Multi-layer logic case pressure capability prediction model and verification integrated method

Abstract

The application discloses a kind of multilayer logic's machine case pressure resistance capability prediction model preferred and verification integration method, comprising the following steps: true stress strain curve is obtained to round bar sample tension, selects ten constitutive models fitting, load displacement simulation curve is obtained by finite element calculation, and compared with test curve screening eight constitutive models;Load displacement curve is obtained to bilateral notch sample tension, eight constitutive models are calculated to obtain load displacement simulation curve, and compared with test curve screening four constitutive models;Load displacement curve is obtained to structural characteristic element tension, four constitutive models are calculated to obtain load displacement simulation curve, and compared with test curve screening two constitutive models;Pressure displacement curve is obtained to machine case simulation test piece pressure test, two constitutive models are calculated to obtain pressure displacement simulation curve, and compared with test curve screening optimal constitutive model.The application solves the problem of constitutive model optimization and verification of new material of combustion chamber casing.

Description

Technical Field

[0001] This invention belongs to the technical field of performance evaluation and structural strength assessment of new materials, specifically involving an integrated method for the selection and verification of a multi-layer logic casing pressure resistance prediction model. Background Technology

[0002] The combustion chamber casing of an aero engine is the part of the engine with the highest pressure. If its strength and rigidity are insufficiently designed, at best, the high-temperature, high-pressure combustion gases inside the casing may leak, potentially burning engine accessories and causing the engine to deviate from its design state, thus affecting the engine's thrust. At worst, it could cause the engine to explode, resulting in a fatal accident. In pursuit of higher-performance aero engines, with the advent of new materials, designers are constantly trying to use these new materials to manufacture engine combustion chamber casings. For example, advanced high-temperature resistant titanium-aluminum intermetallic compound materials, with their lightweight and high strength, have become the preferred material for the next generation of aero engine casings.

[0003] However, due to the high testing costs of new material components, it is difficult to design and verify the combustion chamber casing configuration through large-scale experimental research. Therefore, designers need to establish a reliable prediction model for the ultimate pressure resistance of the combustion chamber casing to conduct an applicability assessment of the casing configuration, and verify the rationality and reliability of the design configuration through a very small number of component tests, thereby enhancing their confidence in the selection and application of new material casings.

[0004] Currently, plastic failure analysis methods for combustion chamber casings are gradually replacing traditional allowable stress design methods. Establishing accurate elastoplastic constitutive models for new materials has become a key focus in developing methods for predicting the ultimate pressure resistance of casings. Traditional methods for establishing elastoplastic constitutive models often involve artificially selecting one or more curves based on the true stress-strain curve trends obtained from tensile tests of smooth round bar specimens, fitting constitutive parameters, and then directly using them for structural strength calculations of the casing, without verification through experimental results of characteristic elements. On the one hand, the success of model establishment depends on the experience of engineers; on the other hand, the constitutive model and parameters lack extensive multi-level verification. The reliability of elastoplastic constitutive models established using traditional methods for predicting the ultimate bearing capacity of actual structures is insufficient, especially for the application of new materials. Therefore, it is necessary to develop a multi-level logic integrated method for selecting and verifying casing pressure resistance prediction models to address the problems existing in current technologies.

[0005] The invention patent with publication number CN113962120A discloses a method for predicting the ultimate pressure resistance of a combustion chamber casing, including the following steps: designing smooth round bar specimens and tandem notched specimens to conduct uniaxial tensile tests, obtaining the true stress-true strain curve of the combustion chamber casing material and the load-displacement curve of the tandem notched specimen; fitting elastoplastic constitutive model parameters based on the true stress-true strain curve of the material and setting them as initial values; obtaining the elastoplastic constitutive model parameters of the combustion chamber casing material through large deformation nonlinear finite element analysis based on the tandem notched axisymmetric model; establishing a finite element model of the combustion chamber casing based on the inverted elastoplastic constitutive model of the material; and using the arc-length method to calculate the change curve of the internal pressure value of the combustion chamber casing with radial deformation through large deformation finite element analysis to determine the ultimate pressure resistance value of the combustion chamber casing. This technical solution predicts the ultimate pressure resistance of the casing under the condition of a known elastoplastic constitutive model of the material, but it is uncertain whether the elastoplastic constitutive model used is the optimal model, and no model verification has been performed, so the prediction result of the ultimate pressure resistance of the casing is inaccurate. Summary of the Invention

