Metal diaphragm overturning performance simulation analysis method based on random distribution thickness method

Abstract

The invention relates to the technical field of aerospace and aviation engineering, in particular to a metal diaphragm overturning performance simulation analysis method based on a random distribution thickness method, which comprises the following steps of: establishing a parameterized metal diaphragm finite element modeling GUI (Graphical User Interface); based on the linear thickness distribution function, parameterizing to generate an initial geometric model and a finite element model of the metal diaphragm; constructing a random thickness deviation assignment GUI (Graphical User Interface), randomly selecting a unit set according to a set proportion through a random function, respectively endowing thickening and thinning thickness deviations, and simulating thickness unevenness caused by an actual process; and an explicit dynamics method is adopted to simulate and analyze the overturning process of the diaphragm under different deviation conditions, and a wrinkle behavior and a vertex transverse displacement change rule are obtained. According to the method, the random thickness deviation is incorporated into a simulation system, so that the simulation precision and the actual working condition adaptability can be improved; rapid modeling is realized through parameterized GUI, so that the simulation efficiency can be improved; the method is suitable for parametric modeling and fine design of the metal diaphragm.

Description

Technical Field

[0001] This method relates to aerospace engineering, specifically a simulation analysis method for the flipping performance of metal diaphragms based on the random thickness allocation method, which is mainly applied to the parametric modeling and refined design of metal diaphragms. Background Technology

[0002] The diaphragm tank is a critical component of a spacecraft propulsion system. Its operation involves high-pressure gas being pumped into the tank from an upper gas cylinder and pressing a metal diaphragm. Under the pressure difference, the diaphragm gradually flips downwards, squeezing propellant into the engine combustion chamber below, thus ensuring an efficient supply of propellant to the propulsion system. The metal diaphragm is a key component of the diaphragm tank and is typically made of highly elastic and corrosion-resistant materials such as stainless steel and titanium alloys. In the microgravity or high-maneuvering environments of spacecraft, the metal diaphragm must completely isolate the liquid propellant from the pressurized gas within the tank, ensuring that the fuel pump or extrusion delivery system draws in pure liquid and preventing cavitation that could cause engine malfunctions. Simultaneously, in high-pressure environments, the metal diaphragm must also maintain pressure and provide structural support. Therefore, the flipping performance of the metal diaphragm is extremely important during propellant system operation; accurately understanding the diaphragm's flipping characteristics is a crucial prerequisite for ensuring reliable operation and improving overall performance.

[0003] However, due to manufacturing limitations, it is difficult to achieve absolutely uniform thickness in the metal diaphragm during production, inevitably resulting in a certain degree of thickness variation. Furthermore, given the extremely thin thickness of the diaphragm itself, this unevenness can cause wrinkles during the flipping process, and in severe cases, even lead to left or right deviation, directly affecting the stable supply of propellant. When simulating the metal diaphragm, ignoring thickness variation will result in insufficient accuracy and significant discrepancies with actual performance; conversely, considering thickness variation, due to the randomness of manufacturing process-induced variations, will complicate the modeling process, significantly extending the simulation cycle and thus impacting the efficiency of refined metal diaphragm design.

[0004] Currently, existing simulation methods for metal diaphragm flipping are all based on metal diaphragms of uniform thickness, which are too idealistic. This leads to the following situation: the scheme can achieve flipping and effective propellant supply during the design phase, but during the experimental verification phase, flipping deviation occurs, and effective propellant supply cannot be achieved. Summary of the Invention

[0005] To address the problems existing in the prior art, this invention proposes a simulation analysis method for the flipping performance of metal diaphragms based on a random thickness assignment method. This method utilizes a parametric modeling GUI built through secondary development in Abaqus software and imports the `random` function into Python code to construct a random thickness deviation assignment GUI. This enables the rapid construction of a finite element model of the metal diaphragm considering thickness deviations, thereby improving simulation efficiency. The method uses a random function to randomly select elements on the initial finite element model according to area ratio to establish an element set for the thickness to be modified. By modifying the initial thickness distribution function to change the thickness deviation amplitude and assigning it to the element set for the thickness to be modified, the method can take into account the impact of random thickness deviations caused by manufacturing processes on the diaphragm flipping process, thus improving simulation accuracy. This method can provide data support for the refined design and process control of diaphragms.

