Simulation platform and calculation method for computational fluid mechanics

Abstract

The invention discloses a simulation platform and a calculation method for computational fluid mechanics, and belongs to the technical field of computational fluid mechanics. In order to solve the problems that precision is insufficient, numerical dissipation is too large and calculation efficiency is low when a traditional method is used for processing the high Reynolds number turbulence or multi-physics coupling problem, a model and boundary conditions are rapidly generated, a grid generation module automatically optimizes a flowing important area grid through an adaptive algorithm, the solving process is accelerated, and the calculation efficiency is improved. Through parallel computing and efficient time integration methods, simulation efficiency of complex transient and steady problems is greatly improved, accurate calculation of critical areas such as a boundary layer and a separation area is ensured through grid encryption and optimization, consistency verification is combined with physical parameters and a control equation, numerical errors and parameter mismatching are avoided, and the method adapts to multi-physical-field complex scenes and is high in practicability. Meanwhile, optimization is carried out by automatically iteratively adjusting input parameters, and accurate and reliable design and research support is provided.

Description

Technical Field

[0001] The present invention relates to the field of computational fluid dynamics technology, and in particular to a simulation platform and calculation method for computational fluid dynamics. Background Art

[0002] Computational fluid dynamics (CFD) is an important tool for studying complex flow and heat transfer phenomena, and plays a vital role in engineering design and scientific exploration. Among them, direct numerical simulation (DNS) has gradually become a cutting-edge method for studying complex flow problems, such as Rayleigh-Benard convection, because it can capture complete flow field details without relying on turbulence models. However, DNS has extremely high requirements on the accuracy and resolution of the calculation method, and requires efficient and stable numerical algorithms and strong computing power support.

[0003] At present, traditional numerical methods often face problems such as insufficient accuracy, excessive numerical dissipation and low computational efficiency when dealing with high Reynolds number turbulence or multi-physics field coupling problems, which limits the widespread application and development of DNS technology. Summary of the invention

[0004] The purpose of the present invention is to provide a simulation platform and calculation method of computational fluid dynamics to solve the problems raised in the above background technology.

[0005] To achieve the above object, the present invention provides the following technical solution: a simulation platform for computational fluid dynamics, comprising:

[0006] Geometric modeling modules for:

[0007] Based on the user-defined geometric parameters, the geometric model is generated through the coordinate system or mathematical expression, the boundary condition distribution is determined and visually verified, the geometric information is discretized into a preliminary grid framework, and the geometric shape description file, boundary condition description file and geometric discretization description file are output;

[0008] Mesh generation module for:

[0009] Based on the geometry description file and boundary condition description file, the mesh of important flow areas is encrypted through the adaptive mesh generation algorithm, hierarchical mesh is generated and the mesh information file is output;

[0010] Physical model definition module for:

[0011] Based on the fluid physical parameters and control equations input by the user, define the mathematical description of thermal boundary conditions and volume forces, verify the correctness and consistency of the physical model parameters, and output the mathematical model description file;

[0012] Numerical solver module for:

[0013] Based on the grid information file and the mathematical model description file, the control equations are discretized through the finite difference format to simulate complex flow and heat transfer problems, and the transient problems are solved through the efficient time integration method. Parallel computing is used to solve and output transient and steady-state flow field variables.

[0014] Data processing module for:

[0015] Calculate key flow parameters based on flow field variables, extract flow characteristics and generate time series and spectrum analysis data, and output flow characteristic files and flow field statistics;

[0016] Visualization modules for:

[0017] Visualize the calculation results, generate two-dimensional and three-dimensional images based on flow characteristic files and flow field statistics, dynamically display the flow field evolution, and output visualization result files;

[0018] Parameter optimization control module for:

[0019] The input parameters are iteratively adjusted based on the flow field statistical results. The results of iterative parameter optimization are fed back through the numerical solution module and the parameters are updated. The optimization effect is verified and an optimization report is generated. The optimized parameter combination and the corresponding calculation results are output.

[0020] Furthermore, the geometric modeling module includes:

[0021] Geometry parameter input unit for:

[0022] Receiving user-defined geometric parameters, the geometric parameters including shape size, position parameters and mathematical expressions describing complex geometry, parsing the geometric parameters, generating and outputting a geometric preliminary representation file including a mathematical expression of a geometric model and point cloud data;

[0023] Boundary condition distribution unit for:

[0024] Receive user-defined boundary conditions, determine the boundary type and attribute distribution of the geometric model surface and fluid area based on the geometric preliminary representation file and boundary conditions, mark the boundary conditions on the geometric model surface and fluid area, assign physical parameters, and mark the boundary condition distribution with colors and symbols;

[0025] The output includes the boundary condition description file including the boundary location and the distribution of physical parameters.