[0006] To address the problems existing in the prior art, this invention provides an integrated method for selecting and verifying a multi-layer logic chassis withstand pressure capability prediction model, comprising the following steps in sequence:

[0007] Step 1: For the new material combustion chamber casing, identify the critical parts of the combustion chamber casing, and provide the stress concentration factor, local geometry, and principal stress distribution along the direction of the maximum principal stress gradient for the critical parts;

[0008] Step 2: Prepare a smooth round bar specimen for tensile testing, and perform tensile testing on it to obtain the engineering stress-engineering strain curve of the smooth round bar specimen, and convert the engineering stress-engineering strain curve into a true stress-true strain curve.

[0009] Step 3: Select ten elastoplastic constitutive models and use the ten elastoplastic constitutive models to fit the true stress-true strain curves of the smooth round bar specimens to obtain the fitting parameters of the ten elastoplastic constitutive models.

[0010] Step 4: Import the ten elastoplastic constitutive models and parameters into the finite element simulation software, and calculate the simulation curves between tensile load and tensile displacement of the ten smooth round bar specimens using the finite element simulation software. At the same time, plot the test curves between tensile load and tensile displacement of the smooth round bar specimens using the test data obtained from the tensile test. Compare the standard deviation and correlation coefficient of the ten simulation curves with the test curves, and select the elastoplastic constitutive model with a small standard deviation and a correlation coefficient close to 1. Based on the comparison results, eight elastoplastic constitutive models are selected.

[0011] Step 5: Prepare a double-notched plate specimen with the same stress gradient distribution as the critical part of the combustion chamber casing, and conduct a tensile test on it to obtain the test curve between the tensile load and tensile displacement of the double-notched plate specimen.

[0012] Step 6: Import the eight selected elastoplastic constitutive models and parameters into the finite element simulation software, and calculate the simulation curves between tensile load and tensile displacement of the eight double-notched plate specimens using the finite element simulation software. Compare the standard deviation and correlation coefficient of the eight simulation curves with the experimental curves, and select the elastoplastic constitutive model with a small standard deviation and a correlation coefficient close to 1. Based on the comparison results, further select four elastoplastic constitutive models.

[0013] Step 7: Prepare structural feature elements with the same stress gradient distribution as the critical parts of the combustion chamber casing, and conduct tensile tests on them to obtain the test curves between tensile load and tensile displacement of the structural feature elements;

[0014] Step 8: Import the four selected elastoplastic constitutive models and parameters into the finite element simulation software, and calculate the simulation curves between the tensile load and tensile displacement of the four structural feature elements using the finite element simulation software. Compare the standard deviation and correlation coefficient of the four simulation curves with the experimental curves, and select the elastoplastic constitutive model with a small standard deviation and a correlation coefficient close to 1. Based on the comparison results, further select two elastoplastic constitutive models.

[0015] Step 9: Using the two selected elastoplastic constitutive models and parameters as initial values, the simulation curves between tensile load and tensile displacement of the smooth round bar specimen, the double-notched plate specimen, and the structural feature element are calculated using finite element simulation software. The standard deviation and correlation coefficient of the six simulation curves are compared with the corresponding test curves. At the same time, the parameters of the two elastoplastic constitutive models are continuously adjusted so that the smooth round bar specimen, the double-notched plate specimen, and the structural feature element simultaneously meet the conditions of small standard deviation and correlation coefficient close to 1 under the same elastoplastic constitutive model and parameters. Based on the adjustment results, the optimal parameters of the two elastoplastic constitutive models are obtained respectively.

