SPH semi-implicit solving method for landslide and debris flow movement process

Abstract

The invention provides an SPH semi-implicit solving method for a landslide and debris flow movement process, and the method comprises the steps: generating a background grid and an SPH particle model of a landslide body or a debris flow body according to the information of a research region and an object source, and applying calculation parameters and boundary conditions; the method comprises the following steps: dividing a momentum conservation equation of a landslide body or a debris flow body into a pressure item, a gradient item and a source item, and carrying out explicit solution on the gradient item and the source item by adopting Runge-Kutta time integral to obtain an explicit speed increment; constructing a finite element solution format for the implicit velocity increment equation by adopting a Galerkin method, and solving to obtain an implicit velocity increment; and combining the explicit speed increment and the implicit speed increment to obtain the SPH particle speed value of the next time step.

Description

Technical Field

[0001] The present invention belongs to the technical fields such as dynamic analysis and simulation of geological disasters, and particularly relates to a SPH semi-implicit solution method for the movement processes of landslides and debris flows. Background Art

[0002] The evolution and development of landslide and debris flow disasters involve large-scale movement of materials. Various particle-based methods in the Lagrangian framework are considered effective analysis means for such problems, and the Smoothed Particle Hydrodynamics (SPH) is one of the typical methods.

[0003] In the study of practical problems, particle-based methods such as the SPH method are prone to the phenomenon of local particle aggregation during the simulation process, which may cause a sharp decrease in the local particle spacing. Due to being restricted by the stability condition of the explicit solution of the SPH method, the iteration step size decreases rapidly. For the simulation of specific disaster processes, too small an iteration step size will significantly increase the computational amount and even lead to the inability to continue the calculation. Summary of the Invention

[0004] The technical problem to be solved by the present invention is that currently, for particle-based methods represented by SPH in simulating large-deformation geological disasters such as landslides and debris flows, due to the time step size being restricted by particle aggregation, the computational amount is too large or even the calculation cannot be carried out. A SPH semi-implicit solution method for the movement processes of landslides and debris flows is proposed. The adopted semi-implicit solution method processes the control equations by item, and solves the terms vulnerable to step size limitation implicitly, while the remaining parts continue to be solved explicitly. This method can effectively solve the problem of too small an iteration step size. Therefore, how to construct a targeted semi-implicit solution method according to the characteristics of the SPH control equations for the movement processes of landslides and debris flows will improve the simulation effect and application value of the SPH numerical simulation method in practical engineering.

[0005] The present invention solves the problem that for particle-based methods in the Lagrangian framework in simulating the dynamic processes of landslides or debris flows, due to local particle accumulation, the explicit solution time step size is too small, resulting in too large a computational amount, and can improve the simulation effect and application value of such methods in practical engineering.

[0006] The technical solution specifically adopted by the present invention to solve its technical problem is as follows:

[0007] A SPH semi-implicit solution method for the movement process of landslides and debris flows: According to the research area and source material information, generate a background grid and an SPH particle model of the landslide body or debris flow body, and apply calculation parameters and boundary conditions; by dividing the momentum conservation equation of the landslide body or debris flow body into three parts: a pressure term, a gradient term, and a source term, and explicitly solving the gradient term and the source term using Runge-Kutta time integration, obtain the explicit velocity increment Δv * (:); Use the Galerkin method to construct a finite element solution format for the implicit velocity increment equation and solve it to obtain the implicit velocity increment Δv ** (:); Combine the explicit velocity increment Δv * (:) and the implicit velocity increment Δv ** (:) to obtain the SPH particle velocity value v n+1 (:) at the next time step.

[0008] Furthermore, the step of generating a background grid and an SPH particle model of the landslide body or debris flow body according to the research area and source material information, and applying calculation parameters and boundary conditions specifically includes: generating a standardized background grid for the research area: according to the research area information, by defining the interval sizes in the x and y directions of the grid, generate a standardized background grid for the research area from the original DEM data, including the coordinates BG(:,:,:) of each grid node; generating source material information: generate SPH particles of the landslide body or debris flow body according to the input source material range and depth distribution; input control parameters and boundary conditions: input calculation parameter information including the iteration time step, the maximum number of iterations, and the output interval step; input boundary conditions, including normal constraint boundaries, transmissive boundaries, and sponge layer boundaries.