[0026] Furthermore, the geometric modeling module further includes:

[0027] Preliminary mesh generation unit for:

[0028] Based on the preliminary geometry representation file and boundary condition description file, a discretization algorithm is used to generate a preliminary mesh framework, and the surface area with large curvature is refined and discretized. The mesh node uniformity and side length ratio quality of the discretization result are verified and a verification report is generated;

[0029] The output is a geometric discretization description file including the coordinates of the discretized points and the associated information of the boundary conditions.

[0030] Furthermore, the grid generation module includes:

[0031] Grid initialization unit, used to:

[0032] Based on the geometric discretization description file, the input geometric discrete point information is converted into grid nodes, the topological relationship between the nodes is constructed, the global layout mode of the grid is determined according to the geometric shape description file, and a preliminary grid framework including unit types and topological connection relationships is generated, marking the grid units where the boundary conditions are located;

[0033] Output a preliminary mesh topology description file including node coordinates, unit types and topological connection relationships;

[0034] Mesh refinement unit for:

[0035] receiving user-defined flow-important region information, wherein the flow-important region includes a boundary layer and a flow separation region, and based on a preliminary grid topology description file and the flow-important region information, refining grid cells and increasing grid density in the flow-important region according to geometric characteristics and flow characteristics of the region, and generating a hierarchical grid structure;

[0036] A mesh information file is output, wherein the mesh information file includes updated node coordinates and unit topology structure.

[0037] Furthermore, the grid generation module further includes:

[0038] Mesh optimization unit for:

[0039] The generated mesh is globally optimized. Based on the mesh information file, the mesh quality indicators are checked, including the orthogonality of the unit shape, node uniformity and side length ratio. Low-quality mesh units are optimized through node smoothing, side length adjustment and topology reconstruction. A verification report is generated for the optimized mesh, which includes mesh quality statistics and visual inspection results.

[0040] Furthermore, the physical model definition module includes:

[0041] Physical property parameter definition unit, used for:

[0042] Receive fluid physical property parameters input by a user, wherein the fluid physical property parameters include fluid density, viscosity, specific heat capacity and thermal conductivity, establish a physical property parameter table according to the range and unit of the fluid physical property parameters, and perform consistency check on the physical meaning and unit of the fluid physical property parameters;

[0043] Associate fluid physical parameters with geometric models and boundary conditions, assign fluid physical parameters to regions and boundaries, and prompt users to supplement if the parameters are incomplete;

[0044] Outputting a physical property parameter file, wherein the physical property parameter file includes spatial distribution information of fluid density, viscosity, specific heat capacity and thermal conductivity;

[0045] Control equation generation unit for:

[0046] Receive the control equation, flow characteristics, source term and volume force information input by the user, introduce the physical property parameters into the control equation based on the physical property parameter file, generate a specific mathematical expression, and verify the mathematical consistency of the control equation;

[0047] Output a mathematical model description file, wherein the mathematical model description file includes mathematical expressions of control equations, physical property parameters and boundary conditions.

[0048] Furthermore, the numerical solution module includes:

[0049] Equation discretization unit for:

[0050] Based on the mathematical model description file and the grid information file, define the discretized grid units and node layout of the calculation area, perform spatial discretization and construct discrete equations according to the control equations and boundary conditions, and generate a sparse matrix representing the discrete equation system;

[0051] Outputting a discretization equation file, wherein the discretization equation file includes a mathematical expression of spatial discretization and temporal discretization;

[0052] Linear solver unit for:

[0053] Based on the discretized equation file and the grid information file, select the solution algorithm suitable for the problem scale and type, solve the transient problem through the efficient time integration method, and use parallel computing to solve and output the transient and steady-state flow field variables;

[0054] Output a flow field variable file, which includes the distribution of velocity, pressure and temperature during the time step.

[0055] Furthermore, the numerical solution module includes:

[0056] Flow field result processing unit, used for:

[0057] Based on the flow field variable file and the grid information file, extract the key flow parameters in the steady-state solution or the transient solution, the key flow parameters include the maximum velocity and pressure distribution, calculate the flow statistics, the statistics include the mean and variance of the average velocity field, the vorticity field, and the temperature distribution, and generate time series data;

[0058] Output flow field result files and time series files, the flow field result files include the distribution and statistical characteristics of transient and steady-state flow field variables, and the time series files are used for spectrum analysis.

