Mixed point implicit time marching method based on residual value decomposition, electronic equipment and storage medium

Abstract

The invention discloses a mixed point implicit time marching method based on residual value decomposition, electronic equipment and a storage medium, and belongs to the technical field of computational fluid mechanics. In order to improve the computational efficiency of computational fluid mechanics, the method comprises the following steps: generating a computational grid of a flow field simulation object, and reading computational grid information of the flow field simulation object; establishing a control equation under a finite volume method calculation framework to obtain an ordinary differential equation set about time, performing time differential on the control equation, and performing linear approximate processing to obtain an implicit discretized control equation; dividing a residual value item in the implicit discretization control equation into a residual value average item and a residual value dissipation item, solving the implicit discretization control equation by adopting a point implicit method LU-SGS, storing the residual value dissipation item in the first sweeping process, adding one sweeping frequency after the original sweeping frequency, and solving the residual value dissipation item in the second sweeping process by adopting a point implicit method LU-SGS; in the second sweeping process, the residual value dissipation items calculated in the first sweeping process are adopted for mixed calculation to complete updating of the flow field, and a flow field simulation result is obtained.

Description

Technical Field

[0001] The present invention belongs to the technical field of computational fluid dynamics, and in particular relates to a mixed point implicit time advancement method based on residual value decomposition, an electronic device and a storage medium. Background Art

[0002] The time marching method is widely used in computational fluid dynamics (CFD) to numerically solve the Euler or Navier-Stokes equations. It can be divided into explicit methods and implicit methods. The explicit method has a small amount of calculation per step, but the time step is limited by stability conditions, the CFL number is too small, and the efficiency is low; while the implicit method has good stability. Although the single-step calculation amount and storage volume are large, the overall efficiency is higher because a larger time step can be used. Therefore, the implicit method is widely used in large-scale flow simulation.

[0003] The implicit lower-upper symmetric Gauss-Seidel format (LU-SGS), also known as the upper-lower symmetric continuous over-relaxation (LU-SSOR) format, has the advantages of small memory usage and stable calculation. Due to its low numerical complexity and moderate storage requirements, it is comparable to the explicit multi-stage format and has been widely used in mature fluid simulation software such as OVERFLOW and CFL3D. In addition, the LU-SGS scheme can be easily implemented on vector and parallel computers, and can be used for structured grids and unstructured grids. When using the LU-SGS method to solve a linear system, the usual practice is to perform a forward sweep and a backward sweep in each iteration step. However, due to the introduction of error terms in the matrix, more Newton iteration steps and time iteration steps are required for iterative convergence. At the same time, with the development of CFD methods and the increasing improvement of CFD software functions, CFD is expanding in the direction of multi-physical processes, multi-scale flow structures, high resolution and high precision. The physical phenomena simulated by CFD are becoming more and more complex, and the corresponding grid size is also getting larger and larger, which leads to a sharp increase in computing requirements and an increasing demand for efficient numerical solution methods. Summary of the invention

[0004] The problem to be solved by the present invention is to improve the computational efficiency of computational fluid dynamics, and propose a mixed point implicit time advancement method based on residual value decomposition, an electronic device and a storage medium.

[0005] To achieve the above object, the present invention is implemented through the following technical solutions:

[0006] A mixed point implicit time marching method based on residual value decomposition includes the following steps:

[0007] S1. Generate a computational grid for a flow field simulation object and read computational grid information for the flow field simulation object;

[0008] S2. Establish the control equations under the finite volume method calculation framework to obtain a group of ordinary differential equations about time, and then perform time differentiation on the control equations based on the calculation grid obtained in step S1, and perform linear approximation processing to obtain implicit discretization of the control equations;

[0009] S3. The residual value term in the implicit discretization control equation is divided into a residual value average term and a residual value dissipation term. The point implicit method LU-SGS is used to solve the implicit discretization control equation. The residual value dissipation term in the first sweep process is saved. The number of sweeps is increased after the original number of sweeps. In the second sweep process, the residual value dissipation term calculated in the first sweep process is used for mixed calculation to complete the update of the flow field.

[0010] S4. Based on steps S1-S3, complete all time step iteration cycles of the flow field simulation object or reach convergence conditions to obtain the flow field simulation results.

