Elastomer simulation method and device, electronic equipment and storage medium

Abstract

The invention relates to the technical field of elastomer simulation, particularly provides an elastomer simulation method and device, electronic equipment and a storage medium, and aims to solve the problem that the simulation speed and scale are limited when a traditional finite element method is used for material simulation. In order to achieve the purpose, the elastomer simulation method comprises the steps that a target matrix equation used for simulating a target elastomer is constructed every preset time step, and the target matrix equation comprises a pressure intensity stabilization matrix; solving the target matrix equation by using a multi-grid method to obtain a solving result; and on the basis of the solving result, geometric model parameters for simulating the target elastomer are updated. According to the method, the problem of volume locking of the target elastomer in the simulation process can be avoided, so that the simulation value is stable, and the simulation precision is improved.

Description

Technical Field

[0001] The present application relates to the technical field of elastomer simulation, and in particular to an elastomer simulation method, device, electronic device and storage medium. Background Art

[0002] In physical simulation, the incompressibility of elastic materials is a common property, especially in the simulation of materials such as human tissue, fat, rubber and hydrogel. Incompressibility means that the volume of the material remains unchanged when it is deformed, which is crucial for accurately simulating the physical behavior of the material. For example, this factor needs to be considered when simulating the behavior of human organs in virtual surgery, simulating soft objects (such as muscles) in animation, and performing safety analysis on materials in engineering.

[0003] Traditional finite element methods are usually used to simulate elastic materials, but as the Poisson's ratio of the material approaches 0.5, that is, the material becomes more incompressible, the simulated numerical system becomes very rigid and prone to locking. Even if the Young's modulus (which describes the degree of hardness) of the material remains unchanged, the numerical simulation results will become harder and harder if the Poisson's ratio is increased. This phenomenon causes the accuracy of traditional finite element methods to decrease when dealing with nearly incompressible materials, and may even lead to numerical instability, which in turn limits the speed and scale of simulation in the process of simulating elastic materials. Summary of the invention

[0004] In view of the above-mentioned deficiencies in the prior art, the present application proposes a method, device, electronic device and storage medium for simulating an elastomer.

[0005] In a first aspect, an embodiment of the present application provides a method for simulating an elastomer, comprising: constructing a target matrix equation for simulating a target elastomer at every preset time step, the target matrix equation comprising a pressure stability matrix; solving the target matrix equation using a multi-grid method to obtain a solution result; and updating the geometric model parameters for simulating the target elastomer based on the solution result.

[0006] In the second aspect, an embodiment of the present application provides a simulation device for an elastomer, comprising: a construction module, used to construct a target matrix equation for simulating a target elastomer at every preset time step, the target matrix equation including a pressure stability matrix; a solution module, used to solve the target matrix equation using a multi-grid method to obtain a solution result; and an update module, used to update the geometric model parameters for simulating the target elastomer based on the solution result.

[0007] In a third aspect, an embodiment of the present application provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the method described in the first aspect above is implemented.

[0008] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method described in the first aspect above is implemented.

[0009] The technical solution provided in the embodiments of the present application has at least the following technical effects or advantages:

[0010] The elastic body simulation method of the embodiment of the present application constructs a target matrix equation for simulating a target elastic body at every preset time step, wherein the target matrix equation includes a pressure stability matrix; the target matrix equation is solved by a multi-grid method to obtain a solution result; and based on the solution result, the geometric model parameters for simulating the target elastic body are updated. Through the above method, the present application can avoid the problem of volume locking of the target elastic body during the simulation process, so that the simulation value is stable and the simulation accuracy is improved.

[0011] Additional aspects and advantages of the present application will be given in part in the description below, and in part will become apparent from the description below, or will be learned through the practice of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0012] Various other advantages and benefits will become apparent to those of ordinary skill in the art by reading the detailed description of the preferred embodiments below. The accompanying drawings are only for the purpose of illustrating the preferred embodiments and are not to be considered as limiting the present application. Also, the same reference symbols are used throughout the accompanying drawings to represent the same components. In the accompanying drawings:

[0013] Figure 1 A flow chart showing a method for simulating an elastic body provided in an embodiment of the present application is shown;

[0014] Figure 2 A schematic diagram of the structure of an elastic body simulation device provided in an embodiment of the present application is shown;

[0015] Figure 3 A schematic structural diagram of an electronic device provided in an embodiment of the present application is shown. DETAILED DESCRIPTION

[0016] The exemplary embodiments of the present application will be described in more detail below with reference to the accompanying drawings. Although the exemplary embodiments of the present application are shown in the accompanying drawings, it should be understood that the present application can be implemented in various forms and should not be limited by the embodiments described herein. On the contrary, these embodiments are provided in order to enable a more thorough understanding of the present application and to fully convey the scope of the present application to those skilled in the art.