[0059] Furthermore, the data processing module includes:

[0060] Flow parameter calculation unit for:

[0061] Based on the flow field variable file and the grid information file, dimensionless parameters are calculated according to the velocity field and temperature field, including the Nussel number and the Rayleigh number, heat flux and shear stress distribution are extracted in the boundary area, the surface average Nussel number and the total drag coefficient are calculated, and local parameters are calculated in the user-specified area, including the local pressure gradient and the velocity gradient;

[0062] Outputting a flow parameter file, the flow parameter file including global and local distribution values ​​of key flow parameters, the key flow parameters including Nussel number and Rayleigh number;

[0063] Flow feature extraction unit for:

[0064] Based on the flow field variable file and the grid information file, the vortex field distribution is extracted, the vortex center and the flow separation area are identified and marked, the streamlines, traces and velocity vector diagrams representing the flow morphology and path are generated, the energy spectrum is calculated and the energy transfer range of the eddy kinetic energy is identified;

[0065] Output flow characteristic files including vorticity distribution, streamline structure and energy spectrum information;

[0066] Statistical analysis unit for:

[0067] Based on the flow field variable file and the grid information file, the time average value, variance and fluctuation intensity of the flow field variables are calculated, the transient data of the flow field variables are generated into a time series, the spectrum analysis is performed using fast Fourier transform, the main frequency and energy distribution are extracted, and key statistical charts are generated, the key statistical charts include time series curves, spectrum curves and statistical distribution charts;

[0068] Output statistical data files and key statistical charts, the statistical data files including time average, variance and spectrum analysis results.

[0069] Furthermore, a computational fluid dynamics calculation method comprises the following steps:

[0070] Step 1: Generate a geometric model and determine the distribution of geometric boundary conditions based on the geometric parameters defined by the user, discretize the geometric model, generate a preliminary grid framework, and output a geometric shape description file, a boundary condition description file, and a geometric discretization description file;

[0071] Step 2: Adopt the adaptive mesh generation algorithm to encrypt the mesh of important flow areas, generate a hierarchical mesh structure, check the mesh quality, improve the mesh quality through node smoothing and topology optimization, and output the optimized mesh information file;

[0072] Step 3: Input the fluid physical parameters and control equations, define the mathematical description of thermal boundary conditions and volume forces, verify the consistency of physical parameters, control equations and boundary conditions, and generate a mathematical model description file;

[0073] Step 4: Discretize the control equations using the finite difference format to generate a discretized equation file in the form of a sparse matrix. Use efficient time integration methods and parallel computing to solve transient and steady-state problems and output the flow field variable file.

[0074] Step 5: Calculate dimensionless key flow parameters, extract key features of the flow field, generate flow feature files, perform statistical analysis on transient data of flow field variables, calculate time average, variance and fluctuation intensity, extract main frequency and spectrum distribution, and output statistical data files and key statistical charts;

[0075] Step 6: Visualize the flow characteristic data and statistics, generate two-dimensional and three-dimensional images, dynamically display the evolution of the flow field, output the visualization result file, iteratively adjust the input parameters based on the flow field statistics and optimization objectives, update the calculation results through feedback iteration, verify the optimization effect and output the optimized parameter combination and optimization report.

[0076] Compared with the prior art, the present invention has the following beneficial effects:

[0077] 1. The present invention uses modular design and full-process automation features to seamlessly connect all links from geometric modeling to simulation result processing, significantly improving the overall efficiency of computational fluid dynamics simulation, automatically receiving user-defined geometric parameters, and quickly generating geometric models and boundary condition files; the grid generation module automatically optimizes the grid distribution through an adaptive grid encryption algorithm, reducing the need for manual intervention, and adopts parallel computing and efficient time integration methods to greatly improve the speed of solving transient and steady-state problems. Through efficient linkage, the platform significantly shortens the simulation cycle and improves the user's modeling and computing efficiency, and is particularly suitable for the rapid processing of complex industrial problems or large-scale flow problems.

[0078] 2. The present invention realizes accurate capture and reliable calculation of flow field characteristics through adaptive grid encryption, discretization algorithm and multi-physics field verification technology. The grid generation module can perform encryption processing on important flow areas (such as boundary layers and flow separation areas), thereby enhancing the accuracy of calculation results in these areas; at the same time, through grid quality optimization technology, the platform further ensures the orthogonality, uniformity and side length ratio quality of the grid structure, avoiding the accumulation of numerical errors. In the verification process of fluid physical parameters, control equations and boundary conditions, a consistency check mechanism is adopted to effectively avoid parameter mismatch problems. It can not only simulate complex flows with high precision, but also flexibly adapt to a variety of physical scenarios to meet a variety of needs from basic research to industrial applications.

[0079] 3. The present invention generates high-quality two-dimensional and three-dimensional images based on flow field statistical data and flow characteristic files, and supports dynamic display of the flow field evolution process, allowing users to intuitively observe the distribution and change patterns of flow field variables, and automatically iterates and adjusts input parameters, combined with simulation feedback to verify the optimization effect, providing users with optimized parameter combinations and corresponding calculation results, and generating detailed optimization reports, which not only helps users locate key problems in the flow more quickly, but also supports parameter tuning and result verification, significantly improving the practical value of the platform in engineering design and scientific research. BRIEF DESCRIPTION OF THE DRAWINGS

[0080] Figure 1 It is a schematic diagram of the simulation platform module of the present invention;

[0081] Figure 2 It is a schematic diagram of the calculation method flow of the present invention. DETAILED DESCRIPTION