[0011] Furthermore, the computational grid of the flow field simulation object in step S1 includes a one-dimensional grid, a two-dimensional grid and a three-dimensional grid.

[0012] Furthermore, the specific implementation method of step S2 includes the following steps:

[0013] S2.1. The control equation is established under the finite volume method calculation framework. The control equation is the Navier-Stokes equation in integral form, which is expressed in the integral form of vectors and matrices, and the conversion from volume integral to surface integral is completed by Gauss's theorem. The expression is:

[0014]

[0015] Where t is time, Ω is the control volume, is the boundary surface, is the vector area, is the conserved quantity, is the convection term, is a sticky item;

[0016] S2.2. Discretize the control equations obtained in step S2.1 in space and time respectively to obtain a set of ordinary differential equations about time, expressed as:

[0017]

[0018] in, is the residual value item;

[0019] They are composed of the residual value of the convection term and the residual value of the viscous term, respectively, and the expression is:

[0020]

[0021] The calculation methods of the convection term include the central format and the upwind format, and the upwind format includes ROE, AUSM, HLLC and VanLeer;

[0022] S2.3. Based on the computational grid obtained in step S1, perform time differentiation on the semi-discrete control equation in each computational grid, and take the residual term as t n+1 Step 1, the implicit time discrete control equation is obtained, which is expressed as:

[0023]

[0024] Where n is the number of iteration steps, n starts from 0, when n = 0, the flow field is initialized; is the conserved quantity from n iteration steps Conserved quantity to n+1 iterations The change in i is the grid number for flow field calculation. The residual term of the n+1th iteration step for the i-th flow field calculation grid;

[0025] S2.4. For the implicit time-discrete control equation obtained in step S3, the implicit discretized control equation is obtained, which is expressed as:

[0026]

[0027] in, is the discrete unit matrix of the flow field, and the terms in square brackets are implicit operator terms.

[0028] Furthermore, the specific implementation method of step S3 includes the following steps:

[0029] S3.1. The residual term in the implicit discretization control equation obtained in step S2 Decomposition into residual average terms and residual dissipation term Two terms, where the residual average term includes the average part of the convection term and the source term, and the residual dissipation term includes the artificial viscosity term of the convection term and the viscous flux viscosity term;

[0030] S3.2. Divide the implicit operator terms in the implicit discretization control equation obtained in step S2 into upper triangular matrices Diagonal Matrix Lower triangular matrix Add to the implicit operator term Item, the expression is:

[0031]

[0032] S3.3. The implicit discretization control equation obtained in step S3.2 is solved by using the point implicit method LU-SGS. Two sweeps are performed. Each sweep is divided into two steps: forward sweep and backward sweep. The expression of the forward sweep is:

[0033]

[0034] in, is the flow field change value obtained for each sweep, and δ represents the sweep order;

[0035] The expression for backward sweep is:

[0036]

[0037] S3.4. Perform the first sweep, record the residual dissipation term and complete the calculation;

[0038] S3.5. Perform the second sweep and use the residual dissipation term of the first sweep when calculating the residual value to complete the update of the flow field.

[0039] Furthermore, the upper triangular matrix in step S3.2 A set of neighboring grid cells including the current grid cell whose numbers are greater than the current grid cell number, which is composed of the difference between the inviscid flux Jacobian matrix and the viscous flux Jacobian matrix of each neighboring surface flux;

[0040] Diagonal Matrix Includes the ratio of the volume of the current grid to the time step, plus the sum of the spectral radius of the inviscid flux Jacobian matrix and the spectral radius of the viscous flux Jacobian matrix of the current grid;

[0041] Lower triangular matrix A set of neighboring mesh cells including the current mesh cell and having numbers smaller than the current mesh cell number is constructed as the sum of the inviscid flux Jacobian matrix and the viscous flux Jacobian matrix of each neighboring surface flux.

[0042] An electronic device comprises a memory and a processor, wherein the memory stores a computer program, and the processor implements the steps of a mixed point implicit time advancement method based on residual value decomposition when executing the computer program.

[0043] A computer-readable storage medium stores a computer program, which, when executed by a processor, implements a mixed point implicit time advancement method based on residual value decomposition.