[0017] In physical simulation, the incompressibility of elastic materials is a common property, especially in the simulation of materials such as human tissue, fat, rubber and hydrogel. Incompressibility means that the volume of the material remains unchanged when it is deformed, which is crucial for accurately simulating the physical behavior of the material. For example, this factor needs to be considered when simulating the behavior of human organs in virtual surgery, simulating soft objects (such as muscles) in animation, and performing safety analysis on materials in engineering.

[0018] Traditional finite element methods are usually used to simulate elastic materials, but as the Poisson's ratio of the material approaches 0.5, that is, the material becomes more incompressible, the simulated numerical system becomes very rigid and prone to locking. Even if the Young's modulus (which describes the degree of hardness) of the material remains unchanged, the numerical simulation results will become harder and harder if the Poisson's ratio is increased. This phenomenon causes the accuracy of traditional finite element methods to decrease when dealing with nearly incompressible materials, and may even lead to numerical instability, which in turn limits the speed and scale of simulation in the process of simulating elastic materials.

[0019] Based on this, the embodiment of the present application provides an elastic body simulation method. The scheme of the embodiment of the present application is specifically described below in conjunction with the accompanying drawings.

[0020] See also Figure 1 A flow chart of an elastic body simulation method is shown, and the method specifically comprises the following steps:

[0021] Step 101: construct a target matrix equation for simulating a target elastic body at every preset time step, wherein the target matrix equation includes a pressure stability matrix.

[0022] In the embodiment of the present application, the preset time step refers to the time interval used in the simulation process of the elastic body, which is used to update the parameters in the geometric model to simulate the passage of time. The preset time step can be a time step obtained by a person skilled in the art based on experiments, or a time step set by a person skilled in the art based on actual needs, or a time step obtained by adjusting the set time step according to actual needs by a person skilled in the art, and the embodiment of the present application does not specifically limit it.

[0023] The target elastic body refers to an object with the property of being incompressible. As the conifer ratio of the target elastic body approaches 0.5, the target elastic body can be approximately considered as incompressible under micro deformation. For example, the target elastic body can be human tissue, muscle, rubber, etc.

[0024] In one embodiment, a target matrix equation for simulating a target elastic body may be constructed at preset time steps, the target matrix equation including a pressure stability matrix. Specifically, a first candidate matrix equation may be constructed using a linear mixed finite element method, the first candidate matrix equation including a diagonal matrix, and then a pressure stability matrix is ​​added to the diagonal matrix to obtain the target matrix equation.

[0025] Furthermore, the target matrix equation is shown in the following formula (1):

[0026]

[0027] Among them, A represents the left-hand term, o represents the target matrix, b represents the right-hand term, K represents the Hessian matrix of the tangential strain energy of the target elastic body, G represents the Jacobian matrix of the vertex volume constraint of the geometric model for the vertex position constraint, C is a diagonal matrix, δc * represents the positional freedom of the vertices of the geometric model, δp represents the pressure freedom of the vertices of the geometric model, f represents the constraint condition of the vertex position of the geometric model, g represents the constraint condition of the vertex pressure of the geometric model, S e represents the pressure stability matrix, α represents a constant, V e represents the volume of the geometric model in the initial state, μ is the shear modulus of the target elastic body, and M represents the preset matrix.

[0028] It should be noted that the target matrix is ​​the unknown variable of the target matrix equation, and the solution obtained by solving the target matrix equation is the target matrix.

[0029] The constraint condition f of the vertex position of the geometric model and the constraint condition g of the vertex pressure of the geometric model both belong to KKT (Karush-Kuhn-Tucker) conditions. The setting of the constraint condition belongs to the conventional technical means used by those skilled in the art, and will not be described in detail here.

