Multi-physics field simulation method and device, equipment, storage medium and program product

Abstract

The invention relates to a multi-physics field simulation method and device, equipment, a storage medium and a program product. The method comprises the following steps: constructing a geometric model of the whole turbofan engine and each component, carrying out grid discretization on a physical space of the geometric model to obtain a grid system of the geometric model, and determining spatial distribution of each physical field according to a discretization control equation set of a plurality of physical fields of the grid system, and determining simulation results of the whole machine and each part of the turbofan engine on the basis of the spatial distribution of each physical field, so that modeling can be performed for the whole machine and each part of the turbofan engine, and tight coupling simulation of multiple physical fields is realized on the basis of geometric models of the whole machine and each part of the turbofan engine. And the simulation precision and accuracy are improved.

Description

Technical Field

[0001] This application relates to the field of aeroengine simulation technology, and particularly to a multi-physical field simulation method, device, equipment, storage medium, and program product. Background Art

[0002] As a core component of modern aviation power systems, the performance of turbofan engines is crucial for the overall performance of aircraft. To understand the internal working mechanisms of engines and physical phenomena such as aerodynamics, heat transfer, and combustion inside the engines, it is necessary to simulate the three-dimensional multi-physical fields of turbofan engines.

[0003] Currently, the three-dimensional multi-physical field simulation of turbofan engines usually models each component separately and simulates each physical field separately, without considering the complex coupling relationships of physical fields between components, resulting in relatively low simulation accuracy. Summary of the Invention

[0004] Based on this, to address the above technical problems, it is necessary to provide a multi-physical field simulation method, device, equipment, storage medium, and program product that can consider the complex coupling relationships of physical fields between components and improve the accuracy of simulation.

[0005] In a first aspect, this application provides a multi-physical field simulation method. The method includes:

[0006] Construct geometric models of the whole turbofan engine and its components;

[0007] Perform grid discretization on the physical space of the geometric model to obtain a grid system of the geometric model;

[0008] Determine the spatial distribution of each physical field according to the discrete control equations of multiple physical fields of the grid system;

[0009] Based on the spatial distribution of each physical field, determine the simulation results of the whole turbofan engine and its components.

[0010] In one embodiment, the step of determining the spatial distribution of each physical field according to the discrete control equations of multiple physical fields of the grid system includes:

[0011] Obtain the initial distribution of each physical field;

[0012] According to the initial distribution of each physical field, perform time marching iterative solution on the discrete control equations to obtain the spatial distribution of each physical field.

[0013] In one embodiment, the step of performing time marching iterative solution on the discrete control equations according to the initial distribution of each physical field to obtain the spatial distribution of each physical field includes:

[0014] At each time step, according to the initial distribution of each physical field, the discrete control equation set is solved to obtain the intermediate distribution of each physical field;

[0015] Taking this intermediate distribution as the initial distribution of each physical field, according to the initial distribution of each physical field, the discrete control equation set is solved until the iteration condition is satisfied, and the spatial distribution of each physical field is determined according to the intermediate distribution of each physical field obtained from the last solution.

[0016] In one embodiment, the method further includes:

[0017] Obtaining the initial control equation set of multiple physical fields in the physical space;

[0018] Based on the finite volume method and the grid system, the initial control equation set is discretized to obtain the discrete control equation set.

[0019] In one embodiment, the physical field includes at least one of an aerodynamic field, a heat transfer field, a combustion reaction field, a phase change component field, and a solid stress field.

[0020] In one embodiment, the discrete control equation set includes at least one of a mass equation, a component equation, a momentum equation, an energy equation, and a turbulence model control equation.

[0021] In a second aspect, the present application further provides a multi-physical field simulation device. The device includes:

[0022] A geometric model construction module for constructing the geometric models of the whole machine and each component of a turbofan engine;

[0023] A grid discretization module for performing grid discretization on the physical space of the geometric model to obtain the grid system of the geometric model;

[0024] A first determination module for determining the spatial distribution of each physical field according to the discrete control equation set of multiple physical fields of the grid system;

[0025] A second determination module for determining the simulation results of the whole machine and each component of the turbofan engine based on the spatial distribution of each physical field.

