Method for simulating flow field near complex wall surface at high precision

Abstract

The invention discloses a method for high-precision simulation of a flow field near a complex wall surface, and relates to the field of computational fluid mechanics. In order to solve the problem of low simulation precision of a flow field near an existing wall surface, the method comprises the following steps: dispersing the flow field and a wall surface structure into right-angle grids; the method comprises the following steps: determining a reference point of a virtual point in a flow field in a virtual unit in a right-angle grid, constructing six interpolation template points around the reference point, constructing a local coordinate system, determining flow field information and gradient information of the reference point, calculating a high-order reconstruction model of the virtual point in combination with boundary conditions at a wall surface, and finally obtaining a high-order reconstruction value of the virtual point. And performing high-order reconstruction on the virtual unit to realize simulation of the flow field near the complex wall surface. According to the method, interpolation template points are selected compactly and robustly, so that the solving precision of the flow field near the complex motion boundary is effectively ensured, different boundary conditions can be expanded at the same time, and high-precision simulation of the flow field near the complex wall surface is realized.

Description

Technical Field

[0001] This invention belongs to the field of computational fluid dynamics, specifically relating to a method for high-precision simulation of flow fields near complex walls. Background Technology

[0002] In problems involving fluid-complex structure interactions, accurately applying boundary conditions at the solid-liquid interface significantly impacts the accuracy and stability of numerical methods. Commonly used body-fitted meshes adapt to the object surface by altering the mesh topology, with boundary conditions applied directly to the surface. However, as the complexity of the structure increases, generating high-quality structured meshes using unstructured body-fitted mesh methods becomes increasingly difficult. Furthermore, high-precision methods using unstructured meshes are computationally intensive and not easily generalized to 3D applications.

[0003] Unlike body-fitted meshes, the Immersed Boundary Method (IBM) simulates complex structures on rectangular meshes. The mesh topology of this method is non-conformal to the object's boundary, avoiding the complex generation process of body-fitted meshes. At the same time, rectangular meshes facilitate the implementation of high-precision numerical methods and large-scale parallel computing. Combined with adaptive mesh refinement methods, IBM can provide refined solutions to flow fields near complex walls.

[0004] A key problem IBM needs to solve is how to apply boundary conditions to complex surfaces. Based on the method of boundary condition application, IBM mainly divides it into two categories: the Continuous Forcing Approach and the Discrete Forcing Approach. The Continuous Forcing Approach introduces boundary forces as source terms into the governing equations to simulate the influence of the boundary on the fluid. The Continuous Forcing Approach is simple to implement and unaffected by the discretization scheme; however, it suffers from mass non-conservation at the boundary, and general boundary conditions are difficult to apply. The Discrete Forcing Approach applies boundary conditions by modifying the discrete governing equations at the surface. The Discrete Forcing Approach mainly includes two types: the Cut-Cell Method and the Ghost-Cell Method. The Cut-Cell Method reconstructs the mesh at the boundary based on the surface shape, making it better fit the local surface shape and ensuring the sharpness of the surface. This method can strictly satisfy the conservation laws; however, the mesh reconstruction process is complex and not conducive to 3D expansion. The Ghost-Cell Method constructs a virtual mesh inside the surface, completes the interpolation template at the surface, and applies boundary conditions using the values ​​of the virtual elements. This method is simple to implement, requires no modification to the governing equations, and is easy to apply with high-precision calculation methods.

[0005] However, the calculation process of the virtual mesh in the virtual element method has a significant impact on the computational accuracy and numerical stability. Common virtual mesh calculation methods assume linear fluid variation at the boundary: first, the mirror image of the virtual mesh with respect to the object surface is determined within the fluid domain; then, the mirror image is interpolated using fluid points surrounding it; finally, the virtual mesh is calculated using boundary condition information and the mirror image. The values ​​of the mirror image are typically calculated using bilinear / trilinear interpolation or inverse distance weighted interpolation. However, when the virtual mesh is close to the object surface boundary, not all interpolation points required to reconstruct the mirror image are within the fluid domain, which reduces the computational accuracy of the mirror image. To address this issue, common methods include using the intersection of the mesh and the object surface as supplementary interpolation points, or extending the mirror image outward along the wall normal direction to ensure that all required interpolation points are within the fluid domain. For Dirichlet-type boundary conditions, a second-order accurate virtual mesh reconstruction value can be obtained using a single mirror image and boundary condition information. However, for Neumann-type boundary conditions, a single mirror image can only yield a first-order accurate virtual mesh reconstruction value, thus affecting the accuracy of the flow field calculation near the boundary.