[0044] Beneficial effects of the present invention:

[0045] The hybrid point implicit time marching method based on residual value decomposition described in the present invention decomposes the residual value terms in the implicit discrete equation, increases the number of sweeps in the point implicit LU-SGS solution process, uses the dissipative residual value terms calculated in the first sweep, simplifies the residual value calculation process of the second sweep, and greatly improves the convergence of implicit iterations while saving computing resources.

[0046] The hybrid point implicit time marching method based on residual decomposition described in the present invention is applicable to grids including but not limited to one-dimensional grids, two-dimensional grids and three-dimensional grids, including but not limited to structured grids and unstructured grids; the spatial discretization formats involved include but are not limited to AUSM-type, Roe, HLLC and other upwind formats and center formats, and are universal.

[0047] The mixed point implicit time marching method based on residual value decomposition described in the present invention has a small modification to the original LU-SGS algorithm, a simple principle and is easy to implement. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] Figure 1 It is a schematic diagram of the process of the present invention;

[0049] Figure 2 A schematic diagram of a numerical calculation grid for an application case of the present invention;

[0050] Figure 3 It is a schematic diagram of residual convergence curves calculated by the method of the present invention and the original method in the application case of the present invention;

[0051] Figure 4 This is a schematic diagram of the convergence curve of the lift coefficient calculated by the method of the present invention and the original method in the application case of the present invention. DETAILED DESCRIPTION

[0052] In order to make the purpose, technical solution and advantages of the present invention more clear, the present invention is further described in detail below in conjunction with the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention, that is, the specific embodiments described are only part of the embodiments of the present invention, rather than all of the specific embodiments. The components of the specific embodiments of the present invention described and shown in the drawings herein can be arranged and designed in various different configurations, and the present invention can also have other embodiments.

[0053] Therefore, the following detailed description of the specific embodiments of the present invention provided in the accompanying drawings is not intended to limit the scope of the invention claimed for protection, but merely represents the selected specific embodiments of the present invention. Based on the specific embodiments of the present invention, all other specific embodiments obtained by those skilled in the art without making creative work are within the scope of protection of the present invention.

[0054] In order to further understand the content, features and effects of the present invention, the following specific implementation methods are given as examples, and the attached Figure 1 -Attached Figure 4 The detailed instructions are as follows:

[0055] Embodiment 1:

[0056] A mixed point implicit time marching method based on residual value decomposition includes the following steps:

[0057] S1. Generate a computational grid for a flow field simulation object and read computational grid information for the flow field simulation object;

[0058] Furthermore, the computational grid of the flow field simulation object in step S1 includes a one-dimensional grid, a two-dimensional grid and a three-dimensional grid;

[0059] S2. Establish the control equations under the finite volume method calculation framework to obtain a group of ordinary differential equations about time, and then perform time differentiation on the control equations based on the calculation grid obtained in step S1, and perform linear approximation processing to obtain implicit discretization of the control equations;

[0060] Furthermore, the specific implementation method of step S2 includes the following steps:

[0061] S2.1. The control equation is established under the finite volume method calculation framework. The control equation is the Navier-Stokes equation in integral form, which is expressed in the integral form of vectors and matrices, and the conversion from volume integral to surface integral is completed by Gauss's theorem. The expression is:

[0062]

[0063] Where t is time, Ω is the control volume, is the boundary surface, is the vector area, is the conserved quantity, is the convection term, is a sticky item;

[0064] S2.2. Discretize the control equations obtained in step S2.1 in space and time respectively to obtain a set of ordinary differential equations about time, expressed as:

[0065]

[0066] in, is the residual value item;

[0067] They are composed of the residual value of the convection term and the residual value of the viscous term, respectively, and the expression is:

[0068]

[0069] The calculation methods of the convection term include the central format and the upwind format, and the upwind format includes ROE, AUSM, HLLC and VanLeer;

[0070] S2.3. Based on the computational grid obtained in step S1, perform time differentiation on the semi-discrete control equation in each computational grid, and take the residual term as t n+1 Step 1, the implicit time discrete control equation is obtained, which is expressed as:

[0071]

[0072] Where n is the number of iteration steps, n starts from 0, when n = 0, the flow field is initialized; is the conserved quantity from n iteration steps Conserved quantity to n+1 iterations The change in i is the grid number for flow field calculation. The residual term of the n+1th iteration step for the i-th flow field calculation grid;

[0073] S2.4. Perform linear approximation processing on the implicit time discrete control equation obtained in step S3 to obtain the implicit discretized control equation, which is expressed as:

[0074]

[0075] in, is the discrete unit matrix of the flow field, and the terms in square brackets are implicit operator terms.