[0026] In a third aspect, the present application further provides a computer device, including a memory and a processor. The memory stores a computer program, and when the processor executes the computer program, the steps of any of the above methods are implemented.

[0027] In a fourth aspect, the present application further provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the steps of any of the above methods are implemented.

[0028] In a fifth aspect, the present application also provides a computer program product, including a computer program which, when executed by a processor, implements the steps of any of the above methods.

[0029] The above multi-physics field simulation method, device, equipment, storage medium and program product construct geometric models of the whole engine and each component of a turbofan engine, discretize the physical space of the geometric models to obtain a grid system of the geometric models, determine the spatial distribution of each physical field according to the discrete control equations of multiple physical fields of the grid system, and determine the simulation results of the whole engine and each component of the turbofan engine based on the spatial distribution of each physical field. Thus, it is possible to model the whole engine and each component of the turbofan engine, and realize the tight coupling simulation of multiple physical fields on the basis of the geometric models of the whole engine and each component of the turbofan engine, improving the simulation accuracy and precision. Description of the Drawings

[0030] Figure 1 is an internal structure diagram of a computer device provided by an embodiment of the present application;

[0031] Figure 2 is a schematic flowchart of a multi-physics field simulation method provided by an embodiment of the present application;

[0032] Figure 3 is a schematic flowchart of a method for determining the spatial distribution of a physical field provided by an embodiment of the present application;

[0033] Figure 4 is a schematic flowchart of another method for determining the spatial distribution of a physical field provided by an embodiment of the present application;

[0034] Figure 5 is a schematic flowchart of a method for determining discrete control equations provided by an embodiment of the present application;

[0035] Figure 6 is a schematic flowchart of a unified modeling and coupling simulation method for multiple physical fields of a turbofan engine provided by an embodiment of the present application;

[0036] Figure 7 is a structural block diagram of a multi-physics field simulation device provided by an embodiment of the present application. Detailed Embodiments

[0037] In order to make the objectives, technical solutions and advantages of the present application clearer, the present application will be further described in detail below with reference to the drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0038] As a core component of modern aero-engine power systems, the high efficiency and reliability of its performance are crucial for the overall performance of aircraft. To understand the internal working mechanism of the engine and physical phenomena such as aerodynamics, heat transfer, and combustion inside the engine, it is necessary to simulate the three-dimensional multi-physical fields of the turbofan engine.

[0039] Currently, the three-dimensional multi-physical field simulation of turbofan engines usually models each component separately and simulates each physical field separately, without considering the complex coupling relationships of the physical fields between components, resulting in relatively low simulation accuracy.

[0040] The multi-physical field simulation method provided by the embodiments of this application can be applied to, for example, Figure 1 the application environment shown. Figure 1 FIG. is the internal structure diagram of a computer device provided by the embodiments of this application. The computer device can be a server, and its internal structure diagram can be as shown in Figure 1 FIG.. The computer device includes a processor, a memory, and a network interface connected through a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The network interface of the computer device is used to communicate with external terminals through a network connection. When the computer program is executed by the processor, it implements a multi-physical field simulation method.

[0041] Those skilled in the art can understand that Figure 1 the structure shown in FIG. is only a block diagram of some structures related to the solution of this application, and does not constitute a limitation on the computer device to which the solution of this application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine some components, or have different component arrangements.

[0042] In one embodiment, as shown in Figure 2 FIG., Figure 2 is the flowchart of a multi-physical field simulation method provided by the embodiments of this application. The method can be applied to the computer device in Figure 1 FIG., and the method includes the following steps:

[0043] S201, construct the geometric models of the whole turbofan engine and its components.

[0044] In one embodiment, the design parameters of the turbofan engine and the dimensions of each component can be obtained, and then the geometric models of the whole turbofan engine and its components can be constructed according to the design parameters and the dimensions of each component.

[0045] Optionally, the geometric models of the whole turbofan engine and its components can be constructed based on the design parameters and the dimensions of the components by using Computer Aided Design (CAD) or geometric modeling tools.