[0006] To improve the computational accuracy near complex walls and achieve refined calculation of flow field structures near complex boundaries, it is necessary to develop high-precision and robust virtual element interpolation methods. Therefore, it is urgent to design a high-precision method for simulating flow fields near complex walls to solve the above problems. Summary of the Invention

[0007] To address the shortcomings of existing technologies, this invention provides a method for high-precision simulation of flow fields near complex walls. This method first discretizes the flow field and wall structure into a rectangular grid. Within the rectangular grid, a reference point is determined for each virtual point within a virtual cell in the flow field. Then, a reference point is constructed based on this reference point M. The surrounding 6 interpolation template points; based on the reference point Based on the spatial distribution characteristics of the surrounding 6 interpolation template points, a local coordinate system is constructed, and a reference point is determined. The flow field information and gradient information are obtained using the reference point. Calculate virtual points based on flow field information, gradient information, and boundary conditions at the wall. coefficient of flow field flux , and Based on coefficients , and Obtain virtual points The higher-order reconstruction value is used to reconstruct the virtual unit, thereby achieving high-precision simulation of the flow field near the complex wall.

[0008] The method of this invention makes the selection of template points compact and robust, effectively ensuring the solution accuracy of the flow field near complex motion boundaries, and can be extended to different boundary conditions, thereby accurately simulating solid-liquid operation.

[0009] To achieve the above objectives, the technical solution adopted by the present invention is as follows: A method for high-precision simulation of flow fields near complex walls, the method comprising: The flow field and wall structure are discretized into rectangular grids, with virtual cells between the flow field and the wall. Determine virtual points in virtual cells Reference point in the flow field ; According to reference point Construct reference points The surrounding 6 interpolation template points; According to reference point Based on the spatial distribution characteristics of the surrounding 6 interpolation template points, a local coordinate system is constructed, and a reference point is determined. Flow field information and gradient information; Using reference points Based on the flow field information, gradient information, and boundary conditions at the wall, a high-order reconstruction model of the virtual point g is constructed. Using virtual points The high-order reconstruction model is used to reconstruct the virtual unit in a high-order manner, thereby simulating the flow field near the complex wall.

[0010] Preferably, the reference point in the flow field is determined in a rectangular grid. The process includes: Passing through virtual points Draw a perpendicular line to the wall boundary, and determine the virtual point with the wall boundary as the axis of symmetry. The corresponding mirror point within the flow field ; Determine the mirror point The four grids that exist around the perimeter Is it a fluid mesh? Yes, mirror point Then it is the reference point M; No, then the virtual point Extend the grid diagonal along the direction of the wall's outward normal and set that location as the reference point. .

[0011] Preferably, a reference point is constructed below the stationary wall. The process for the surrounding 6 interpolation template points includes: Reference point The four nearest fluid points were determined as the first four interpolation template points. ; In a right-angled grid Direction determination and interpolation template point Adjacent fluid mesh interpolation template points , put template point Center and reference point The nearest fluid mesh interpolation template point is used as the 5th template point; In a right-angled grid Direction determination and Adjacent fluid mesh interpolation template points , put template point Center and reference point The nearest fluid mesh interpolation template point is used as the 6th template point.

