A simulation method and system for incompressible viscoelastic-plastic properties

Abstract

This invention discloses a simulation method and system for incompressible viscoelastic-plastic materials, designed to simulate the large deformation behavior of these materials. By decomposing the material properties into viscosity and elastic-plasticity, and extracting rotation from the deformation gradient, this invention addresses the issue that using a fixed smoothing length may lead to particles becoming unconstrained and irregularly ejected. By employing a novel non-iterative algorithm to adjust the smoothing length and combining it with artificial viscous forces, this invention can correct particle dispersion and avoid artifacts caused by severe non-physical oscillations. Compared with existing models, this invention provides a fast and stable solution for various solid and fluid dynamic behaviors. Comprehensive experiments on various mechanical energy behaviors demonstrate the versatility and effectiveness of this invention.

Description

Technical Field

[0001] This invention relates to the field of adaptive implicit framework technology, and more specifically to a simulation method and system for incompressible viscoelastic-plastic properties. Background Technology

[0002] With advancements in computer graphics and virtual reality technologies, an increasing number of application areas require the creation and display of realistic virtual worlds, encompassing games, engineering, and film. The ability of virtual environments to accurately replicate real-world scenes has been a driving force behind the research and development of physics-based simulators. Over the past few decades, meshless methods have been extensively researched and applied. These methods effectively handle complex geometries, large deformations, and free surfaces, thus achieving significant success in both visual effects and physical simulation. Among these methods, the meshless simulation (SPH) method has become one of the preferred methods in computer graphics simulations, and SPH schemes for deformable objects have been a continuous area of ​​research. Recent studies have shown that SPH is becoming increasingly effective in simulating viscous fluids, elastoplastic solids, and viscoplastic solids.

[0003] Current methods for simulating deformable objects often simulate viscosity by mimicking the properties of various fluids and quasi-solids. However, viscous forces only affect the rate of deformation, not the degree of deformation, thus this approach has significant limitations. Furthermore, from a viscoelastic perspective, simulating the original plastic flow of materials and its corresponding hardening mechanisms remains restricted. Real-world objects frequently exhibit both viscoelastic and plastic properties; the absence of either aspect negatively impacts both visual appeal and simulation results. Summary of the Invention

[0004] The purpose of this invention is to provide a method and system for simulating incompressible viscoelastic-plastic properties, in order to overcome the shortcomings of the prior art.

[0005] To achieve the above objectives, the technical solution adopted by the present invention is as follows:

[0006] A simulation method for incompressible viscoelastic-plastic properties includes the following steps:

[0007] S1, construct the viscous constitutive model and the elastoplastic constitutive model of the particle respectively;

[0008] S2, based on the viscous constitutive model of particles, the viscous force of ions is simulated to obtain the viscous force of particles, and based on the elastoplastic constitutive model of particles, the elastoplastic force is obtained;

[0009] S3, based on the obtained particle viscous force and elastoplastic force, obtains the final velocity of the particle, realizing the simulation of the particle's viscoelasticity and plasticity.

[0010] Preferably, the incompressible Navier-Stokes equations are used, incorporating the forces acting on the particle into the momentum balance equations, as shown below:

[0011] (1)

[0012] In the formula, Represents density, Indicates pressure, Representing other external forces, , These represent viscous stress and elastoplastic stress, respectively.

[0013] Preferably, the viscous force of ions is obtained by simulating the viscous force based on the viscous constitutive model of particles, and the rate of change of the influence of the viscosity term on the solution velocity is:

[0014] (2)

[0015] in, The viscosity represents the kinetic viscosity of particles. Represents the velocity of the particle.

[0016] Preferably, an implicit simulation method based on the velocity field Laplacian operator is used to simulate viscous forces.

[0017] Preferably, an elastoplastic constitutive model based on particles is used to obtain elastoplastic forces, combining elastic strain and plastic strain to generate an elastoplastic strain equation:

[0018] (5)

[0019] In the calculation process of the elastoplastic constitutive model, the elastoplastic stress rate is derived from the elastoplastic strain rate, thereby obtaining the elastoplastic stress.