[0046] Exemplarily, the components of the turbofan engine can include, for example, a compressor, a combustion chamber, a turbine, etc.

[0047] S202, discretize the physical space of the geometric model to obtain the grid system of the geometric model.

[0048] In one embodiment, the physical space of the geometric model can be discretized by using a grid generation tool or algorithm according to the set grid division parameters to generate a unified grid system. Among them, the grids of the components should be seamlessly docked.

[0049] Optionally, the generated grid system can be checked to determine whether the generated grid system meets the actual usage requirements. If the generated grid system does not meet the actual usage requirements, the grid division parameters, the grid generation tool or algorithm, etc. can be modified to regenerate the grid system.

[0050] S203, determine the spatial distribution of each physical field according to the discrete control equations of multiple physical fields of the grid system.

[0051] Optionally, the physical fields can include, for example, an aerodynamic field, a heat transfer field, a combustion reaction field, a phase change component field, and a solid stress field. The discrete control equations can include at least one of a mass equation, a component equation, a momentum equation, an energy equation, and a turbulence model control equation.

[0052] In one embodiment, unified boundary conditions and discrete rules can be set for multiple physical fields. According to the boundary conditions and the grid system, the initial control equations of multiple physical fields in the physical space are discretized based on the discrete rules to obtain the discrete control equations.

[0053] In a possible implementation manner, the initial distribution of each physical field can be obtained, and then the discrete control equations are solved according to the initial distribution of each physical field and the equation solving method to obtain the spatial distribution of each physical field.

[0054] Exemplarily, the equation solving method can include at least one of an iterative method, a direct method, and a spectral method, etc.

[0055] S204, determine the simulation results of the whole turbofan engine and its components based on the spatial distribution of each physical field.

[0056] Exemplarily, the spatial distributions of the physical fields can be corrected, and then the spatial distributions of the corrected physical fields can be processed to obtain the simulation results of the whole engine and each component of the turbofan engine.

[0057] Optionally, the simulation results can include, for example, distribution diagrams of the velocity field, pressure field, and temperature field, as well as data of key parameters such as the thermal stress of the turbine blade and gas-solid heat transfer caused by the combustion chamber reaction. Among them, since the key effects of the combustion chamber reaction on the thermal stress of the turbine blade and gas-solid heat transfer are considered in the embodiments of the present application, the comprehensiveness and accuracy of the simulation are improved.

[0058] In the embodiments of the present application, by constructing the geometric models of the whole engine and each component of the turbofan engine, discretizing the physical space of the geometric models to obtain the grid system of the geometric models, determining the spatial distributions of the physical fields according to the discrete control equations of the multiple physical fields of the grid system, and determining the simulation results of the whole engine and each component of the turbofan engine based on the spatial distributions of the physical fields, it is possible to model the whole engine and each component of the turbofan engine, and realize the tight coupling simulation of multiple physical fields based on the geometric models of the whole engine and each component of the turbofan engine, improving the simulation accuracy and precision.

[0059] Referring to Figure 3 , Figure 3 is a schematic flowchart of a method for determining the spatial distribution of a physical field provided by an embodiment of the present application. This embodiment relates to a possible implementation manner of how to determine the spatial distribution of each physical field according to the discrete control equations of the multiple physical fields of the grid system. On the basis of the above embodiment, the above S203 includes the following steps:

[0060] S301, obtain the initial distributions of the physical fields.

[0061] In one embodiment, the preset initial distributions of the physical fields can be obtained, and then the initial distributions of the physical fields can be used as the initial conditions of the discrete control equations.

[0062] S302, perform time marching iterative solution on the discrete control equations according to the initial distributions of the physical fields to obtain the spatial distributions of the physical fields.

[0063] Optionally, the time step can be set, starting from the initial moment, and the time can be gradually advanced according to the set time step. In each time step, iterative solution is performed on the discrete control equations according to the initial distributions of the physical fields. If the iterative condition is satisfied in the current time step, continue to advance to the next time step until the solutions of all time steps converge, and obtain the spatial distributions of the physical fields at the same moment.