[0012] Preferably, below the moving wall, the reference point The methods for the surrounding 6 interpolation template points include: Along in the right-angled grid Direction, distance from reference point Recent interpolation template point and These are the first two interpolation template points; along Direction, distance from reference point Recent interpolation template point and For the third and fourth interpolation template points; With interpolation template points x-coordinate and interpolation template point The ordinate determines the interpolation template point. This is the fifth interpolation template point; With interpolation template points x-coordinate and interpolation template point The ordinate determines the interpolation template point. interpolation template points x-coordinate and interpolation template point The ordinate determines the interpolation template point. At the interpolation template point and interpolation template points The point closest to the reference point M is selected as the sixth interpolation template point.

[0013] Preferably, a reference point is obtained. Methods for obtaining flow field information include: Based on reference point Calculate the coordinates of the 6 interpolation template points. Point flow flux value; according to By using the point flow flux values ​​and higher-order polynomials, the coefficients of the flow flux in the region covered by the template formed by the six interpolation template points are obtained. ; Based on coefficients and reference points You can reach the reference point by using the coordinates. The flow field information.

[0014] Preferably, a reference point is obtained. Gradient information methods include: according to Point coordinates and virtual points Calculate the normal vector at the wall using coordinates; Based on the normal vector at the wall, find the directional derivative of the higher-order polynomial along the wall normal direction; Will Substituting the point coordinates into the directional derivative, we get Point gradient information.

[0015] Preferably, using a reference point Based on the flow field information, gradient information, and boundary conditions at the wall, the specific steps for constructing a high-order reconstruction model of the virtual point g include the following:

[0016] Based on the quadratic polynomial, the model parameters of the higher-order reconstruction model from point M to the wall are determined; Based on the model parameters of the high-order reconstruction model from point M to the wall, virtual points are established. A higher-order reconstruction model.

[0017] Preferably, the higher-order reconstruction model from point M to the wall is: P2(r n )=a2 r n 2 + a1 r n +a0; in, Let a0, a1, and a2 be the distances from any point in the flow field to the wall, and let a0, a1, and a2 be the model parameters.

[0018] Preferably, the higher-order reconstruction model from point M to the wall Model parameters , and The solution method is as follows: in, For reference point The higher-order reconstruction value, For reference point The derivative of the higher-order reconstructed value along the wall normal direction, , , These are different constants.

[0019] Preferably, virtual points The higher-order reconstruction model is represented as: P2(r g )=a2 r g 2 - a1 r g +a0; in, For virtual points The higher-order reconstruction value, For virtual points Distance to the wall boundary.

[0020] The beneficial effects of this invention are: This invention discloses a method for high-precision simulation of flow fields near complex walls. Compared with the prior art, the improvement of this invention lies in: For static complex walls, this invention compares all possible interpolation template points based on the position of the virtual point in the flow field reference point, and determines multiple interpolation template points of the reference point under the standard of a certain distance from the reference point. Therefore, the selection of interpolation template points in this invention is more compact, flexible and robust. For moving complex walls, after the wall boundary moves, there are no fluid variables on the newly formed fluid points corresponding to it, which leads to the inability to calculate new fluid points under moving complex walls. This invention proposes an interpolation method for new fluid points under moving complex walls. Under static boundaries, the method of determining multiple interpolation template points of the reference point of the new fluid point is optimized to obtain higher-order reconstructed values ​​of the new fluid points, achieving high-precision interpolation. This enables high-precision solution of the flow field at the boundary of moving complex walls, effectively improving the calculation accuracy of the flow field near complex boundaries, thereby achieving high-precision simulation of the flow field near complex walls and accurately simulating solid-liquid motion. Attached Figure Description

[0021] Figure 1 This is a schematic diagram of the template point for the mirror point interpolation method of the present invention; Figure 2 This is a schematic diagram of template points for the current high-precision interpolation method of the present invention; Figure 3 This is a schematic diagram of one of the interpolation template point combination schemes of the present invention; Figure 4 This is a schematic diagram of the second interpolation template point combination scheme of the present invention; Figure 5 This is a schematic diagram of the interpolation template for the new fluid during wall movement according to the present invention; Figure 6 This is a schematic diagram of a combination scheme for interpolation template points of new fluid during wall movement according to the present invention; Figure 7This is a schematic diagram of the second combination scheme of new fluid interpolation template points when the wall moves according to the present invention. Detailed Implementation

[0022] To enable those skilled in the art to better understand the technical solutions of the present invention, the technical solutions of the present invention will be further described below in conjunction with the accompanying drawings and embodiments. The following embodiments are used to illustrate the present invention, but should not be used to limit the scope of the present invention.