[0076] Furthermore, linear approximation refers to The term is expanded using the first-order approximation. Since the equation represented by the residual term of the n+1th step will bring difficulties in numerical processing, that is, according to the time development sequence, when iterating in the nth step, the conservation quantity of the n+1th step has not yet been obtained, resulting in the conservation quantity of the n+1th step No further calculation is possible. At this point, the Taylor first-order expansion can be used to Do the following processing, that is, the linear approximation expression is:

[0077]

[0078] Among them, the flux Jacobian matrix Convective flux Jacobian matrix included and the viscous flux Jacobian matrix

[0079] S3. The residual value term in the implicit discretization control equation is divided into a residual value average term and a residual value dissipation term. The point implicit method LU-SGS is used to solve the implicit discretization control equation. The residual value dissipation term in the first sweep process is saved. The number of sweeps is increased after the original number of sweeps. In the second sweep process, the residual value dissipation term calculated in the first sweep process is used for mixed calculation to complete the update of the flow field.

[0080] Furthermore, the specific implementation method of step S3 includes the following steps:

[0081] S3.1. The residual term in the implicit discretization control equation obtained in step S2 Decomposition into residual average terms and residual dissipation term Two terms, where the residual average term includes the average part of the convection term and the source term, and the residual dissipation term includes the artificial viscosity term of the convection term and the viscous flux viscosity term;

[0082] S3.2. Divide the implicit operator terms in the implicit discretization control equation obtained in step S2 into upper triangular matrices Diagonal Matrix Lower triangular matrix Add to the implicit operator term Item, the expression is:

[0083]

[0084] Furthermore, in the LU-SGS algorithm, in order to ensure the convergence of the Gauss-Seidel iterative process, the coefficient matrix of the linear algebraic equations corresponding to the iterative algorithm should be guaranteed to be diagonally dominant. The flux Jacobian matrix is ​​divided into and in The eigenvalues ​​of the matrix are all non-negative, The eigenvalues ​​of the matrix are all non-positive. Usually, the matrix Defined as:

[0085]

[0086] in, is the Jacobian matrix of the convection flux, ω is the relaxation factor, which determines the dissipation of the implicit format, and thus affects the convergence of the format. The coefficient range is 1<ω≤2. A higher value will increase the robustness of LU-SGS but slow down the convergence. is the spectral radius of the convection Jacobian matrix, and in order to avoid explicit storage of the flux Jacobian matrix;

[0087] In the LU-SGS implicit scheme, the product can be approximated by calculating the change in the convective flux Introducing the Taylor series expansion of flux to replace the product The expression is:

[0088]

[0089] in, and are the inviscid fluxes at time n and time n+1 respectively;

[0090] In the subsequent calculation, the product of the upper and lower triangular matrices and the change in the conservation value is and The above approximate method was used.

[0091] Furthermore, the upper triangular matrix in step S3.2 A set of neighboring grid cells including the current grid cell whose numbers are greater than the current grid cell number, which is composed of the difference between the inviscid flux Jacobian matrix and the viscous flux Jacobian matrix of each neighboring surface flux;

[0092] For structured grids, the upper triangular matrix Defined as:

[0093]

[0094] Where i, j, k represent the node index in different directions, ΔS represents the area of ​​the unit surface, and I, J, K represent the direction in the computational space;

[0095] For unstructured grids, the upper triangular matrix Defined as:

[0096]

[0097] Among them, U(i) represents the collinear nodes of node i belonging to the upper triangular matrix, ΔS ij Represents the area of ​​the face associated with edge ij.