[0064] It should be noted that there are various implementation methods for time marching iterative solution. The above steps are just one possible implementation method, and it is not necessary to solve the discrete control equations according to the above steps. Other time marching iterative solution methods can also be selected according to requirements to solve the discrete control equations.

[0065] In the embodiments of the present application, the initial distributions of each physical field are obtained. According to the initial distributions of each physical field, the discrete control equations are solved by time marching iteration to obtain the spatial distributions of each physical field. Since the discrete control equations are solved by time marching iteration in the embodiments of the present application, the continuity of the velocity field, pressure field, and temperature field in the simulation process of the whole turbofan engine and each component is considered, further improving the simulation accuracy and accuracy.

[0066] Refer to Figure 4 , Figure 4 is a schematic flowchart of another method for determining the spatial distribution of a physical field provided by the embodiments of the present application. This embodiment relates to a possible implementation method for solving the discrete control equations by time marching iteration according to the initial distributions of each physical field to obtain the spatial distributions of each physical field. On the basis of the above embodiments, the above S302 includes the following steps:

[0067] S401, within each time step, solve the discrete control equations according to the initial distributions of each physical field to obtain the intermediate distributions of each physical field.

[0068] Exemplarily, within the target time step, the discrete control equations can be solved according to the initial distributions of each physical field to obtain the intermediate distributions of each physical field. Wherein, the target time step is any one of the time steps.

[0069] S402, use the intermediate distribution as the initial distribution of each physical field, and solve the discrete control equations according to the initial distributions of each physical field until the iteration condition is satisfied. Determine the spatial distributions of each physical field according to the intermediate distributions of each physical field obtained from the last solution.

[0070] Exemplarily, within the target time step, the intermediate distributions of each physical field can be used as the initial distributions of each physical field, and the discrete control equations can be solved again according to the initial distributions of each physical field, then new intermediate distributions of each physical field are obtained. The new intermediate distributions of each physical field are used as the initial distributions of each physical field again to solve the discrete control equations, and the above process is continuously repeated until the iteration condition is satisfied. Then, take the next time step after the target time step as the new target time step, and execute the above steps until the solutions of all time steps converge. Finally, determine the spatial distributions of each physical field at the same moment according to the intermediate distributions of each physical field obtained from the last solution in each time step.

[0071] Optionally, during the process of solving the discrete control equations, the initial distribution, intermediate distribution of each physical field, and the solutions at all time steps can be stored in a database, so that the intermediate distribution of each physical field can be obtained from the database to perform the next round of iteration, and the data generated during the process of solving the discrete control equations can be queried.

[0072] In the embodiments of the present application, within each time step, according to the initial distribution of each physical field, the discrete control equations are solved to obtain the intermediate distribution of each physical field. The intermediate distribution is used as the initial distribution of each physical field, and according to the initial distribution of each physical field, the discrete control equations are solved until the iteration condition is satisfied. The spatial distribution of each physical field is determined according to the intermediate distribution of each physical field obtained from the last solution, taking into account the continuity of the velocity field, pressure field, and temperature field during the simulation of the whole machine and each component of the turbofan engine, further improving the simulation accuracy and precision.

[0073] Referring to Figure 5 , Figure 5 FIG. is a schematic flowchart of a method for determining discrete control equations provided by an embodiment of the present application. On the basis of the above embodiments, the method further includes the following steps:

[0074] S501, obtain the initial control equations of multiple physical fields in physical space.

[0075] In one embodiment, continuous initial control equations of multiple physical fields in physical space can be obtained.

[0076] Optionally, the physical fields may include, for example, an aerodynamic field, a heat transfer field, a combustion reaction field, a phase change component field, and a solid stress field. The initial control equations may include, for example, at least one of a mass equation, a component equation, a momentum equation, an energy equation, and a turbulence model control equation.

[0077] S502, discretize the initial control equations based on the finite volume method and the grid system to obtain discrete control equations.