[0023] Example 1: See attached document Figures 1-7 The method shown is a high-precision simulation method for flow fields near complex walls, the method comprising: Step 1: Discretize the flow field and wall structure into a rectangular grid, with virtual cells between the fluid and the wall; By using the immersion boundary method, the flow field and wall structure are discretized into rectangular grids, with the flow field and wall being set as virtual elements and the wall being set as solid elements.

[0024] Step 2: Determine the virtual points in the virtual unit Reference point in the flow field ; Specifically, based on the virtual points in the virtual unit (virtual point) Multiple virtual points are labeled as follows: 1、 2... n (where n represents the number of virtual points), the reference point in the flow field is determined along the normal direction of the wall. and based on reference points Construct a local coordinate system.

[0025] Reference point The method for determining it is as follows: According to the requirements of the interpolation format, the number of virtual cells in the rectangular grid is determined. If one virtual cell is required, the grid adjacent to the fluid region in the solid cell is marked as a virtual cell. If two grids are required, the two grids adjacent to the fluid region in the solid cell are marked as virtual cells. In this embodiment, one virtual cell is used.

[0026] Passing through virtual points Draw a perpendicular line to the wall boundary, and determine the virtual point with the wall boundary as the axis of symmetry. The corresponding mirror point within the flow field For example, attached Figure 1 As shown, the determination of virtual points is given. 1 and Mirror point of 2 Legend of the diagram.

[0027] Mirror point Once the location is determined, the mirror point There are four grids around it. (In three dimensions, there are 8 grids; this application uses two dimensions.) Determine Are they all fluid meshes? Yes, mirror the point. Set as reference point M; no; virtual points Extend the grid diagonal along the direction of the wall's outward normal and set that location as the reference point. ,like Figure 2 As shown; Step 3: Based on the reference point Construct reference points The surrounding 6 interpolation template points; specifically: S301. Reference point The four nearest fluid points were determined as the first four interpolation template points. , Figure 2 As shown.

[0028] S302. In a right-angled grid Direction determination and interpolation template point Adjacent fluid mesh interpolation template points ,like Figure 2 , put template point Center and reference point The nearest fluid mesh interpolation template point is used as the 5th template point.

[0029] S303. In a right-angled grid Direction determination and Adjacent fluid mesh interpolation template points , put template point Center and reference point The nearest fluid mesh interpolation template point is used as the 6th template point.

[0030] The six final interpolation template points are attached. Figure 3 Or attached Figure 4 As shown, two possible combinations of template points are given, which always satisfy the following condition: A straight line contains One interpolation template point, It is a constant, such as Figure 3 and Figure 4 As shown, two possible combinations of template points are given.

[0031] Step 4: Based on the reference point Based on the spatial distribution characteristics of the surrounding 6 interpolation template points, a local coordinate system is constructed, and a reference point is determined. The flow field information and gradient information.

[0032] S401. Confirm Examination Center The coordinates of the six surrounding interpolation template points.

[0033] by Figure 3 Taking the template point as an example, If the point is set to (0,0), then The coordinates of the location are ( ,0), The coordinates of the location are ( ,0), The coordinates of the location are (0, ), The coordinates of the location are (0, ), The coordinates of the location are ( , ).

[0034] S402. Based on test points Calculate the coordinates of the surrounding 6 interpolation template points. Point flow flux value. The formula for calculating the flux value of a point flow field is: (1) in, , , , , as well as These are constant coefficients with different values. The x-axis is... The vertical axis represents the constant coefficients, which are calculated based on the coordinates of the template point and its corresponding flux.

