Full-process simulation closed-loop optimization method for air inlet casing

Abstract

The invention discloses an air inlet casing full-process simulation closed-loop optimization method, which relates to the technical field of mechanical manufacturing and processing, and comprises the following steps: simplifying an air inlet casing model; selecting a plurality of key procedures from the whole procedures; according to process parameters and boundary conditions of the key process, grid division is carried out on the simplified model, and a corresponding finite element simulation model is constructed; sequentially simulating the finite element simulation model according to a key process sequence, correcting a simulation result according to deformation data of actual processing, transmitting the corrected simulation result to a next key process for model simulation until simulation and correction of all key processes are completed, and constructing a full-process simulation prediction model; performing iterative optimization on multiple parameters in the whole-process simulation prediction model to obtain an optimal parameter combination; and correcting the simulation model according to the deviation between the actual processing data and the simulation result under the control of the optimal parameter combination. According to the method, high-precision prediction of various complex manufacturing processes can be realized, and the manufacturing precision is improved.

Description

Technical Field

[0001] This invention relates to the field of mechanical manufacturing and processing technology, and more specifically to a closed-loop optimization method for the entire process of an intake casing. Background Technology

[0002] The air intake casing is a critical load-bearing component in an aero-engine, manufactured through complex processes from multiple parts. Its production typically involves various techniques such as machining, heat treatment, electron beam welding, and diffusion welding. During processing, factors such as assembly precision, structural rigidity, and processing heat input can influence the internal structure, introducing complex residual stress distributions and leading to structural deformation. To date, residual stress remains a significant factor affecting the quality and operational safety of the air intake casing. Residual stress not only impacts the manufacturing process but also affects the product's performance. Therefore, accurately predicting and controlling residual stress and deformation during the manufacturing stage has become a pressing technical challenge.

[0003] Currently, there are two main methods for predicting residual stress: experimental methods and numerical simulation methods. Experimental methods typically use scaled-down test pieces or simulated parts, obtaining residual stress distribution data through multiple processing tests. However, this method requires repeated adjustments to process parameters during trial production to ensure quality, leading to extended production cycles and increased testing costs, especially for complex structural components such as air intake casings. In contrast, with the improvement of computer performance and the development of finite element theory, numerical simulation has become an important means of optimizing manufacturing processes, controlling residual stress, and improving product performance. However, applying numerical simulation to complex aerospace structural components has significant shortcomings: firstly, the stress and deformation result transfer mechanism between different meshes is not clearly defined, limiting the process integration under multi-software, multi-mesh model conditions; secondly, the process does not fully consider manufacturing stages with high heat input, such as welding, making it difficult to fully reflect the actual stress evolution process during air intake casing manufacturing.

[0004] Therefore, how to adapt to multiple sizes and realize full-process simulation across multiple processes, and improve the prediction accuracy of residual stress and deformation in the air intake box manufacturing process, is a problem that urgently needs to be solved by those skilled in the art. Summary of the Invention

[0005] In view of the above problems, this invention is proposed to provide a closed-loop optimization method for full-process simulation of air intake casing to overcome or at least partially solve the above problems. It supports full-process numerical simulation with multiple mesh sizes and cross-process data transfer, and can achieve high-precision prediction of residual stress and deformation in various complex manufacturing processes, thereby improving manufacturing accuracy, reducing manufacturing costs, and improving the service safety of components.

