Compressor flow field numerical determination method, device, equipment and storage medium

Abstract

The present application is applicable to the technical field of numerical simulation of flow field of compressor, and provides a method, device, equipment and storage medium for determining the flow field value of compressor, the method comprising: constructing a three-dimensional model of compressor; selecting a single flow channel model from the three-dimensional model as a calculation model, the single flow channel model is obtained by dividing according to the blades of the compressor; constructing the fluid control equation of the air flow inside the calculation model; introducing the S‑A turbulence model into the fluid control equation to construct the turbulence control equation; solving the fluid control equation and the turbulence control equation to obtain the flow field value of the calculation model. In this way, only one of the single flow channel models needs to be calculated for the three-dimensional model of the entire compressor, which reduces the amount of calculation. Moreover, by introducing the S‑A turbulence model into the fluid control equation to construct the turbulence control equation, and then solving the fluid control equation and the turbulence control equation to obtain the flow field value of the calculation model, the accuracy of the calculated flow field value is improved.

Description

Technical Field

[0001] The present application belongs to the technical field of numerical simulation of flow fields of compressors, and in particular, relates to a method, device, equipment and storage medium for determining flow field values ​​of a compressor. Background Art

[0002] The function of the compressor is to compress the inhaled gas and greatly increase the speed and pressure of the compressed gas through the high-speed rotation of the turbine blades. The compressor is a key component of an aircraft engine, and improving the performance of the compressor is the main means to improve the performance of an aircraft engine. The design of a high-performance compressor relies heavily on the numerical calculation results of the compressor flow field, so how to calculate the compressor flow field numerical value with high precision becomes an important issue.

[0003] In related technologies, the MRF (Moving reference, multiple reference system) method is usually used to calculate the flow field values ​​of the compressor. In the MRF method, the rotating body does not actually move during the calculation process, and the calculation is achieved by setting multiple reference systems. For example, a three-dimensional model of the compressor is first constructed, and then the fluid control equation of the air flow inside the three-dimensional model is established. After that, the multiple reference system method is used to solve the process control equation to obtain the flow field value of the compressor.

[0004] However, the above method of using the multiple reference system method to solve the process control equations of the entire three-dimensional model to calculate the flow field values ​​of the compressor has a large amount of calculation and low calculation accuracy. Summary of the invention

[0005] The embodiments of the present application provide a method, device, equipment and storage medium for determining the flow field values ​​of a compressor, which can solve the problem of low calculation accuracy of the flow field values ​​of the compressor existing in the related art.

[0006] In a first aspect, an embodiment of the present application provides a method for determining a flow field value of a compressor, the method comprising:

[0007] Construct a 3D model of the compressor;

[0008] Selecting a single-channel model from the three-dimensional model as a calculation model, wherein the single-channel model is obtained by dividing according to the blades of the compressor;

[0009] Constructing a fluid control equation for air flow inside the computational model;

[0010] Introducing the SA turbulence model into the fluid control equation to construct the turbulence control equation;

[0011] The fluid control equation and the turbulence control equation are solved to obtain the flow field value of the calculation model.

[0012] Optionally, the SA turbulence model is introduced into the fluid control equation to construct the turbulence control equation, including:

[0013] Performing time-average processing on the fluid control equation to obtain a time-averaged fluid control equation;

[0014] Introducing the SA turbulence model into the time-averaged fluid control equation to construct the turbulence control equation;

[0015] The step of solving the fluid control equation and the turbulence control equation to obtain the flow field value of the calculation model includes:

[0016] The time-averaged fluid control equation and the turbulence control equation are solved to obtain the flow field value of the calculation model.

[0017] Optionally, the time-averaged fluid control equations include a mass equation, a momentum equation and a state equation.

[0018] Optionally, the mass equation is:

[0019]

[0020] in, is the gradient, ρ is the air density, is the average speed of air;

[0021] The momentum equation is:

[0022]

[0023] in, is the gradient, p is the air pressure, is the time-averaged velocity of the air, τ is the viscosity of the air;

[0024] The state equation is:

[0025] p=ρRT

[0026] Where p is the air pressure, T is the air temperature, and R is the gas constant.

[0027] Optionally, the turbulence control equation is the following equation:

[0028]

[0029] in, is the gradient, ρ is the air density, is the average speed of air, is the transport variable in the SA turbulence model, is the optimized vorticity size, d is the distance to the nearest surface, and f w is a function of d, σ, C b1 , C b2 , C w1 are all constants;

[0030] in, S is the vorticity size, v is the molecular viscosity, k, C v1 is a constant;

[0031] in, g=r+C w2 (r 6 -r), C w2 , C w3 is a constant.