[0016] Step 10: Fabricate a casing simulation specimen based on the new material combustion chamber casing, and conduct a pressure resistance test on it to obtain the test curve between pressure and displacement of the casing simulation specimen;

[0017] Step 11: Import the two selected elastoplastic constitutive models and parameters into the finite element simulation software, and calculate the simulation curves between pressure and displacement of the two casing simulation specimens using the finite element simulation software. Compare the standard deviation and correlation coefficient of the two simulation curves with the experimental curves, and select the elastoplastic constitutive model with a smaller standard deviation and a correlation coefficient close to 1. Based on the comparison results, further select an elastoplastic constitutive model and take it as the best elastoplastic constitutive model.

[0018] Preferably, in step one, the new material is a titanium-aluminum intermetallic compound material, and the dangerous parts include the borehole, fuel nozzle opening, igniter opening, and compressor vent.

[0019] In any of the above schemes, it is preferred that, in step three, the ten elastoplastic constitutive models selected include the rate-independent Mises type multilinear isotropic hardening model, the rate-independent Hill type multilinear isotropic hardening model, the rate-independent Mises type multilinear kinematic hardening model, the rate-independent Hill type multilinear kinematic hardening model, the rate-independent Mises type Chaboche model, the rate-independent Hill type Chaboche model, the rate-independent Mises type Chaboche combined with multilinear isotropic hardening model, the rate-independent Hill type Chaboche combined with multilinear isotropic hardening model, the rate-dependent Mises type multilinear isotropic hardening model, and the rate-dependent Hill type multilinear isotropic hardening model.

[0020] In any of the above schemes, it is preferred that, in step four, the eight elastoplastic constitutive models selected based on the comparison results include the rate-independent Mises type multilinear isotropic hardening model, the rate-independent Hill type multilinear isotropic hardening model, the rate-independent Mises type multilinear kinematic hardening model, the rate-independent Hill type multilinear kinematic hardening model, the rate-independent Mises type Chaboche model, the rate-independent Hill type Chaboche model, the rate-independent Mises type Chaboche combined with multilinear isotropic hardening model, and the rate-independent Hill type Chaboche combined with multilinear isotropic hardening model.

[0021] In any of the above schemes, the preferred option is that, in step six, the four elastoplastic constitutive models selected based on the comparison results include the rate-independent Mises type multilinear isotropic hardening model, the rate-independent Mises type multilinear kinematic hardening model, the rate-independent Mises type Chaboche model, and the rate-independent Mises type Chaboche and multilinear isotropic hardening combination model.

[0022] In any of the above schemes, it is preferred that, in step eight, the two elastoplastic constitutive models selected based on the comparison results include the rate-independent Mises-type Chaboche model and the rate-independent Mises-type Chaboche combined with the multilinear isotropic hardening model.

[0023] In any of the above schemes, it is preferred that, in step eleven, the optimal elastoplastic constitutive model selected based on the comparison results includes the rate-independent Mises-type Chaboche model.

[0024] Preferably, in any of the above embodiments, the smooth round bar specimen, the double-notched plate specimen, and the structural feature elements are made of the same material as the combustion chamber casing. The finite element simulation software and elasto-plastic constitutive model parameter optimization software used in this invention include Abaqus, Ansys, MSC.Marc, and Isight. The parameters used in this invention include elasto-plastic constitutive model parameters, elastic modulus, Poisson's ratio, etc.

[0025] To improve the accuracy of elastoplastic constitutive modeling for new materials applied to aero-engine combustor casings and to address the issues of optimizing and verifying elastoplastic constitutive models for new combustor casing materials, this invention proposes an integrated method for optimizing and verifying casing pressure resistance prediction models using multi-level logic. This method utilizes multi-level logic for optimization and verification, ensuring that optimization and verification at each level are completed simultaneously, ultimately obtaining the optimal elastoplastic constitutive model and parameters. This enhances the reliability of applying elastoplastic constitutive models of new materials and the maturity of applying new materials to aero-engine combustor casings, thereby increasing the confidence of engineering designers in using elastoplastic constitutive models of new materials for aero-engine combustor casings.