[0009] Furthermore, the step of dividing the momentum conservation equation of the landslide body or debris flow body into three parts: a pressure term, a gradient term, and a source term, and explicitly solving the gradient term and the source term using Runge-Kutta time integration to obtain the explicit velocity increment Δv * (:) specifically includes:

[0010] According to the normal component b 3 of the gravitational acceleration on the slope surface and the information carried by the SPH particles, including: depth h(:) and porosity n(:), calculate the gradient term velocity increment Δv g (:):

[0011]

[0012] In the formula, grad{} is the SPH method gradient solving operator;

[0013] According to the normal component b 3 of the gravitational acceleration on the slope surface and the information carried by the SPH particles, including: friction force τ b(:), depth h(:), solid-liquid interaction force R(:), source density ρ(:), porosity n(:), particle velocity v at the current time step n (:), erosion rate e R (:) information of the bottom sliding surface, calculate the source term velocity increment Δv s (:):

[0014]

[0015] Calculate the explicit solution velocity increment Δv for this time step * (:):

[0016] Δv * (:) = Δv g (:)+Δv s (:).

[0017] Furthermore, the Galerkin method is applied to construct a finite element solution format for the implicit velocity increment equation and solve it to obtain the implicit velocity increment Δv ** (:) specifically includes:

[0018] Calculate the shape function calculation matrix K(:,:) of the divergence term and the shape function calculation matrix M(:,:) of the constant term in the finite element solution format;

[0019] Calculate the explicit solution velocity increment term T in the finite element solution format of the implicit velocity increment equation 3 , and the boundary condition term BDs;

[0020] Calculate the pressure term p at the next time step n+1 (:):

[0021]

[0022] Calculate the implicit velocity increment Δv ** (:):

[0023]

[0024] In the formula, Δt is the calculation time step.

[0025] Furthermore, the explicit velocity increment Δv * (:) and the implicit velocity increment Δv ** (:) are combined to obtain the SPH particle velocity value v n+1 (:) at the next time step, and the calculation formula is:

[0026] v n+1 (:) = v n (:)+Δv * (:)+Δv **(:).

[0027] Further, on the basis of obtaining the SPH particle velocity value v at the next time step n+1 (:), according to the particle coordinates x_coor at the current time step n (:), calculate and obtain the particle coordinates x_coor at the next time step n+1 (:);

[0028]

[0029] And, a SPH semi-implicit solution system for the movement process of landslides and debris flows, including:

[0030] SPH particle model generation module: Generate a background grid and an SPH particle model of a landslide body or debris flow body according to the research area and source material information, and apply calculation parameters and boundary conditions;

[0031] Explicit velocity increment calculation module: By dividing the momentum conservation equation of the landslide body or debris flow body into three parts: pressure term, gradient term, and source term, and explicitly solving the gradient term and source term using Runge-Kutta time integration, obtain the explicit velocity increment Δv * (:);

[0032] Implicit velocity increment calculation module: Use the Galerkin method to construct a finite element solution format for the implicit velocity increment equation and solve it to obtain the implicit velocity increment Δv ** (:);

[0033] SPH particle velocity value calculation module: Combine the explicit velocity increment Δv * (:) and the implicit velocity increment Δv ** (:) to obtain the SPH particle velocity value v at the next time step n+1 (:).

[0034] Further, it further includes a particle coordinate calculation module: On the basis of obtaining the SPH particle velocity value v at the next time step n +1 (:), according to the particle coordinates x_coor at the current time step n (:), calculate and obtain the particle coordinates x_coor at the next time step n+1 (:);

[0035]

[0036] And, an electronic device, including a memory, a processor, and a computer program stored on the memory and executable on the processor, and when the processor executes the program, it implements the steps of the above-mentioned SPH semi-implicit solution method for the movement process of landslides and debris flows.