[0032] Optionally, before solving the fluid control equation and the turbulence control equation to obtain the flow field value of the calculation model, the method further includes:

[0033] constructing boundary conditions of the computational model;

[0034] The step of solving the fluid control equation and the turbulence control equation to obtain the flow field value of the calculation model includes:

[0035] Discretizing the fluid control equation, the turbulence control equation and the boundary condition to obtain a linear matrix;

[0036] The linear matrix is ​​solved by using a multi-grid method to obtain the flow field value of the calculation model.

[0037] Optionally, the boundary conditions include:

[0038] The inlet boundary conditions of the calculation model are:

[0039] U inlet = Speed ​​threshold

[0040]

[0041]

[0042] Among them, U inlet is the inlet air velocity, p 总 is the total inlet air pressure, p 静 is the inlet air static pressure, U is the outlet air velocity, T 总 is the total inlet air temperature, T 静 is the static temperature of the outlet air, γ is the specific heat capacity of the air, and Ma is the Mach number;

[0043] The outlet boundary conditions of the calculation model are:

[0044]

[0045]

[0046]

[0047] in, is the gradient, U outlet is the outlet air velocity, p outlet is the outlet air pressure, T outlet is the outlet air temperature.

[0048] Optionally, the boundary condition further includes:

[0049] The boundary conditions of the blade flow path surface of the calculation model are periodic boundary conditions;

[0050] The boundary conditions of the blades, hub and casing of the calculation model are wall boundary conditions.

[0051] Optionally, the discretizing the fluid control equation, the turbulence control equation and the boundary condition comprises:

[0052] The velocity gradient term and the pressure gradient term in the fluid control equation, the turbulence control equation and the boundary condition are discretized in a restricted discretization manner;

[0053] The velocity convection term in the fluid control equation, the turbulence control equation and the boundary condition is discretized using a second-order central difference format;

[0054] The fluid control equation, the turbulence control equation and the pressure convection term in the boundary condition are discretized using a second-order upwind scheme.

[0055] Optionally, before establishing the fluid control equation of the air flow inside the calculation model, the method further includes:

[0056] Performing gridding processing on the calculation model to obtain a gridded calculation model;

[0057] The fluid control equation for establishing the air flow inside the calculation model includes:

[0058] The fluid control equations within the gridded computational model are established.

[0059] Optionally, before the multi-grid method is used to solve the fluid control equation and the turbulence control equation to obtain the flow field value of the calculation model, the method further includes:

[0060] dividing the computational model into a rotational part and a non-rotational part;

[0061] Converting the absolute speed in the fluid control equation and the turbulence control equation of the rotating part into the sum of the relative speed and the coordinate system speed, wherein the coordinate system speed refers to the rotation speed of the rotating coordinate system constructed for the calculation model;

[0062] The absolute velocities in the fluid governing equations and turbulence governing equations of the non-rotating portion are converted into the coordinate system velocities.

[0063] In a second aspect, an embodiment of the present application provides a flow field value determination device for a compressor, the device comprising:

[0064] A first building module is used to build a three-dimensional model of the compressor;

[0065] A selection module, used to select a single flow channel model from the three-dimensional model as a calculation model, wherein the single flow channel model is obtained by dividing according to the blades of the compressor;

[0066] A second construction module is used to construct a fluid control equation for the air flow inside the calculation model;

[0067] A third building block is used to introduce the SA turbulence model into the fluid control equation to construct the turbulence control equation;

[0068] The solution module is used to solve the fluid control equation and the turbulence control equation by using a multi-grid method to obtain the flow field value of the calculation model.

[0069] Optionally, the third building block includes:

[0070] A time-average processing unit, used for performing time-average processing on the fluid control equation to obtain a time-averaged fluid control equation;

[0071] A construction unit, used for introducing the SA turbulence model into the time-averaged fluid control equation to construct the turbulence control equation;

[0072] The solver module is used to:

[0073] The time-averaged fluid control equation and the turbulence control equation are solved to obtain the flow field value of the calculation model.

[0074] Optionally, the time-averaged fluid control equations include a mass equation, a momentum equation and a state equation.

[0075] Optionally, the mass equation is:

[0076]

[0077] in, is the gradient, ρ is the air density, is the average speed of air;

[0078] The momentum equation is:

[0079]

[0080] in, is the gradient, p is the air pressure, is the time-averaged velocity of the air, τ is the viscosity of the air;

[0081] The state equation is:

[0082] p=ρRT

[0083] Where p is the air pressure, T is the air temperature, and R is the gas constant.

[0084] Optionally, the turbulence control equation is the following equation:

[0085]

[0086] in, is the gradient, ρ is the air density, is the average speed of air, is the transport variable in the SA turbulence model, is the optimized vorticity size, d is the distance to the nearest surface, and f w is a function of d, σ, C b1 , C b2 , C w1 are all constants;

[0087] in, S is the vorticity size, v is the molecular viscosity, k, C v1 is a constant;

[0088] in, g=r+C w2 (r 6 -r), C w2 , C w3 is a constant.