[0006] This invention is achieved through the following technical solution:

[0007] A simulation analysis method for the flipping performance of a metal diaphragm based on a randomly assigned thickness method includes the following steps:

[0008] Step 1: Create a graphical user interface (GUI) for parametric finite element modeling of metal diaphragms;

[0009] In Abaqus software, a graphical user interface is built based on the AFX function; by inputting shape parameters, material parameters, mesh parameters, and load parameters through the graphical user interface, a parameterized finite element model with uniform mesh size can be automatically generated according to the preset thickness.

[0010] Step 2: Parametrically generate the initial geometric model and initial finite element model of the metal diaphragm;

[0011] According to the rule that the thickness of the diaphragm changes linearly from bottom to top, the initial metal diaphragm thickness function is set, and the shape parameters, material parameters, mesh parameters, and load parameters are input through the graphical user interface in step 1 to parametrically generate the initial geometric model and initial finite element model of the metal diaphragm.

[0012] Step 3: Establish a graphical user interface (GUI) for assigning random thickness deviations, modify the thickness within a random range based on the initial finite element model, and obtain a finite element model of the metal diaphragm that takes into account random thickness deviations;

[0013] A graphical interface is constructed for randomly selecting elements and assigning thickness deviations according to a set ratio. Input boxes for model name and area ratio are set on the graphical user interface. The area ratio refers to the proportion of the element area considering thickness deviations to the total area. Elements are randomly selected from the initial finite element model according to the area ratio using a random function to establish an element set with the thickness to be modified. The thickness deviation amplitude is changed by modifying the initial thickness distribution function and assigned to the element set with the thickness to be modified, thus obtaining a finite element model of the metal diaphragm considering random thickness deviations.

[0014] Step 4: Simulation analysis of the diaphragm flipping process with thickness deviation;

[0015] Based on the finite element model of the metal diaphragm considering random thickness deviation obtained in step 3, the analysis method preset in step 1 is used to simulate the flipping process of the metal diaphragm with thickness deviation under pressure load. By changing the thickness deviation amplitude and area ratio, the wrinkling behavior and the change law of the lateral displacement of the vertex during the flipping process of the metal diaphragm with different thickness deviation amplitudes and different area ratios are obtained.

[0016] Further, step 1 specifically involves: in Abaqus software, using the Run Script Generator (RSG) to record Python scripts for preprocessing operations, and constructing a graphical user interface (GUI) for metal membrane preprocessing based on the AFX (Abaqus Framework for eXtensions) function; setting input boxes for model name, shape parameters, material parameters, mesh parameters, and load parameters on the graphical user interface; setting the parameters corresponding to the above input boxes as keywords in the script, and generating a reusable modeling plugin;

[0017] The default boundary condition in the script file is: apply a fixed constraint at the edge of the pre-flanged edge;

[0018] The default analysis method in the script file is: display dynamics method;

[0019] Running the script file will provide a graphical user interface. By inputting shape parameters, material parameters, mesh parameters, and load parameters through the graphical user interface, a parameterized finite element model with uniform mesh size can be automatically generated.

[0020] Furthermore, the shape parameters mentioned in step 1 include the radius of the arc to be flipped, the radius of the arc to be flipped, the angle between the cone segment and the horizontal direction, and the distance between the two grooves;

[0021] The material parameters include density, elastic modulus, Poisson's ratio, and yield strength;

[0022] The grid parameter is the grid size;

[0023] The load parameter is the pressure magnitude.

[0024] Furthermore, the thickness distribution function described in step 2 is a linear variation form, specifically expressed as:

[0025]

[0026] Where t is the actual thickness of the diaphragm at a certain point, t0 is the top thickness, t1 is the bottom thickness, X and Z are the coordinate values ​​at that point, and H is the height of the diaphragm in the Y-axis direction.