[0006] To achieve the above objectives, the present invention adopts the following technical solution: In a first aspect, embodiments of the present invention provide a closed-loop optimization method for full-process simulation of an intake casing, comprising the following steps: Step 1: Based on the three-dimensional digital model of the intake casing, the geometric features are simplified in stages to obtain a simplified model; local features that do not significantly affect residual stress and deformation are removed, including rounded corners, small holes and small ribs; Step 2: Select several key processes that are sensitive to residual stress and deformation from the entire process of machining the intake casing according to the processing sequence; Step 3: Based on the actual process parameters and boundary conditions corresponding to the key processes, mesh the simplified model and construct the corresponding finite element simulation model for each key process; Step 4: Simulate the corresponding finite element simulation models sequentially according to the key process sequence, and correct the simulation results based on the actual deformation data of the actual sample feature surfaces of the corresponding key process. The finite element simulation models are then calibrated, and the corrected simulation results are passed to the next key process for simulation, until all key processes are simulated and corrected. All calibrated finite element simulation models constitute the full-process simulation prediction model. During this process, initial conditions are applied sequentially to each key process for simulation, calibration correction, and data mapping. Calibration correction involves extracting deformation from the actual deformation data and inferring stress to correct the simulation results. Data mapping involves setting the corrected simulation results for subsequent key process simulations. Step 5: Call the optimization software to iteratively optimize the key parameters of multiple processes in the full-process simulation prediction model, obtain the optimal parameter combination, and input the optimal parameter combination into the full-process simulation prediction model for simulation to obtain the full-process simulation results; Step 6: Control the actual processing according to the optimal parameter combination, collect the actual residual stress and actual deformation data of each process, and obtain the deviation value by subtracting it from the simulation results of the whole process. If the deviation value exceeds the set threshold, the key parameters of the corresponding process are corrected according to the deviation value to realize the feedback closed-loop optimization of the whole process.

[0007] Preferably, the key processes include, in sequence, forging of the support plate blank, machining of the inner cavity of the support plate, diffusion welding of the support plate, electron beam welding of the support plate, overall heat treatment of the casing after welding, and precision machining of the casing.

[0008] Preferably, the specific process of step 4 is as follows: Step 41: Select the first critical process as the current process; Step 42: Apply initial conditions to the finite element simulation model corresponding to the current process and perform simulation calculations. Use data transfer software to extract the stress field and deformation field from the simulation results. Step 43: Collect the actual deformation data of the feature surface of the actual sample in the current process, and perform back calculation to obtain the residual stress field. Use the residual stress field to iteratively correct the stress field and deformation field of the current simulation results. Step 44: Write the corrected stress and strain into the next key process through a standardized interface file to achieve cross-process data transfer. Set the next key process as the current process and return to step 5, until all key processes are traversed. The finite element simulation models of all key processes that have been simulated and corrected are combined to form the full-process simulation prediction model.

[0009] Preferably, the finite element software used for simulation calculations is Abaqus and Simufact Welding.

[0010] Preferably, when performing simulation calculations, the initial conditions such as initial stress, initial strain, or temperature field are defined by modifying the .inp file when writing data to the finite element software Abaqus; and the initial conditions are set through the initial field definition module when writing data to the finite element software Simufact Welding.

[0011] Preferably, the data transfer software is Digimat-MAP, which extracts and transfers stress and strain through geometric mapping between models. Specifically, the simulation results of the upstream process and the corresponding finite element simulation models of the downstream process are imported into Digimat-MAP, and a spatial correspondence is established through geometric boundary matching to generate the source model result file. The stress and strain of the nodes or integration points are extracted from the source model result file, and the field variables under different mesh densities are reconstructed by multi-point interpolation based on element shape functions. The Field Transfer function is used to complete the mapping and generate an input file that can be directly used for subsequent simulations.

[0012] Preferably, the specific process of step 43 is as follows: Step 431: Use a coordinate measuring system to obtain the actual deformation data of the feature surface of the actual sample, i.e. the deformation field, and solve the residual stress field of the feature surface of the actual sample based on the deformation field. Step 432: Based on the principle of intrinsic strain incompatibility, establish the static equilibrium equation, and according to the static equilibrium equation, cyclically map the stress field to the corresponding finite element simulation model, perform static equilibrium iteration of the stress field, and reconstruct the actual residual stress field inside the actual sample of the intake casing. Step 433: Reconstruct the actual overall deformation field corresponding to the intake casing using the reconstructed actual residual stress field; Step 434: Correct the stress field of the current simulation results to the actual residual stress field, and correct the deformation field to the actual overall deformation field.