[0089] Optionally, the device further comprises:

[0090] A fourth construction module, used to construct boundary conditions of the calculation model;

[0091] The solution module includes:

[0092] A discrete processing unit, used for performing discrete processing on the fluid control equation, the turbulence control equation and the boundary condition to obtain a linear matrix;

[0093] The solving unit is used to solve the linear matrix by adopting a multi-grid method to obtain the flow field value of the calculation model.

[0094] Optionally, the boundary conditions include:

[0095] The inlet boundary conditions of the calculation model are:

[0096] U inlet = Speed ​​threshold

[0097]

[0098]

[0099] Among them, U inlet is the inlet air velocity, p 总 is the total inlet air pressure, p 静 is the inlet air static pressure, U is the outlet air velocity, T 总 is the total inlet air temperature, T 静 is the static temperature of the outlet air, γ is the specific heat capacity of the air, and Ma is the Mach number;

[0100] The outlet boundary conditions of the calculation model are:

[0101]

[0102]

[0103]

[0104] in, is the gradient, U outlet is the outlet air velocity, p outlet is the outlet air pressure, T outlet is the outlet air temperature.

[0105] Optionally, the boundary condition further includes:

[0106] The boundary conditions of the blade flow path surface of the calculation model are periodic boundary conditions;

[0107] The boundary conditions of the blades, hub and casing of the calculation model are wall boundary conditions.

[0108] Optionally, the discrete processing unit is used to:

[0109] The velocity gradient term and the pressure gradient term in the fluid control equation, the turbulence control equation and the boundary condition are discretized in a restricted discretization manner;

[0110] The velocity convection term in the fluid control equation, the turbulence control equation and the boundary condition is discretized using a second-order central difference format;

[0111] The fluid control equation, the turbulence control equation and the pressure convection term in the boundary condition are discretized using a second-order upwind scheme.

[0112] Optionally, the device further comprises:

[0113] A gridding module, used for performing gridding processing on the calculation model to obtain a gridded calculation model;

[0114] The second building block is used to:

[0115] The fluid control equations within the gridded computational model are established.

[0116] Optionally, the device further comprises:

[0117] A division module, used for dividing the calculation model into a rotation part and a non-rotation part;

[0118] A first speed conversion module, used for converting the absolute speed in the fluid control equation and the turbulence control equation of the rotating part into the sum of the relative speed and the coordinate system speed, wherein the coordinate system speed refers to the rotation speed of the rotating coordinate system constructed for the calculation model;

[0119] The second speed conversion module is used to convert the absolute speed in the fluid control equation and the turbulence control equation of the non-rotating part into the coordinate system speed.

[0120] In a third aspect, an embodiment of the present application provides an electronic device, comprising a processor, a memory, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the method for numerically determining the flow field of any compressor described in the first aspect above is implemented.

[0121] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, characterized in that the computer-readable storage medium stores instructions, which, when executed on a computer, enable the computer to execute any one of the methods for determining the flow field numerical value of a compressor described in the first aspect.

[0122] In a fifth aspect, an embodiment of the present application provides a computer program product, which, when executed on a computer device, enables the computer device to execute any of the methods described in the first aspect above.

[0123] Compared with the prior art, the embodiments of the present invention have the following beneficial effects:

[0124] In an embodiment of the present application, a three-dimensional model of a compressor can be constructed, and a single-channel model can be selected from the three-dimensional model as a calculation model. Then, a fluid control equation for the air flow inside the calculation model is constructed, and the SA turbulence model is introduced into the fluid control equation to construct the turbulence control equation. The fluid control equation and the turbulence control equation are then solved to obtain the flow field values ​​of the calculation model. In this way, only one single-channel model needs to be calculated for the three-dimensional model of the entire compressor, which reduces the amount of calculation. Moreover, by introducing the SA turbulence model into the fluid control equation to construct the turbulence control equation, and then solving the fluid control equation and the turbulence control equation to obtain the flow field values ​​of the calculation model, the accuracy of the calculated flow field values ​​is improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0125] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0126] Figure 1 It is a flow chart of a method for determining flow field values ​​of a compressor provided in an embodiment of the present application;

[0127] Figure 2 is a schematic diagram of a three-dimensional model of a compressor provided in an embodiment of the present application;

[0128] Figure 3 is a schematic diagram of a single flow channel model provided in an embodiment of the present application;

[0129] Figure 4 is a flow chart of another method for determining flow field values ​​of a compressor provided in an embodiment of the present application;

[0130] Figure 5 is a schematic diagram of a gridded computing model provided in an embodiment of the present application;

[0131] Figure 6 is a schematic diagram of boundary conditions of a calculation model provided in an embodiment of the present application;