[0035] S403. Will Substituting the point flow flux value into the higher-order polynomial yields the coefficients of the flow flux in the region covered by the template formed by the six interpolation template points. .

[0036] The higher-order polynomial is: (2) in, For coefficients, for The i-th power of the axis coordinates, for The coordinates are raised to the power of j, where i, j, and k are constants, and 0 ≤ i + j ≤ k.

[0037] S404. Based on coefficients and reference points coordinates You can reach the reference point immediately. Flow field information .

[0038] S405. For higher-order polynomials Find the directional derivative along the normal direction of the wall, and combine it with... Point coordinates, obtain Point gradient information.

[0039] 1) According to Point coordinates and virtual points Calculate the normal vector at the wall using coordinates: (3) In the formula, for The x-coordinate of the point for The x-coordinate of the point for The ordinate of the point, for The ordinate of the point.

[0040] 2) Based on formula (3), for higher-order polynomials Taking the directional derivative along the wall normal direction yields the higher-order polynomial. Directional derivative along the normal direction of the wall: ; (4) in, Let be the distance from the midpoint of the flow field to the wall.

[0041] 3) Substituting the point coordinates into formula (4) will yield the result. Point gradient information.

[0042] Step 5: Using reference points Based on the flow field information, gradient information, and boundary conditions at the wall, virtual points are constructed. A higher-order reconstruction model.

[0043] S501. Based on the quadratic polynomial, establish a high-order reconstruction model from point M to the wall. : P2(r n )=a2 r n 2 + a1 r n +a0 (5) in, , , For model parameters, Let be the distance from any point in the flow field to the wall.

[0044] S502. Based on reference point Based on the flow field information, gradient information, and boundary conditions at the wall, a high-order reconstruction model from point M to the wall is constructed. Solve the equations to determine the model parameters a0, a1, and a2 of the higher-order reconstruction model from point M to the wall.

[0045] Taking the derivative of formula (5) yields the derivative along the normal direction of the wall; (6) in, This is the derivative along the normal direction of the wall.

[0046] when When =0, the boundary conditions applied at the wall can be expressed as: (7) in, , indicating the wall surface , , For different constants, / Let q be the directional derivative, and q be any flow field variable.

[0047] In formula (7), by adjusting , and The value of is used to obtain the boundary conditions applied at the wall, thus enabling the application of different boundary conditions at the wall, for example... , , indicating Dirichlet type boundary conditions, , , representing Neumann-type boundary conditions, while , , indicating Robin-type boundary conditions.

[0048] exist In this case, combined with reference points Based on the flow field information and gradient information, we construct a system of equations by simultaneously applying equations (4), (5), and (6): (8) in, For reference point The higher-order reconstruction value, For reference point The derivative of the higher-order reconstructed value along the wall normal direction, , , These are different constants. The coefficients a0, a1 and a2 can be obtained through formula (8).

[0049] S503: Based on the model parameters of the high-order reconstruction model from point M to the wall, establish virtual points. Higher-order reconstruction model; virtual points The higher-order reconstruction model at the location is represented as:

[0050] in, For virtual points The higher-order reconstruction value; For virtual points Distance to the wall boundary.

[0051] Step 6: Utilize virtual points The high-order reconstruction model is used to reconstruct the virtual unit in a high-order manner, thereby simulating the flow field near the complex wall.

[0052] Specifically, virtual points Substitute the distance from the wall boundary The calculation formula yields virtual points. The higher-order reconstruction value can then be used to perform higher-order reconstruction on the virtual unit, thereby achieving high-precision calculation of the virtual unit.

[0053] Using virtual points quadratic polynomial This ensures that the interpolation accuracy at the static wall boundary is at least second-order, thus achieving high-precision reconstruction of virtual units. This effectively improves the reconstruction accuracy of the flow field near complex boundaries, enabling high-precision simulation of the interaction between fluids and complex walls. It can be used to optimize heat dissipation design, verify engineering solutions, and improve product performance. Specifically, by analyzing the temperature and flow field distribution, overheated areas can be identified and heat dissipation solutions (such as air duct layout and cooling system design) optimized to prevent equipment damage due to high temperatures; the flow resistance of components such as heat exchangers and fans can be evaluated to optimize heat transfer efficiency and reduce energy consumption. For example, adjusting fan parameters can match the system resistance characteristics, achieving efficient and low-noise operation. In complex structures such as power compartments and engine rooms, flow field values ​​can verify whether airflow smoothly reaches critical parts, reducing backflow and short-circuit problems.