[0027] Furthermore, in step 2, the mesh of the finite element model uses four-node quadrilateral shell elements, which are cut and divided based on symmetry to avoid the generation of deformed elements.

[0028] Furthermore, the specific process of modifying the thickness deviation amplitude according to the area ratio in step 3 to obtain the finite element model of the metal diaphragm considering random thickness deviation is as follows: Import the random function into the Python code, and pass the area ratio parameter input by the graphical user interface through the random thickness deviation to the random function. Based on the initial finite element model obtained in step 2, the random function randomly selects some elements on the initial finite element model according to the area ratio to form the element set of the thickness to be modified; for the element set of the thickness to be modified, the thickness deviation amplitude is changed by modifying its initial thickness distribution function, and the element thickness in the element set of the thickness to be modified is updated, thus obtaining the finite element model of the metal diaphragm considering random thickness deviation.

[0029] Furthermore, the specific process in step 3 of changing the thickness deviation amplitude by modifying the initial thickness distribution function and updating the element thickness in the element set whose thickness needs to be modified is as follows:

[0030] Let the thickness deviation amplitude be The area ratio is Considering that random thickness deviations could result in either thickening or thinning, the set of cells whose thickness to be modified, selected by the random function, is randomly divided into two equal parts, with one part having a certain area ratio. The thickness is adjusted according to the following formula:

[0031]

[0032] Substitute into the thickness distribution function, keeping the other parameters unchanged:

[0033]

[0034] Update the element thickness of this element set;

[0035] Meanwhile, another part of the area accounts for The thickness is adjusted according to the following formula:

[0036]

[0037] Substitute into the thickness distribution function, keeping the other parameters unchanged:

[0038]

[0039] Update the element thickness of this part of the element set, that is, complete the element thickness update of all element sets whose thicknesses need to be modified.

[0040] Beneficial effects

[0041] This invention proposes a simulation analysis method for the flipping performance of metal diaphragms based on a random thickness assignment method. This method utilizes a parametric modeling GUI built through secondary development in Abaqus software and a random thickness deviation assignment GUI constructed by importing the `random` function into Python code. This enables the rapid construction of a finite element model of the metal diaphragm considering thickness deviations, thereby improving simulation efficiency. The method establishes a set of elements with the desired thickness by randomly selecting elements on the initial finite element model according to area proportions using a random function. By modifying the initial thickness distribution function to change the thickness deviation amplitude and assigning it to the set of elements with the desired thickness, the method can take into account the impact of random thickness deviations caused by manufacturing processes on the diaphragm flipping process, thus improving simulation accuracy. This method can provide data support for the refined design and process control of diaphragms. Attached Figure Description

[0042] Figure 1 This is a flowchart of a simulation analysis method for the flipping performance of a metal diaphragm based on a random thickness allocation method, according to an embodiment of the present invention.

[0043] Figure 2 This is a schematic diagram of the initial geometric model of the metal diaphragm according to an embodiment of the present invention;

[0044] Figure 3 This is a schematic diagram of the initial finite element model and coordinate axis orientation of the metal diaphragm according to an embodiment of the present invention;

[0045] Figure 4 This is a graphical user interface for parametric finite element modeling of metal diaphragms in an embodiment of the present invention.

[0046] Figure 5 A graphical user interface is assigned to the random thickness deviation in this embodiment of the invention;

[0047] Figure 6 This is a schematic diagram of a finite element model of a metal diaphragm considering random thickness deviations according to an embodiment of the present invention;

[0048] Figure 7Comparison of the flipping process of metal films with different thickness deviation amplitudes;

[0049] in, Figure 7 (a) shows the flipping process when the thickness deviation amplitude is 0%. Figure 7 (b) shows the flipping process when the thickness deviation amplitude is 2%. Figure 7 (c) shows the flipping process when the thickness deviation amplitude is 5%. Figure 7 (d) shows the flipping process when the thickness deviation amplitude is 10%;

[0050] Figure 8 Graphs showing the lateral displacement of the apex of metal films with different thickness deviation amplitudes;