[0078] In one embodiment, a unified boundary condition can be set for multiple physical fields, and based on this boundary condition and the grid system, the initial control equations of multiple physical fields in physical space are discretized based on the finite volume method to obtain discrete control equations.

[0079] In the embodiments of the present application, the initial control equations of multiple physical fields in physical space are obtained, and the initial control equations are discretized based on the finite volume method and the grid system to obtain discrete control equations, so that the continuous physical fields can be transformed into numerical values at discrete grid points, facilitating subsequent solution of the control equations, simplifying the solution process of the control equations, and improving the solution efficiency of the control equations.

[0080] Based on the above embodiments, the discrete control equation set includes at least one of the mass equation, the component equation, the momentum equation, the energy equation, and the turbulence model control equation.

[0081] Exemplarily, the aerodynamic simulation of the rotating blade row is realized on a fixed single-channel grid by using the Multiple Frames of Reference (MRF). The spray combustion uses the Partially Stirred Reactor Model (PaSR) to calculate the heat release power of the turbulent combustion chemical reaction. The Reynolds Averaged Navier-Stokes (RANS) turbulence model is used to realize the turbulent viscosity simulation. The control equation set of the aerodynamic combustion multi-physical field in the rotating coordinate system is as follows:

[0082] Mass equation:

[0083]

[0084] Component equation:

[0085]

[0086] Momentum equation:

[0087]

[0088] where the viscous stress tensor is defined as follows:

[0089]

[0090] Energy equation (enthalpy conservation):

[0091]

[0092] k-ε turbulence model control equation set:

[0093]

[0094]

[0095] where is the calculated source term, expressed as:

[0096]

[0097] The turbulent viscosity is expressed as:

[0098]

[0099] The model constants are set to:

[0100]

[0101] The Partially Stirred Reactor (PaSR) model is an extension of the Eddy Dissipation Concept that employs detailed chemical assumptions where the finite reaction rate is based on chemical and turbulent time scales. The computational domain is divided into a finite number of cells, each of which is further divided into a reactive and a non-reactive part. The reactive part is assumed to be a perfectly stirred reactor where reactions occur instantaneously. After the reaction occurs, the mixing process begins with a mixing time of . When the mixing time is less than the chemical characteristic time of the system , i.e., , is close to 1, indicating high mixing efficiency and the final composition being mainly determined by chemistry. Conversely, when , is close to zero.

[0102] The turbulent mixing time is defined as:

[0103]

[0104] where the effective dynamic viscosity is the sum of the laminar and turbulent dynamic viscosities, and is a model parameter typically set between 0.10 and 0.15. The reaction rate is calculated as:

[0105]

[0106] The mixture fraction of the reaction is defined as:

[0107]

[0108] where is the minimum residence time to sustain combustion, calculated by solving the following equation:

[0109]

[0110] The PaSR model is able to divide the computational cells into reactive and non-reactive parts. This is particularly important for use in industrial simulations as the grid size is often a limiting factor. By considering the mixing and chemical time scales, the PaSR model can be used in a wide range of reactive flows without the need for "a priori" knowledge of the flow type.

[0111] The reaction rate is independent of concentration and typically uses the Arrhenius empirical equation based on the pre-exponential constant , temperature index and activation energy are calculated as follows:

[0112]

[0113] Refer to Figure 6 , Figure 6 which is a schematic flow chart of a multi - physical - field unified modeling and coupling simulation method for a turbofan engine provided by an embodiment of the present application. The method includes the following steps:

[0114] S601, construct the geometric models of the whole turbofan engine and its components.

[0115] S602, perform grid discretization on the physical space of the geometric model to obtain the grid system of the geometric model.

[0116] S603, discretize the initial control equation set based on the finite volume method and the grid system to obtain the discretized control equation set.

[0117] S604, according to the initial distribution of each physical field, perform time - marching iterative solution on the discretized control equation set to obtain the spatial distribution of each physical field.

[0118] S605, determine the simulation results of the whole turbofan engine and its components based on the spatial distribution of each physical field.