[0030] The constant α may be a constant set by a person skilled in the art according to actual needs, or may be a constant obtained by adjusting a set constant according to actual needs, and the present application embodiment does not specifically limit this. In the present application embodiment, the constant α may be 1.

[0031] The preset matrix M may be a matrix set by a person skilled in the art according to actual needs, or a matrix obtained by adjusting a set matrix according to actual needs, which is not specifically limited in the present embodiment.

[0032] The process of constructing the first candidate matrix equation using the linear mixed finite element method is a technical means commonly used by those skilled in the art and will not be described in detail in the embodiments of the present application.

[0033] The embodiment of the present application constructs a first candidate matrix equation by utilizing a linear mixed finite element method, and adds a pressure stabilization matrix to the diagonal matrix of the first candidate matrix equation, which can effectively solve the non-physical oscillation problem that occurs in the process of solving the target matrix equation, making it easier to converge and shortening the calculation time, thereby improving the accuracy and reliability of the elastic body simulation.

[0034] Based on the above embodiment, in some modified implementations, before constructing the target matrix equation for simulating the target elastic body, the positions of the vertices of the geometric model may be updated. The update may be performed according to the following formula (2):

[0035] c * =c n +v n h+g_ah 2 (2)

[0036] Among them, c * represents the updated vertex position, c n represents the position of the vertex at the nth time step, v n It represents the velocity of the vertex at the nth time step, h represents the time step size, and g_a represents the gravitational acceleration.

[0037] Step 102: Solve the target matrix equation using a multi-grid method to obtain a solution.

[0038] In one embodiment, a multi-grid method is used to solve a target matrix equation to obtain a solution result. Specifically, an initial matrix including a preset initial position degree of freedom and an initial pressure degree of freedom can be smoothed to obtain a first candidate matrix, and then the first candidate matrix is ​​sparsely interpolated to obtain a second candidate matrix. Based on the second candidate matrix and the left-hand term, a second candidate matrix equation is constructed and solved to obtain a third candidate matrix. The third candidate matrix is ​​compactly interpolated to obtain a fourth candidate matrix. Finally, the fourth candidate matrix is ​​smoothed again to obtain a solution result.

[0039] On the basis of the above implementation, in some modified implementations, the geometric model may include multiple vertices, and the initial matrix including the preset initial position degree of freedom and the initial pressure degree of freedom is smoothed to obtain a first candidate matrix. Specifically, the following formula (3) may be used to smooth the initial matrix including the preset initial position degree of freedom and the initial pressure degree of freedom to obtain the first candidate matrix:

[0040]

[0041] Among them, R m It represents the extraction of the positional degrees of freedom and pressure degrees of freedom of the mth vertex, o1 represents the initial matrix, and ω represents the preset relaxation factor.

[0042] The embodiment of the present application can significantly reduce the propagation and amplification of errors by simultaneously smoothing the positional degrees of freedom and the pressure degrees of freedom of each vertex of the geometric model, making the calculation process more stable, and can also better maintain the continuity of the simulation process, so that the simulation results of the target elastic body are more consistent with the actual physical phenomena, and the simulation results are less dependent on the grid, and the applicability of the model under different grid conditions is enhanced. In addition, the results of each iteration can be made closer to the true solution, thereby accelerating the convergence speed of the iteration and reducing the time and resources required for calculation.

[0043] On the basis of the above implementation manner, in some modified implementation manners, the first candidate matrix is ​​subjected to sparse difference processing to obtain a second candidate matrix. Specifically, residual calculation can be performed based on the left-hand term, the right-hand term and the first candidate matrix to obtain a residual matrix, and the residual matrix is ​​subjected to sparse interpolation processing to obtain the second candidate matrix.

[0044] On the basis of the above implementation, in some modified implementations, the second candidate matrix equation is solved. Specifically, the second candidate matrix equation can be converted into a first sub-equation and a second sub-equation using the Schur complement method, and the first sub-equation and the second sub-equation are solved respectively.

[0045] Furthermore, the first sub-equation can be expressed as the following formula (4):

[0046]

[0047] Furthermore, the second sub-equation can be expressed as the following formula (5):

[0048]

[0049] Wherein, l represents the second candidate matrix.