[0082] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0083] See also Figure 1-2 , the present invention provides the following technical solutions:

[0084] A computational fluid dynamics simulation platform, comprising:

[0085] Geometric modeling modules for:

[0086] Based on the user-defined geometric parameters, the geometric model is generated through the coordinate system or mathematical expression, the boundary condition distribution is determined and visually verified, the geometric information is discretized into a preliminary grid framework, and the geometric shape description file, boundary condition description file and geometric discretization description file are output;

[0087] Mesh generation module for:

[0088] Based on the geometry description file and boundary condition description file, the mesh of important flow areas is encrypted through the adaptive mesh generation algorithm, hierarchical mesh is generated and the mesh information file is output;

[0089] Physical model definition module for:

[0090] Based on the fluid physical parameters and control equations input by the user, define the mathematical description of thermal boundary conditions and volume forces, verify the correctness and consistency of the physical model parameters, and output the mathematical model description file;

[0091] Numerical solver module for:

[0092] Based on the grid information file and the mathematical model description file, the control equations are discretized through the finite difference format to simulate complex flow and heat transfer problems, and the transient problems are solved through the efficient time integration method. Parallel computing is used to solve and output transient and steady-state flow field variables.

[0093] Data processing module for:

[0094] Calculate key flow parameters based on flow field variables, extract flow characteristics and generate time series and spectrum analysis data, and output flow characteristic files and flow field statistics;

[0095] Visualization modules for:

[0096] Visualize the calculation results, generate two-dimensional and three-dimensional images based on flow characteristic files and flow field statistics, dynamically display the flow field evolution, and output visualization result files;

[0097] Parameter optimization control module for:

[0098] The input parameters are iteratively adjusted based on the flow field statistical results. The results of iterative parameter optimization are fed back through the numerical solution module and the parameters are updated. The optimization effect is verified and an optimization report is generated. The optimized parameter combination and the corresponding calculation results are output.

[0099] In the above embodiments, the modular design realizes the full process automated simulation from geometric modeling to result analysis. Its main features are high precision, adaptability and high efficiency. In practical applications, it can significantly improve the simulation efficiency, reduce the need for manual intervention, and ensure that the calculation accuracy meets the needs of industry and scientific research. The platform optimizes the geometric modeling, mesh generation, physical modeling, numerical solution, data processing and visualization, making the simulation of complex flow problems more convenient and efficient. It is suitable for a variety of practical scenarios in the fields of aerospace, energy, machinery, environmental engineering, etc. The modules are highly integrated and coordinated with each other. Through the automated iterative optimization technology, the platform can quickly adjust the parameter combination and feedback the optimization results, thereby improving the accuracy and reliability of the calculation. In addition, the modular design makes the platform have good scalability, and users can add new physical models or numerical solution methods as needed to meet the diverse simulation needs.

[0100] Geometric modeling module, including:

[0101] Geometry parameter input unit for:

[0102] Receiving user-defined geometric parameters, the geometric parameters including shape size, position parameters and mathematical expressions describing complex geometry, parsing the geometric parameters, generating and outputting a geometric preliminary representation file including a mathematical expression of a geometric model and point cloud data;

[0103] Boundary condition distribution unit for:

[0104] Receive user-defined boundary conditions, determine the boundary type and attribute distribution of the geometric model surface and fluid area based on the geometric preliminary representation file and boundary conditions, mark the boundary conditions on the geometric model surface and fluid area, assign physical parameters, and mark the boundary condition distribution with colors and symbols;

[0105] Output boundary condition description files including boundary locations and physical parameter distributions;

[0106] Preliminary mesh generation unit for:

[0107] Based on the preliminary geometry representation file and boundary condition description file, a discretization algorithm is used to generate a preliminary mesh framework, and the surface area with large curvature is refined and discretized. The mesh node uniformity and side length ratio quality of the discretization result are verified and a verification report is generated;

[0108] The output is a geometric discretization description file including the coordinates of the discretized points and the associated information of the boundary conditions.

[0109] In the above embodiment, by providing a user-friendly interface, the user is allowed to define the geometric model of complex shapes with mathematical expressions or geometric parameters, thereby simplifying the difficulty of geometric modeling. Through the preliminary mesh discretization and boundary condition distribution functions, the module can quickly verify the rationality of the geometric model and reduce the impact of model errors on subsequent simulations. In addition, the discretized geometric information can be used for refined mesh generation, which helps to improve the overall efficiency and accuracy of the simulation. By displaying the boundary conditions and geometric distribution states in an intuitive way, the user's understanding threshold of complex geometric modeling is greatly reduced, and it is ensured that the generated geometric model can accurately reflect the actual physical problem requirements.

