Abstract
Large castings used for steam turbine casings are often subjected to severe service conditions, and the occurrence of casting defects during manufacturing is almost inevitable. The presence of casting defects not only reduces the structural integrity of the component but also creates potential sites for crack initiation and premature failure. Repair welding is therefore a critical technology for restoring defective castings and reducing production losses. However, repair welding of large castings is challenging because the non-uniform temperature field generated during welding leads to complex residual stresses, deformation, and sometimes secondary defects such as gas pores and cold cracks. In this study, I used the welding simulation software Simufact Welding to investigate the repair welding process for casting defects in a ZG20CrMoV steam turbine casing. The study focused on temperature field evolution, stress response, process optimization, and experimental validation. I established a three-dimensional finite element model of a typical defect region and compared two repair welding schemes. The scheme employing R317 heat-resistant steel electrode with hot welding was selected as the optimum scheme. Through detailed analysis of the transient temperature field, thermal cycles at characteristic points, equivalent stress, equivalent elastic strain, and equivalent plastic strain, I identified the main causes of secondary defect formation during repair welding. I then optimized the welding parameters by reducing heat input, lowering the preheat temperature, and adopting a controlled heating rate. The optimized process was evaluated numerically and then verified by actual repair welding experiments. X-ray inspection after the optimized process showed no detectable defects in the repaired area. This research demonstrates that simulation-guided process optimization can significantly improve the repair quality of large castings and effectively minimize the formation of secondary casting defects.
1. Introduction and Background
Castings are essential components in power plants, marine propulsion systems, and industrial machinery. In particular, steam turbine casings are usually produced as large steel castings with complex geometries and thick sections. During solidification and cooling, large castings are highly susceptible to various casting defects such as shrinkage porosity, gas holes, sand inclusion, slag entrapment, hot tears, and cold cracks. These casting defects can seriously harm the mechanical properties and service life of the component. Because steam turbine casings operate under high temperature and high pressure, even a small defect can lead to catastrophic failure. Therefore, effective repair of casting defects is necessary to ensure safe and reliable operation.
In the past, manual repair welding was the most common method for repairing casting defects. Experienced welders would gouge out the defective region, grind a suitable groove, and then fill the cavity with weld metal. Although this approach is flexible, it depends heavily on operator skill and often leads to inconsistent quality. In addition, the welding heat cycle may create new defects, such as hydrogen-induced cracking and reheat cracking. Because large casings are massive and have high stiffness, the repair welding process can generate severe residual stresses. These stresses combine with the service stresses and may promote cracking during subsequent operation. Therefore, a more scientific approach is needed to control the repair welding process and reduce the risk of secondary casting defects.
Numerical simulation has become a powerful tool for understanding and optimizing welding processes. By simulating the temperature field, residual stress field, and deformation, engineers can predict the influence of welding parameters before actual production. This reduces trial-and-error experiments, saves time, and improves the reliability of repair welding. In this project, I used Simufact Welding, a commercial finite element software, to simulate the repair welding of a ZG20CrMoV steam turbine casing. The objectives were to compare different repair welding schemes, analyze the temperature and stress evolution, optimize the welding parameters, and verify the optimized process by experimental repair welding.
The automatic pouring line has already improved the initial quality of castings and reduced the number of casting defects through better filling and feeding behavior. Nevertheless, large and complex castings still require repair welding because of unavoidable variability in solidification and cooling.
Repair welding of casting defects is particularly difficult for pearlitic heat-resistant steels because their weldability is influenced by carbon equivalent, alloy content, and heat treatment sensitivity. In this study, I focused on ZG20CrMoV, a chromium-molybdenum-vanadium cast steel commonly used for steam turbine casings. This material has good elevated-temperature strength but also exhibits a strong tendency to harden during welding. Therefore, the repair welding procedure must be designed carefully to avoid the formation of hard martensite and brittle microstructures.