[0026] The integrated method for selecting and verifying the multi-layer logic chassis withstand pressure capability prediction model of the present invention has the following beneficial effects:

[0027] (1) It can determine the optimal elastoplastic constitutive model and parameters for the development of new materials for the combustion chamber casing of aero-engines, and can also perform multi-level optimization and verification in an integrated manner.

[0028] (2) It can significantly improve the accuracy and reliability of the prediction model of the ultimate pressure resistance of the combustion chamber casing of new materials, and enhance the maturity and confidence of the application of new materials in engineering design.

[0029] (3) It can broadly and systematically verify the applicability of the new material elastoplastic constitutive model and the accuracy of the model parameters. Attached Figure Description

[0030] Figure 1 A flowchart of a preferred embodiment of the integrated method for selecting and verifying the multi-layer logic casing pressure resistance prediction model according to the present invention;

[0031] Figure 2 for Figure 1 The schematic diagram of the combustion chamber casing of the aero-engine shown in the embodiment is as follows;

[0032] Figure 3 for Figure 1 The principal stress distribution at the characteristic parts of the hole structure in the illustrated embodiment;

[0033] Figure 4 for Figure 1 A schematic diagram of the smooth round bar sample in the embodiment shown;

[0034] Figure 5 for Figure 1 The true stress-true strain curve of the smooth round bar specimen in step two of the embodiment shown;

[0035] Figure 6 for Figure 1 Simulation curves of the eight elastoplastic constitutive models selected in step four of the illustrated embodiment;

[0036] Figure 7 for Figure 1 A schematic diagram of the structure of the double-notched flat plate specimen in the embodiment shown;

[0037] Figure 8 for Figure 1 The load versus displacement test curves of the double-notched plate specimen in step five of the illustrated embodiment;

[0038] Figure 9 for Figure 1 A schematic diagram of the structure of the central hole reinforced plate specimen in the embodiment shown;

[0039] Figure 10 for Figure 1 The load-displacement test curves of the central hole reinforced plate specimen in step seven of the embodiment shown;

[0040] Figure 11 for Figure 1 Simulation curves of the two elastoplastic constitutive models selected in step eight of the illustrated embodiment;

[0041] Figure 12 for Figure 1 The curve showing the relationship between the pressure applied to the casing and the strain measured by the surface strain gauge in the illustrated embodiment.

[0042] Figure 13 for Figure 1 The simulation curve of the optimal elastoplastic constitutive model selected in step eleven of the embodiment shown.

[0043] The diagram shows the following markings: 1-Probe opening, 2-Fuel nozzle opening, 3-Compressor vent, 4-Ignition device opening. Detailed Implementation

[0044] To further understand the invention, the following detailed description of the invention will be provided in conjunction with specific embodiments.

[0045] like Figure 1 As shown, a preferred embodiment of the integrated method for selecting and verifying the multi-layer logic casing pressure resistance prediction model according to the present invention includes the following steps in sequence:

[0046] Step 1: For the new material combustion chamber casing, identify the critical parts of the combustion chamber casing, and provide the stress concentration factor, local geometry, and principal stress distribution along the direction of the maximum principal stress gradient for the critical parts;

[0047] Step 2: Prepare a smooth round bar specimen for tensile testing, and perform tensile testing on it to obtain the engineering stress-engineering strain curve of the smooth round bar specimen, and convert the engineering stress-engineering strain curve into a true stress-true strain curve.

[0048] Step 3: Select ten elastoplastic constitutive models and use the ten elastoplastic constitutive models to fit the true stress-true strain curves of the smooth round bar specimens to obtain the fitting parameters of the ten elastoplastic constitutive models.

[0049] Step 4: Import the ten elastoplastic constitutive models and parameters into the finite element simulation software, and calculate the simulation curves between tensile load and tensile displacement of the ten smooth round bar specimens using the finite element simulation software. At the same time, plot the test curves between tensile load and tensile displacement of the smooth round bar specimens using the test data obtained from the tensile test. Compare the standard deviation and correlation coefficient of the ten simulation curves with the test curves, and select the elastoplastic constitutive model with a small standard deviation and a correlation coefficient close to 1. Based on the comparison results, eight elastoplastic constitutive models are selected.