[0098] Diagonal Matrix Includes the ratio of the volume of the current grid to the time step, plus the sum of the spectral radius of the inviscid flux Jacobian matrix and the spectral radius of the viscous flux Jacobian matrix of the current grid;

[0099] For structured grids, the diagonal matrix Defined as:

[0100]

[0101] Among them, i, j, k represent the node index in different directions, ΔS represents the area of ​​the unit surface, I, J, K represent the direction in the calculation space, and Ω represents the unit volume. Represents the cell matrix.

[0102] For unstructured grids, the diagonal matrix Defined as:

[0103]

[0104] Among them, N F represents the number of faces of the unit control volume, represents the spectral radius of the convective flux, ΔS ij Represents the area of ​​the face associated with edge ij.

[0105] Lower triangular matrix A set of neighboring mesh cells including the current mesh cell and having numbers smaller than the current mesh cell number is constructed as the sum of the inviscid flux Jacobian matrix and the viscous flux Jacobian matrix of each neighboring surface flux.

[0106] For structured meshes, the lower triangular matrix Defined as:

[0107]

[0108] Where i, j, k represent the node index in different directions, ΔS represents the area of ​​the unit surface, and I, J, K represent the direction in the calculation space.

[0109] For unstructured grids, the lower triangular matrix Defined as:

[0110]

[0111] Where L(i) represents the collinear nodes of node i belonging to the lower triangular matrix, ΔS ij Represents the area of ​​the face associated with edge ij.

[0112] The inviscid flux Jacobian matrix refers to the matrix formed by the first-order partial derivatives of the inviscid flux with respect to each variable in the conserved quantity, and the viscous flux Jacobian matrix refers to the matrix formed by the first-order partial derivatives of the viscous flux with respect to each variable in the conserved quantity, which is usually approximated by the spectral radius.

[0113] S3.3. The implicit discretization control equation obtained in step S3.2 is solved by using the point implicit method LU-SGS. Two sweeps are performed. Each sweep is divided into two steps: forward sweep and backward sweep. The expression of the forward sweep is:

[0114]

[0115] in, is the flow field change value obtained for each sweep, and δ represents the sweep order;

[0116] The expression for backward sweep is:

[0117]

[0118] S3.4. Perform the first sweep, record the residual dissipation term and complete the calculation;

[0119] Furthermore, the first scanning process is as follows:

[0120] Scan forward:

[0121] Scan backward:

[0122] in, is the residual value average term calculated in the first sweep, is the residual dissipation term obtained by the first sweep calculation;

[0123] After the calculation is completed, we get And get the flow field update value

[0124] S3.5. Perform the second sweep and use the residual dissipation term of the first sweep when calculating the residual value to complete the update of the flow field.

[0125] Furthermore, the second scanning process is as follows:

[0126] Scan forward:

[0127] Scan backward:

[0128] in, is the average residual value calculated in the second sweep, is the residual dissipation term obtained by the first sweep calculation. After the calculation is completed, we get And get the flow field update value

[0129] S4. Based on steps S1-S3, complete all time step iteration cycles of the flow field simulation object or reach convergence conditions to obtain the flow field simulation results.

[0130] Furthermore, the time step refers to the number of cycles specified manually during the numerical simulation of the flow field. The iteration stops when the maximum value of the cycle is met. Convergence refers to the relative value of the residual change within a time step being less than the specified numerical precision, which is a convergence judgment method involved in various explicit and implicit time iteration algorithms.

[0131] Application effect example description:

[0132] The application effect of the present invention is illustrated by taking the transonic numerical simulation of the RAE2822 airfoil as an example. The present invention can be used in this working condition, but is not limited to this working condition.

[0133] Calculation conditions: RAE2822 airfoil standard model, Mach number 0.734, Reynolds number Re = 6500000, temperature T = 288.15K, angle of attack 2.79°, calculation grid type is quadrilateral grid, number of grid elements is 59598, the grid diagram is as follows Figure 2 As shown, the turbulence model adopts the kw-SST two-equation model.

[0134] Figure 3 The figure shows the residual value convergence curve comparison between the LU-SGS method of the present invention and the original LU-SGS method. In the figure, the horizontal axis is the number of iteration steps, and the calculation stops at 10,000 steps this time, and the vertical axis is the residual value of the mass flow field. It can be seen from the figure that under the same working conditions (maintaining the same grid, Mach number, Reynolds number, etc.), the LU-SGS convergence curve of the present invention is about 1 order of magnitude lower than the residual value of the original LU-SGS, and the residual value curve is relatively stable.