2. Material and Methodology
2.1 Base Material ZG20CrMoV
ZG20CrMoV is a low-alloy pearlitic heat-resistant cast steel used for high-pressure and medium-pressure steam turbine casings, valve chests, and steam chests. The material is designed for service temperatures up to about 540 °C. Its chemical composition is given in Table 1. The chromium and molybdenum contents provide solid-solution strengthening and improve creep resistance, while vanadium promotes fine precipitation and high-temperature strength.
| Element | Content (wt.%) |
|---|---|
| Carbon, C | 0.18–0.25 |
| Silicon, Si | 0.20–0.60 |
| Manganese, Mn | 0.40–0.70 |
| Chromium, Cr | 0.90–1.20 |
| Molybdenum, Mo | 0.50–0.70 |
| Vanadium, V | 0.20–0.30 |
| Copper, Cu | ≤0.30 |
| Sulfur, S | ≤0.030 |
| Phosphorus, P | ≤0.030 |
The material properties of ZG20CrMoV vary significantly with temperature. In the welding simulation, it is necessary to input temperature-dependent thermal and mechanical properties. Some representative values are listed in Table 2. These values were used in the finite element model to calculate heat conduction, thermal expansion, and stress development during repair welding.
| Temperature (°C) | Specific Heat Cp (J·kg−1·°C−1) | Thermal Conductivity λ (W·m−1·°C−1) | Young’s Modulus E (GPa) | Expansion Coefficient α (×10−6/°C) | Yield Strength σy (MPa) |
|---|---|---|---|---|---|
| 20 | 420 | 41.2 | 216.7 | 11.86 | 490 |
| 100 | 448 | 43.1 | 212.5 | 12.18 | 441 |
| 200 | 502 | 46.2 | 206.3 | 12.58 | 415 |
| 300 | 515 | 44.0 | 198.2 | 13.18 | 419 |
| 400 | 527 | 41.8 | 190.5 | 13.06 | 419 |
| 500 | 552 | 39.0 | 178.8 | 13.96 | 392 |
| 550 | 560 | 37.4 | 174.3 | 14.10 | 304 |
| 600 | 572 | 36.1 | 169.5 | 14.20 | 251 |
2.2 Weldability Analysis of ZG20CrMoV
ZG20CrMoV is a typical low-alloy heat-resistant steel with limited weldability. To evaluate its weldability, I used the International Institute of Welding carbon equivalent formula:
$$CE_{IIW} = \left[ C + \frac{Mn}{6} + \frac{Cr+Mo+V}{5} + \frac{Ni+Cu+Si}{15} \right] \times 100\%$$
Substituting the actual composition into the equation gives:
$$CE_{IIW} = 0.81\%$$
Because the carbon equivalent is significantly higher than the recommended limit of 0.45%, the steel is considered difficult to weld. Fast cooling after welding may produce martensite, leading to high hardness and cold cracking. In addition, the presence of Cr, Mo, and V increases the reheat cracking susceptibility. I calculated the reheat cracking parameter using the following formula:
$$\Delta G = Cr + 3.3Mo + 8.1V + 10C – 2$$
Another suitable parameter is:
$$\Delta P_{SR} = Cr + Cu + 2Mo + 10V + 7Nb + 5Ti – 2$$
For ZG20CrMoV, the value was calculated to be about 1.9, which is above zero. This confirms that repair welding of this material requires strict preheating, controlled interpass temperature, and proper post-weld heat treatment. Otherwise, the repaired casting defect may become even more dangerous than the original defect.
2.3 Defect Characterization and Modeling
To build a realistic repair welding model, I measured typical casting defects after carbon arc gouging and grinding. The defects were of various types, including gas pores, sand inclusions, slag entrapments, and cracks. The measured dimensions are summarized in Table 3. Most defects had lengths between 130 mm and 320 mm, widths between 20 mm and 80 mm, and depths between 20 mm and 60 mm.
| Defect Type | Length (mm) | Width (mm) | Depth (mm) |
|---|---|---|---|
| Gas pore | 320 | 80 | 60 |
| Gas pore | 200 | 40 | 40 |
| Gas pore | 180 | 50 | 35 |
| Gas pore | 220 | 45 | 30 |
| Sand inclusion | 170 | 30 | 40 |
| Sand inclusion | 185 | 30 | 25 |
| Slag entrapment | 130 | 20 | 25 |
| Slag entrapment | 200 | 35 | 30 |
| Slag entrapment | 160 | 25 | 20 |
| Slag entrapment | 300 | 80 | 60 |
| Crack | 250 | 60 | 50 |
| Crack | 300 | 70 | 60 |
| Crack | 320 | 65 | 50 |
Based on these measurements, I selected a representative non-penetrating defect with dimensions of 180 mm × 60 mm × 40 mm for the simulation. According to the repair welding procedure, the defect was opened with a groove angle of 12° and a root radius of 8 mm. The base model size was chosen as 600 mm × 300 mm × 250 mm. This size was sufficient to include the heat-affected zone and stress redistribution area around the casting defect without modeling the entire steam turbine casing.