[0054] Example 2: Example 1 provides a method for high-precision simulation of the flow field near a complex wall under static conditions. This example, however, provides a method for high-precision simulation of the flow field near a complex wall under moving conditions. The difference between the high-fidelity interpolation method in this example and the high-fidelity interpolation method under static conditions in Example 1 lies only in the new fluid point under moving conditions. The method for determining the six interpolation template points of the reference point M differs from the following steps, which involve establishing the subsequent local coordinate system and reference point based on the six interpolation template points of the reference point M. The flow field information and gradient information are ultimately used as a reference point. Based on the flow field information, gradient information, and boundary conditions at the wall, new fluid points are determined. The process of reconstructing the higher-order values ​​and performing higher-order reconstruction on the virtual units to simulate the flow field near the complex wall is the same, and will not be described in detail here.

[0055] Determining new fluid points under moving complex walls The method for determining the 6 interpolation template points of the reference point M is as follows: when the wall moves, a newly generated fluid mesh appears in the computational domain, resulting in new fluid points. ,like Figure 5-7 As shown, to improve numerical stability and accuracy, this invention proposes to construct a high-precision interpolation method that includes boundary condition information to calculate new fluid points. ,like Figure 5 As shown, new fluid point Starting from the wall, extend along the wall's normal direction by one grid diagonal length. Determine its extended reference point M using a higher-order polynomial. Reconstruct the reference point M. Along... Direction, closest to reference point M and For the first two template points, along Direction, distance, distance reference point Recent and For the third and fourth template points, x-coordinate and Determine the ordinate For the fifth template point, with point x-coordinate and point Determine the ordinate Use a little x-coordinate and point Determine the point by its ordinate At point and Select the point closest to reference point M as the sixth template point. Figure 6-7This illustrates two possible combinations of interpolation template points. After the six template points of the interpolation template are determined, new fluid points are calculated through steps S3-S6. The reconstructed value, calculation process and calculation of virtual points The reconstructed values ​​are the same, so I will not repeat them again.

[0056] new fluid point The formula for calculating the reconstructed value is:

[0057] in, For new fluid points Distance to the boundary point For new fluid points The reconstructed value.

[0058] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The embodiments and descriptions in the specification are merely illustrative of the principles of the invention. Various changes and modifications can be made to the invention without departing from its spirit and scope, and all such changes and modifications fall within the scope of the present invention as claimed. The scope of protection of this invention is defined by the appended claims and their equivalents.

Claims

1. A method for high-precision simulation of flow fields near complex walls, characterized in that, The method includes: The flow field and wall structure are discretized into rectangular grids, with virtual cells between the flow field and the wall. Determine virtual points in virtual cells Reference point in the flow field ; According to reference point Construct reference points The surrounding 6 interpolation template points; According to reference point Based on the spatial distribution characteristics of the surrounding 6 interpolation template points, a local coordinate system is constructed, and a reference point is determined. Flow field information and gradient information; Using reference points Based on the flow field information, gradient information, and boundary conditions at the wall, virtual points are constructed. Higher-order reconstruction model; Using virtual points The high-order reconstruction model is used to reconstruct the virtual unit in a high-order manner, thereby simulating the flow field near the complex wall.

2. The method for high-precision simulation of flow fields near complex walls according to claim 1, characterized in that, Determine the reference point in the flow field within a rectangular grid. The process includes: Passing through virtual points Draw a perpendicular line to the wall boundary, and determine the virtual point with the wall boundary as the axis of symmetry. The corresponding mirror point within the flow field ; Determine the mirror point The four grids that exist around the perimeter Is it a fluid mesh? Yes, mirror point Then it is the reference point M; No, then the virtual point Extend the grid diagonal along the direction of the wall's outward normal and set that location as the reference point. .