[0132] Figure 7It is a schematic diagram comparing the total pressure ratio of the flow field numerically calculated and the experimental total pressure ratio determined by the method provided in the example of this application;

[0133] Figure 8 It is a block diagram of a device for determining flow field values ​​of a compressor provided in an embodiment of the present application;

[0134] Fig. 9 It is a structural block diagram of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0135] In the following description, specific details such as specific system structures, technologies, etc. are provided for the purpose of illustration rather than limitation, so as to provide a thorough understanding of the embodiments of the present application. However, it should be clear to those skilled in the art that the present application may also be implemented in other embodiments without these specific details. In other cases, detailed descriptions of well-known systems, devices, circuits, and methods are omitted to prevent unnecessary details from obstructing the description of the present application.

[0136] It should be understood that in the description of the present application specification and the attached claims, the terms "first", "second", "third", etc. are only used to distinguish the description and cannot be understood as indicating or implying relative importance. The terms "including", "comprising", "having" and their variations all mean "including but not limited to", unless otherwise specifically emphasized in other ways. The references to "one embodiment" or "some embodiments", etc. described in the present application specification mean that one or more embodiments of the present application include specific features, structures or characteristics described in conjunction with the embodiment. Therefore, the statements "in one embodiment", "in some embodiments", "in some other embodiments", "in some other embodiments", etc. that appear in different places in this specification do not necessarily refer to the same embodiment, but mean "one or more but not all embodiments", unless otherwise specifically emphasized in other ways.

[0137] First, the application scenarios involved in the embodiments of the present application are described.

[0138] The compressor mainly uses high-speed rotating blades to work on the air to increase the air pressure. The compressor includes a rotor and a casing. The rotor is provided with a number of blades. The casing is provided with an inlet and an outlet for the air flow. The ratio of the total pressure of the air at the compressor outlet to the total pressure of the air at the inlet is called the total pressure ratio of the compressor.

[0139] The flow field of a compressor refers to the spatial distribution of the airflow inside the compressor. The flow field values ​​include velocity, pressure, temperature and other values ​​of the flow field.

[0140] In actual operation, the compressor blades have extremely high rotation speeds, and the tip speed of the compressor blades can reach 500m / s. The overall flow field distribution near the compressor is relatively complex. Since the overall flow velocity distribution crosses the speed of sound, shock wave effects are easily formed around the blades, and the numerical calculation of the flow field includes the rotation of the blades, which makes numerical solutions difficult. There are two main problems in the overall numerical calculation process: the stability of the calculation process and the rotation processing of the rotating blades.

[0141] In the process of calculating flow field data values, it is mainly divided into transient calculation and steady-state calculation according to the time term. Transient calculation can show the changes of flow field during the calculation process, but its calculation amount is generally large. Steady-state calculation mainly obtains the results when the flow field is stable, its calculation amount is small, and the calculation stability requirement is better, but the change process of the entire flow field cannot be observed.

[0142] In the prior art, there are three main processing technologies for the rotating part, FRT (Frozen Rotor Technique), MPA (Mixing Plane Apporach) and DM (dynamic mesh). The representative method of the fixed rotor technology and the mixed plane technology is the multiple reference system method. In this method, the rotating body does not actually move during the calculation process. The calculation is achieved by setting multiple reference systems. This method is mainly used for steady-state calculations and has a low calculation cost. In the dynamic mesh technology, the grid actually rotates during the calculation. It is mainly used for transient calculations. Compared with the other two methods, it has higher accuracy and can accurately display the flow field change trend during the rotation process, but its calculation time is about 30 times that of the steady-state calculation time.

[0143] In this application, the main focus is on the performance of the entire compressor, that is, the total pressure ratio obtained by compressing the gas after the compressor runs stably, so a steady-state calculation method can be used.

[0144] In the actual operating environment of high speed, high pressure and rotation, the stability of numerical calculation becomes a big problem. At present, most calculations for compressors adopt the method of multiple reference systems. This method has high requirements on calculation stability but low calculation accuracy. How to ensure calculation stability and calculation accuracy is the main problem to be solved in this application.

[0145] In addition, currently, professional software provided by enterprises is mainly used to calculate the flow field values ​​of compressors, and this software has low portability and scalability.

[0146] Next, the method for determining the flow field value of the compressor provided in the embodiment of the present application is described in detail. Figure 1 , Figure 11 is a flow chart of a method for determining the flow field value of a compressor provided in an embodiment of the present application. The method can be applied to an electronic device, which can be a terminal device or a server, etc. The terminal device can be a mobile phone, a tablet computer or a computer, etc. Figure 1 As shown, the method comprises the following steps:

[0147] Step 101: Construct a three-dimensional model of the compressor.