[0110] Mesh generation module, including:

[0111] Grid initialization unit, used to:

[0112] Based on the geometric discretization description file, the input geometric discrete point information is converted into grid nodes, the topological relationship between the nodes is constructed, the global layout mode of the grid is determined according to the geometric shape description file, and a preliminary grid framework including unit types and topological connection relationships is generated, marking the grid units where the boundary conditions are located;

[0113] Output a preliminary mesh topology description file including node coordinates, unit types and topological connection relationships;

[0114] Mesh refinement unit for:

[0115] receiving user-defined flow-important region information, wherein the flow-important region includes a boundary layer and a flow separation region, and based on a preliminary grid topology description file and the flow-important region information, refining grid cells and increasing grid density in the flow-important region according to geometric characteristics and flow characteristics of the region, and generating a hierarchical grid structure;

[0116] Outputting a mesh information file, wherein the mesh information file includes updated node coordinates and unit topology structure;

[0117] Mesh optimization unit for:

[0118] The generated mesh is globally optimized. Based on the mesh information file, the mesh quality indicators are checked, including the orthogonality of the unit shape, node uniformity and side length ratio. Low-quality mesh units are optimized through node smoothing, side length adjustment and topology reconstruction. A verification report is generated for the optimized mesh, which includes mesh quality statistics and visual inspection results.

[0119] In the above embodiment, through the adaptive grid generation algorithm, the grid can be automatically encrypted in important flow areas (such as boundary layers, flow separation areas, etc.), ensuring the calculation accuracy of key areas, while maintaining a reasonable degree of grid density in non-important areas, significantly reducing the demand for computing resources. The grid topology initialization function in the module converts geometric point information into a topological structure through automated processing steps, thereby reducing the workload of manual intervention by the user. The introduction of grid optimization units improves the quality of the generated grid. Through node smoothing and topology reconstruction technology, the module can improve the orthogonality and uniformity of the grid units, ensuring the stability and accuracy of the numerical solution process. In addition, the verification report generated by the module can quickly identify and solve grid problems, providing users with a high-quality grid foundation.

[0120] Physical model definition module, including:

[0121] Physical property parameter definition unit, used for:

[0122] Receive fluid physical property parameters input by a user, wherein the fluid physical property parameters include fluid density, viscosity, specific heat capacity and thermal conductivity, establish a physical property parameter table according to the range and unit of the fluid physical property parameters, and perform consistency check on the physical meaning and unit of the fluid physical property parameters;

[0123] Associate fluid physical parameters with geometric models and boundary conditions, assign fluid physical parameters to regions and boundaries, and prompt users to supplement if the parameters are incomplete;

[0124] Outputting a physical property parameter file, wherein the physical property parameter file includes spatial distribution information of fluid density, viscosity, specific heat capacity and thermal conductivity;

[0125] Control equation generation unit for:

[0126] Receive the control equation, flow characteristics, source term and volume force information input by the user, introduce the physical property parameters into the control equation based on the physical property parameter file, generate a specific mathematical expression, and verify the mathematical consistency of the control equation;

[0127] Output a mathematical model description file, wherein the mathematical model description file includes mathematical expressions of control equations, physical property parameters and boundary conditions.

[0128] In the above embodiments, the systematized physical property parameter definition and control equation generation functions provide users with highly flexible physical model definition capabilities. The physical property parameter consistency verification function added to the module can discover and correct potential problems during the data entry stage to avoid calculation deviations caused by incorrect physical property parameters. The control equation generation unit automatically converts complex mathematical models into computable discrete expressions, improves the mathematical consistency of the control equations through system verification, and ensures that users can efficiently establish accurate physical models. The close integration of the module with the geometric modeling and mesh generation modules realizes the automatic association of physical property parameters with geometric models and boundary conditions, reducing the time for manual settings by users.

[0129] Numerical solution module, including:

[0130] Equation discretization unit for:

[0131] Based on the mathematical model description file and the grid information file, define the discretized grid units and node layout of the calculation area, perform spatial discretization and construct discrete equations according to the control equations and boundary conditions, and generate a sparse matrix representing the discrete equation system;

[0132] Outputting a discretization equation file, wherein the discretization equation file includes a mathematical expression of spatial discretization and temporal discretization;

[0133] Linear solver unit for:

[0134] Based on the discretized equation file and the grid information file, select the solution algorithm suitable for the problem scale and type, solve the transient problem through the efficient time integration method, and use parallel computing to solve and output the transient and steady-state flow field variables;

[0135] Outputting a flow field variable file, wherein the flow field variable file includes the distribution of velocity, pressure and temperature during the time stepping process;

[0136] Flow field result processing unit, used for:

[0137] Based on the flow field variable file and the grid information file, extract the key flow parameters in the steady-state solution or the transient solution, the key flow parameters include the maximum velocity and pressure distribution, calculate the flow statistics, the statistics include the mean and variance of the average velocity field, the vorticity field, and the temperature distribution, and generate time series data;

[0138] Output flow field result files and time series files, the flow field result files include the distribution and statistical characteristics of transient and steady-state flow field variables, and the time series files are used for spectrum analysis.