[0051] Figure 9 Graphs showing the lateral displacement of the apex of metal films with different thickness deviation amplitudes and different area ratios;

[0052] in, Figure 9 (a) shows the lateral displacement curves of the apex of the metal film with different area ratios when the thickness deviation amplitude is 2%. Figure 9 (b) shows the lateral displacement curves of the metal diaphragm apex for different area ratios when the thickness deviation amplitude is 5%. Figure 9 (c) shows the lateral displacement curves of the metal film apex with different area ratios when the thickness deviation amplitude is 10%;

[0053] Figure 10 This is a schematic diagram of the unbiased diaphragm flipping process under the implicit analysis method selected in an embodiment of the present invention; Detailed Implementation

[0054] To make the technical problems solved, the technical solutions, and the beneficial effects of this invention clearer and to enable those skilled in the art to better understand the invention, the invention will be further described in detail and in full below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are for illustrative purposes only and are not intended to limit the invention.

[0055] This embodiment utilizes a simulation analysis method for the flipping performance of metal diaphragms based on a randomly assigned thickness method proposed in this invention to simulate a metal diaphragm considering thickness deviations. Figure 1 As shown, the above method specifically includes the following steps:

[0056] Step 1: Create a graphical user interface (GUI) for parametric finite element modeling of metal diaphragms;

[0057] In Abaqus software, a graphical user interface is built based on the AFX function; by inputting shape parameters, material parameters, mesh parameters, and load parameters through the graphical user interface, a parameterized finite element model with uniform mesh size can be automatically generated according to the preset thickness.

[0058] Step 1 specifically involves: In Abaqus software, using the Run Script Generator (RSG) to record Python scripts for preprocessing operations, and building a graphical user interface (GUI) for metal membrane preprocessing based on the AFX (Abaqus Framework for eXtensions) function; setting input boxes for model name, shape parameters, material parameters, mesh parameters, and load parameters on the GUI; setting the corresponding parameters in the above input boxes as keywords in the script, and generating a reusable modeling plugin;

[0059] The default boundary condition in the script file is: apply a fixed constraint at the edge of the pre-flanged edge;

[0060] The default analysis method in the script file is: display dynamics method;

[0061] The shape parameters mentioned in step 1 include the radius of the arc to be flipped, the radius of the arc to be flipped, the angle between the cone segment and the horizontal direction, and the distance between the two grooves;

[0062] The material parameters include density, elastic modulus, Poisson's ratio, and yield strength;

[0063] The grid parameter is the grid size;

[0064] The load parameter is the pressure magnitude.

[0065] Running the script file will provide a graphical user interface. By inputting shape parameters, material parameters, mesh parameters, and load parameters through the graphical user interface, a parameterized finite element model with uniform mesh size can be automatically generated.

[0066] In this embodiment, the graphical user interface (GUI) for the metal film pretreatment process is as follows: Figure 4 As shown;

[0067] Step 2: Parametrically generate the initial geometric model and initial finite element model of the metal diaphragm;

[0068] According to the rule that the thickness of the diaphragm changes linearly from bottom to top, the initial metal diaphragm thickness function is set, and the shape parameters, material parameters, mesh parameters, and load parameters are input through the graphical user interface in step 1 to parametrically generate the initial geometric model and initial finite element model of the metal diaphragm.

[0069] The thickness distribution function mentioned in step 2 is specifically expressed as follows:

[0070]

[0071] Where t is the actual thickness of the diaphragm at a certain point, t0 is the top thickness, t0=1.5mm, t1 is the bottom thickness, t1=0.75mm, X and Z are the coordinate values ​​of that point, and H is the height of the diaphragm in the Y-axis direction, H=169 mm.

[0072] In this embodiment, the following specific parameters are input through the graphical user interface (GUI) for metal film pretreatment:

[0073] External parameters: Spacing between the two grooves D=300mm, radius of the arc to be flipped R=135mm, radius of the pre-flanged arc r=5mm, angle between the cone segment and the horizontal direction =78°;

[0074] Material parameters: The conical metal diaphragm is made of pure titanium with a density of 4500 kg / m³, an elastic modulus of 113 GPa, a Poisson's ratio of 0.32, and a yield strength of 250 MPa.