[0148] As an example, a geometry description file of a compressor may be established, and a three-dimensional model of the compressor may be constructed based on the geometry description file.

[0149] It should be noted that since a compressor is usually provided with a plurality of blades evenly distributed inside, the entire flow field of the compressor is usually evenly distributed on the plurality of blades, and the three-dimensional model can be divided into a plurality of flow channel models according to the number of blades. Each flow channel model includes a blade and the flow field distributed on the blade.

[0150] For example, the geometric description file of the rotor model of rotor37 can be used, and the three-dimensional model of the compressor constructed based on the geometric description file is as follows: Figure 2 The rotor model of rotor37 includes 37 blades, which are evenly distributed. Please refer to Figure 2 , the entire three-dimensional model of the compressor is cylindrical in shape, and the entire flow field of the three-dimensional model is uniformly distributed.

[0151] Step 102: Select a single-channel model from the three-dimensional model as a calculation model. The single-channel model is obtained by dividing according to the blades of the compressor.

[0152] Since the entire flow field of the compressor is uniformly distributed, a single flow channel model can be selected from the three-dimensional model as the calculation model, and the flow field values ​​of the entire compressor can be simulated based on the flow field values ​​of the single flow channel model. In this way, the amount of calculation can be reduced. Figure 2 A single flow path model selected in the three-dimensional model of the compressor shown can be Figure 3 shown.

[0153] Step 103: Construct a fluid control equation for the air flow inside the computational model.

[0154] In this computational model, the computational problem type is compressible supersonic fluid. When the steady-state equation is used for solution, there will be no time term. The fluid control equations may include mass equation, momentum equation and state equation.

[0155] Among them, the mass equation, momentum equation and state equation are shown in the following formula (1), formula (2) and formula (3) respectively:

[0156]

[0157]

[0158] p=ρRT (3)

[0159] in, is the gradient, ρ is the air density, U is the air velocity, p is the air pressure, τ is the viscous force of the air, T is the air temperature, and R is the gas constant. For example, R = 8.3144626 J / (K·mol).

[0160] Among them, U, P, T and τ are the unknowns to be solved, that is, the flow field values ​​to be solved.

[0161] Among them, τ can include turbulent stress, Reynolds stress, sub-grid stress, etc.

[0162] In another embodiment, after selecting a single flow channel model from the three-dimensional model as the calculation model, the calculation model may be gridded to obtain a gridded calculation model, and then the fluid control equations within the gridded calculation model are established. The specific implementation method will be described below. Figure 4 The details are described in the examples.

[0163] Step 104: Introduce the SA (Spalart-Allmaras) turbulence model into the fluid control equation to construct the turbulence control equation.

[0164] As an example, the turbine viscosity coefficient method can be used to model the subgrid stress τ in the viscous force using Smagorinsky's model to obtain the model of the subgrid stress τ. Then, based on the model of the subgrid stress τ and the momentum equation in the fluid control equation, the turbulence control equation is constructed. For example, the model of the subgrid stress τ is substituted into the above formula (2) as the viscous force to obtain the turbulence control equation.

[0165] In the embodiment of the present application, other stresses in the viscous force can be ignored, and the subgrid stress can be used as the viscous force. By modeling the subgrid stress τ, the four unknowns to be solved in the above fluid control equations can be simplified to three unknowns, namely U, P, and T.

[0166] For example, the operation of introducing the SA turbulence model into the fluid control equation includes the following steps:

[0167] 1) The turbine viscosity coefficient method is used to model the subgrid stress τ using the Smagorinsky's model, and the model of the subgrid stress τ is obtained as shown in the following formula (4):

[0168]

[0169] Where τ is the subgrid stress, v T is the eddy viscosity and U is the air velocity.

[0170] In the model shown in the above formula (4), v T It can be expressed as the following formula (5):

[0171]

[0172] in, is the transport variable in the SA turbulence model, v is the molecular viscosity, C v1 is a constant.

[0173] 2) According to the above formula (4), formula (5) and formula (2), the turbulence control equation shown in the following formula (6) can be obtained:

[0174]

[0175] in, is the gradient, ρ is the air density, U is the air velocity, is the transport variable in the SA turbulence model, is the optimized vorticity size, d is the distance to the nearest surface, and f w is a function of d, σ, C b1 , C b2 , C w1 are all constants.

[0176] in, S is the vorticity size, v is the molecular viscosity, k, C v1 is a constant.

[0177] in, g=r+C w2 (r 6 -r), C w2 , C w3 is a constant.

[0178] In another embodiment, after constructing the fluid control equation for the air flow in the calculation model, the fluid control equation may be first time-averaged to obtain the time-averaged fluid control equation, and then the SA turbulence model may be introduced into the time-averaged fluid control equation to construct the turbulence control equation. The specific implementation method will be described below. Figure 4 The details are described in the examples.