[0037] A non-transitory computer-readable storage medium stores a computer program thereon. When the computer program is executed by a processor, it implements the steps of a semi-implicit SPH solution method for the landslide and debris flow movement process as described above.

[0038] Traditional particle-based simulation methods (such as the SPH method) often face the problem of local particle aggregation, which in turn causes a sharp decrease in the particle spacing. Due to the stability limitation of the explicit solution of the SPH method, the iteration step size decreases rapidly. In the simulation of specific disaster processes, an overly small iteration step size will lead to a sharp increase in the computational cost and even make the calculation impossible to perform. The present invention introduces a semi-implicit solution method, which effectively solves the above problems. By separately processing the governing equations and using an implicit solution for the terms that limit the step size while continuing to use an explicit solution for the remaining parts, the step size limitation is effectively relaxed, thus significantly improving the simulation effect and application value of such numerical simulation methods in practical engineering.

[0039] The present invention adopts a semi-implicit solution strategy, separately processes and solves the momentum conservation equation in the SPH method, and forms a new solution framework.

[0040] The main differences between it and other existing related solutions are as follows:

[0041] (a) Compared with the semi-implicit moving particle semi-implicit method (MPS): This algorithm obtains the pressure field of the fluid by solving the pressure Poisson equation and corrects the predicted fluid velocity through the pressure gradient, approximating the physical quantities and their derivatives of the fluid through the interaction between particles. Usually, a Gaussian weight function or other similar weight functions are used to calculate the interpolation and differential operations between particles. For example, the velocity gradient and pressure gradient of particles can be obtained by weighted averaging the information of surrounding particles, thus avoiding the dependence on grids. The SPH method approximates the physical quantities and their derivatives of the fluid through a kernel function. The kernel function is used to interpolate and approximate the fluid properties around particles, thus discretizing the continuous fluid field into a discrete particle set. Numerically, each particle interacts with surrounding particles through the kernel function to calculate physical quantities and their derivatives. The present invention is an improvement and enhancement based on the SPH method and has significant differences from MPS in both basic theory and numerical framework. Specifically, based on the general SPH method, the present invention realizes a semi-implicit solution strategy through the separate processing of the momentum equation to solve the problem of excessive computational cost.

[0042] (b) Finite Volume Particle Method (FVP): In FVP, the conservation equations (such as the mass conservation equation, momentum conservation equation, etc.) are discretized on the control volume of each particle. By integrating the conservation equations, the partial differential equations are transformed into a system of algebraic equations, and its numerical method is similar to MPS. The present invention is an improvement and enhancement based on the SPH method, and there are significant differences in the basic theory and numerical framework from the finite volume particle method. The present invention realizes the efficient solution of the pressure term of the control equation by binding finite element meshes to SPH particles, which is a specific scheme for implicit solution in the above semi-implicit solution strategy.

[0043] Thus, the main innovation points and advantages of the present invention and its preferred embodiments at least include:

[0044] 1. Introduction of semi-implicit solution strategy and separate treatment of terms in the momentum equation:

[0045] Traditional SPH methods usually adopt explicit solutions, which may lead to very small time steps in areas with dense particles, thereby increasing the computational amount or causing instability.

[0046] Traditional SPH methods usually solve the momentum conservation equation as a whole, while the present method divides the momentum equation into a pressure term, a gradient term, and a source term, and processes them separately. The gradient term and the source term are solved explicitly, while the pressure term is solved implicitly. This not only improves the stability but also reduces the numerical instability caused by particle accumulation. Thus, the problem of too small explicit solution step size is avoided, and the computational efficiency is improved.

[0047] 2. Improvement of time integration:

[0048] By using the Runge-Kutta method to explicitly solve the gradient term and the source term, the accuracy and stability of the solution are significantly improved. Compared with traditional explicit methods, the Runge-Kutta method has better effects in dealing with complex nonlinear problems.