[0013] Preferably, after the sample is processed, the actual residual stress is measured using an X-ray residual stress tester, and the post-weld deformation is measured using a three-coordinate measuring system with a three-dimensional scanning modeling method to obtain the actual deformation data.

[0014] Preferably, when iteratively optimizing key parameters of multiple processes in the full-process simulation prediction model, the Isight software integrates a multi-objective particle swarm optimization algorithm to achieve hierarchical coupled optimization of parameters. The specific process is as follows: Step 51: In each iteration, call the finite element simulation model of each key process after data iteration correction, calculate the response values ​​of stress field and deformation field in objective function respectively, and adopt adaptive weight allocation and dynamic inertia factor update mechanism to improve local search accuracy while maintaining global convergence. Step 52: Based on the response values ​​of the stress field and deformation field, for different process parameters (such as forging temperature, diffusion welding pressure, electron beam welding power, heat treatment temperature and holding time, etc.), combined with the established cross-process influence matrix, perform coupling correlation calculations between parameters to obtain equivalent coupling parameters; Step 53: Based on the response values ​​of the stress field and deformation field and the equivalent coupling parameters, the velocity and position are iteratively updated in the multidimensional design space through particle swarm optimization to obtain the optimal parameter combination that satisfies the dual objective constraints of global minimum deformation and minimum residual stress. Step 54: The optimal parameter combination is automatically fed back to the full-process simulation prediction model for recalculation to obtain the full-process simulation results, which can be used for further verification, realizing an integrated closed-loop optimization process of optimization-simulation-correction.

[0015] Preferably, the process of calculating the deviation between the actual residual stress and the stress field in the simulation results, and the deviation between the actual deformation data and the deformation field in the simulation results, and then correcting the corresponding simulation model based on the deviation values ​​is as follows: Step 61: Analyze and determine the main sources of deviation; Step 62: Select the correction method and the key parameters to be corrected based on the source of the deviation value, and correct the key parameters of the corresponding process according to the correction method and the deviation value to achieve model optimization; The corresponding simulation model is corrected; the sources of deviation values ​​include material parameter deviations, boundary condition setting deviations, and process parameter deviations; for material parameter deviations, inversion or least squares optimization methods are used to correct simulation parameters such as elastic modulus and coefficient of thermal expansion based on the deviation values; for boundary condition setting deviations, clamping constraints are adjusted based on the deviation values; for process parameter deviations, heat source power and heat input distribution are corrected based on the deviation values.

[0016] As can be seen from the above technical solution, compared with the prior art, this invention discloses a closed-loop optimization method for full-process simulation of the air intake casing, overcoming the problems of insufficient result transfer accuracy, incomplete coverage of process links, and inability to accurately optimize complex aerospace structural components in the multi-process residual stress simulation of the prior art. It can achieve high-precision prediction, continuous result transfer, and multi-objective optimization of residual stress and deformation during continuous simulation in a multi-process, multi-grid environment. Specifically, it has the following beneficial effects: (1) Numerical simulation of all manufacturing processes that significantly affect the residual stress and deformation of the structure, such as forging, machining, heat treatment, diffusion welding, and electron beam welding, was carried out, breaking through the limitations of existing technologies that only simulate and analyze single or partial processes. Through full-process modeling and calculation, the stress evolution, deformation accumulation, and mutual influence between different processes of the intake casing at different processing stages can be systematically reflected, thus providing a scientific basis for optimizing the overall manufacturing scheme of the casing.

[0017] (2) It is applicable to geometric mapping and simulation data transfer for different finite element platforms and different mesh sizes, and can transfer the stress, deformation and other results calculated in the previous process to the simulation model of the next process with high precision. It greatly improves the flexibility of process simulation model establishment and cross-platform adaptability, ensures the physical consistency and calculation stability of result transfer in the whole process simulation, and avoids the risk of data accuracy loss in the transfer process.

[0018] (3) Based on the simulation results of the whole process, the multi-objective particle swarm optimization algorithm is integrated to realize the multi-objective iterative optimization of multiple process parameters, which can achieve a balance among multiple performance indicators and thus obtain the optimal combination of process parameters. Attached Figure Description

[0019] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on the provided drawings without creative effort.