[0119] It should be understood that although the steps in the flow charts involved in the above - mentioned embodiments are shown in sequence according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless there is a clear description in this article, the execution of these steps has no strict order limit, and these steps can be executed in other orders. Moreover, at least a part of the steps in the flow charts involved in the above - mentioned embodiments may include multiple steps or multiple stages. These steps or stages are not necessarily executed at the same moment, but can be executed at different moments, and the execution order of these steps or stages is not necessarily sequential, but can be executed alternately or in turn with at least a part of other steps or steps or stages in other steps.

[0120] Based on the same inventive concept, an embodiment of the present application also provides a multi - physical - field simulation device for implementing the above - mentioned multi - physical - field simulation method. The solution provided by this device for solving problems is similar to the solution recorded in the above method. Therefore, the specific limitations in one or more embodiments of the multi - physical - field simulation device provided below can refer to the limitations on the multi - physical - field simulation method in the above text, and will not be repeated here.

[0121] In one embodiment, as Figure 7 shown,Figure 7 It is a structural block diagram of a multi - physical - field simulation device provided by an embodiment of the present application. The device 700 includes:

[0122] A geometric model construction module 701, configured to construct geometric models of the whole turbofan engine and its components.

[0123] A grid discretization module 702, configured to perform grid discretization on the physical space of the geometric model to obtain a grid system of the geometric model.

[0124] A first determination module 703, configured to determine the spatial distribution of each physical field according to the discrete control equations of multiple physical fields of the grid system.

[0125] A second determination module 704, configured to determine the simulation results of the whole turbofan engine and its components based on the spatial distribution of each physical field.

[0126] In one embodiment, the first determination module 703 includes:

[0127] An acquisition unit, configured to acquire the initial distribution of each physical field.

[0128] An iterative solution unit, configured to perform time - marching iterative solution on the discrete control equations according to the initial distribution of each physical field to obtain the spatial distribution of each physical field.

[0129] In one embodiment, the iterative solution unit includes:

[0130] A first solution sub - unit, configured to solve the discrete control equations according to the initial distribution of each physical field within each time step to obtain the intermediate distribution of each physical field.

[0131] A second solution sub - unit, configured to use the intermediate distribution as the initial distribution of each physical field, solve the discrete control equations according to the initial distribution of each physical field until the iteration condition is satisfied, and determine the spatial distribution of each physical field according to the intermediate distribution of each physical field obtained from the last solution.

[0132] In one embodiment, the device 700 further includes:

[0133] An acquisition module, configured to acquire the initial control equations of multiple physical fields in the physical space.

[0134] A control equation discretization module, configured to discretize the initial control equations based on the finite volume method and the grid system to obtain the discrete control equations.

[0135] In one embodiment, the physical field includes at least one of an aerodynamic field, a heat transfer field, a combustion reaction field, a phase - change component field, and a solid stress field.

[0136] In one embodiment, the discrete control equation set includes at least one of a mass equation, a component equation, a momentum equation, an energy equation, and a turbulence model control equation.

[0137] Each module in the above multi-physical field simulation device can be implemented in whole or in part by software, hardware, and their combination. Each of the above modules can be embedded in the processor of the computer device in hardware form or be independent of it, or can be stored in the memory of the computer device in software form, so that the processor can call and execute the operations corresponding to each of the above modules.

[0138] In one embodiment, a computer device is provided, including a memory and a processor. A computer program is stored in the memory. When the processor executes the computer program, the following steps are implemented:

[0139] Construct the geometric models of the whole turbofan engine and its components;

[0140] Perform grid discretization on the physical space of the geometric model to obtain the grid system of the geometric model;

[0141] Determine the spatial distribution of each physical field according to the discrete control equation set of multiple physical fields of the grid system;

[0142] Determine the simulation results of the whole turbofan engine and its components based on the spatial distribution of each physical field.

[0143] In one embodiment, when the processor executes the computer program, the following steps are also implemented:

[0144] Obtain the initial distribution of each physical field;

[0145] According to the initial distribution of each physical field, perform time marching iterative solution on the discrete control equation set to obtain the spatial distribution of each physical field.