[0135] Figure 4 The figure shows the lift coefficient convergence curve comparison between the LU-SGS method of the present invention and the original LU-SGS method. The horizontal axis is the number of iterations, and the vertical axis is the lift coefficient curve. It can be seen from the figure that the original LU-SGS method converges at about 2800 iterations, while the LU-SGS of the present invention converges at about 2200 iterations. The convergence of the calculation is significantly improved when the present invention is used.

[0136] Embodiment 2:

[0137] An electronic device includes a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the steps of a mixed point implicit time advancement method based on residual value decomposition as described in any one of Embodiment 1 are implemented.

[0138] The computer device of the present invention may be a device including a processor and a memory, such as a single chip microcomputer including a central processing unit, etc. Moreover, the processor is used to implement the steps of the above-mentioned mixed point implicit time advancement method based on residual value decomposition when executing the computer program stored in the memory.

[0139] The processor may be a central processing unit (CPU), other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor, etc.

[0140] The memory may mainly include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application required for at least one function (such as a sound playback function, an image playback function, etc.), etc.; the data storage area may store data created according to the use of the mobile phone (such as audio data, a phone book, etc.), etc. In addition, the memory may include a high-speed random access memory, and may also include a non-volatile memory, such as a hard disk, a memory, a plug-in hard disk, a smart memory card (Smart Media Card, SMC), a secure digital (Secure Digital, SD) card, a flash card (Flash Card), at least one disk storage device, a flash memory device, or other volatile solid-state storage devices.

[0141] Embodiment 3:

[0142] A computer-readable storage medium stores a computer program, which, when executed by a processor, implements a mixed point implicit time advancement method based on residual value decomposition as described in Example 1.

[0143] The computer-readable storage medium of the present invention can be any form of storage medium that can be read by a processor of a computer device, including but not limited to non-volatile memory, volatile memory, ferroelectric memory, etc. A computer program is stored on the computer-readable storage medium. When the processor of the computer device reads and executes the computer program stored in the memory, the steps of the above-mentioned mixed point implicit time advancement method based on residual value decomposition can be implemented.

[0144] The computer program includes computer program code, which may be in source code form, object code form, executable file or some intermediate form, etc. The computer readable medium may include: any entity or device capable of carrying the computer program code, recording medium, USB flash drive, mobile hard disk, magnetic disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electric carrier signal, telecommunication signal and software distribution medium, etc.

[0145] It should be noted that relational terms such as "first" and "second" are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the sentence "comprise a ..." do not exclude the existence of other identical elements in the process, method, article or device including the elements.

[0146] Although the present application has been described above with reference to specific embodiments, various modifications may be made thereto and parts thereof may be replaced with equivalents without departing from the scope of the present application. In particular, as long as there is no structural conflict, the various features in the specific embodiments disclosed in the present application may be used in combination with each other in any manner, and the fact that these combinations are not exhaustively described in this specification is only for the sake of omitting space and saving resources. Therefore, the present application is not limited to the specific embodiments disclosed herein, but includes all technical solutions falling within the scope of the claims.

Claims

1. A hybrid point implicit time marching method based on residual value decomposition, characterized in that: The steps include: S1. Generate a computational grid for a flow field simulation object and read computational grid information for the flow field simulation object; S2. Establish the control equations under the finite volume method calculation framework to obtain a group of ordinary differential equations about time, and then perform time differentiation on the control equations based on the calculation grid obtained in step S1, and perform linear approximation processing to obtain implicit discretization of the control equations; S3. The residual value term in the implicit discretization control equation is divided into a residual value average term and a residual value dissipation term. The point implicit method LU-SGS is used to solve the implicit discretization control equation. The residual value dissipation term in the first sweep process is saved. The number of sweeps is increased after the original number of sweeps. In the second sweep process, the residual value dissipation term calculated in the first sweep process is used for mixed calculation to complete the update of the flow field. S4. Based on steps S1-S3, complete all time step iteration cycles of the flow field simulation object or reach convergence conditions to obtain the flow field simulation results.