[0050] Step 5: Prepare a double-notched plate specimen with the same stress gradient distribution as the critical part of the combustion chamber casing, and conduct a tensile test on it to obtain the test curve between the tensile load and tensile displacement of the double-notched plate specimen.

[0051] Step 6: Import the eight selected elastoplastic constitutive models and parameters into the finite element simulation software, and calculate the simulation curves between tensile load and tensile displacement of the eight double-notched plate specimens using the finite element simulation software. Compare the standard deviation and correlation coefficient of the eight simulation curves with the experimental curves, and select the elastoplastic constitutive model with a small standard deviation and a correlation coefficient close to 1. Based on the comparison results, further select four elastoplastic constitutive models.

[0052] Step 7: Prepare structural feature elements with the same stress gradient distribution as the critical parts of the combustion chamber casing, and conduct tensile tests on them to obtain the test curves between tensile load and tensile displacement of the structural feature elements;

[0053] Step 8: Import the four selected elastoplastic constitutive models and parameters into the finite element simulation software, and calculate the simulation curves between the tensile load and tensile displacement of the four structural feature elements using the finite element simulation software. Compare the standard deviation and correlation coefficient of the four simulation curves with the experimental curves, and select the elastoplastic constitutive model with a small standard deviation and a correlation coefficient close to 1. Based on the comparison results, further select two elastoplastic constitutive models.

[0054] Step 9: Using the two selected elastoplastic constitutive models and parameters as initial values, the simulation curves between tensile load and tensile displacement of the smooth round bar specimen, the double-notched plate specimen, and the structural feature element are calculated using finite element simulation software. The standard deviation and correlation coefficient of the six simulation curves are compared with the corresponding test curves. At the same time, the parameters of the two elastoplastic constitutive models are continuously adjusted so that the smooth round bar specimen, the double-notched plate specimen, and the structural feature element simultaneously meet the conditions of small standard deviation and correlation coefficient close to 1 under the same elastoplastic constitutive model and parameters. Based on the adjustment results, the optimal parameters of the two elastoplastic constitutive models are obtained respectively.

[0055] Step 10: Fabricate a casing simulation specimen based on the new material combustion chamber casing, and conduct a pressure resistance test on it to obtain the test curve between pressure and displacement of the casing simulation specimen;

[0056] Step 11: Import the two selected elastoplastic constitutive models and parameters into the finite element simulation software, and calculate the simulation curves between pressure and displacement of the two casing simulation specimens using the finite element simulation software. Compare the standard deviation and correlation coefficient of the two simulation curves with the experimental curves, and select the elastoplastic constitutive model with a smaller standard deviation and a correlation coefficient close to 1. Based on the comparison results, further select an elastoplastic constitutive model and take it as the best elastoplastic constitutive model.

[0057] In step one, the new material is a titanium-aluminum intermetallic compound. The hazardous areas include the borehole 1, fuel injector opening 2, igniter opening 3, and compressor vent 4. The specific locations of each opening on the combustion chamber casing are as follows: Figure 2 As shown. This embodiment takes borehole drilling as an example, and the stress concentration factor K at the borehole location is... t =1.8, the local geometry is an open-hole reinforced structure, and the distribution of the principal stress σ along the direction of the maximum principal stress gradient at the stress concentration point at the hole edge with respect to the distance r from the maximum stress concentration point at the hole edge is as follows. Figure 3 As shown.

[0058] In step two, the structure of the smooth round rod sample is as follows: Figure 4 As shown in the figure, three smooth round bar specimens were prepared in this embodiment, and tensile tests were performed on them respectively to obtain three sets of tensile test data. The average value of the three sets of tensile test data was taken, and finally a true stress-true strain curve of the smooth round bar specimen was obtained, as shown in the figure. Figure 5 As shown.