[0075] Mesh parameters: The mesh size is 5mm. The finite element model uses four-node quadrilateral shell elements. The mesh is divided based on symmetry to avoid the generation of distorted elements. The model is divided into 8140 elements. The symmetry-based meshing means that considering the central symmetry of the diaphragm, XY and ZY reference planes are created, the diaphragm geometry is divided into four equal parts, and the mesh is generated on the divided geometry to ensure that the meshes on the four divided models are identical.

[0076] Load parameters: The pressure load increases linearly from 0 to 0.4 MPa within 1 second;

[0077] In this embodiment, the initial geometric model is as follows: Figure 2 As shown, the initial finite element model is as follows: Figure 3 As shown.

[0078] Step 3: Establish a graphical user interface (GUI) for assigning random thickness deviations, modify the thickness within a random range based on the initial finite element model, and obtain a finite element model of the metal diaphragm that takes into account random thickness deviations;

[0079] A graphical user interface (GUI) is constructed to randomly select elements and assign thickness deviations according to a set ratio. Input boxes for model name and area ratio are set on this GUI. The area ratio refers to the proportion of the element area considering thickness deviations to the total area. Elements are randomly selected from the initial finite element model according to the area ratio using a random function to establish an element set for which the thickness to be modified is determined. The thickness deviation amplitude is changed by modifying the initial thickness distribution function and then assigned to the element set for which the thickness to be modified, thus obtaining a finite element model of a metal membrane considering random thickness deviations. In this embodiment, the GUI for establishing the element set by randomly selecting elements according to a set ratio is as follows: Figure 5As shown.

[0080] In this embodiment, the specific process of modifying the thickness deviation amplitude according to the area ratio in step 3 to obtain the finite element model of the metal diaphragm considering random thickness deviation is as follows: The `random` function is imported into the Python code. The area ratio parameter input by the graphical user interface is passed to the `random` function through the random thickness deviation assignment. Based on the initial finite element model obtained in step 2, the `random` function randomly selects some elements on the initial finite element model according to the area ratio to form an element set whose thickness is to be modified. For the element set whose thickness is to be modified, the thickness deviation amplitude is changed by modifying its initial thickness distribution function, and the element thickness in the element set whose thickness is to be modified is updated, thus obtaining the finite element model of the metal diaphragm considering random thickness deviation.

[0081] In this embodiment, the considered thickness deviation amplitudes are 0%, 2%, 5%, and 10%, respectively, and the proportions of the unit areas with thickness deviations to the total area are 5%, 10%, 15%, and 20%, respectively; the established finite element model of the metal diaphragm with thickness deviations is as follows: Figure 6 As shown, the specific process of changing the thickness deviation amplitude by modifying the initial thickness distribution function and updating the element thickness in the element set whose thickness needs to be modified is as follows:

[0082] Let the thickness deviation amplitude be The area ratio is Considering that random thickness deviations could result in either thickening or thinning, the set of cells whose thickness to be modified, selected by the random function, is randomly divided into two equal parts, with one part having a certain area ratio. The thickness is adjusted according to the following formula:

[0083]

[0084] Substitute into the thickness distribution function, keeping the other parameters unchanged:

[0085]

[0086] Update the element thickness of this element set;

[0087] Meanwhile, another part of the area accounts for The thickness is adjusted according to the following formula:

[0088]

[0089] Substitute into the thickness distribution function, keeping the other parameters unchanged:

[0090]

[0091] Update the element thickness of this part of the element set, that is, complete the element thickness update of all element sets whose thicknesses need to be modified.

[0092] Step 4: Simulation analysis of the diaphragm flipping process with thickness deviation;

[0093] Based on the finite element model of the metal diaphragm considering random thickness deviation obtained in step 3, the analysis method preset in step 1 is used to simulate the flipping process of the metal diaphragm with thickness deviation under pressure load. By changing the thickness deviation amplitude and area ratio, the wrinkling behavior and the change law of the lateral displacement of the vertex during the flipping process of the metal diaphragm with different thickness deviation amplitudes and different area ratios are obtained.