[0146] In one embodiment, when the processor executes the computer program, the following steps are also implemented:

[0147] In each time step, according to the initial distribution of each physical field, solve the discrete control equation set to obtain the intermediate distribution of each physical field;

[0148] Take the intermediate distribution as the initial distribution of each physical field, and according to the initial distribution of each physical field, solve the discrete control equation set until the iteration condition is satisfied. Determine the spatial distribution of each physical field according to the intermediate distribution of each physical field obtained from the last solution.

[0149] In one embodiment, when the processor executes the computer program, the following steps are also implemented:

[0150] Obtain the initial control equation set of multiple physical fields in the physical space;

[0151] The initial control equations are discretized based on a grid system to obtain discretized control equations.

[0152] In one embodiment, the physical field includes at least one of an aerodynamic field, a heat transfer field, a combustion reaction field, a phase change component field, and a solid stress field.

[0153] In one embodiment, the discretized control equations include at least one of a mass equation, a component equation, a momentum equation, an energy equation, and a turbulence model control equation.

[0154] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the following steps are implemented:

[0155] Construct geometric models of the whole turbofan engine and its components;

[0156] Perform grid discretization on the physical space of the geometric models to obtain a grid system of the geometric models;

[0157] Determine the spatial distributions of the physical fields according to the discretized control equations of multiple physical fields of the grid system;

[0158] Determine the simulation results of the whole turbofan engine and its components based on the spatial distributions of the physical fields.

[0159] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented:

[0160] Obtain the initial distributions of the physical fields;

[0161] According to the initial distributions of the physical fields, perform time marching iterative solution on the discretized control equations to obtain the spatial distributions of the physical fields.

[0162] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented:

[0163] In each time step, according to the initial distributions of the physical fields, solve the discretized control equations to obtain the intermediate distributions of the physical fields;

[0164] Use the intermediate distributions as the initial distributions of the physical fields, and according to the initial distributions of the physical fields, solve the discretized control equations until the iteration conditions are met. Determine the spatial distributions of the physical fields according to the intermediate distributions of the physical fields obtained from the last solution.

[0165] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented:

[0166] Obtain the initial control equations of multiple physical fields in the physical space;

[0167] Discretize the initial control equations based on the grid system to obtain the discretized control equations.

[0168] In one embodiment, the physical field includes at least one of an aerodynamic field, a heat transfer field, a combustion reaction field, a phase change component field, and a solid stress field.

[0169] In one embodiment, the discretized control equations include at least one of a mass equation, a component equation, a momentum equation, an energy equation, and a turbulence model control equation.

[0170] In one embodiment, a computer program product is provided, including a computer program which, when executed by a processor, implements the following steps:

[0171] Construct the geometric models of the whole turbofan engine and its components;

[0172] Perform grid discretization on the physical space of the geometric models to obtain the grid system of the geometric models;

[0173] Determine the spatial distributions of the respective physical fields according to the discretized control equations of multiple physical fields of the grid system;

[0174] Determine the simulation results of the whole turbofan engine and its components based on the spatial distributions of the respective physical fields.

[0175] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented:

[0176] Obtain the initial distributions of the respective physical fields;

[0177] According to the initial distributions of the respective physical fields, perform time marching iterative solution on the discretized control equations to obtain the spatial distributions of the respective physical fields.

[0178] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented:

[0179] Within each time step, according to the initial distributions of the respective physical fields, solve the discretized control equations to obtain the intermediate distributions of the respective physical fields;

[0180] Take the intermediate distributions as the initial distributions of the respective physical fields, and according to the initial distributions of the respective physical fields, solve the discretized control equations until the iteration conditions are met, and determine the spatial distributions of the respective physical fields according to the intermediate distributions of the respective physical fields obtained from the last solution.

[0181] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented:

[0182] Obtain the initial control equations of multiple physical fields in the physical space;

[0183] The initial control equations are discretized based on a grid system to obtain the discretized control equations.

[0184] In one embodiment, the physical field includes at least one of an aerodynamic field, a heat transfer field, a combustion reaction field, a phase change component field, and a solid stress field.