The three-dimensional solid model was created in SolidWorks and then meshed in Hypermesh. A fine mesh was applied near the repair groove and a coarse mesh was applied away from it. Only a symmetric half-model was used in the simulation to reduce computational time. The model represented the actual repair welding process including preheating, multilayer deposition, cooling, and post-weld heat treatment.
3. Repair Welding Schemes and Temperature Field Analysis
3.1 Definition of Two Repair Schemes
Two repair welding schemes were proposed for comparison. Scheme 1 used R317 heat-resistant steel electrodes and a hot-welding procedure. Scheme 2 used A307 austenitic stainless steel electrodes and a semi-hot-welding procedure. The welding process parameters are summarized in Table 4.
| Parameter | Scheme 1 | Scheme 2 |
|---|---|---|
| Electrode type | R317 (φ5.0 mm) | A307 (φ5.0 mm) |
| Current (A) | 200 | 200 |
| Voltage (V) | 28 | 28 |
| Welding speed (mm/s) | 5 | 5 |
| Preheat temperature (°C) | 250 | 150 |
| Interpass temperature (°C) | 200–350 | 200–300 |
| Post-weld heat treatment | 700 °C × 6 h | Slow cooling with insulation |
The welding heat input for the original scheme was calculated with the formula:
$$Q = \eta \frac{U I}{v}$$
Assuming an arc efficiency of η = 0.65, the heat input for Scheme 1 is:
$$Q_1 = 0.65 \times \frac{28 \times 200}{5} = 728\ \text{J/mm}$$
For Scheme 2, the same heat input was used because the current and voltage were identical. The simulation environment had an ambient temperature of 25 °C and a convection coefficient of 10 W/m²·°C. The initial base temperature was 20 °C before preheating.
3.2 Temperature Field Comparison
During repair welding, a double-ellipsoid volumetric heat source model was applied to simulate the moving arc. The temperature field results showed that a molten pool was formed in the region where the temperature exceeded approximately 1237 °C. The shape of the temperature field was elongated: the isotherms ahead of the heat source were dense, indicating a steep temperature gradient, while the isotherms behind the heat source were wider and less steep. This is typical of a moving heat source during repair welding.
In the early stage of welding, the base material was relatively cool, and the thermal influence zone was limited. As the deposition layers increased, the accumulated heat caused the average temperature of the base material to rise. The maximum molten pool temperature gradually stabilized at about 1517 °C. In Scheme 1, because the preheat temperature was higher, the temperature distribution around the molten pool was more uniform. The heat-affected zone was larger, but the thermal gradient was lower in the direction perpendicular to the weld. In Scheme 2, the lower preheat temperature produced a more concentrated temperature field and a smaller heat-affected zone. However, the higher thermal gradient increased the risk of residual stress and cold cracking.
After comparing the transient temperature fields at different welding times, I concluded that Scheme 1 was more suitable for repairing casting defects in ZG20CrMoV steam turbine casings. The use of R317 heat-resistant steel electrode provided good metallurgical compatibility with the base material. The higher preheat temperature helped to reduce the cooling rate and avoid martensite formation. Therefore, Scheme 1 was selected as the basis for further analysis and optimization.
4. Thermal Cycle Analysis and Identification of Problems
4.1 Temperature Gradient Evolution
After selecting Scheme 1, I analyzed the transient temperature gradient at the end of the first, second, fifth, and eighth layers. The temperature gradient values increased from 3775 K/m at the first layer to 3883 K/m at the second layer, then to 4685 K/m at the fifth layer, and finally to 4909 K/m at the eighth layer. The maximum temperature gradient always appeared in the region close to the molten pool. The increase in temperature gradient with the layer number was caused by heat accumulation in the base material. During subsequent welding passes, the previously deposited layers were reheated and cooled repeatedly. This repeated thermal cycling may lead to significant thermal stresses in the repair area.
The high temperature gradient is important because it directly relates to thermal stress. A higher gradient means greater differential expansion and contraction between adjacent regions. If the local stress exceeds the material yield strength, plastic deformation will occur. In repair welding of casting defects, this plastic strain can accumulate with each layer and eventually lead to hot cracking or cold cracking.