[0059] In step three, the ten selected elastoplastic constitutive models are: rate-independent Mises-type multilinear isotropic hardening model, rate-independent Hill-type multilinear isotropic hardening model, rate-independent Mises-type multilinear kinematic hardening model, rate-independent Hill-type multilinear kinematic hardening model, rate-independent Mises-type Chaboche model, rate-independent Hill-type Chaboche model, rate-independent Mises-type Chaboche combined with multilinear isotropic hardening model, rate-independent Hill-type Chaboche combined with multilinear isotropic hardening model, rate-dependent Mises-type multilinear isotropic hardening model, and rate-dependent Hill-type multilinear isotropic hardening model.

[0060] In step four, the eight elastoplastic constitutive models selected based on the comparison results are: rate-independent Mises-type multilinear isotropic hardening model, rate-independent Hill-type multilinear isotropic hardening model, rate-independent Mises-type multilinear kinematic hardening model, rate-independent Hill-type multilinear kinematic hardening model, rate-independent Mises-type Chaboche model, rate-independent Hill-type Chaboche model, rate-independent Mises-type Chaboche combined with multilinear isotropic hardening model, and rate-independent Hill-type Chaboche combined with multilinear isotropic hardening model. The simulation curves of these eight elastoplastic constitutive models are shown in the figure below. Figure 6 As shown in (1)-(8) of the table.

[0061] In step five, the structure of the double-notched flat plate specimen is as follows: Figure 7 As shown in the figure, three double-notched plate specimens were prepared in this embodiment, and tensile tests were performed on them respectively to obtain three sets of tensile test data. The average value of the three sets of tensile test data was taken, and finally a load-displacement test curve of the double-notched plate specimen was obtained, as shown in the figure. Figure 8 As shown.

[0062] In step six, the four elastoplastic constitutive models selected based on the comparison results are: rate-independent Mises type multilinear isotropic hardening model, rate-independent Mises type multilinear kinematic hardening model, rate-independent Mises type Chaboche model, and rate-independent Mises type Chaboche combined with multilinear isotropic hardening model.

[0063] In step seven, the structural feature element is a centrally hole-reinforced flat plate specimen, the specific structure of which is as follows: Figure 9 As shown in the figure, three centrally-hole reinforced plate specimens were prepared in this embodiment, and tensile tests were performed on them respectively to obtain three sets of tensile test data. The average value of the three sets of tensile test data was taken, and finally a load-displacement test curve of the centrally-hole reinforced plate specimen was obtained, as shown in the figure. Figure 10 As shown.

[0064] In step eight, the two elastoplastic constitutive models selected based on the comparison results are the rate-independent Mises-type Chaboche model and the rate-independent Mises-type Chaboche combined with a multilinear isotropic hardening model. The simulation curves of these two elastoplastic constitutive models are shown below. Figure 11 As shown in (1) and (2) in the figure.

[0065] In step ten, a pressure resistance test is performed on the casing simulation specimen. The test curve of the casing simulation specimen between pressure and displacement can be obtained from... Figure 12 Transformation, Figure 12 The curve showing the relationship between the pressure applied to the casing and the strain measured by surface strain gauges.

[0066] In step eleven, the optimal elastoplastic constitutive model selected based on the comparison results is the rate-independent Mises-type Chaboche model. The simulation curve of this optimal elastoplastic constitutive model is shown below. Figure 13 As shown. Optimal parameters include E_E = 113832.92, POSO = 0.3, C1 = 852, C2 = 543003.40899, C3 = 3914.11203, C4 = 542935.07812, C5 = 3913.28783, C6 = 19432.38179, C7 = 130.73546, etc.

[0067] In this embodiment, the materials used to prepare the smooth round bar specimen, the double-notched plate specimen, and the structural feature element are the same as those used to prepare the combustion chamber casing. The finite element simulation software and the elastoplastic constitutive model parameter optimization software used are Ansys and Isight. The parameters used include elastoplastic constitutive model parameters, elastic modulus, and Poisson's ratio.

[0068] To improve the accuracy of elastoplastic constitutive modeling of new materials applied to aero-engine combustor casings and to address the issues of optimizing and verifying the elastoplastic constitutive model of new combustor casing materials, this embodiment proposes a multi-level logic-based integrated method for optimizing and verifying the casing pressure resistance prediction model. This method utilizes multi-level logic for optimization and verification, ensuring that optimization and verification at each level are completed simultaneously, ultimately obtaining the optimal elastoplastic constitutive model and parameters. This enhances the reliability of the new material's elastoplastic constitutive model application and the maturity of its application in aero-engine combustor casings, thereby increasing the confidence of engineering designers in using the new material's elastoplastic constitutive model for aero-engine combustor casings.