[0185] In one embodiment, the discretized control equations include at least one of a mass equation, a component equation, a momentum equation, an energy equation, and a turbulence model control equation.

[0186] Those of ordinary skill in the art can understand that all or part of the processes in the methods of the above embodiments can be completed by instructing relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above methods. Among them, any reference to a memory, a database, or other media provided in the various embodiments of the present application can include at least one of non-volatile and volatile memories. Non-volatile memories can include read-only memory (ROM), magnetic tapes, floppy disks, flash memories, optical memories, high-density embedded non-volatile memories, resistive random access memories (ReRAM), magnetoresistive random access memories (MRAM), ferroelectric random access memories (FRAM), phase change memories (PCM), graphene memories, etc. Volatile memories can include random access memory (RAM) or external cache memories, etc. By way of illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM), etc. The databases involved in the various embodiments provided in the present application can include at least one of relational databases and non-relational databases. Non-relational databases can include distributed databases based on blockchain, etc., and are not limited thereto. The processors involved in the various embodiments provided in the present application can be general-purpose processors, central processors, graphics processors, digital signal processors, programmable logic devices, data processing logics based on quantum computing, etc., and are not limited thereto.

[0187] The technical features of the above embodiments can be combined arbitrarily. For the sake of concise description, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, it should be considered as the scope described in this specification.

[0188] The above-described embodiments merely represent several implementation manners of the present application. The description is relatively specific and detailed, but it should not be construed as a limitation on the scope of the patent of the present application. It should be noted that for those of ordinary skill in the art, without departing from the concept of the present application, several modifications and improvements can still be made, and these all belong to the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the appended claims.

Claims

1. A multi-physics field simulation method, characterized in that: The method comprises: Construct geometric models of the whole turbofan engine and its components; Performing grid discretization on the physical space of the geometric model to obtain a grid system of the geometric model; Determining the spatial distribution of each of the physical fields according to a discrete control equation group of the multiple physical fields of the grid system; The simulation results of the whole machine and each component of the turbofan engine are determined based on the spatial distribution of each physical field.

2. The method according to claim 1, characterized in that Determining the spatial distribution of each of the physical fields according to the discrete control equations of the multiple physical fields of the grid system comprises: Obtaining the initial distribution of each of the physical fields; According to the initial distribution of each of the physical fields, the discrete control equations are solved by time-marching iteration to obtain the spatial distribution of each of the physical fields.

3. The method according to claim 2, characterized in that The step of performing time-marching iterative solutions on the discrete control equations according to the initial distribution of each of the physical fields to obtain the spatial distribution of each of the physical fields comprises: In each time step, according to the initial distribution of each physical field, the discrete control equations are solved to obtain the intermediate distribution of each physical field; The intermediate distribution is used as the initial distribution of each of the physical fields. According to the initial distribution of each of the physical fields, the discrete control equations are solved until the iteration condition is met. The spatial distribution of each of the physical fields is determined according to the intermediate distribution of each of the physical fields obtained by the last solution.

4. The method according to claim 1, characterized in that The method further comprises: Obtaining an initial control equation set of a plurality of physical fields in the physical space; The initial control equations are discretized based on the finite volume method and the grid system to obtain the discrete control equations.

5. The method according to any one of claims 1 to 4, characterized in that: The physical field includes at least one of an aerodynamic field, a heat transfer field, a combustion reaction field, a phase change component field and a solid stress field.

6. The method according to any one of claims 1 to 4, characterized in that: The discrete control equations include at least one of a mass equation, a component equation, a momentum equation, an energy equation, and a turbulence model control equation.

7. A multi-physics field simulation device, characterized in that: The device comprises: The geometric model building module is used to build the geometric model of the whole machine and each component of the turbofan engine; A grid discretization module, used for performing grid discretization on the physical space of the geometric model to obtain a grid system of the geometric model; A first determination module is used to determine the spatial distribution of each of the physical fields according to a discrete control equation group of the multiple physical fields of the grid system; The second determination module is used to determine the simulation results of the whole machine and each component of the turbofan engine based on the spatial distribution of each physical field.

8. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 6 are implemented.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

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