[0049] 3. Application of the finite element method:

[0050] In the implicit solution process, the Galerkin method is applied to construct a finite element solution format, which enhances the accuracy and stability of the solution. Especially when dealing with nonlinear and dynamically changing problems, this method has better control compared with the direct explicit SPH method.

[0051] 4. Iterative update mechanism:

[0052] By updating the particle velocity and position at each time step, the continuity and stability of the simulation process are ensured, and the calculation is not interrupted due to the time step problem caused by local particle accumulation.

[0053] 5. Main differences and advantages

[0054] Computational efficiency: Since the semi-implicit method uses implicit solutions in some parts, it avoids the slow calculation caused by too small time steps in the explicit solution method. Therefore, there is a significant improvement in computational efficiency.

[0055] Stability: This method effectively avoids the numerical instability problem of traditional SPH methods in extreme cases. Especially when simulating large-scale landslides and debris flows, the calculation is more stable and reliable.

[0056] Applicability: Traditional SPH methods may encounter calculation difficulties due to particle aggregation when dealing with large-scale disaster simulations. However, this method makes it more applicable to large-scale and complex geological disaster simulations through sub-item solutions and the introduction of implicit processing. Brief Description of the Drawings

[0057] The present invention will be further described in detail below in conjunction with the drawings and specific embodiments:

[0058] Figure 1 This is the flowchart of the method according to the embodiment of the present invention.

[0059] Figure 2 This is a schematic diagram of generating a standardized background grid of the research area from the original DEM data according to the embodiment of the present invention.

[0060] Figure 3 This is an example diagram of the one-dimensional linear element shape function and differentiation according to the embodiment of the present invention. Specific Embodiments

[0061] To make the features and advantages of this patent more obvious and understandable, specific embodiments are given below for detailed description as follows:

[0062] It should be noted that the following detailed description is exemplary and is intended to provide further explanation of the present application. Unless otherwise specified, all technical and scientific terms used in this specification have the same meaning as commonly understood by those of ordinary skill in the technical field to which this application belongs.

[0063] It should be noted that the terms used here are only for describing specific embodiments and are not intended to limit the exemplary embodiments according to the present application. As used herein, unless the context clearly indicates otherwise, the singular form is also intended to include the plural form. In addition, it should be understood that when the terms "comprise" and / or "include" are used in this specification, they indicate the presence of features, steps, operations, devices, components, and / or combinations thereof.

[0064] In view of the problems that in the current simulation process of particle-based methods such as the SPH method, local particle aggregation is likely to occur, the particle spacing decreases, and it is limited by the stability condition of explicit solution, resulting in a rapid reduction of the iteration step size and an excessive calculation amount, a semi-implicit SPH solution method for the movement process of landslides and debris flows is proposed. By separately processing the governing equations, this method implicitly solves the terms that limit the step size, while the remaining parts continue to be explicitly solved, effectively relaxing the step size limit, thereby significantly improving the simulation effect and application value of such numerical simulation methods in practical engineering. The specific implementation process is as Figure 1 shown. It mainly includes the following 4 steps:

[0065] Step 1: According to the research area and source information, generate the background grid and the SPH particle model of the landslide body or debris flow body, and apply calculation parameters and boundary conditions;

[0066] Step 2: By dividing the momentum conservation equation of the landslide body or debris flow body into three parts: the pressure term, the gradient term, and the source term, and explicitly solving the gradient term and the source term using the Runge-Kutta time integration, obtain the explicit velocity increment Δv * (:);

[0067] Step 3: Apply the Galerkin method to construct a finite element solution format for the implicit velocity increment equation and solve it to obtain the implicit velocity increment Δv ** (:);

[0068] Step 4: Obtain the SPH particle velocity value v n+1 (:) at the (n + 1)-th time step, update the particle position information, and enter the next time step loop.