[0020] Figure 1 This is a simulation closed-loop optimization flowchart of the entire process of the intake casing provided in this embodiment of the invention; Figure 2 This is a schematic diagram of the simulation result correction process of the finite element simulation model provided in the embodiments of the present invention; Figure 3 This is a schematic diagram of the process for correcting the structural mapping between processes provided in an embodiment of the present invention; Figure 4This is a simplified structural diagram of the intake casing and its forming process provided in an embodiment of the present invention; Figure 5 This is a comparison diagram of the support plate before and after different grid mappings provided in the embodiments of the present invention. Detailed Implementation

[0021] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0022] This invention discloses a closed-loop optimization method for the entire process of an intake casing simulation, comprising the following steps: S1: Based on the three-dimensional digital model of the intake casing, the geometric features are simplified in stages to obtain a simplified model; S2: Select several key processes that are sensitive to residual stress and deformation from the entire process of machining the intake casing according to the machining sequence; S3: Based on the actual process parameters and boundary conditions corresponding to the key processes, the simplified model is meshed to construct the corresponding finite element simulation model for each key process; S4: Simulate the corresponding finite element simulation model in sequence according to the key process order, and correct the simulation results according to the actual deformation data of the actual sample feature surface of the corresponding key process. Calibrate the finite element simulation model, and transfer the corrected simulation results to the next key process for finite element simulation model simulation until all key processes are simulated and corrected. Construct the full process simulation prediction model for the finite element simulation models corresponding to all key processes that have been simulated and corrected. S5: Call the optimization software to iteratively optimize the key parameters of multiple processes in the full-process simulation prediction model, obtain the optimal parameter combination, and input the optimal parameter combination into the full-process simulation prediction model to obtain the full-process simulation results; S6: Control the actual processing based on the verified optimal parameter combination, collect the actual residual stress and actual deformation data of each process, and obtain the deviation value by subtracting it from the simulation results of the whole process. If the deviation value exceeds the set threshold, the key parameters of the corresponding process are corrected according to the deviation value to achieve feedback closed-loop optimization of the whole process.

[0023] Furthermore, the key processes include, in sequence, forging of the support plate blank, machining of the inner cavity of the support plate, diffusion welding of the support plate, electron beam welding of the support plate, overall heat treatment of the casing after welding, and precision machining of the casing.

[0024] Furthermore, the specific process of S4 is as follows: S41: Select the first critical process as the current process; S42: Apply initial conditions to the finite element simulation model corresponding to the current process and perform simulation calculations. Use data transfer software to extract the stress field and deformation field from the simulation results. S43: Collect the actual deformation data of the feature surface of the actual sample in the current process, and perform inverse calculation to obtain the residual stress field. Use the residual stress field to iteratively correct the stress field and deformation field of the current simulation results. S44: Write the corrected stress and strain into the next key process through a standardized interface file to achieve cross-process data transfer. Take the next key process as the current process and return to step 5. Repeat this process until all key processes are traversed. Apply initial conditions to all key processes in sequence, perform numerical simulation, conduct result calibration and data mapping, and build a full-process simulation prediction model.

[0025] Furthermore, the finite element software used for the simulation calculations was Abaqus and Simufact Welding.

[0026] Furthermore, when performing simulation calculations, the initial stress, initial strain, or temperature field is defined by modifying the .inp file when writing data to the finite element software Abaqus; and it is set through the initial field definition module when writing data to the finite element software Simufact Welding.

[0027] Furthermore, the data transfer software is Digimat-MAP, which extracts and transfers stress and strain through geometric mapping between models. Specifically, the simulation results of the upstream process and the corresponding finite element simulation models of the downstream process are imported into Digimat-MAP, and a spatial correspondence is established through geometric boundary matching to generate the source model result file. The stress and strain of the nodes or integration points are extracted from the source model result file, and the field variables under different mesh densities are reconstructed by multi-point interpolation based on element shape functions. The Field Transfer function is used to complete the mapping and generate an input file that can be directly used for subsequent simulations.