4.2 Characteristic Point Temperature Curve
To understand the thermal cycles experienced by the material, I monitored a characteristic point located near the repair groove. The temperature-time curve of this point is shown by the simulation results over the entire repair welding process, which included 36 welding passes. During the first pass, the temperature at the characteristic point rose extremely quickly to 1648.7 °C within about 60 seconds. After the heat source moved away, the temperature dropped rapidly to below 400 °C. Such a fast thermal cycle is typical for arc welding and is beneficial for refining the microstructure of the weld metal.
However, the temperature curve also revealed that the characteristic point was heated above the melting temperature during the first three passes. This means that the deposited metal and a thin layer of the base material were remelted several times during the repair welding process. This repeated melting and solidification improved the interlayer fusion but also increased the risk of segregation and gas entrapment. After the early passes, the peak temperature at the characteristic point gradually decreased because the heat source was farther away and the thermal path to the surface became longer.
The valley temperatures of the thermal cycles remained stable at approximately 200 °C. This result indicated that the interpass temperature control was effective. Maintaining the interpass temperature at about 200 °C helped to prevent excessive hardening of the heat-affected zone and reduced the danger of hydrogen-induced cracking. Nevertheless, the simulation showed that the original Scheme 1 still produced high stress concentrations, especially at the root of the repair groove and at the end of each welding pass.
5. Stress Analysis and Experimental Verification of Original Scheme
5.1 Equivalent Stress and Strain
Welding stress arises from non-uniform thermal expansion and contraction. The von Mises equivalent stress is widely used to evaluate the combined effect of multiaxial stresses. It is defined as:
$$\sigma_v = \frac{1}{\sqrt{2}} \sqrt{(\sigma_x – \sigma_y)^2 + (\sigma_y – \sigma_z)^2 + (\sigma_z – \sigma_x)^2 + 6(\tau_{xy}^2 + \tau_{yz}^2 + \tau_{zx}^2)}$$
In the original Scheme 1, the maximum equivalent stress at the end of the first layer reached 310 MPa. This value approached the yield strength of ZG20CrMoV at the corresponding temperature. At the end of subsequent layers, the stress in the weld area decreased slightly because the newly deposited layers experienced a local tempering effect. However, the stresses in the heat-affected zone and the base material near the repair groove remained high.
After cooling to room temperature, the X, Y, and Z directional stress components all showed tensile stresses in the outer part of the repair region and compressive stresses near the base material. The maximum values were 273 MPa in the X direction, 342 MPa in the Y direction, and 383 MPa in the Z direction. The equivalent stress concentrated at the bottom of the repair groove. This stress concentration is dangerous because the bottom of the repair groove is a geometric discontinuity and acts as a stress raiser.
The equivalent elastic strain in the repaired region reached 0.097, and the equivalent plastic strain reached 0.24. The plastic strain was especially concentrated at the bottom of the repair groove. Such a large plastic strain indicates that the material in this region yielded and experienced permanent deformation. This deformation was not only dimensional but also microstructural. It introduced dislocations, residual stresses, and potential microcracks that could propagate during service. Therefore, the original process was considered likely to produce secondary casting defects in the repaired area.
5.2 Experimental Verification of Original Scheme
To verify the numerical results, I performed an actual repair welding experiment using the original Scheme 1 parameters. The workpiece was a ZG20CrMoV casting with a defect groove of approximately 170 mm × 40 mm × 40 mm. The welding was carried out by a qualified welder according to the procedure. The workpiece was preheated to 250 °C with flame heating, and the interpass temperature was maintained at around 200 °C. The welding current was 200 A and the voltage was 28 V.
After welding and subsequent cooling, the repaired area was inspected by X-ray radiography. The X-ray film showed clear indications of gas pores and a crack-like linear defect. The presence of these secondary casting defects proved that the original welding parameters were not suitable for this repair condition. The simulation results had already suggested that the stress concentration and plastic strain in the repair groove were high enough to generate cracks. The experimental result confirmed this prediction.