2. A mixed point implicit time marching method based on residual value decomposition according to claim 1, characterized in that: The computational grids of the flow field simulation object in step S1 include a one-dimensional grid, a two-dimensional grid and a three-dimensional grid.

3. A hybrid point implicit time advancement method based on residual value decomposition according to claim 1 or 2, characterized in that: The specific implementation method of step S2 includes the following steps: S2.

1. The control equation is established under the finite volume method calculation framework. The control equation is the Navier-Stokes equation in integral form, which is expressed in the integral form of vectors and matrices, and the conversion from volume integral to surface integral is completed by Gauss's theorem. The expression is: Where t is time, Ω is the control volume, is the boundary surface, is the vector area, is the conserved quantity, is the convection term, is a sticky item; S2.

2. Discretize the control equations obtained in step S2.1 in space and time respectively to obtain a set of ordinary differential equations about time, expressed as: in, is the residual value item; They are composed of the residual value of the convection term and the residual value of the viscous term, respectively, and the expression is: The calculation methods of the convection term include the central format and the upwind format, and the upwind format includes ROE, AUSM, HLLC and VanLeer; S2.

3. Based on the computational grid obtained in step S1, perform time differentiation on the semi-discrete control equation in each computational grid, and take the residual term as t n+1 Step 1, the implicit time discrete control equation is obtained, which is expressed as: Where n is the number of iteration steps, n starts from 0, when n = 0, the flow field is initialized; is the conserved quantity from n iteration steps Conserved quantity to n+1 iterations The change in i is the grid number for flow field calculation. The residual term of the n+1th iteration step for the i-th flow field calculation grid; S2.

4. Perform linear approximation processing on the implicit time discrete control equation obtained in step S3 to obtain the implicit discretized control equation, which is expressed as: in, is the discrete unit matrix of the flow field, and the terms in square brackets are implicit operator terms.

4. The hybrid point implicit time advancement method based on residual value decomposition according to claim 3, characterized in that: The specific implementation method of step S3 includes the following steps: S3.

1. The residual term in the implicit discretization control equation obtained in step S2 Decomposition into residual average terms and residual dissipation term Two terms, where the residual average term includes the average part of the convection term and the source term, and the residual dissipation term includes the artificial viscosity term of the convection term and the viscous flux viscosity term; S3.

2. Divide the implicit operator terms in the implicit discretization control equation obtained in step S2 into upper triangular matrices Diagonal Matrix Lower triangular matrix Add to the implicit operator term Item, the expression is: S3.

3. The implicit discretization control equation obtained in step S3.2 is solved by using the point implicit method LU-SGS. Two sweeps are performed. Each sweep is divided into two steps: forward sweep and backward sweep. The expression of the forward sweep is: in, is the flow field change value obtained for each sweep, and δ represents the sweep order; The expression for backward sweep is: S3.

4. Perform the first sweep, record the residual dissipation term and complete the calculation; S3.

5. Perform the second sweep and use the residual dissipation term of the first sweep when calculating the residual value to complete the update of the flow field.

5. The hybrid point implicit time advancement method based on residual value decomposition according to claim 4, characterized in that: The upper triangular matrix in step S3.2 A set of neighboring grid cells including the current grid cell whose numbers are greater than the current grid cell number, which is composed of the difference between the inviscid flux Jacobian matrix and the viscous flux Jacobian matrix of each neighboring surface flux; Diagonal Matrix Includes the ratio of the volume of the current grid to the time step, plus the sum of the spectral radius of the inviscid flux Jacobian matrix and the spectral radius of the viscous flux Jacobian matrix of the current grid; Lower triangular matrix A set of neighboring mesh cells including the current mesh cell and having numbers smaller than the current mesh cell number is constructed as the sum of the inviscid flux Jacobian matrix and the viscous flux Jacobian matrix of each neighboring surface flux.

6. An electronic device, characterized in that: It comprises a memory and a processor, the memory stores a computer program, and the processor implements the steps of a mixed point implicit time advancement method based on residual value decomposition as described in any one of claims 1 to 5 when executing the computer program.

7. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the mixed point implicit time advancement method based on residual value decomposition as described in any one of claims 1 to 5 is implemented.

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