[0020] Preferably, the elastic force is obtained through stress divergence, and a correction kernel function and rotation processing are introduced to multiply the stress tensor by the corresponding kernel gradient; non-iterative particle smoothing length correction is introduced to obtain the elastoplastic force acting on the particle at a set time.

[0021] A simulation system for incompressible viscoelastic-plastic properties includes a model building module, a model processing module, and a simulation module.

[0022] The model building module constructs viscous constitutive models and elastoplastic constitutive models of particles;

[0023] The model processing module simulates the viscous forces of ions based on the viscous constitutive model of particles to obtain the viscous forces of particles, and obtains the elastoplastic forces based on the elastoplastic constitutive model of particles.

[0024] The simulation module obtains the final velocity of the particles based on the acquired viscous and elastoplastic forces, thereby simulating the viscoelasticity and plasticity of the particles.

[0025] Preferably, the incompressible Navier-Stokes equations are used, incorporating the forces acting on the particle into the momentum balance equations, as shown below:

[0026] (1)

[0027] In the formula, Represents density, Indicates pressure, Representing other external forces, , These represent viscous stress and elastoplastic stress, respectively.

[0028] Preferably, the viscous force of ions is obtained by simulating the viscous force based on the viscous constitutive model of particles, and the rate of change of the influence of the viscosity term on the solution velocity is:

[0029] (2)

[0030] in, The viscosity represents the kinetic viscosity of particles. Represents the velocity of the particle.

[0031] Preferably, an implicit simulation method based on the velocity field Laplacian operator is used to simulate viscous forces.

[0032] Compared with the prior art, the present invention has the following beneficial technical effects:

[0033] This invention provides a simulation method for incompressible viscoelastic-plastic properties, designed to simulate the large deformation behavior of viscoelastic-plastic materials. By decomposing material properties into viscosity and elastoplasticity, and extracting rotation from the deformation gradient, this invention addresses the issue that using a fixed smoothing length can lead to particles becoming unconstrained and irregularly ejected. By employing a novel non-iterative algorithm to adjust the smoothing length and combining it with artificial viscous forces, this invention can correct particle dispersion and avoid artifacts caused by severe non-physical oscillations. Compared to existing models, this invention provides a fast and stable solution for various solid and fluid dynamic behaviors. Comprehensive experiments on multiple mechanical energy behaviors demonstrate the versatility and effectiveness of this invention. Attached Figure Description

[0034] Figure 1 This is a schematic diagram of the simulation method for incompressible viscoelastic-plastic properties in an embodiment of the present invention.

[0035] Figure 2 This is a schematic diagram of the overall framework simulated in an embodiment of the present invention.

[0036] Figure 3 This is a schematic diagram illustrating the behavior of elastoplastic materials in an embodiment of the present invention.

[0037] Figure 4 This is a schematic diagram of the variable smooth length in an embodiment of the present invention.

[0038] Figure 5 This is a schematic diagram comparing the elastoplastic behavior in an embodiment of the present invention.

[0039] Figure 6 This is a schematic diagram illustrating the average particle variation in the number of adjacent elements in an embodiment of the present invention.

[0040] Figure 7 This is a schematic diagram comparing the rendering effects in an embodiment of the present invention.

[0041] Figure 8 This is a schematic diagram illustrating different materials falling onto an armadillo in an embodiment of the present invention.

[0042] Figure 9 This is a schematic diagram comparing the fabric simulation results of different methods in the embodiments of the present invention.

[0043] Figure 10 This is a schematic diagram of a dragon falling into a non-Newtonian fluid in an embodiment of the present invention.

[0044] Figure 11 This is a schematic diagram illustrating the data changes during the entire collision process between the rigid body and the shear-thickening fluid in an embodiment of the present invention.

[0045] Figure 12 This is a schematic diagram of a disaster simulation using different materials in the same environment, as described in an embodiment of the present invention.