[0094] In this embodiment, the flipping process of metal films with different thickness deviation amplitudes is as follows: Figure 7 As shown in the figure, the four types of diaphragms with thickness deviation amplitudes of 0%, 2%, 5%, and 10% all started flipping after 600 iterations and achieved complete flipping after 800 iterations. As the thickness deviation amplitude increases, the wrinkling phenomenon becomes more pronounced during the diaphragm flipping process. To verify the reliability of the numerical simulation method, an implicit dynamics method was used to simulate and compare the initial finite element models with thickness deviation amplitudes of 0%. The flipping process of the metal diaphragm without considering the deviation is shown in the figure. Figure 10 As shown, with Figure 7 The flipping process is consistent with that in (a).

[0095] In this embodiment, the lateral displacement curves of the apex during the flipping process of the four types of diaphragm with thickness deviation amplitudes of 0%, 2%, 5%, and 10% are shown below. Figure 8 As shown, it can be found that the thickness deviation of the diaphragm significantly affects the diaphragm flipping performance. When the thickness deviation increases, the eccentric displacement of the diaphragm apex also increases.

[0096] In this embodiment, the considered thickness deviation amplitudes are 2%, 5%, and 10%, respectively. When the area of ​​the unit with thickness deviation accounts for 5%, 10%, 15%, and 20% of the total area, the lateral displacement of the diaphragm vertex under different area ratios is as follows: Figure 9 As shown, by Figure 9 It can be seen that, since the selection of thickness units is random, the lateral displacement of the diaphragm vertex is also random when the area of ​​units with thickness deviations is different. However, the vertex eccentricity still shows a trend of increasing with the increase of the proportion of the deviation area.

[0097] In summary, the method of the present invention can take into account the influence of random thickness deviation on the wrinkling of the membrane during the flipping process and the top eccentricity in the simulation of metal membrane flipping, and can provide a reliable methodological basis for parametric modeling and fine processing of metal membranes.

[0098] Although embodiments of the present invention have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present invention. Those skilled in the art can make changes, modifications, substitutions and variations to the above embodiments within the scope of the present invention without departing from the principles and spirit of the present invention.

Claims

1. A simulation analysis method for the flipping performance of a metal diaphragm based on a randomly assigned thickness method, characterized in that: Includes the following steps: Step 1: Establish a graphical user interface for parametric finite element modeling of metal diaphragms; In Abaqus software, a graphical user interface is built based on the AFX function; by inputting shape parameters, material parameters, mesh parameters, and load parameters through the graphical user interface, a parametric finite element model can be automatically generated according to the preset thickness. Step 2: Parametrically generate the initial geometric model and initial finite element model of the metal diaphragm; According to the rule that the thickness of the diaphragm changes linearly from bottom to top, the initial metal diaphragm thickness function is set, and the shape parameters, material parameters, mesh parameters, and load parameters are input through the graphical user interface in step 1 to parametrically generate the initial geometric model and initial finite element model of the metal diaphragm. Step 3: Establish a graphical user interface for assigning random thickness deviations, modify the thickness within a random range based on the initial finite element model, and obtain a finite element model of the metal diaphragm that takes into account random thickness deviations. A graphical interface is constructed for randomly selecting elements and assigning thickness deviations according to a set ratio. Input boxes for model name and area ratio are set on the graphical user interface. The area ratio refers to the proportion of the element area considering thickness deviations to the total area. Elements are randomly selected from the initial finite element model according to the area ratio using a random function to establish an element set with the thickness to be modified. The thickness deviation amplitude is changed by modifying the initial thickness distribution function and assigned to the element set with the thickness to be modified, thus obtaining a finite element model of the metal diaphragm considering random thickness deviations. Step 4: Simulation analysis of the diaphragm flipping process with thickness deviation; Based on the finite element model of the metal diaphragm considering random thickness deviation obtained in step 3, the analysis method preset in step 1 is used to simulate the flipping process of the metal diaphragm with thickness deviation under pressure load. By changing the thickness deviation amplitude and area ratio, the wrinkling behavior and the change law of the lateral displacement of the vertex during the flipping process of the metal diaphragm with different thickness deviation amplitudes and different area ratios are obtained.