[0028] Furthermore, the specific process of S43 is as follows: S431: Use a three-coordinate measuring system to obtain the actual deformation data of the feature surface of the actual sample, i.e. the deformation field, and solve the residual stress field of the feature surface of the actual sample based on the deformation field. S432: Based on the principle of intrinsic strain incompatibility, a static equilibrium equation is established. The stress field is cyclically mapped to the corresponding finite element simulation model according to the static equilibrium equation. The static equilibrium of the stress field is iterated to reconstruct the actual residual stress field inside the actual sample of the intake casing. S433: Reconstruct the actual overall deformation field corresponding to the intake casing using the reconstructed actual residual stress field; S434: Corrects the stress field of the current simulation results to the actual residual stress field and the deformation field to the actual overall deformation field.

[0029] Furthermore, after the sample processing is completed, the actual residual stress is measured using an X-ray residual stress tester, and the post-weld deformation is measured using a three-coordinate measuring system with a three-dimensional scanning modeling method to obtain the actual deformation data.

[0030] Furthermore, when iteratively optimizing the key parameters of multiple processes in the full-process simulation prediction model, the Isight software integrates a multi-objective particle swarm optimization algorithm to achieve hierarchical coupled optimization of the parameters. The specific process is as follows: S51: In each iteration, the finite element simulation models of each key process after data iteration correction are called to calculate the response values ​​of stress field and deformation field in objective function respectively. An adaptive weight allocation and dynamic inertia factor update mechanism are adopted to improve local search accuracy while maintaining global convergence. S52: Based on the response values ​​of the stress field and deformation field, for different process parameters (such as forging temperature, diffusion welding pressure, electron beam welding power, heat treatment temperature and holding time, etc.), combined with the established cross-process influence matrix, the coupling correlation between parameters is calculated to obtain the equivalent coupling parameters. S53: By iteratively updating the velocity and position of the particle swarm in the multidimensional design space, the optimal combination of parameters that satisfies the dual objective constraints of global minimum deformation and minimum residual stress is obtained. S54: The optimal parameter combination is automatically fed back to the full-process simulation prediction model for recalculation to obtain the full-process simulation results, which can be used for further verification, realizing an integrated closed-loop optimization process of optimization-simulation-correction.

[0031] Furthermore, the deviations between the actual residual stress and the stress field in the simulation results, and the deviations between the actual deformation data and the deformation field in the simulation results are calculated separately. The process of correcting the corresponding simulation model based on these deviations is as follows: S61: Analyze and determine the main sources of deviation values; S62: Select the correction method and the key parameters to be corrected based on the source of the deviation value, and correct the key parameters of the corresponding process according to the correction method and the deviation value to achieve model optimization; The corresponding simulation model is corrected; the sources of deviation values ​​include material parameter deviations, boundary condition setting deviations, and process parameter deviations; for material parameter deviations, inversion or least squares optimization methods are used to correct simulation parameters such as elastic modulus and coefficient of thermal expansion based on the deviation values; for boundary condition setting deviations, clamping constraints are adjusted based on the deviation values; for process parameter deviations, heat source power and heat input distribution are corrected based on the deviation values.

[0032] In one specific embodiment, according to Figure 4As shown, the intake casing is mainly made of support plate structure processed and welded. The blank is forged and internally machined, then diffusion welded. After that, electron beam welding is used to weld the diffusion welded support plates together and heat treatment, and then precision machining is performed to obtain the finished casing.

