):
Where, ρ represents metal density (kg/m3); C represents specific heat capacity of metal (J/(kg·K); ΔTm=Tm - To increase from the initial temperature (To) to the melting point (Tm); Lm - specific heat of fusion (J/kg). Sm equals 8.915×109 J/m3, derived from the given parameters.
Based on the input power (P) and welding velocity (VW), the cross-sectional area of the weld zone (Fm = B.H) can be obtained by equation (10)17),
Solving equations (6, 8 & 10), The upper radius of the conical heat source, (r0 =d/2) is calculated as equation (11):
The Zuev18) model requires the information of mean weld width, depth of penetration and thermal efficiency of welding processes in advance. However, it provides a fair estimate of relation between beam sport diameter and beam depth of penetration assuming parabolic shape of heat source distribution. By mapping the truncated conical geometry (as used by eq.2) with the parabolic heat source geometry one can developed a relation between ro and ri. The mapping is achieved by equating the respective volumes of the heat source with the same top radius, thereby eliminating the variable parameter ri. The relation between the top and bottom radius of the heat source is given by equation (12).
The numerical analysis was performed using FE based welding analysis software. This software utilizes input parameters (q,η,Vw,ri,ro,H) to simulate the electron beam welding process. Table 4 presents the input parameters derived for numerically simulate the EBW process, as elaborated in the preceding paragraphs.
Table 4
Input parameters used in numerical simulations.
4. Results & Discussion
This section presents the outcomes derived from the finite element (FE) analysis of pipe butt weld joint, following the methodology outlined in Section 3. The analysis results are extracted in the form of maximum temperature contour for weld pool, weld pool size, residual stresses and distortion.
4.1 Pipe weld joint-1
The coupled thermo-mechanical welding simulation of pipe weld joint-1 has been carried out using the heat source input parameters provided in Table 4, consistent with the actual welding conditions. The heat source height specified in Table 4 has been estimated using correlations provided by Kar et al.10). The numerical simulation continued till the temperature of the weld reached 30°C. The weld pool shape obtained from the simulation, as depicted in Fig. 12, indicates a depth of penetration of 21.78 mm and a weld width of 1.71 mm at the root of the pipe. The weld pool is delineated based on regions where the temperature exceeds the melting temperature (1428°C). Notably, there is an overpenetration of 8.28 mm into the backup ring of pipe weld joint-1.
The experimental and numerical weld pool shape/size and deformation for pipe weld joint-1 have been compared, as summarized in Fig. 10(a) and Table 5. Overall, results compare well except at the weld top which has higher width as observed in experiment. The axial shrinkage obtained from experiment and numerical analysis for pipe weld joint-1 are compared in Table 5. Experimental results for axial shrinkage are higher compared to the numerical analysis result.
4.2 Pipe weld joint-2
The numerical simulation of pipe joint-2 has been performed using heat source input parameters provided in Table 4. The weld pool shape obtained from the simulation, as depicted in Fig. 10(b), indicates a depth of penetration of 16.40 mm included penetration in back up ring and a weld width of 1.49 mm at the root of the pipe weld. The experimental and numerical results of pipe weld joint-2 have been compared for weld pool shape and deformation and is summarized in Fig. 10(b) and Table 5. Overall, results compare well except at the weld top which has higher width as observed in experiment. Experimental results for axial shrinkage are higher compared to the numerical analysis result.
The experimental and numerical analysis results of the both pipe weld joints 1 and 2 compare well. This validates that numerical analysis procedure.
4.3 Optimization of Heat Input for Pipe Welding
The depth of penetrations for the pipe weld joints-1 and 2 indicate overpenetration of the beam which could be due to higher beam power during welding. Therefore, numerical analyses have been carried out to evaluate optimum beam power required for welding of pipe of given size under present study. Optimizing the beam power can control this overpenetration, thereby saving a significant amount of power. Optimum beam power can be evaluated assuming that there is no or minimum over-penetration. Optimum beam power will lead to lower weld pool, lower Heat-Affected Zone (HAZ), lower residual stresses and shrinkage in the pipe weld joint.
Thermal numerical analyses of pipe weld joints have been performed with varying input power ranging from 450 to 650 J/mm. The weld pool geometry based on the temperature profile of the weld joints are shown in Fig. 11. Molten weld pool has been defined as the regions of the weld joint having temperature higher than 1428 oC. Temperature of 1428 oC at the weld root with its width of 0.3 mm has been considered as the full penetration (i.e. no over or under penetration) of the wall thickness (13.5mm) of pipe weld joint
Fig. 11
Temperature contour and weld pool shape at various heat input (a) 450 J/mm, (b) 500 J/mm, (c) 550 J/mm, (d) 600 J/mm, (e) 650 J/mm
Temperature contours of the pipe weld joint with varying heat input shows that weld with 600 J/mm has no over-penetration or under penetration based on the melting point of the material.
4.3.1 Comparison of weld pool geometry and HAZ
The temperature contour plot obtained from the numerical simulation of pipe weld joint-3 (600 J/mm) has been compared with those of pipe weld joints-1 and 2, as shown in Fig. 12.
Fig. 12
Comparison of weld pool geometry and HAZ obtained using numerical simulations. (a) Temperature contour of pipe weld joint-1, (b) Temperature contour of pipe weld joint-2, (c) Temperature contour of pipe weld joint-3
The Heat-Affected Zones (HAZ) at the half of thickness of the pipe weld joints have been calculated based on the region of the temperatures between the lower critical temperature (723°C) and the melting temperature (1428°C). The comparison of HAZ for pipe weld joints-1, 2, and 3 is provided in Table 6. Pipe weld joint-3 exhibited lower HAZ by 13% and 5 % compared to pipe weld joints-1 and 2 respectively.