[0139] In the above embodiment, by integrating the finite difference method and efficient time integration technology, transient and steady-state flow field problems can be quickly solved. With the support of parallel computing, this module significantly improves the computational efficiency of complex large-scale problems. The sparse matrix generated by the equation discretization unit optimizes the use of computing resources, making it adaptable to fluid problems of different scales and complexities. The linear solution unit has a variety of solution algorithm options, and users can optimize the computational efficiency and accuracy according to their needs. In addition, the transient and steady-state flow field variables generated by the module can provide detailed basic information for subsequent data processing and visualization, ensuring the comprehensiveness and reliability of the calculation results.

[0140] Data processing module, including:

[0141] Flow parameter calculation unit for:

[0142] Based on the flow field variable file and the grid information file, dimensionless parameters are calculated according to the velocity field and temperature field, including the Nussel number and the Rayleigh number, heat flux and shear stress distribution are extracted in the boundary area, the surface average Nussel number and the total drag coefficient are calculated, and local parameters are calculated in the user-specified area, including the local pressure gradient and the velocity gradient;

[0143] Outputting a flow parameter file, the flow parameter file including global and local distribution values ​​of key flow parameters, the key flow parameters including Nussel number and Rayleigh number;

[0144] Flow feature extraction unit for:

[0145] Based on the flow field variable file and the grid information file, the vortex field distribution is extracted, the vortex center and the flow separation area are identified and marked, the streamlines, traces and velocity vector diagrams representing the flow morphology and path are generated, the energy spectrum is calculated and the energy transfer range of the eddy kinetic energy is identified;

[0146] Output flow characteristic files including vorticity distribution, streamline structure and energy spectrum information;

[0147] Statistical analysis unit for:

[0148] Based on the flow field variable file and the grid information file, the time average value, variance and fluctuation intensity of the flow field variables are calculated, the transient data of the flow field variables are generated into a time series, the spectrum analysis is performed using fast Fourier transform, the main frequency and energy distribution are extracted, and key statistical charts are generated, the key statistical charts include time series curves, spectrum curves and statistical distribution charts;

[0149] Output statistical data files and key statistical charts, the statistical data files including time average, variance and spectrum analysis results.

[0150] In the above embodiment, by calculating key flow parameters (such as Nusselt number and Rayleigh number) and extracting flow characteristics (such as vortex distribution and flow separation zone), comprehensive fluid mechanics analysis capabilities are provided to users. The flow parameter calculation unit supports dimensionless analysis and provides theoretical guidance for scientific research and engineering design. The statistical analysis unit in the module reveals the dynamic characteristics and energy distribution laws of flow field variables through time series data and spectrum analysis functions, providing an important tool for in-depth research on complex flow phenomena. In addition, the output file format of this module is compatible with mainstream post-processing tools, which is convenient for integration with other analysis systems.

[0151] A computational fluid dynamics calculation method comprises the following steps:

[0152] Step 1: Generate a geometric model and determine the distribution of geometric boundary conditions based on the geometric parameters defined by the user, discretize the geometric model, generate a preliminary grid framework, and output a geometric shape description file, a boundary condition description file, and a geometric discretization description file;

[0153] Step 2: Adopt the adaptive mesh generation algorithm to encrypt the mesh of important flow areas, generate a hierarchical mesh structure, check the mesh quality, improve the mesh quality through node smoothing and topology optimization, and output the optimized mesh information file;

[0154] Step 3: Input the fluid physical parameters and control equations, define the mathematical description of thermal boundary conditions and volume forces, verify the consistency of physical parameters, control equations and boundary conditions, and generate a mathematical model description file;

[0155] Step 4: Discretize the control equations using the finite difference format to generate a discretized equation file in the form of a sparse matrix. Use efficient time integration methods and parallel computing to solve transient and steady-state problems and output the flow field variable file.

[0156] Step 5: Calculate dimensionless key flow parameters, extract key features of the flow field, generate flow feature files, perform statistical analysis on transient data of flow field variables, calculate time average, variance and fluctuation intensity, extract main frequency and spectrum distribution, and output statistical data files and key statistical charts;

[0157] Step 6: Visualize the flow characteristic data and statistics, generate two-dimensional and three-dimensional images, dynamically display the evolution of the flow field, output the visualization result file, iteratively adjust the input parameters based on the flow field statistics and optimization objectives, update the calculation results through feedback iteration, verify the optimization effect and output the optimized parameter combination and optimization report.

[0158] The above description is only a preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can make equivalent replacements or changes according to the technical scheme and inventive concept of the present invention within the technical scope disclosed by the present invention, which should be covered by the protection scope of the present invention.