[0050] By converting the second candidate matrix equation into the first sub-equation and the second sub-equation, and then solving the first sub-equation and the second sub-equation respectively, it is possible to effectively avoid the performance loss of the simulation caused by directly solving the non-positive second candidate matrix equation, reduce the risk of errors or abnormal results in the solution process, and ensure the stability and reliability of the calculation process. In addition, it can also significantly improve the calculation efficiency, reduce the demand for computing resources, and enable the simulation of the target elastic body to be carried out more efficiently under limited hardware conditions.

[0051] Step 103: Based on the solution results, update the geometric model parameters used to simulate the standard elastic body.

[0052] In one embodiment, when the multi-grid method is used to iteratively solve the target matrix equation, when the difference between the m-th solution result and the m+1-th solution result is less than a preset threshold, it is determined that the target matrix equation has reached convergence, and the position and pressure of each vertex of the geometric model at the time of convergence are used as the position c of the next time step. n+1 and pressure p n+1 , and the velocity v of each vertex of the geometric model at the next time step n+1 Updated to (c n+1 -c n ) / h, and then continue to execute the step of constructing a target matrix equation for simulating the target elastic body at every preset time step, wherein the target matrix equation includes a pressure stabilization matrix.

[0053] The embodiment of the present application constructs a target matrix equation for simulating a target elastic body at every preset time step, wherein the target matrix equation includes a pressure stability matrix; solves the target matrix equation using a multigrid method to obtain a solution result; and updates the geometric model parameters for simulating the target elastic body based on the solution result. The present application can avoid the problem of volume locking of the target elastic body during the simulation process by using the above method, so that the simulation value is stable and the simulation accuracy is improved.

[0054] See also Figure 2 The embodiment of the present application further provides a simulation device for an elastic body, the device is used to execute the simulation method for an elastic body described in the above embodiment, the device comprising:

[0055] A construction module 201 is used to construct a target matrix equation for simulating a target elastic body at every preset time step, wherein the target matrix equation includes a pressure stability matrix;

[0056] A solution module 202 is used to solve the target matrix equation using a multi-grid method to obtain a solution result;

[0057] The updating module 203 is used to update the geometric model parameters used to simulate the target elastic body based on the solution result.

[0058] The simulation device for elastomer provided in the embodiment of the present application and the simulation method for elastomer provided in the above embodiment are based on the same inventive concept and have the same beneficial effects as the methods adopted, operated or implemented therein.

[0059] The present application also provides an electronic device corresponding to the elastic body simulation method provided in the above embodiment. Figure 3 , which shows a schematic diagram of an electronic device provided by some embodiments of the present application. Figure 3 As shown, the electronic device 30 may include: a processor 300, a memory 301, a bus 302 and a communication interface 303, wherein the processor 300, the communication interface 303 and the memory 301 are connected via the bus 302; the memory 301 stores a computer program that can be run on the processor 300, and when the processor 300 runs the computer program, the elastomer simulation method provided in any of the aforementioned embodiments of the present application is executed.

[0060] The memory 301 may include a high-speed random access memory (RAM), and may also include a non-volatile memory, such as at least one disk memory. The communication connection between the system network element and at least one other network element is realized through at least one physical port 303 (which may be wired or wireless), and the Internet, wide area network, local area network, metropolitan area network, etc. may be used.

[0061] The bus 302 may be an ISA bus, a PCI bus, or an EISA bus, etc. The bus may be divided into an address bus, a data bus, a control bus, etc. The memory 301 is used to store a program, and the processor 300 executes the program after receiving an execution instruction. The elastic body simulation method disclosed in any implementation of the embodiment of the present application may be applied to the processor 300, or implemented by the processor 300.

[0062] The processor 300 may be an integrated circuit with signal processing capabilities. In the implementation process, each step of the above method can be completed by an integrated logic circuit of hardware in the processor 300 or an instruction in the form of software. The above processor 300 may be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc.; it may also be a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a readily available programmable gate array (FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components. The methods, steps and logic block diagrams disclosed in the embodiments of the present application can be implemented or executed. The general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc. The steps of the method disclosed in conjunction with the embodiments of the present application can be directly embodied as a hardware decoding processor for execution, or a combination of hardware and software modules in the decoding processor for execution. The software module may be located in a mature storage medium in the field such as a random access memory, a flash memory, a read-only memory, a programmable read-only memory or an electrically erasable programmable memory, a register, etc. The storage medium is located in the memory 301, and the processor 300 reads the information in the memory 301 and completes the steps of the above method in combination with its hardware.