[0046] Figure 13 This is a schematic diagram illustrating the washing away of soil, iron, and rubber rabbits by water in an embodiment of the present invention. Detailed Implementation

[0047] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0048] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0049] like Figure 1 , Figure 2 As shown, the present invention provides a method for simulating incompressible viscoelastic-plastic properties, specifically including the following steps:

[0050] S1, construct the viscous constitutive model and the elastoplastic constitutive model of the particle respectively;

[0051] S2, based on the viscous constitutive model of particles, the viscous force of ions is simulated to obtain the viscous force of particles, and based on the elastoplastic constitutive model of particles, the elastoplastic force is obtained;

[0052] S3, based on the obtained particle viscous force and elastoplastic force, obtains the final velocity of the particle, realizing the simulation of the particle's viscoelasticity and plasticity.

[0053] In a specific embodiment of this application, the incompressible Navier-Stokes equations are used to introduce the forces acting on the particles into the momentum balance equations, as shown below:

[0054] (1)

[0055] In the specific embodiments of this application, a viscoelastic-plastic method is used to construct the viscous constitutive model and the elastoplastic constitutive model of the particles. The viscoelastic-plastic constitutive model implicitly handles both viscosity and elastoplastic aspects. Wherein, Represents density, Indicates pressure, Representing other external forces, , These represent viscous stress and elastoplastic stress, respectively.

[0056] Based on the viscous constitutive model of particles, the viscous force of ions is simulated to obtain the particle viscous force. The rate of change of the influence of the viscosity term on the solution velocity is:

[0057] (2)

[0058] in, The viscosity represents the kinetic viscosity of particles. Represents the velocity of the particle.

[0059] Due to volume viscosity This will affect the scattering of the velocity field, so an implicit simulation of viscous forces based on the velocity field Laplace operator is adopted.

[0060] The SPH kernel gradient interpolation formula is introduced by... The solution is obtained using Brookshaw's finite difference method. As shown in equation (3), where Representing dimension, Indicates the velocity difference between particles. Indicates distance, It is a smooth length.

[0061] (3)

[0062] also, Used to represent particles The viscosity of a dynamic viscosity exhibits a nonlinear change in strain rate, where the strain rate is determined by... The following is given. This application uses the Ostwald-dwell nonlinear viscosity model as follows:

[0063] (4)

[0064] The above represents the classic power-law relationship model, where n and m are the power exponent and the consistency exponent, respectively, which can simulate shear thinning (when...). ) and shear thickening (when hour).

[0065] Elastic-plastic forces are obtained based on a particle-based elastoplastic constitutive model, which combines elastic strain and plastic strain to generate an elastoplastic strain equation:

[0066] (5)

[0067] In the calculation of the elastoplastic constitutive model, the elastoplastic stress rate is derived from the elastoplastic strain rate, thereby obtaining the elastoplastic stress. Since the kernel gradient lacks first-order consistency and cannot accurately capture rotation, this application uses the mechanical frame reference to the initial position for rotation calculation; this application extends the yield criterion as follows:

[0068] Yield criteria based on elastic strain deviation, such as Figure 3 As shown, the yield criterion condition is:

[0069] (6)

[0070] (7)

[0071] in Represents the elastic limit, when the yield condition is met. When the yield condition is met, the material is in an elastic or plastic unloading state and does not produce plastic strain; when the yield condition is met... When this condition is met, the material is in a state of plastic flow, resulting in the following increments in plastic strain:

[0072] (8)

[0073] In addition, there exists a plastic limit. If this limit is exceeded, fracture will occur.

[0074] Plastic strain is expressed as:

[0075] (9)

[0076] Incompressibility is achieved by considering density invariance as a source term; however, in cases involving large deformations (such as plastic failure), the number of neighbors for some divergent particles may decrease. This phenomenon not only leads to a decrease in the density of these particles but also causes erroneous splashing due to insufficient neighboring particles. Therefore, this application adjusts the smooth length of the particles based on the principle of maintaining particle density invariance, essentially ensuring that the total mass of particles within a neighborhood remains constant.