[0179] Step 105: Solve the fluid control equation and the turbulence control equation to obtain the flow field value of the calculation model.

[0180] As an example, the fluid control equation and the turbulence control equation can be discretized to obtain a discretized linear matrix, and then the multi-grid method is used to solve the discretized linear matrix to obtain the flow field value of the compressor.

[0181] By introducing the SA turbulence model to close the above fluid control equations, the flow field values ​​of the calculation model can be realized, and the calculation accuracy of the flow field values ​​can be improved. For example, by introducing the SA turbulence model on the basis of the above formulas (1) to (3), the four equations of formulas (1) to (3) and (6) can be obtained. According to these four equations, the three unknowns U, P and T can be solved more accurately, thereby realizing the high-precision calculation of the flow field values ​​of the calculation model.

[0182] In an embodiment of the present application, a three-dimensional model of a compressor can be constructed, and a single-channel model can be selected from the three-dimensional model as a calculation model. Then, a fluid control equation for the air flow inside the calculation model is constructed, and the SA turbulence model is introduced into the fluid control equation to construct the turbulence control equation. The fluid control equation and the turbulence control equation are then solved to obtain the flow field values ​​of the calculation model. In this way, only one single-channel model needs to be calculated for the three-dimensional model of the entire compressor, which reduces the amount of calculation. Moreover, by introducing the SA turbulence model into the fluid control equation to construct the turbulence control equation, and then solving the fluid control equation and the turbulence control equation to obtain the flow field values ​​of the calculation model, the accuracy of the calculated flow field values ​​is improved.

[0183] Please refer to Figure 4 , Figure 4 1 is a flow chart of another method for determining the flow field value of a compressor provided in an embodiment of the present application. The method can be applied to an electronic device, which can be a terminal device or a server, etc. The terminal device can be a mobile phone, a tablet computer or a computer, etc. Figure 4 As shown, the method comprises the following steps:

[0184] Step 401: construct a three-dimensional model of the compressor.

[0185] Step 402: Select a single-channel model from the three-dimensional model as a calculation model. The single-channel model is obtained by dividing according to the blades of the compressor.

[0186] It should be noted that step 401-step 402 is the same as the above Figure 1 The same is true for steps 101 to 102 in the embodiment. The specific implementation process can refer to the above Figure 1 The description of step 101 to step 102 in the embodiment will not be repeated here in the embodiment of the present application.

[0187] Step 403: gridding the calculation model to obtain a gridded calculation model.

[0188] For example, a grid generation module may be used to grid the computational model to obtain a gridded computational model.

[0189] In addition, the computational model can be divided into a rotating part and a non-rotating part so that the two parts can be processed differently later. For example, a periodic boundary condition can be adopted for the rotating surface of the computational model to ensure the information exchange of the flow field during the rotation process.

[0190] As an example, in the process of meshing the computational model, the meshes of each face of the computational model may be divided into mesh attributes, and the mesh attributes may include rotation attributes and non-rotation attributes, so as to divide the meshed computational model into rotational parts and non-rotational parts according to the mesh attributes.

[0191] For example, a gridded computational model can be Figure 5 As shown. Among them, Figure 5 Figure (a) and Figure 5 Figure (b) is a schematic diagram of the gridded computational model at different angles.

[0192] Step 404: Establish the fluid control equations within the gridded computational model.

[0193] The fluid control equations within the gridded computational model may include a mass equation, a momentum equation, and a state equation. For example, the mass equation, the momentum equation, and the state equation may be shown in the above formulas (1) to (3), respectively.

[0194] Step 405: Perform time-average processing on the fluid control equation to obtain a time-averaged fluid control equation.

[0195] As an example, the mass equation and momentum equation in the fluid control equation may be time-averaged to obtain the time-averaged fluid control equation, so that the fluid control equation can be better solved.

[0196] The time averaging method used in the time averaging process may be the Reynolds time averaging method, or other time averaging methods, which is not limited in the embodiments of the present application.

[0197] For example, the fluid control equation is subjected to time-averaged processing, and the obtained time-averaged fluid control equation can be shown as the following formula (7) to formula (9):

[0198]

[0199]

[0200] p=ρRT (9)

[0201] in, is the gradient, ρ is the air density, is the time-averaged velocity of the air, p is the air pressure, τ is the viscosity of the air, T is the air temperature, and R is the gas constant. For example, R = 8.3144626 J / (K·mol).

[0202] Step 406: Introduce the SA turbulence model into the time-averaged fluid control equation to construct the turbulence control equation.

[0203] As an example, the turbine viscosity coefficient method can be used to model the subgrid stress τ in the viscous force using Smagorinsky's model to obtain the model of the subgrid stress τ. Then, based on the model of the subgrid stress τ and the momentum equation in the fluid control equation, the turbulence control equation is constructed. For example, the model of the subgrid stress τ is substituted into the above formula (8) as the viscous force to obtain the turbulence control equation.