4.3.2 Comparison of welding shrinkage
Axial and radial shrinkages have been calculated using numerical analysis for pipe weld joint-3 and compared with pipe weld joints-1 and 2, as shown in Fig. 13. The axial shrinkage is least for pipe weld joint-3, indicating better dimensional stability along the length of the pipe. The radial shrinkage is also minimized in pipe weld joint-3, suggesting a more uniform and controlled weld profile.
5. Residual Stresses in Pipe Weld Joint
During the welding process, the temperature near the weld area rises significantly, causing the expansion of the metals. After welding, the base metal and weld pool begin to cool due to heat dissipation into the surrounding environment. This cooling leads to a reduction in temperature and thereby contraction of the metals. This contraction of the metal is resisted by the surrounding colder metal which leads to generation of residual stresses and shrinkage in the weld joint. Residual stresses gradually increase as the metal cools to room temperature. Specifically, higher residual stresses are observed in the weld pool and its immediate vicinity, while residual stresses farther away from the weld centre are comparatively lower. The von Mises residual stress contour plot obtained through numerical analysis, illustrating the variations in residual stresses, is presented in Fig. 14 (a and b). The von Mises residual contour plots indicates that the residual stresses are highest near the weld joint. The von Mises residual stresses are slightly higher at 825 J/mm heat input as compare to 700 J/mm heat input.
The residual stress curves along the thickness of the pipe weld, at the weld center, starting from root are depicted in Fig. 15. Additionally, residual stresses at top of the pipe weld are illustrated in Fig. 16. Notably, as one moves away from the weld center, the stresses gradually diminish. Furthermore, the residual stresses are predominantly tensile at the root of the pipe weld, transitioning to compressive stresses towards the top.
It is observed that axial residual stresses at top of the pipe weld are compressive near the weld center and transition to tensile stresses at around 25 mm distance from the weld center. Axial residual stresses are nearly zero far away from the weld center. Specifically, at the top of the pipe weld, the axial residual stress at the weld center is -280 MPa, and the peak axial residual stress reaches 70 MPa, as shown in Fig. 16. These axial stress patterns have been compared with existing literature. For example, Akbari et al.8) reported -200 MPa axial residual stress at the weld center and a peak axial residual stress of 130 MPa at the outer surface of stainless-steel pipe welds using multi-pass arc welding. Wang et al.9) found -400 MPa axial residual stress at the weld center and a peak axial residual stress of 165 MPa for shielded metal arc welding of ASME-grade P92 steel. Davood et al.20) reported -320 MPa axial residual stress at the weld center and 180 MPa peak axial residual stress at the outer surface of stainless-steel pipe welded by gas tungsten arc welding (GTAW).
The axial residual stresses in the current analysis show a change from compressive to tensile stresses at a distance from the weld center, a pattern also observed by Akbari et al.8) and Wang et al.16), albeit marginally lower in magnitude compared to these studies as depicted in Fig. 16. Importantly, the axial residual stresses reported by Akbari et al.8), Wang et al.9), and Davood et al.20) are significantly higher than those observed in the pipe welds made by EBW in this study, indicating that EBW tends to produce lower residual stresses compared to other welding processes. However, despite the differences in magnitude, the axial stress observations in this study (Fig. 16) exhibit a similar trend to those reported in8-10), thereby confirming the validity and consistency of the stress results obtained in this analysis.
5.1 Comparison of residual stresses with heat input
The coupled thermo-mechanical welding simulation of pipe weld joint has been carried out at optimum heat input 600 J/mm, and the residual stresses in pipe weld joint have been obtained. Fig. 17-Fig. 19 illustrate the comparison of residual stresses at the pipe root with varying heat inputs. Near the weld joint, the residual stresses are predominantly tensile, transitioning to compressive further away. Comparing axial residual stresses shows a 40% reduction at a 600 J/mm heat input compared to 825 J/mm. Hoop and radial stresses are also minimized at the 600 J/mm heat input.
6. Conclusion
Experimental and numerical analyses were conducted to establish optimal welding parameters for joining 13.5 mm thick pipes made of 304 L stainless steel using electron beam welding. The analyses focused on weld pool geometry, deformation, and residual stresses. The following conclusions were drawn:
1) Welding of pipe was carried out using electron beam welding with parameters selected based on literature and expertise. Axial and radial deformations were measured, followed by weld pool geometry analysis. Numerical simulations of the actual welding conditions were performed and compared with experimental measurements. The results showed a close agreement, with differences of 12% for deformation and 10% for weld pool geometry. This validation confirmed the accuracy of the numerical analysis procedure for pipe weld joints. Simulations using reduced power settings were also conducted, and the resulting deformations and weld pool geometries were compared with experimental outcomes.
2) Residual stresses in the pipe weld joints were estimated during the study. It was observed that lower beam power settings resulted in lower residual stresses. This observation prompted subsequent optimization endeavors aimed at further refining welding parameters to minimize residual stresses to the greatest extent possible.
3) Through numerical analysis, optimized parameters for electron beam welding of 13.5 mm thick pipes made of 304 L stainless steel were established. The optimized heat input of 600 J/mm results in desirable weld pool geometry, minimal heat-affected zone, reduced deformation, and lower residual stresses. These findings underscore the effectiveness of optimizing welding parameters to enhance weld quality and reduce structural concerns in welded pipe joints.
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