[0077] (10)

[0078] in Representing the scene dimension, when , ,when , To maintain constant quality, differentiate with respect to time and eliminate common factors. Then, the above formula can be further simplified to:

[0079] (11)

[0080] Suppose that after a time step Afterwards, the smooth length and density of particle i become... and (represented as:) and in and (These are the initial density and smooth length of the particles). Then, multiply both sides of the equation by... This allows us to obtain equation (11) above. During the simulation, numerical errors may lead to uneven particle distribution, resulting in density changes. For example... Figure 4 As shown, the particle smoothing length remains unchanged in high-density regions, but the smoothing length is increased in low-density regions through an algorithm. The goal of this application is to maintain a stable particle density and ensure a smooth change in the number of particle neighbors by adjusting the particle smoothing length.

[0081] (12)

[0082] The smooth length is updated at fixed time step intervals, and the operation is tailored to the specific simulation scenario.

[0083] This application addresses the issue of non-physical oscillations that do not conform to physical laws in numerical analysis by introducing specific dissipation terms into the governing equations. Therefore, artificial viscosity is introduced into the momentum balance equation (1):

[0084] (13)

[0085] in:

[0086] (14)

[0087] In the specific embodiments of this application, the method for processing the elastoplastic model differs from the method for processing the viscous model. The viscous model can be directly processed using the finite difference method, as shown in equation (3) above, ensuring the rotational invariance of the rigid body. The elastoplastic model generally uses standard SPH kernel gradient interpolation. To achieve first-order consistency in the kernel gradient, the following must be satisfied:

[0088] (15)

[0089] Therefore, the corrected kernel gradient is:

[0090] (16)

[0091] (17)

[0092] In this case, the particle The components may be collinear or coplanar, causing the matrix to become singular. This can be solved using the Moore-Penrose generalized inverse matrix. The linear Cauchy-Green strain tensor is calculated as follows:

[0093] (18)

[0094] Deformation gradient obtained through displacement field Therefore, the solution of the linear Cauchy-Green strain tensor is directly extracted from the displacement field:

[0095] (19)

[0096] Rotation processing: This application extracts the linear Cauchy-Green strain tensor from the displacement field. To capture the rotation strategy, the initial position needs to be rotated to the current position. Therefore, a kernel gradient correction is performed at the start of the simulation. Thus, equation (19) above relies entirely on SPH interpolation to capture constant rotation:

[0097] (20)

[0098] (twenty one)

[0099] Method for obtaining elastic stress: Based on the above equations (5) and (19), this application can derive the elastic strain of the particle:

[0100] (twenty two)

[0101] In this application, the total elastoplastic stress caused by the particle is calculated using the generalized Hooke's law:

[0102] (twenty three)

[0103] In the above equation, Indicates shear modulus, Let represent the bulk modulus. Therefore, the elastic force is obtained through the stress divergence. Due to the introduction of the correction kernel function and rotation treatment, the stress tensor needs to be multiplied by the corresponding kernel gradient. Furthermore, a non-iterative particle smoothing length correction must be introduced to obtain the elastoplastic force acting on particle i at time t.

[0104] (twenty four).

[0105] In the specific embodiments of this application, equations (19) and (20) above are shown during the simulation process. and Since the parameters are linearly dependent, equation (19) above can be restated as:

[0106] (25)

[0107] However, due to The linear dependence between the two parameters is not displayed; this aspect must be handled separately in the overall elastoplastic stress calculation.

[0108] (26)

[0109] in:

[0110] (27)

[0111] Similarly, improved particles In time Elastic-plastic forces:

[0112] (28)

[0113] (29)

[0114] In a viscous framework, the above equation (3) is modified by combining a non-iterative smooth length correction method to obtain the following equation:

[0115] (30)

[0116] Viscous scheme shows velocity vector The linear dependence of the equation leads to the final implicit velocity acquisition equation:

[0117] (31)

[0118] The implicit velocity acquisition equation above is transformed using the conjugate gradient method to obtain:

[0119] (32)

[0120] and It can also be transformed into This forms a conjugate gradient iteration formula, which simplifies the original expression to the following form using the conjugate gradient iteration method:

[0121] (33)

[0122] The basis vectors of the conjugate gradient algorithm are This application uses the conjugate gradient algorithm to ensure that the matrix It is crucial that it is symmetric and positive definite. Therefore, and The fact that the matrix remains the same initially during the analysis of elasto-plastic forces indicates a uniform particle distribution. Meanwhile, the diagonal matrix for the analytical viscous forces needs to be modified as follows:

[0123] (34)

[0124] In this specific embodiment, a constant density solver is used to obtain the initial updated predicted velocity, and then the pressure term is placed in a scatterless solver and updated to obtain the final velocity. .