[0069] Select a specific debris flow case and introduce it in detail according to the method process ( Figure 1 ):

[0070] Step 1: According to the research area and source information, generate the background grid and the SPH particle model of the landslide body or debris flow body, and apply calculation parameters and boundary conditions, including the following steps:

[0071] ① Generate the standardized background grid of the research area. According to the research area information, define the interval sizes in the x and y directions of the grid as 5 m, and generate the standardized background grid of the research area from the original DEM data, including 2000 grid node coordinates BG(2000, :, :) (see Figure 2 ).

[0072] ② Generate the source information. According to the input source range and depth distribution, generate 1000 SPH particles of the landslide body or debris flow body.

[0073] ③ Input control parameters and boundary conditions. The input calculation parameter information includes control parameters such as the iterative time step of 0.01, the maximum number of iterations of 100,000, and the output interval step of 10. Input boundary conditions, and arrange 3 normal boundaries.

[0074] Step 2: Divide the momentum conservation equation of the landslide body or debris flow into three parts: the pressure term, the gradient term, and the source term, and explicitly solve the gradient term and the source term using the Runge-Kutta time integration to obtain the explicit velocity increment Δv * (1000,:,:).

[0075] It includes the following steps:

[0076] ① Calculate the gradient term velocity increment Δv g (1000,:,:), according to the normal component b of the gravitational acceleration on the slope 3 , and the information carried by SPH particles, including: depth h(1000,:), porosity n(1000,:), which are calculated by the following formula:

[0077]

[0078] In the formula, grad{} is the SPH method gradient solver operator.

[0079] ② Calculate the source term velocity increment Δv s (1000,:,:), according to the normal component b of the gravitational acceleration on the slope 3 , and the information of the basal slip surface carried by SPH particles, including: friction force τ b (1000,:,:), depth h(1000,:), solid-liquid interaction force R(1000,:,:), source density ρ(1000,:), porosity n(1000,:), particle velocity v n (1000,:,:) at the current time step, erosion rate e R (1000,:), which are calculated by the following formula:

[0080]

[0081] ③ Calculate the explicit solution velocity increment Δv at this time step * (1000,:,:):

[0082] Δv * (1000,:,:) = Δv g (1000,:,:) + Δv s (1000,:,:)(3)

[0083] Step 3: Apply the Galerkin method to construct a finite element solution scheme for the implicit velocity increment equation and solve it to obtain the implicit velocity increment Δv ** (1000,:,:). It includes the following steps:

[0084] ① Calculate the shape function calculation matrix K(:,:) of the divergence term and the shape function calculation matrix M(:,:) of the constant term in the finite element solution scheme.

[0085] ② Calculate the explicit solution velocity increment term T in the finite element solution scheme of the implicit velocity increment equation 3 , and the boundary condition term BDs.

[0086] ③ Calculate the pressure term p at the n+1 time step n+1 (1000,:):

[0087]

[0088] Taking a one-dimensional linear element as an example (taking the shape function N 1 =1 - x / L e , N 2 =x / L e , then there are: ), L e is the length of the linear element (see Figure 3 ). Then there are:

[0089]

[0090] In the formula, i and j represent the finite element grid node numbers, and ipoin represents the SPH particle number.

[0091] ④ Calculate the implicit velocity increment Δv ** (1000,:,:):

[0092]

[0093] In the formula, Δt is the calculation time step.

[0094] Step 4: Obtain the SPH particle velocity value v at the n+1 time step n+1 (1000,:,:), update the particle position information, and enter the next time step loop. It includes the following steps:

[0095] ① Calculate the velocity value v at the n+1 time step n+1 (:):

[0096] v n+1 (1000,:,:) = v n (1000,:,:) + Δv * (1000,:,:) + Δv** (1000,:,:)(7)

[0097] ② Calculate the particle coordinates x_coor at the n+1 time step n+1 (1000,:,:). Based on the particle coordinates x_coor at the current time step n (1000,:,:), which is calculated by the following formula:

[0098]

[0099] Based on the same inventive concept, the present invention also provides a computer device, which includes: one or more processors, and a memory for storing one or more computer programs; the program includes program instructions, and the processor is configured to execute the program instructions stored in the memory. The processor may be a Central Processing Unit (CPU), or may also be other general-purpose processors, Digital Signal Processors (DSPs), Application Specific Integrated Circuits (ASICs), Field-Programmable Gate Arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. It is the computing core and control core of the terminal, and is used to implement one or more instructions. Specifically, it is used to load and execute one or more instructions in the computer storage medium to implement the above method.