The formation of gas pores in the repair weld was attributed to the high heat input and fast cooling rate, which trapped gas before it could escape from the molten pool. The crack was most likely caused by the combination of high residual stress, high restraint of the large casting, and the sensitivity of ZG20CrMoV to cold cracking. This experience showed that repair welding of casting defects cannot rely only on the welder’s skill. Instead, numerical simulation should be used to optimize the process parameters before actual production.
6. Process Optimization and Numerical Results
6.1 Optimized Welding Parameters
Based on the stress analysis and the X-ray inspection results, I optimized the repair welding process. The main goals were to reduce the heat input, lower the temperature gradient, decrease the residual stress, and improve the microstructure of the repaired region. The optimized parameters are listed in Table 5.
| Parameter | Original Scheme | Optimized Scheme |
|---|---|---|
| Electrode type | R317 φ5.0 mm | R317 φ5.0 mm |
| Current (A) | 200 | 180 |
| Voltage (V) | 28 | 26 |
| Welding speed (mm/s) | 5 | 5 |
| Heat input (J/mm) | 728 | 608 |
| Preheat temperature (°C) | 250 | 200 |
| Heating rate (°C/h) | ≤150 | ≤100 |
| Interpass temperature (°C) | 200–350 | about 200 |
| Post-weld heat treatment | 700 °C × 6 h | 700 °C × 6 h |
The optimized heat input was calculated as:
$$Q_{opt} = 0.65 \times \frac{26 \times 180}{5} = 608\ \text{J/mm}$$
This reduction in heat input lowered the peak temperature and the temperature gradient in the repair zone. It also reduced the width of the heat-affected zone and the degree of thermal shrinkage during cooling. At the same time, the preheat temperature was reduced from 250 °C to 200 °C, and the heating rate was limited to 100 °C/h. This slower heating process helped to avoid excessive thermal shock and produced a more uniform temperature distribution inside the large casting.
6.2 Temperature Field of the Optimized Process
The simulated temperature field of the optimized process showed a well-defined molten pool with a lower maximum temperature. The heat-affected zone was narrower, and the temperature distribution around the repair groove was more uniform. As the welding progressed, the heat accumulation in the base material was still present, but the maximum temperature did not become excessively high. The isotherms around the molten pool were smoother, and the local temperature gradient decreased compared with the original process.
The peak temperature of the molten pool remained above the melting point of ZG20CrMoV, which is necessary for good fusion. However, the volume of superheated metal was smaller. This reduced the tendency for burn-through, overheating, and weld pool sagging. The interpass temperature remained stable at about 200 °C, which was beneficial for preventing the formation of martensite in the heat-affected zone.
6.3 Stress Field of the Optimized Process
After optimizing the welding parameters, the maximum equivalent stress at the end of the first layer decreased to 306 MPa. At the end of the second layer, it decreased further to 267 MPa. At the end of the eighth and final layer, the maximum equivalent stress was about 266 MPa. These values were below the yield strength of the material at the corresponding temperatures. Therefore, the optimized process significantly reduced the risk of plastic deformation and cracking.
The X, Y, and Z component stresses after cooling were also lower. The maximum values were 227 MPa in the X direction, 213 MPa in the Y direction, and 329 MPa in the Z direction. The equivalent stress concentration at the bottom of the repair groove was still present, but its magnitude was much lower than that of the original process. The lower stress level means that the repaired casting defect region can better withstand the service loads without crack initiation.
The equivalent elastic strain after cooling decreased to 0.065, and the equivalent plastic strain decreased to 0.09. This indicates that the optimized repair welding process produced only a small amount of permanent deformation. The microstructural damage in the heat-affected zone was therefore less severe. This is particularly important for large castings because excessive plastic strain can lead to dimensional instability and premature fatigue failure.
6.4 Post-Weld Heat Treatment Simulation
After the optimized repair welding process, the component was subjected to post-weld heat treatment at 700 °C for 6 hours. This heat treatment is commonly used to reduce residual stresses and temper the weld metal and heat-affected zone. The Larson-Miller parameter, defined as:
$$P = T \left( C + \log_{10} t \right)$$
is often used to relate the heat treatment cycle to long-term service exposure. In this context, the 700 °C × 6 h treatment was considered sufficient to simulate the thermal aging effect that the ZG20CrMoV material would experience under service conditions.