[0125] The method described in this application is integrated into the implicit solver of DFSPH, using a Wendland fifth-order kernel function. All simulations were performed in parallel using a 2.50GHz i7-11700F CPU and rendered using Blender. Dynamically adjusting particle smoothing length and elasticity solutions significantly improves overall computational speed in terms of time step size under CFL conditions.

[0126] In another embodiment of the present invention, a simulation system for incompressible viscoelastic-plastic properties is provided, comprising a model building module, a model processing module, and a simulation module:

[0127] The model building module constructs viscous constitutive models and elastoplastic constitutive models of particles;

[0128] The model processing module simulates the viscous forces of ions based on the viscous constitutive model of particles to obtain the viscous forces of particles, and obtains the elastoplastic forces based on the elastoplastic constitutive model of particles.

[0129] The simulation module obtains the final velocity of the particles based on the acquired viscous and elastoplastic forces, thereby simulating the viscoelasticity and plasticity of the particles.

[0130] Preferably, the incompressible Navier-Stokes equations are used, incorporating the forces acting on the particle into the momentum balance equations, as shown below:

[0131] (1)

[0132] In the formula, Represents density, Indicates pressure, Representing other external forces, , These represent viscous stress and elastoplastic stress, respectively.

[0133] Preferably, the viscous force of ions is obtained by simulating the viscous force based on the viscous constitutive model of particles, and the rate of change of the influence of the viscosity term on the solution velocity is:

[0134] (2)

[0135] in, The viscosity represents the kinetic viscosity of particles. Represents the velocity of the particle.

[0136] To verify the effectiveness and superiority of the method proposed in this application, a comparison was made with more complex elastoplastic materials. Because elastoplastic materials not only undergo significant deformation but also require dynamic constraints on the particles experiencing such deformation, comparative simulations were performed on the same material using the classical dp elastoplastic constitutive model proposed by Bui and the viscoelastic-plastic constitutive model proposed by Li.

[0137] Compared to the method of Bui et al.: such as Figure 5 As shown, the top row employs the method from the Bui study. This method incorporates the original dp yield criterion from the Bui study and enhances it with a simple fracture criterion to simulate this type of destructive scenario. By applying artificial viscosity correction, fewer uncontrolled dispersed particles are observed, with many particles agglomerating into small clusters. However, compared to the scheme presented in this paper, the extensive iterations and adjustments required by Bui's dp constitutive method result in a significantly slower simulation speed.

[0138] Compared with the method of Li et al.: Figure 5 The second line utilizes a viscoelastic-plastic simulation of Li, where the particle dispersion is very severe, resulting in significant artifacts. Figure 5 The third line is a simulated scene using this application, and its rendered scene is as follows: Figure 6 As shown. This application employs a non-iterative smooth length algorithm for correction. Figure 5 In the image, the change in the number of neighboring particles changes from red to blue. Simultaneously, from... Figure 7 The change in the number of middle-neighbor particles shows that the framework in this application further restricts the irregular dispersion of head particles, thereby enhancing the realism of the simulated scene. The method in this application has greater advantages in both simulation effect and simulation speed.