2. The simulation analysis method for the flipping performance of metal films based on the random thickness allocation method according to claim 1, characterized in that: Step 1 is as follows: In Abaqus software, the Script Generator (RSG) is used to record Python scripts for preprocessing operations, and a graphical user interface (GUI) for metal membrane preprocessing is built based on the AFX (Abaqus Framework for eXtensions) function. On the GUI, input boxes for model name, shape parameters, material parameters, mesh parameters, and load parameters are set. The parameters corresponding to the above input boxes are set as keywords in the script, and a reusable modeling plugin is generated. The default boundary condition in the script file is: apply a fixed constraint at the edge of the pre-flanged edge; The default analysis method in the script file is: display dynamics method; Running the script file will provide a graphical user interface. By inputting shape parameters, material parameters, mesh parameters, and load parameters through the graphical user interface, a parameterized finite element model with uniform mesh size can be automatically generated.

3. The simulation analysis method for the flipping performance of metal films based on the random thickness allocation method according to claim 2, characterized in that: The shape parameters mentioned in step 1 include the radius of the arc to be flipped, the radius of the arc to be flipped, the angle between the cone segment and the horizontal direction, and the distance between the two grooves; The material parameters include density, elastic modulus, Poisson's ratio, and yield strength; The grid parameter is the grid size; The load parameter is the pressure magnitude.

4. The simulation analysis method for the flipping performance of metal films based on the random thickness allocation method according to claim 1, characterized in that: The thickness distribution function mentioned in step 2 is specifically expressed as follows: Where t is the actual thickness of the diaphragm at a certain point, t0 is the top thickness, t1 is the bottom thickness, X and Z are the coordinate values ​​at that point, and H is the height of the diaphragm in the Y-axis direction.

5. The simulation analysis method for the flipping performance of a metal diaphragm based on the random thickness allocation method according to claim 1, characterized in that: In step 2, the mesh of the finite element model uses four-node quadrilateral shell elements, which are cut and divided based on symmetry to avoid the generation of malformed elements.

6. The simulation analysis method for the flipping performance of metal films based on the random thickness allocation method according to claim 1, characterized in that: The specific process of modifying the thickness deviation amplitude according to the area ratio in step 3 to obtain the finite element model of the metal diaphragm considering random thickness deviation is as follows: Import the random function into the Python code, and pass the area ratio parameter input by the graphical user interface through the random thickness deviation to the random function. Based on the initial finite element model obtained in step 2, the random function randomly selects some elements on the initial finite element model according to the area ratio to form the element set of the thickness to be modified; for the element set of the thickness to be modified, the thickness deviation amplitude is changed by modifying its initial thickness distribution function, and the element thickness in the element set of the thickness to be modified is updated, thus obtaining the finite element model of the metal diaphragm considering random thickness deviation.

7. The simulation analysis method for the flipping performance of a metal diaphragm based on the random thickness allocation method according to claim 6, characterized in that: The specific process of changing the thickness deviation magnitude by modifying the initial thickness distribution function and updating the element thickness in the element set whose thickness needs to be modified is as follows: Let the thickness deviation amplitude be The area ratio is Considering that random thickness deviations could result in either thickening or thinning, the set of cells whose thickness to be modified, selected by the random function, is randomly divided into two equal parts, with one part having a certain area ratio. The thickness is adjusted according to the following formula: Substitute into the thickness distribution function, keeping the other parameters unchanged: Update the element thickness of this element set; Meanwhile, another part of the area accounts for The thickness is adjusted according to the following formula: Substitute into the thickness distribution function, keeping the other parameters unchanged: Update the element thickness of this part of the element set, that is, complete the element thickness update of all element sets whose thicknesses need to be modified.

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