[0204] For example, the operation of introducing the SA turbulence model into the fluid control equation includes the following steps:

[0205] 1) The turbine viscosity coefficient method is used to model the subgrid stress τ using the Smagorinsky's model, and the model of the subgrid stress τ is obtained as shown in the following formula (10):

[0206]

[0207] Where τ is the subgrid stress, v T is the eddy viscosity, is the average speed of air.

[0208] In the model shown in the above formula (10), v T It can be expressed as the following formula (11):

[0209]

[0210] in, is the transport variable in the SA turbulence model, v is the molecular viscosity, C v1 is a constant.

[0211] 2) According to the above formula (10), formula (11) and formula (8), the turbulence control equation shown in the following formula (12) can be obtained:

[0212]

[0213] in, is the gradient, ρ is the air density, is the average speed of air, is the transport variable in the SA turbulence model, is the optimized vorticity size, d is the distance to the nearest surface, and f w is a function of d, σ, C b1 , C b2 , C w1 are all constants.

[0214] in, S is the vorticity size, v is the molecular viscosity, k, C v1 is a constant;

[0215] in, g=r+C w2 (r 6 -r), C w2 , C w3 are constants. r and f w The maximum value reaches a constant, and the maximum value of r is 10.

[0216] In the above turbulence control equation, formula (12), on the right side of the equation, and They are mutually balanced terms. If the air flow is in a state of local equilibrium, the flow can be considered correct.

[0217] As an example, the values ​​of the relevant parameters in the above formula may be shown in Table 1 below:

[0218] Table 1

[0219]

[0220] It should be noted that Table 1 is only an example of an embodiment of the present application, and it is not sufficient to limit the above-mentioned related parameters. The values ​​of the related parameters in the above formula can also be set to other values ​​as needed, and the embodiment of the present application does not limit this.

[0221] Step 407: Construct boundary conditions of the calculation model.

[0222] According to the above fluid control equations and turbulence control equations, the boundary conditions of the calculation model can be established.

[0223] The boundary conditions of the calculation model may include one or more of an inlet boundary condition, an outlet boundary condition, and boundary conditions of each surface. The boundary conditions may be set as required.

[0224] For example, the inlet boundary condition is as shown in the following formula (13):

[0225]

[0226] Among them, U inlet is the inlet air velocity, p 总 is the total inlet air pressure, p 静 is the inlet air static pressure, U is the outlet air velocity, T 总 is the total inlet air temperature, T 静 is the static temperature of the outlet air, γ is the specific heat capacity of the air, Ma is the Mach number, 1 Mach is 1 times the speed of sound, and the value is equivalent to the speed divided by 340.

[0227] The speed threshold may be preset, for example, the speed threshold is 145 m / s. 总 =101325Pa, T 总 =288.15K.

[0228] For example, the exit boundary condition can be expressed as follows:

[0229]

[0230] in, is the gradient, U outlet is the outlet air velocity, p outlet is the outlet air pressure, T putlet is the outlet air temperature.

[0231] In addition, periodic boundary conditions can be used for the blade flow surface of the calculation model. Wall boundary conditions can be used for the blades, hub and shell parts of the calculation model. Please refer to Figure 6 , Figure 6 Shows Figure 3 Schematic diagram of the boundary conditions of the computational model shown.

[0232] Step 408: Use a multiple reference system method to perform speed conversion on the rotating part of the calculation model in different coordinate systems.

[0233] In the embodiment of the present application, a multiple reference method can be used for the rotating part of the calculation model. This method divides the entire calculation model into a rotating part and a non-rotating area, and the rotating part performs corresponding speed conversion.

[0234] For example, for the rotating part, the absolute speed in the fluid control equation and turbulence control equation of the rotating part is converted into the sum of the relative speed and the coordinate system speed. The coordinate system speed refers to the rotation speed of the rotating coordinate system constructed for the calculation model. For the non-rotating part, the absolute speed in the fluid control equation and turbulence control equation of the non-rotating part is converted into the coordinate system speed, that is, there is no need to perform speed conversion for the non-rotating part, and its absolute speed is the coordinate system speed. In this way, the conversion of coordinate speed is achieved without the blade actually rotating.

[0235] That is, for the rotating part, the absolute speed, relative speed and coordinate system speed satisfy the following formula (15):

[0236] U 绝对 =U 相对 +U 坐标系 (15)

[0237] For the non-rotating part, the absolute velocity and the coordinate system velocity satisfy the following formula (16):

[0238] U 绝对 =U 坐标系 (16)

[0239] Among them, U 绝对 is the absolute speed, U 相对 is the relative speed, U 坐标系 is the coordinate system velocity.