[0139] Experiments investigating the effects of different material properties:

[0140] Different materials elicited different responses in the silver armadillo. For example... Figure 8 As shown in the first line, water (or a low-viscosity substance) falling from a height quickly bypasses the silver armadillo, but this action has almost no effect on the water that doesn't touch the armadillo, which continues to fall with a constant acceleration. Finally, at 0.87 seconds, the water flows past the armadillo's shoulder, leaving very little water residue on its body. When transformed into an elastic fabric of the same size, such as... Figure 8 As shown in the second line, the fabric has a Young's modulus of 0.5 MPa, a Poisson's ratio of 0.33, an elastic limit of 0.147, and a plastic limit of 0.642. This material exhibits a certain degree of elastic deformation; once its elastic limit is exceeded, irreversible plastic deformation occurs. At 1.5 seconds, when the fabric comes into contact with the silver armadillo, its edges appear to contract slightly. By 2 seconds, inertia causes the fabric edges to bounce back, remaining in the deformation phase. After the elastic deformation and recovery phases, the fabric gradually stabilizes, with no further dynamic changes. Furthermore, the armadillo's ears and hands cause the fabric to tear, resulting in irreversible deformation, which remains in the state at 5 seconds, regardless of the calculated time.

[0141] When the material is switched to high-viscosity honey of the same size, Figure 8In the third scene, the honey is given a dynamic viscosity of 1500 kg / m·s. The honey is like... Figure 4 The 1.5-second mark landed on his head, but with... Figure 4 Subsequent simulations showed a different effect: its high viscosity caused it to break apart on the armadillo's hand. Then, after 6 seconds, the viscous honey slowly covered the upper body of the silver armadillo and dripped gently. Over time, most of the honey fell to the ground and adhered to the armadillo's legs, with some honey remaining on the upper body. Furthermore, the method described in this application also performs well in simulating non-Newtonian viscous fluids. Figure 9 As shown, this application simulates three dragons falling into a mixture of cornstarch and water. Figure 10 This reflects the changes in strain rate and dynamic viscosity during the simulation. It can be observed that the strain rate suddenly surges when the dragon falls into the mixture. Simultaneously, the strain rate and dynamic viscosity change exponentially, corresponding in the simulation to the dragon suddenly stopping and then gradually sinking into the mixture.

[0142] To further verify the broad applicability of the simulation method presented in this application, a simulation using 3 million particles was conducted using Benjamin's dataset on water erosion, but the original water properties were replaced with those of a mudflow material exhibiting viscoelastic-plastic characteristics. In this study, the mudflow properties were set to a Young's modulus of 207 MPa, a Poisson's ratio of 0.3, an elastic limit of 0.001, a plastic limit of 0.05, and a dynamic viscosity of 100 kg / (m·s). Figure 11 As shown, a clear difference can be seen; there is obvious stratification and separation on the left, without the strong dispersion typical of water, achieving an effect similar to the erosion of mudflows in the real world.

[0143] Multiple couplings:

[0144] In simulations involving four different materials, such as Figure 12 , Figure 13 In a complex scene, the number of participating particles reached 145,828, with a computation time of 1050.695 milliseconds per frame. The simulation also demonstrated strong stability, achieving a time step ∆t of up to 3 milliseconds under CFL conditions. Furthermore, in... Figure 11 In scenario (a), using 3 million viscoelastic-plastic debris flow materials, computation takes 89,658.33 milliseconds per frame. This demonstrates that the method employed in this application can effectively handle complex scenarios with multiple material properties and multiphase coupling.

[0145] The method in this application decomposes the mechanical behavior of particle materials into viscosity and elastoplasticity for implicit solution. In addition to addressing rotational invariance through kernel gradient correction, this application also performs adaptive correction for smooth length and adjusts artificial viscosity, reducing artifacts from unconstrained particle dispersion in large deformations. Compared to existing methods, this application's method offers significant advantages in terms of stability and speed. Embedded in the DFSPH solver, this method can skillfully handle large deformations, composite materials, and multiphase coupling.

[0146] This application, based on existing Newtonian fluid simulations, employs the fundamental generalized Maxwell model to incorporate elastoplastic constitutive behavior and viscosity into a unified framework applicable to all stages. Experimental evidence demonstrates that the method of this invention can accurately simulate the mechanical behavior of most real materials.