[0100] It should be further noted that, based on the same inventive concept, the present invention also provides a computer storage medium, on which a computer program is stored, and when the computer program is run by a processor, it executes the above-mentioned method. The storage medium may adopt any combination of one or more computer-readable media. The computer-readable medium may be a computer-readable signal medium or a computer-readable storage medium. The computer-readable storage medium may, for example, but not be limited to, an electrical, magnetic, optical, electrical, magnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the above. More specific examples (non-exhaustive list) of the computer-readable storage medium include: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present invention, the computer-readable storage medium may be any tangible medium that contains or stores a program, and this program can be used by or in combination with an instruction execution system, apparatus, or device.

[0101] It should be noted that, unless otherwise defined, the technical terms or scientific terms used in the present invention should have the ordinary meanings understood by those of ordinary skill in the field to which the present invention pertains. The "first", "second", and similar terms used in the present invention do not denote any order, quantity, or importance, but are only used to distinguish different components. The terms such as "comprising" or "including" mean that the elements or items appearing before this word cover the elements or items listed after this word and their equivalents, without excluding other elements or items. The terms such as "connected" or "coupled" are not limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect. The terms such as "upper", "lower", "left", "right", etc. are only used to represent relative positional relationships, and when the absolute position of the object being described changes, the relative positional relationship may also change accordingly.

[0102] As mentioned above, these are only the preferred embodiments of the present invention, and the present invention is not limited to other forms. Any person skilled in the art may use the disclosed technical content to make changes or modifications into equivalent embodiments with equivalent changes. However, any simple modifications, equivalent changes, and modifications made to the above embodiments based on the technical essence of the present invention without departing from the technical solution content of the present invention still fall within the protection scope of the technical solution of the present invention.

[0103] This patent is not limited to the above-mentioned best implementation modes. Anyone inspired by this patent can obtain various other forms of a SPH semi-implicit solution method for the movement process of landslides and debris flows. All equal changes and modifications made according to the scope of the patent application of the present invention shall fall within the scope covered by this patent.

Claims

1. A SPH semi-implicit solution method for landslide and debris flow motion process, characterized by: According to the research area and material source information, the background grid and the SPH particle model of the landslide body or debris fluid are generated, and the calculation parameters and boundary conditions are applied. The momentum conservation equation of the landslide body or debris fluid is divided into three parts: pressure term, gradient term and source term, and the gradient term and source term are explicitly solved by Runge-Kutta time integration to obtain the explicit velocity increment Δv * (:); Using the Galerkin method, a finite element solution format is constructed for the implicit velocity increment equation, and the implicit velocity increment Δv is obtained by solving it. ** (:); combined with explicit velocity increment Δv * (:) and implicit velocity increment Δv ** (:) Get the SPH particle velocity value v of the next time step n+1 (:).

2. The SPH semi-implicit solution method for landslide and debris flow motion process according to claim 1 is characterized by: The method of generating a background grid and an SPH particle model of a landslide or debris fluid according to the study area and material source information, and applying calculation parameters and boundary conditions specifically includes: generating a standardized background grid for the study area: generating a standardized background grid for the study area from original DEM data by defining the interval size of the grid in the x and y directions according to the study area information, including the coordinates BG (:,:,:) of each grid node; generating material source information: generating SPH particles of a landslide or debris fluid according to the input material source range and depth distribution; inputting control parameters and boundary conditions: inputting calculation parameter information including iteration time step, maximum number of iterations, and output interval step; inputting boundary conditions including normal restriction boundary, transmission boundary and sponge layer boundary.