[0069] Special Note: The technical solution of this invention involves numerous parameters, and the synergistic effects between these parameters must be comprehensively considered to achieve the beneficial effects and significant progress of this invention. Furthermore, the value ranges of each parameter in the technical solution were obtained through extensive experimentation. For each parameter and the combinations thereof, the inventors have recorded a large amount of experimental data; however, due to space limitations, the specific experimental data is not disclosed here.

[0070] Those skilled in the art will readily understand that the integrated method for selecting and verifying the multi-layer logic casing withstand pressure capability prediction model of the present invention includes any combination of the inventive content and specific embodiments described in the above specification and the various parts shown in the accompanying drawings. Due to space limitations and for the sake of brevity, not all of these combined solutions have been described. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for integrating the selection and verification of a multi-layer logic chassis withstand voltage capability prediction model, comprising the following steps in sequence: Step 1: For the new material combustion chamber casing, identify the critical parts of the combustion chamber casing, and provide the stress concentration factor, local geometry, and principal stress distribution along the direction of the maximum principal stress gradient for the critical parts; Step 2: Prepare a smooth round bar specimen for tensile testing, and perform tensile testing on it to obtain the engineering stress-engineering strain curve of the smooth round bar specimen, and convert the engineering stress-engineering strain curve into a true stress-true strain curve. Step 3: Select ten elastoplastic constitutive models and use the ten elastoplastic constitutive models to fit the true stress-true strain curves of the smooth round bar specimens to obtain the fitting parameters of the ten elastoplastic constitutive models. Step 4: Import the ten elastoplastic constitutive models and parameters into the finite element simulation software, and calculate the simulation curves between tensile load and tensile displacement of the ten smooth round bar specimens using the finite element simulation software. At the same time, plot the test curves between tensile load and tensile displacement of the smooth round bar specimens using the test data obtained from the tensile test. Compare the standard deviation and correlation coefficient of the ten simulation curves with the test curves, and select the elastoplastic constitutive model with a small standard deviation and a correlation coefficient close to 1. Based on the comparison results, eight elastoplastic constitutive models are selected. Step 5: Prepare a double-notched plate specimen with the same stress gradient distribution as the critical part of the combustion chamber casing, and conduct a tensile test on it to obtain the test curve between the tensile load and tensile displacement of the double-notched plate specimen. Step 6: Import the eight selected elastoplastic constitutive models and parameters into the finite element simulation software, and calculate the simulation curves between tensile load and tensile displacement of the eight double-notched plate specimens using the finite element simulation software. Compare the standard deviation and correlation coefficient of the eight simulation curves with the experimental curves, and select the elastoplastic constitutive model with a small standard deviation and a correlation coefficient close to 1. Based on the comparison results, further select four elastoplastic constitutive models. Step 7: Prepare structural feature elements with the same stress gradient distribution as the critical parts of the combustion chamber casing, and conduct tensile tests on them to obtain the test curves between tensile load and tensile displacement of the structural feature elements; Step 8: Import the four selected elastoplastic constitutive models and parameters into the finite element simulation software, and calculate the simulation curves between the tensile load and tensile displacement of the four structural feature elements using the finite element simulation software. Compare the standard deviation and correlation coefficient of the four simulation curves with the experimental curves, and select the elastoplastic constitutive model with a small standard deviation and a correlation coefficient close to 1. Based on the comparison results, further select two elastoplastic constitutive models. Step 9: Using the two selected elastoplastic constitutive models and parameters as initial values, the simulation curves between tensile load and tensile displacement of the smooth round bar specimen, the double-notched plate specimen, and the structural feature element are calculated using finite element simulation software. The standard deviation and correlation coefficient of the six simulation curves are compared with the corresponding test curves. At the same time, the parameters of the two elastoplastic constitutive models are continuously adjusted so that the smooth round bar specimen, the double-notched plate specimen, and the structural feature element simultaneously meet the conditions of small standard deviation and correlation coefficient close to 1 under the same elastoplastic constitutive model and parameters. Based on the adjustment results, the optimal parameters of the two elastoplastic constitutive models are obtained respectively. Step 10: Fabricate a casing simulation specimen based on the new material combustion chamber casing, and conduct a pressure resistance test on it to obtain the test curve between pressure and displacement of the casing simulation specimen; Step 11: Import the two selected elastoplastic constitutive models and parameters into the finite element simulation software, and calculate the simulation curves between pressure and displacement of the two casing simulation specimens using the finite element simulation software. Compare the standard deviation and correlation coefficient of the two simulation curves with the experimental curves, and select the elastoplastic constitutive model with a smaller standard deviation and a correlation coefficient close to 1. Based on the comparison results, further select an elastoplastic constitutive model and take it as the best elastoplastic constitutive model.