Claims

1. A computational fluid dynamics simulation platform, characterized in that: include: Geometric modeling modules for: Based on the user-defined geometric parameters, the geometric model is generated through the coordinate system or mathematical expression, the boundary condition distribution is determined and visually verified, the geometric information is discretized into a preliminary grid framework, and the geometric shape description file, boundary condition description file and geometric discretization description file are output; Mesh generation module for: Based on the geometry description file and boundary condition description file, the mesh of important flow areas is encrypted through the adaptive mesh generation algorithm, hierarchical mesh is generated and the mesh information file is output; Physical model definition module for: Based on the fluid physical parameters and control equations input by the user, define the mathematical description of thermal boundary conditions and volume forces, verify the correctness and consistency of the physical model parameters, and output the mathematical model description file; Numerical solver module for: Based on the grid information file and the mathematical model description file, the control equations are discretized through the finite difference format to simulate complex flow and heat transfer problems, and the transient problems are solved through the efficient time integration method. Parallel computing is used to solve and output transient and steady-state flow field variables; Data processing module for: Calculate key flow parameters based on flow field variables, extract flow characteristics and generate time series and spectrum analysis data, and output flow characteristic files and flow field statistics; Visualization modules for: Visualize the calculation results, generate two-dimensional and three-dimensional images based on flow characteristic files and flow field statistics, dynamically display the flow field evolution, and output visualization result files; Parameter optimization control module for: The input parameters are iteratively adjusted based on the flow field statistical results. The results of iterative parameter optimization are fed back through the numerical solution module and the parameters are updated. The optimization effect is verified and an optimization report is generated. The optimized parameter combination and the corresponding calculation results are output.

2. A computational fluid dynamics simulation platform as claimed in claim 1, characterized in that: The geometric modeling module comprises: Geometry parameter input unit for: Receiving user-defined geometric parameters, the geometric parameters including shape size, position parameters and mathematical expressions describing complex geometry, parsing the geometric parameters, generating and outputting a geometric preliminary representation file including a mathematical expression of a geometric model and point cloud data; Boundary condition distribution unit for: Receive user-defined boundary conditions, determine the boundary type and attribute distribution of the geometric model surface and fluid area based on the geometric preliminary representation file and boundary conditions, mark the boundary conditions on the geometric model surface and fluid area, assign physical parameters, and mark the boundary condition distribution with colors and symbols; The output includes the boundary condition description file including the boundary location and the distribution of physical parameters.

3. A computational fluid dynamics simulation platform as claimed in claim 2, characterized in that: The geometric modeling module further includes: Preliminary mesh generation unit for: Based on the preliminary geometry representation file and boundary condition description file, a discretization algorithm is used to generate a preliminary mesh framework, and the surface area with large curvature is refined and discretized. The mesh node uniformity and side length ratio quality of the discretization result are verified and a verification report is generated; The output is a geometric discretization description file including the coordinates of the discretized points and the associated information of the boundary conditions.

4. A computational fluid dynamics simulation platform as claimed in claim 1, characterized in that: The grid generation module comprises: Grid initialization unit, used to: Based on the geometric discretization description file, the input geometric discrete point information is converted into grid nodes, the topological relationship between the nodes is constructed, the global layout mode of the grid is determined according to the geometric shape description file, and a preliminary grid framework including unit types and topological connection relationships is generated, marking the grid units where the boundary conditions are located; Output a preliminary mesh topology description file including node coordinates, unit types and topological connection relationships; Mesh refinement unit for: receiving user-defined flow-important region information, wherein the flow-important region includes a boundary layer and a flow separation region, and based on a preliminary grid topology description file and the flow-important region information, refining grid cells and increasing grid density in the flow-important region according to geometric characteristics and flow characteristics of the region, and generating a hierarchical grid structure; A mesh information file is output, wherein the mesh information file includes updated node coordinates and unit topology structure.

5. A computational fluid dynamics simulation platform as claimed in claim 4, characterized in that: The grid generation module further includes: Mesh optimization unit for: The generated mesh is globally optimized. Based on the mesh information file, the mesh quality indicators are checked, including the orthogonality of the unit shape, node uniformity and side length ratio. Low-quality mesh units are optimized through node smoothing, side length adjustment and topology reconstruction. A verification report is generated for the optimized mesh, which includes mesh quality statistics and visual inspection results.

6. A computational fluid dynamics simulation platform as claimed in claim 1, characterized in that: The physical model definition module includes: Physical property parameter definition unit, used for: Receive fluid physical property parameters input by a user, wherein the fluid physical property parameters include fluid density, viscosity, specific heat capacity and thermal conductivity, establish a physical property parameter table according to the range and unit of the fluid physical property parameters, and perform consistency check on the physical meaning and unit of the fluid physical property parameters; Associate fluid physical parameters with geometric models and boundary conditions, assign fluid physical parameters to regions and boundaries, and prompt users to supplement if the parameters are incomplete; Outputting a physical property parameter file, wherein the physical property parameter file includes spatial distribution information of fluid density, viscosity, specific heat capacity and thermal conductivity; Control equation generation unit for: Receive the control equation, flow characteristics, source term and volume force information input by the user, introduce the physical property parameters into the control equation based on the physical property parameter file, generate a specific mathematical expression, and verify the mathematical consistency of the control equation; Output a mathematical model description file, wherein the mathematical model description file includes mathematical expressions of control equations, physical property parameters and boundary conditions.