3. The SPH semi-implicit solution method for landslide and debris flow motion process according to claim 1 is characterized by: The momentum conservation equation of the landslide body or debris fluid is divided into three parts: pressure term, gradient term and source term, and the gradient term and source term are explicitly solved by using the Runge-Kutta time integration method to obtain the explicit velocity increment Δv * (:)Specifically include: According to the slope normal component b3 of the gravitational acceleration and the information carried by the SPH particles, including depth h(:) and porosity n(:), the gradient term velocity increment Δv is calculated. g (:): Where, grad{} is the gradient solution operator of the SPH method; According to the normal component b3 of the slope due to gravity acceleration, the SPH particles carry: friction force τ b (:), depth h(:), solid-liquid interaction force R(:), source density ρ(:), porosity n(:), particle velocity v in the current time step n (:), erosion rate e R (:) the information of the bottom sliding surface, and calculate the source term velocity increment Δv s (:): Calculate the explicit solution velocity increment Δv for this time step * (:): Δv * (:)=Δv g (:)+Δv s (:)。 4. The SPH semi-implicit solution method for landslide and debris flow motion process according to claim 2 is characterized by: The Galerkin method is applied to construct a finite element solution format for the implicit velocity increment equation, and the implicit velocity increment Δv is obtained by solving the equation. ** (:)Specifically include: Calculate the shape function calculation matrix K(:,:) of the divergence term and the shape function calculation matrix M(:,:) of the constant term in the finite element solution format; Calculate the explicit solution velocity increment term T3 and the boundary condition term BDs in the finite element solution format of the implicit velocity increment equation; Calculate the pressure term p for the next time step n+1 (:): Calculate the implicit velocity increment Δv ** (:): Where Δt is the calculation time step.

5. The SPH semi-implicit solution method for landslide and debris flow motion process according to claim 4 is characterized by: The combined explicit velocity increment Δv * (:) and implicit velocity increment Δv ** (:) Get the SPH particle velocity value v of the next time step n+1 The calculation formula for (:) is: v n+1 (:)=v n (:)+Δv * (:)+Δv ** (:)。 6. The SPH semi-implicit solution method for landslide and debris flow motion process according to claim 5 is characterized by: Get the SPH particle velocity value v of the next time step n+1 (:) Based on the particle coordinates x_coor at the current time step n (:), calculate the particle coordinates x_coor of the next time step n+1 (:); 7. A SPH semi-implicit solution system for landslide and debris flow motion process, characterized in that: include: SPH particle model generation module: Generates the SPH particle model of the background grid and landslide body or debris flow according to the research area and material source information, and applies calculation parameters and boundary conditions; Explicit velocity increment calculation module: The momentum conservation equation of the landslide or debris fluid is divided into three parts: pressure term, gradient term and source term, and the gradient term and source term are explicitly solved using the Runge-Kutta time integral to obtain the explicit velocity increment Δv * (:); Implicit velocity increment calculation module: The Galerkin method is used to construct a finite element solution format for the implicit velocity increment equation, and the implicit velocity increment Δv is obtained by solving it. ** (:); SPH particle velocity value calculation module: combined with explicit velocity increment Δv * (:) and implicit velocity increment Δv ** (:) Get the SPH particle velocity value v of the next time step n+1 (:).

8. The SPH semi-implicit solution system for landslide and debris flow motion process according to claim 7 is characterized by: It also includes a particle coordinate calculation module: after obtaining the SPH particle velocity value v of the next time step n+1 (:) Based on the particle coordinates x_coor at the current time step n (:), calculate the particle coordinates x_coor of the next time step n+1 (:); 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 program, the steps of the SPH semi-implicit solution method for the landslide and debris flow movement process as described in any one of claims 1-6 are implemented.

10. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the SPH semi-implicit solution method for the landslide and debris flow movement process as described in any one of claims 1 to 6 are implemented.

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