The simulation of post-weld heat treatment showed a dramatic reduction in equivalent stress. The maximum equivalent stress after heat treatment was only about 100 MPa. This value is far below the yield strength of the material and indicates that most of the residual stress introduced by repair welding was successfully relieved. The maximum equivalent plastic strain rate after heat treatment was 0.06, confirming that no additional plastic deformation occurred during cooling. The heat treatment not only relieved stress but also improved the ductility and toughness of the repaired region.
These numerical results demonstrate that the optimized combination of reduced heat input, controlled preheating, and post-weld heat treatment can effectively prevent the formation of secondary casting defects during repair welding.
7. Experimental Validation of the Optimized Repair Welding Process
To verify the optimized process under production conditions, I performed another actual repair welding experiment. A ZG20CrMoV casting with a defect groove of approximately 250 mm × 40 mm × 30 mm was prepared. The groove angle was 12°, which was close to the simulation model. Before welding, the workpiece was preheated to 200 °C using flame heating. The heating rate was limited to about 100 °C/h. The welding current was 180 A, and the voltage was 26 V. R317 electrodes with a diameter of 5.0 mm were used.
During welding, the interpass temperature was maintained at about 200 °C. Each weld pass was deposited with a back-and-forth welding path. The weld was peened with a stainless steel hammer after each pass, except for the final cover layer. Peening introduced compressive stresses on the surface and helped to reduce the tensile residual stresses that could cause cracking. After the repair welding was completed, the casting was placed in a heat-treatment furnace and subjected to 700 °C for 6 hours. The cooling rate after heat treatment was controlled to be less than 100 °C/h.
After heat treatment, the repaired area was inspected using X-ray radiography. The X-ray film showed a uniform and continuous radiographic appearance. There were no bright spots, dark lines, or other indications that would suggest gas pores, slag inclusions, lack of fusion, or cracks. The repaired casting defect was considered acceptable according to the acceptance criteria. This result confirmed that the optimized repair welding process is reliable and suitable for production.
The successful experimental validation also demonstrates the effectiveness of simulation in the repair welding process design. By analyzing the temperature field, stress field, and plastic strain field before actual welding, I was able to identify the weaknesses of the original procedure and modify it in a rational manner. This approach reduced the number of trial-and-error experiments, saved time and materials, and improved the quality of large castings.
8. Conclusion and Outlook
In this study, I conducted a systematic numerical simulation and experimental verification of the repair welding process for casting defects in large ZG20CrMoV steam turbine casings. The main conclusions are summarized as follows.
First, repair welding of large castings is a complex process that requires careful control of the temperature field and stress field. The non-uniform heating and cooling during multilayer deposition can easily lead to secondary defects such as cracks and gas pores if the process parameters are not optimized. Simulation software such as Simufact Welding is an effective tool for predicting the thermal and mechanical response of the component before actual welding.
Second, the comparable analysis of two repair welding schemes showed that the hot-welding scheme using R317 heat-resistant steel electrode was more suitable for ZG20CrMoV castings. The higher preheat temperature and the use of a matching electrode provided a more uniform temperature distribution and better metallurgical compatibility. This scheme reduced the risk of hard zone formation and cracking.
Third, the analysis of the original process revealed high temperature gradients, high residual stresses, and significant plastic strain in the repair groove. The maximum equivalent stress approached the yield strength of the material, and the plastic strain reached 0.24 at the bottom of the groove. These simulation results were confirmed by actual X-ray inspection, which showed gas pores and cracks in the original repaired area.
Fourth, the optimized process, using a lower heat input of 608 J/mm, a preheat temperature of 200 °C, a controlled heating rate, and a thorough post-weld heat treatment at 700 °C for 6 hours, significantly reduced the residual stress and plastic strain. The maximum equivalent stress after heat treatment was only about 100 MPa. The actual repair welding test using the optimized process produced a defect-free repaired area, as verified by X-ray radiography.
Therefore, the combination of welding simulation and experiment is a powerful approach for improving the reliability of repair welding of casting defects in large castings. In the future, I plan to extend this method to other materials and defect geometries. More advanced simulation models, including phase transformation and microstructure evolution, could further improve the prediction accuracy. It is also desirable to integrate real-time monitoring and adaptive control into the repair welding process so that welding parameters can be adjusted automatically based on the measured temperature field. This would bring the foundry industry closer to the goal of intelligent, high-quality, and low-cost repair of large castings with casting defects.
Keywords: casting defect; repair welding; simulation; process optimization; temperature field; stress field; large castings