7. A computational fluid dynamics simulation platform as claimed in claim 1, characterized in that: The numerical solution module comprises: Equation discretization unit for: Based on the mathematical model description file and the grid information file, define the discretized grid units and node layout of the calculation area, perform spatial discretization and construct discrete equations according to the control equations and boundary conditions, and generate a sparse matrix representing the discrete equation system; Outputting a discretization equation file, wherein the discretization equation file includes a mathematical expression of spatial discretization and temporal discretization; Linear solver unit for: Based on the discretized equation file and the grid information file, select the solution algorithm suitable for the problem scale and type, solve the transient problem through the efficient time integration method, and use parallel computing to solve and output the transient and steady-state flow field variables; Output a flow field variable file, which includes the distribution of velocity, pressure and temperature during the time step.

8. A computational fluid dynamics simulation platform as claimed in claim 7, characterized in that: The numerical solution module comprises: Flow field result processing unit, used for: Based on the flow field variable file and the grid information file, extract the key flow parameters in the steady-state solution or the transient solution, the key flow parameters include the maximum velocity and pressure distribution, calculate the flow statistics, the statistics include the mean and variance of the average velocity field, the vorticity field, and the temperature distribution, and generate time series data; Output flow field result files and time series files, the flow field result files include the distribution and statistical characteristics of transient and steady-state flow field variables, and the time series files are used for spectrum analysis.

9. A computational fluid dynamics simulation platform as claimed in claim 1, characterized in that: The data processing module comprises: Flow parameter calculation unit for: Based on the flow field variable file and the grid information file, dimensionless parameters are calculated according to the velocity field and the temperature field, the dimensionless parameters include the Nusselt number and the Rayleigh number, the heat flux and shear stress distribution are extracted in the boundary area, the surface average Nusselt number and the total resistance coefficient are calculated, and the local parameters are calculated in the user-specified area, the local parameters include the local pressure gradient and the velocity gradient; Outputting a flow parameter file, the flow parameter file including global and local distribution values ​​of key flow parameters, the key flow parameters including Nusselt number and Rayleigh number; Flow feature extraction unit for: Based on the flow field variable file and the grid information file, the vortex field distribution is extracted, the vortex center and the flow separation area are identified and marked, the streamlines, traces and velocity vector diagrams representing the flow morphology and path are generated, the energy spectrum is calculated and the energy transfer range of the eddy kinetic energy is identified; Output flow characteristic files including vorticity distribution, streamline structure and energy spectrum information; Statistical Analysis Unit for: Based on the flow field variable file and the grid information file, the time average value, variance and fluctuation intensity of the flow field variables are calculated, the transient data of the flow field variables are generated into a time series, the spectrum analysis is performed using fast Fourier transform, the main frequency and energy distribution are extracted, and key statistical charts are generated, the key statistical charts include time series curves, spectrum curves and statistical distribution charts; Output statistical data files and key statistical charts, the statistical data files including time average, variance and spectrum analysis results.

10. A computational fluid dynamics calculation method, applied to the computational fluid dynamics simulation platform according to any one of claims 1 to 9, characterized in that: The steps include: Step 1: Generate a geometric model and determine the distribution of geometric boundary conditions based on the geometric parameters defined by the user, discretize the geometric model, generate a preliminary grid framework, and output a geometric shape description file, a boundary condition description file, and a geometric discretization description file; Step 2: Adopt the adaptive mesh generation algorithm to encrypt the mesh of important flow areas, generate a hierarchical mesh structure, check the mesh quality, improve the mesh quality through node smoothing and topology optimization, and output the optimized mesh information file; Step 3: Input the fluid physical parameters and control equations, define the mathematical description of thermal boundary conditions and volume forces, verify the consistency of physical parameters, control equations and boundary conditions, and generate a mathematical model description file; Step 4: Discretize the control equations using the finite difference format to generate a discretized equation file in the form of a sparse matrix. Use efficient time integration methods and parallel computing to solve transient and steady-state problems and output the flow field variable file. Step 5: Calculate dimensionless key flow parameters, extract key features of the flow field, generate flow feature files, perform statistical analysis on transient data of flow field variables, calculate time average, variance and fluctuation intensity, extract main frequency and spectrum distribution, and output statistical data files and key statistical charts; Step 6: Visualize the flow characteristic data and statistics, generate two-dimensional and three-dimensional images, dynamically display the evolution of the flow field, output the visualization result file, iteratively adjust the input parameters based on the flow field statistics and optimization objectives, update the calculation results through feedback iteration, verify the optimization effect and output the optimized parameter combination and optimization report.

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