[0033] In this embodiment, the entire process of inlet casing manufacturing is simulated and optimized using a closed-loop process, such as... Figure 1 As shown, it mainly includes: (1) Simplify the geometric model by removing unnecessary rounded corners and small holes; (2) The key processes are identified as forging of the support plate blank, machining of the inner cavity of the support plate, diffusion welding of the support plate, electron beam welding of the support plate, overall heat treatment of the casing after welding, and precision machining of the casing. (3) Based on the actual process of each key process, determine the process parameters and boundary conditions required for simulation, mesh the simplified geometric model, and establish the finite element simulation model of each key process; (4) Perform simulation analysis of the finite element simulation model corresponding to the first key process of forging the support plate billet. After completion, use Digimat-MAP software to perform high-precision mapping and extraction of stress and strain data in the simulation results. (5) Measure the actual deformation of the characteristic surface of the forged support plate blank, infer its residual stress field, and iteratively correct the extracted stress and strain results. The correction process is as follows: Figure 2 As shown, the actual deformation of the characteristic surface of the sample forged from the support plate blank is measured. The residual stress is obtained by solving the local solution based on the deformation field corresponding to the deformation. The local residual stress is substituted into the finite element simulation model for static equilibrium iteration to obtain the actual residual stress field after overall correction of the intake casing. Then, the actual deformation field of the intake casing is corrected according to the actual residual stress field. Finally, the simulation results of the actual residual stress field and the actual deformation field are corrected. (6) The corrected simulation results are written into the finite element simulation model of the subsequent process through a standardized interface file to achieve effective transfer of simulation data; the transfer process is as follows: Figure 3 As shown, taking the result transfer between different processes in Abaqus as an example, firstly, the ".odb" result file of the preceding process is imported into the mapping software, the stress (stress field) and strain (deformation field) of the preceding process results are extracted, corrected, and finally the corrected results are written into the ".inp" file of the subsequent process for simulation calculation; as shown... Figure 5 The figures shown are comparisons of the support plate before and after different mesh mappings. The two sets of figures at the top are simulation results, and the two sets of figures at the bottom are mapping results. (7) Conduct multi-process coupled simulation analysis in sequence to obtain a full-process simulation prediction model of the intake casing manufacturing process; (8) Use the iSight software to iteratively optimize the key parameters of multiple processes in the full-process simulation prediction model to obtain the optimal parameter combination; (9) Apply the obtained optimal parameter combination to the actual product processing, detect the residual stress and deformation in each process, and compare it with the simulation prediction results of the corresponding process; if there is a deviation and the deviation value exceeds the set threshold, then correct the corresponding simulation model to realize the feedback closed-loop optimization of the whole system.

[0034] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on its differences from other embodiments. Similar or identical parts between embodiments can be referred to interchangeably. For the apparatus disclosed in the embodiments, since they correspond to the methods disclosed in the embodiments, the description is relatively simple; relevant parts can be referred to the method section.

[0035] The above description of the disclosed embodiments enables those skilled in the art to make or use the invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the invention. Therefore, the invention is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A closed-loop optimization method for the entire process of an intake casing, characterized in that, Includes the following steps: Step 1: Based on the three-dimensional digital model of the intake casing, the geometric features are simplified in stages to obtain a simplified model; Step 2: Select several key processes that are sensitive to residual stress and deformation from the entire process of machining the intake casing according to the machining sequence; Step 3: Based on the actual process parameters and boundary conditions corresponding to the key processes, mesh the simplified model and construct the corresponding finite element simulation model for each key process; Step 4: Simulate the corresponding finite element simulation model in sequence according to the key process order, and correct the simulation results according to the actual deformation data of the actual sample feature surface of the corresponding key process. Calibrate the finite element simulation model, and transfer the corrected simulation results to the next key process for finite element simulation model simulation until all key processes are simulated and corrected. All finite element simulation models form a full process simulation prediction model. Step 5: Call the optimization software to iteratively optimize the key parameters of multiple processes in the full-process simulation prediction model, obtain the optimal parameter combination, and input the optimal parameter combination into the full-process simulation prediction model for simulation to obtain the full-process simulation results; Step 6: Control the actual processing according to the verified optimal parameter combination, collect the actual residual stress and actual deformation data of each process, and obtain the deviation value by subtracting it from the full process simulation result. If the deviation value exceeds the set threshold, correct the corresponding full process simulation result according to the deviation value.

2. The closed-loop optimization method for full-process simulation of the intake casing as described in claim 1, characterized in that, The key processes include, in sequence, forging of the support plate blank, machining of the inner cavity of the support plate, diffusion welding of the support plate, electron beam welding of the support plate, overall heat treatment of the casing after welding, and precision machining of the casing.