3. The method for high-precision simulation of flow fields near complex walls according to claim 2, characterized in that, Construction reference point under static wall surface The process for the surrounding 6 interpolation template points includes: Reference point The four nearest fluid points were determined as the first four interpolation template points. ; In a right-angled grid Direction determination and interpolation template point Adjacent fluid mesh interpolation template points , put template point Center and reference point The nearest fluid mesh interpolation template point is used as the 5th template point; In a right-angled grid Direction determination and Adjacent fluid mesh interpolation template points , put template point Center and reference point The nearest fluid mesh interpolation template point is used as the 6th template point.

4. The method for high-precision simulation of flow fields near complex walls according to claim 3, characterized in that, Reference point under moving wall The methods for the surrounding 6 interpolation template points include: Along in the right-angled grid Direction, distance from reference point Recent interpolation template point and These are the first two interpolation template points; along Direction, distance from reference point Recent interpolation template point and For the third and fourth interpolation template points; With interpolation template points x-coordinate and interpolation template point The ordinate determines the interpolation template point. This is the fifth interpolation template point; With interpolation template points x-coordinate and interpolation template point The ordinate determines the interpolation template point. interpolation template points x-coordinate and interpolation template point The ordinate determines the interpolation template point. At the interpolation template point and interpolation template points The point closest to the reference point M is selected as the sixth interpolation template point.

5. A method for high-precision simulation of flow fields near complex walls according to claim 3 or 4, characterized in that, Get reference point Methods for obtaining flow field information include: Based on reference point Calculate the coordinates of the 6 interpolation template points. Point flow flux value; according to By using the point flow flux values ​​and higher-order polynomials, the coefficients of the flow flux in the region covered by the template formed by the six interpolation template points are obtained. ; Based on coefficients and reference points You can reach the reference point by using the coordinates. Flow field information.

6. The method for high-precision simulation of flow fields near complex walls according to claim 5, characterized in that, Get reference point Gradient information methods include: according to Point coordinates and virtual points Calculate the normal vector at the wall using coordinates; Based on the normal vector at the wall, find the directional derivative of the higher-order polynomial along the wall normal direction; Will Substituting the point coordinates into the directional derivative, we get Point gradient information.

7. The method for high-precision simulation of flow fields near complex walls according to claim 6, characterized in that, Using reference points Based on the flow field information, gradient information, and boundary conditions at the wall, the specific steps for constructing a high-order reconstruction model of the virtual point g include the following: Based on the quadratic polynomial, a high-order reconstruction model from point M to the wall is established. Based on reference point Based on the flow field information, gradient information, and boundary conditions at the wall, the higher-order reconstruction model from point M to the wall is solved to determine the model parameters of the higher-order reconstruction model from point M to the wall. Based on the model parameters of the high-order reconstruction model from point M to the wall, virtual points are established. A higher-order reconstruction model.

8. The method for high-precision simulation of flow fields near complex walls according to claim 7, characterized in that, The higher-order reconstruction model P2(r) from point M to the wall n )for: P2(r n )=a2 r n 2 + a1 r n +a0 ; in, Let a0, a1, and a2 be the distances from any point in the flow field to the wall, and let a0, a1, and a2 be the model parameters.

9. The method for high-precision simulation of flow fields near complex walls according to claim 8, characterized in that, High-order reconstruction model of point M to the wall Model parameters , and The solution method is as follows: ； in, The higher-order reconstruction value of reference point M, For reference point The derivative of the higher-order reconstructed value along the wall normal direction, , , These are different constants.

10. The method for high-precision simulation of flow fields near complex walls according to claim 9, characterized in that, virtual points The higher-order reconstruction model is represented as: P2(r g )=a2 r g 2 - a1 r g +a0; in, For virtual points The higher-order reconstruction value, For virtual points Distance to the wall boundary.

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