[0147] Within the viscoelastic-plastic framework, the method of this invention employs an implicit solution strategy and integrates the conjugate gradient algorithm into the DFSPH solver, thereby accelerating the computation speed per frame. Furthermore, this method significantly increases the time step size under CFL conditions, further accelerating computation.

[0148] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A method for simulating incompressible viscoelastic-plastic properties, characterized in that, Includes the following steps: S1, construct the viscous constitutive model and the elastoplastic constitutive model of the particle respectively; S2, based on the viscous constitutive model of particles, the viscous force of ions is simulated to obtain the viscous force of particles, and based on the elastoplastic constitutive model of particles, the elastoplastic force is obtained; S3, based on the obtained particle viscous force and elastoplastic force, obtains the final velocity of the particle, realizing the simulation of the particle's viscoelasticity and plasticity; Based on the viscous constitutive model of particles, the viscous force of ions is simulated to obtain the particle viscous force. The rate of change of the influence of the viscosity term on the solution velocity is: Among them, v i The viscosity of a particle is represented by v. i Represents the velocity of the particle; Elastic-plastic forces are obtained based on a particle-based elastoplastic constitutive model, which combines elastic strain and plastic strain to generate an elastoplastic strain equation: In the calculation process of the elastoplastic constitutive model, the elastoplastic stress rate is derived from the elastoplastic strain rate, thereby obtaining the elastoplastic stress; Indicates elastic strain. Indicates plastic strain; Elastic force is obtained through stress divergence. A correction kernel function and rotation processing are introduced to multiply the stress tensor by the corresponding kernel gradient. Non-iterative particle smoothing length correction is introduced to obtain the elastoplastic force acting on the particle at a set time.

2. The simulation method for incompressible viscoelastic-plastic properties according to claim 1, characterized in that, By employing the incompressible Navier-Stokes equations, the forces acting on the particle are introduced into the momentum balance equations, as shown below: In the formula, ρ i p represents density i Indicates pressure, Representing other external forces, These represent viscous stress and elastoplastic stress, respectively.

3. The simulation method for incompressible viscoelastic-plastic properties according to claim 1, characterized in that, An implicit simulation method based on the velocity field Laplace operator is adopted to simulate viscous forces.

4. A simulation system for incompressible viscoelastic-plastic properties, characterized in that, It includes a model building module, a model processing module, and a simulation module: The model building module constructs viscous constitutive models and elastoplastic constitutive models of particles; The model processing module simulates the viscous forces of ions based on the viscous constitutive model of particles to obtain the viscous forces of particles, and obtains the elastoplastic forces based on the elastoplastic constitutive model of particles. The simulation module obtains the final velocity of the particles based on the acquired viscous and elastoplastic forces, thereby simulating the viscoelasticity and plasticity of the particles. Based on the viscous constitutive model of particles, the viscous force of ions is simulated to obtain the particle viscous force. The rate of change of the influence of the viscosity term on the solution velocity is: Among them, v i The viscosity of a particle is represented by v. i Represents the velocity of the particle; Elastic-plastic forces are obtained based on a particle-based elastoplastic constitutive model, which combines elastic strain and plastic strain to generate an elastoplastic strain equation: In the calculation process of the elastoplastic constitutive model, the elastoplastic stress rate is derived from the elastoplastic strain rate, thereby obtaining the elastoplastic stress; Indicates elastic strain. Indicates plastic strain; Elastic force is obtained through stress divergence. A correction kernel function and rotation processing are introduced to multiply the stress tensor by the corresponding kernel gradient. Non-iterative particle smoothing length correction is introduced to obtain the elastoplastic force acting on the particle at a set time.

5. A simulation system for incompressible viscoelastic-plastic properties according to claim 1, characterized in that, By employing the incompressible Navier-Stokes equations, the forces acting on the particle are introduced into the momentum balance equations, as shown below: In the formula, ρ i p represents density i Indicates pressure, Representing other external forces, These represent viscous stress and elastoplastic stress, respectively.

6. A simulation system for incompressible viscoelastic-plastic properties according to claim 1, characterized in that, An implicit simulation method based on the velocity field Laplace operator is adopted to simulate viscous forces.

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