3. The closed-loop optimization method for full-process simulation of the intake casing as described in claim 1, characterized in that, The specific process of step 4 is as follows: Step 41: Select the first critical process as the current process; Step 42: Apply initial conditions to the finite element simulation model corresponding to the current process and perform simulation calculations. Use data transfer software to extract the stress field and deformation field from the simulation results. Step 43: Collect the actual deformation data of the feature surface of the actual sample in the current process, and perform back calculation to obtain the residual stress field. Use the residual stress field to iteratively correct the stress field and deformation field of the current simulation results. Step 44: Write the corrected stress and strain into the next key process through a standardized interface file to achieve cross-process data transfer. Set the next key process as the current process and return to step 5, until all key processes are traversed. The finite element simulation models of all key processes that have been simulated and corrected are combined to form the full-process simulation prediction model.

4. The closed-loop optimization method for the entire process of the intake casing as described in claim 1, characterized in that, The finite element software used for the simulation calculations was Abaqus and Simufact Welding.

5. The closed-loop optimization method for full-process simulation of the intake casing as described in claim 4, characterized in that, When performing simulation calculations, the initial conditions are defined by modifying the .inp file when writing data to the finite element software Abaqus; and the initial conditions are set through the initial field definition module when writing data to the finite element software Simufact Welding.

6. The closed-loop simulation optimization method for the entire process of the intake casing as described in claim 3, characterized in that, The data transfer software is Digimat-MAP, which extracts and transfers stress and strain through geometric mapping between finite element simulation models.

7. The closed-loop optimization method for full-process simulation of the intake casing as described in claim 3, characterized in that, The specific process of step 43 is as follows: Step 431: Use a coordinate measuring system to obtain the actual deformation data of the feature surface of the actual sample, and solve the residual stress field of the feature surface of the actual sample based on the actual deformation data; Step 432: Based on the principle of intrinsic strain incompatibility, establish the static equilibrium equation, and according to the static equilibrium equation, cyclically map the stress field to the corresponding finite element simulation model, perform static equilibrium iteration of the stress field, and reconstruct the actual residual stress field inside the actual sample of the intake casing. Step 433: Reconstruct the actual overall deformation field corresponding to the intake casing using the reconstructed actual residual stress field; Step 434: Correct the stress field of the current simulation results to the actual residual stress field, and correct the deformation field to the actual overall deformation field.

8. The closed-loop optimization method for full-process simulation of the intake casing as described in claim 3, characterized in that, The multi-objective particle swarm optimization algorithm is used to iteratively optimize the key parameters of multiple processes in the full-process simulation prediction model. The specific process is as follows: Step 51: In each iteration, call the finite element simulation model of each key process after data iteration correction, and use the adaptive weight allocation and dynamic inertia factor update mechanism to search, and calculate the response values ​​of stress field and deformation field in objective function respectively. Step 52: Based on the response values ​​of the stress field and deformation field for different process parameters, and combined with the established cross-process influence matrix, perform coupling correlation calculations between parameters to obtain equivalent coupling parameters; Step 53: Based on the response values ​​of the stress field and deformation field and the equivalent coupling parameters, the velocity and position are iteratively updated in the multidimensional design space through particle swarm optimization to obtain the optimal parameter combination that satisfies the dual objective constraints of global minimum deformation and minimum residual stress. Step 54: Automatically transmit the optimal parameter combination back to the full-process simulation prediction model for recalculation to obtain the full-process simulation results.

9. The closed-loop simulation optimization method for the entire process of the intake casing as described in claim 3, characterized in that, The process of calculating the deviation between the actual residual stress and the stress field in the simulation results, and the deviation between the actual deformation data and the deformation field in the simulation results, and then correcting the corresponding simulation model based on the deviation values ​​is as follows: Step 61: Analyze and determine the main sources of deviation; Step 62: Select the correction method and the key parameters to be corrected based on the source of the deviation value, and correct the key parameters based on the correction method and the deviation value.

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