[0063] The electronic device provided in the embodiment of the present application and the elastomer simulation method provided in the embodiment of the present application are based on the same inventive concept and have the same beneficial effects as the methods adopted, operated or implemented therein.

[0064] An embodiment of the present application also provides a computer-readable storage medium corresponding to the elastomer simulation method provided in the aforementioned embodiment, on which a computer program (i.e., a program product) is stored. When the computer program is run by a processor, it will execute the elastomer simulation method provided in any of the aforementioned embodiments.

[0065] It should be noted that examples of the computer-readable storage medium may also include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other optical or magnetic storage media, which are not listed here one by one.

[0066] An embodiment of the present application also provides a computer program product corresponding to the elastomer simulation method provided in the aforementioned embodiment, including a computer program, which is executed by a processor to implement the elastomer simulation method provided in the aforementioned embodiments.

[0067] The computer-readable storage medium and computer program product provided in the above-mentioned embodiments of the present application are based on the same inventive concept as the elastomer simulation method provided in the embodiments of the present application, and have the same beneficial effects as the methods adopted, run or implemented by the application programs stored therein.

[0068] It should be noted that:

[0069] The algorithm and display provided herein are not inherently related to any particular computer, virtual device or other equipment. Various general purpose devices can also be used together with the teachings based on this. According to the above description, it is obvious to construct the structure required for this type of device. In addition, the application is not directed to any specific programming language. It should be understood that the content of the application described herein can be realized using various programming languages, and the description of the specific language above is to disclose the best mode of implementation of the application.

[0070] In the description provided herein, a large number of specific details are described. However, it is understood that the embodiments of the present application can be practiced without these specific details. In some instances, well-known methods, structures and techniques are not shown in detail so as not to obscure the understanding of this description.

[0071] Similarly, it should be understood that in order to streamline the present application and help understand one or more of the various inventive aspects, in the above description of the exemplary embodiments of the present application, the various features of the present application are sometimes grouped together into a single embodiment, figure, or description thereof. However, the disclosed method should not be interpreted as reflecting the following intention: the claimed application requires more features than the features clearly stated in each claim. More specifically, as reflected in the claims below, the inventive aspects are less than all the features of the single embodiment disclosed above. Therefore, the claims following the specific embodiment are hereby expressly incorporated into the specific embodiment, wherein each claim itself serves as a separate embodiment of the present application.

[0072] Those skilled in the art will appreciate that the modules in the devices in the embodiments may be adaptively changed and arranged in one or more devices different from the embodiments. The modules or units or components in the embodiments may be combined into one module or unit or component, and in addition they may be divided into a plurality of submodules or subunits or subcomponents. Except that at least some of such features and / or processes or units are mutually exclusive, all features disclosed in this specification (including the accompanying claims, abstracts and drawings) and all processes or units of any method or device disclosed in this manner may be combined in any combination. Unless otherwise expressly stated, each feature disclosed in this specification (including the accompanying claims, abstracts and drawings) may be replaced by an alternative feature providing the same, equivalent or similar purpose.

[0073] In addition, those skilled in the art will appreciate that, although some embodiments described herein include certain features included in other embodiments but not other features, the combination of features of different embodiments is meant to be within the scope of the present application and form different embodiments. For example, in the claims below, any one of the claimed embodiments may be used in any combination.

[0074] The various component embodiments of the present application can be implemented in hardware, or in software modules running on one or more processors, or in a combination thereof. It should be understood by those skilled in the art that a microprocessor or digital signal processor (DSP) can be used in practice to implement some or all functions of some or all components in the creation device of the virtual machine according to the embodiment of the present application. The application can also be implemented as a device or device program (e.g., computer program and computer program product) for executing part or all of the methods described herein. Such a program implementing the present application can be stored on a computer-readable medium, or can have the form of one or more signals. Such a signal can be downloaded from an Internet website, or provided on a carrier signal, or provided in any other form.

[0075] It should be noted that the above embodiments illustrate the present application rather than limit the present application, and that those skilled in the art may design alternative embodiments without departing from the scope of the appended claims. In the claims, any reference symbol between brackets should not be constructed as a limitation to the claims. The word "comprising" does not exclude the presence of elements or steps not listed in the claims. The word "one" or "an" preceding an element does not exclude the presence of multiple such elements. The present application may be implemented by means of hardware including several different elements and by means of a suitably programmed computer. In a unit claim that lists several devices, several of these devices may be embodied by the same hardware item. The use of the words first, second, and third, etc. does not indicate any order. These words may be interpreted as names.