2. The integrated method for selecting and verifying the multi-layer logic chassis withstand voltage capability prediction model according to claim 1, characterized in that: In step one, the new material is a titanium-aluminum intermetallic compound material, and the dangerous parts include the borehole, fuel nozzle opening, igniter opening, and compressor vent.

3. The integrated method for selecting and verifying the multi-layer logic chassis withstand voltage capability prediction model according to claim 2, characterized in that: In step three, the ten selected elastoplastic constitutive models include the rate-independent Mises type multilinear isotropic hardening model, the rate-independent Hill type multilinear isotropic hardening model, the rate-independent Mises type multilinear kinematic hardening model, the rate-independent Hill type multilinear kinematic hardening model, the rate-independent Mises type Chaboche model, the rate-independent Hill type Chaboche model, the rate-independent Mises type Chaboche combined with multilinear isotropic hardening model, the rate-independent Hill type Chaboche combined with multilinear isotropic hardening model, the rate-dependent Mises type multilinear isotropic hardening model, and the rate-dependent Hill type multilinear isotropic hardening model.

4. The integrated method for selecting and verifying the multi-layer logic chassis withstand voltage capability prediction model according to claim 3, characterized in that: In step four, the eight elastoplastic constitutive models selected based on the comparison results include the rate-independent Mises type multilinear isotropic hardening model, the rate-independent Hill type multilinear isotropic hardening model, the rate-independent Mises type multilinear kinematic hardening model, the rate-independent Hill type multilinear kinematic hardening model, the rate-independent Mises type Chaboche model, the rate-independent Hill type Chaboche model, the rate-independent Mises type Chaboche combined with multilinear isotropic hardening model, and the rate-independent Hill type Chaboche combined with multilinear isotropic hardening model.

5. The integrated method for selecting and verifying the multi-layer logic chassis withstand voltage capability prediction model according to claim 4, characterized in that: In step six, the four elastoplastic constitutive models selected based on the comparison results include the rate-independent Mises type multilinear isotropic hardening model, the rate-independent Mises type multilinear kinematic hardening model, the rate-independent Mises type Chaboche model, and the rate-independent Mises type Chaboche combined with multilinear isotropic hardening model.

6. The integrated method for selecting and verifying the multi-layer logic chassis withstand voltage capability prediction model according to claim 5, characterized in that: In step eight, the two elastoplastic constitutive models selected based on the comparison results include the rate-independent Mises-type Chaboche model and the rate-independent Mises-type Chaboche combined with the multilinear isotropic hardening model.

7. The integrated method for selecting and verifying the multi-layer logic chassis withstand voltage capability prediction model according to claim 6, characterized in that: In step eleven, the optimal elastoplastic constitutive model selected based on the comparison results includes the rate-independent Mises-type Chaboche model.

8. The integrated method for selecting and verifying the multi-layer logic chassis withstand voltage capability prediction model according to claim 1, characterized in that: The smooth round bar specimen, the double-notched flat plate specimen, and the structural feature elements are made of the same material as the combustion chamber casing.

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