[0076] The above is only a preferred specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any changes or substitutions that can be easily thought of by a person skilled in the art within the technical scope disclosed in the present application should be included in the protection scope of the present application. Therefore, the protection scope of the present application shall be based on the protection scope of the claims.

Claims

1. A method for simulating an elastic body, characterized in that: include: At every preset time step, constructing a target matrix equation for simulating a target elastic body, wherein the target matrix equation includes a pressure stability matrix; Solving the target matrix equation using a multi-grid method to obtain a solution result; Based on the solution result, the parameters of the geometric model used to simulate the target elastic body are updated.

2. The method for simulating an elastic body according to claim 1, characterized in that: The target matrix equation for simulating the target elastic body is constructed, including: constructing a first candidate matrix equation using a linear mixed finite element method, wherein the first candidate matrix equation includes a diagonal matrix; The pressure stabilization matrix is ​​added to the diagonal matrix to obtain the target matrix equation.

3. The method for simulating an elastic body according to claim 2, characterized in that: The target matrix equation is shown in the following formula: Where A represents the left-hand term, o represents the target matrix, b represents the right-hand term, K represents the Hessian matrix of the tangential strain energy of the target elastic body, G represents the Jacobian matrix of the vertex volume constraint of the geometric model for the vertex position constraint, C is a diagonal matrix, δc * represents the positional freedom of the vertices of the geometric model, δp represents the pressure freedom of the vertices of the geometric model, f represents the constraint condition of the vertex position of the geometric model, g represents the constraint condition of the vertex pressure of the geometric model, S e represents the pressure stability matrix, α represents a constant, V e represents the volume of the geometric model in the initial state, μ is the shear modulus of the target elastic body, and M represents a preset matrix.

4. The method for simulating an elastic body according to claim 3, characterized in that: The method of solving the target matrix equation using a multi-grid method to obtain a solution result includes: Performing a smoothing process on an initial matrix including a preset initial position degree of freedom and an initial pressure degree of freedom to obtain a first candidate matrix; Performing sparse interpolation processing on the first candidate matrix to obtain a second candidate matrix; Based on the second candidate matrix and the left-hand term, construct a second candidate matrix equation and solve it to obtain a third candidate matrix; Performing compact interpolation processing on the third candidate matrix to obtain a fourth candidate matrix; The fourth candidate matrix is ​​smoothed again to obtain the solution result.

5. The method for simulating an elastic body according to claim 4, characterized in that: The geometric model includes a plurality of vertices, and the initial matrix including the preset initial position degree of freedom and the initial pressure degree of freedom is smoothed to obtain a first candidate matrix, including: The initial matrix including the preset initial position degrees of freedom and initial pressure degrees of freedom is smoothed by the following formula to obtain the first candidate matrix: Among them, R m represents the extraction of the positional degrees of freedom and the pressure degrees of freedom of the mth vertex, o1 represents the initial matrix, and ω represents the preset relaxation factor.

6. The method for simulating an elastic body according to claim 4, characterized in that: The step of performing sparse difference processing on the first candidate matrix to obtain a second candidate matrix includes: Performing residual calculation based on the left-hand term, the right-hand term and the first candidate matrix to obtain a residual matrix; Perform sparse interpolation processing on the residual matrix to obtain the second candidate matrix.

7. The method for simulating an elastic body according to claim 4, characterized in that: Solving the second candidate matrix equation includes: The second candidate matrix equation is transformed into a first sub-equation and a second sub-equation by using a Schur complement method; The first sub-equation and the second sub-equation are solved respectively.

8. A simulation device for an elastic body, characterized in that: include: A construction module, for constructing a target matrix equation for simulating a target elastic body at every preset time step, wherein the target matrix equation includes a pressure stability matrix; A solution module, used for solving the target matrix equation by using a multi-grid method to obtain a solution result; An updating module is used to update the geometric model parameters used to simulate the target elastic body based on the solution result.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the method according to any one of claims 1 to 7 is implemented.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the method according to any one of claims 1 to 7 is implemented.

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