[0240] For example, for Figure 3 The calculation model shown, since the entire area of ​​the calculation model is a rotation area, the entire area satisfies the above formula (15).

[0241] Step 409: Discretize the fluid control equation, turbulence control equation and boundary conditions to obtain a linear matrix.

[0242] For example, in a gridded computational model, the fluid control equations, turbulence control equations, and boundary conditions can be discretized to obtain a linear matrix.

[0243] As an example, in the process of discretizing the fluid control equations, turbulence control equations and boundary conditions, the velocity gradient terms, pressure gradient terms, velocity convection terms and pressure convection terms in the fluid control equations, turbulence control equations and boundary conditions can be discretized using different discretization methods. For example, a restricted discretization method is used for the velocity gradient terms and the pressure gradient terms. A second-order central difference format is used for the velocity convection terms. A second-order upwind format is used for the pressure convection terms. Of course, other discretization methods can also be used for discretization, and the embodiments of the present application do not limit this.

[0244] Among them, the velocity gradient term can be expressed as The pressure gradient term can be expressed as The velocity convection term can be expressed as The pressure convection term can be expressed as

[0245] Step 410: Use a multi-grid method to solve the linear matrix to obtain the flow field value of the calculation model.

[0246] For example, by using the multi-grid method to solve the linear matrix, the values ​​of the three variables U, P, and T can be obtained.

[0247] After obtaining the flow field values ​​of the calculation model, the total pressure ratio of the compressor can be calculated based on the calculated flow field values. Figure 7 , Figure 7 It is a schematic diagram comparing the total pressure ratio calculated by numerical calculation of the flow field determined by the method provided in the example of this application and the total pressure ratio of the experiment, wherein the horizontal axis is the flow rate and the vertical axis is the total pressure ratio. Figure 7 The error between the calculated total pressure ratio and the experimental total pressure ratio can be shown in Table 2 below:

[0248] Table 2

[0249] flow Calculated total pressure ratio Experimental total pressure ratio error 19.85 2.194 2.136 2.7％ 20.11 2.197 2.115 3.8％ 20.17 2.199 2.111 4.2％ 20.29 2.186 2.100 4.1％ 20.57 2.165 2.086 3.7％ 20.61 2.164 2.072 4.4％ 20.19 2.199 2.106 4.4％

[0250] It can be seen from Table 2 above that the average error between the total pressure ratio calculated by the flow field values ​​determined by the method provided in the example of this application and the experimental total pressure ratio is 3.9%, and the error is about 4%, and the calculation accuracy is relatively high.

[0251] It should be noted that the method for determining the flow field value of the compressor provided in the embodiment of the present application can be completed based on open source software, such as based on the open source software OpenFOAM. The flow field numerical calculation platform of the compressor implemented based on open source software can be well transplanted to a large-scale computing cluster, with strong portability and scalability, and high calculation accuracy.

[0252] In an embodiment of the present application, a three-dimensional model of the compressor can be constructed, and a single-channel model can be selected from the three-dimensional model as a calculation model. Then, a fluid control equation for the air flow inside the calculation model is constructed, and the SA turbulence model is introduced into the fluid control equation to construct the turbulence control equation. The fluid control equation and the turbulence control equation are then solved to obtain the flow field values ​​of the calculation model. In this way, only one of the single-channel models needs to be calculated for the three-dimensional model of the entire compressor, which reduces the amount of calculation. Moreover, by introducing the SA turbulence model into the fluid control equation to construct the turbulence control equation, and then solving the fluid control equation and the turbulence control equation to obtain the flow field values ​​of the calculation model, the accuracy of the calculated flow field values ​​is improved. For example, the error is only about 4% compared with the actual experimental results.

[0253] In addition, by constructing boundary conditions for the computational model, in the process of discretizing the fluid control equations, turbulence control equations and boundary conditions, the velocity gradient term, pressure gradient term, velocity convection term and pressure convection term in the fluid control equations, turbulence control equations and boundary conditions can be discretized using different discretization methods, further improving the accuracy of the calculated flow field values. In addition, by using the method of multiple reference systems for the rotating part of the computational model, steady-state calculation based on this method is realized. In the calculation, only the final flow field results need to be paid attention to. Under the premise of ensuring the stability of the overall calculation, the calculation speed is fast, the consumption of computing resources is small, and the calculation results are accurate.

[0254] Figure 8 is a block diagram of a device for determining a flow field value of a compressor provided in an embodiment of the present application. The device can be integrated in an electronic device, which can be a terminal device or a server, etc. Figure 8 As shown, the device includes: a first construction module 801, a selection module 802, a second construction module 803, a third construction module 804 and a solution module 805.

[0255] A first construction module 801 is used to construct a three-dimensional model of a compressor;

[0256] A selection module 802 is used to select a single flow channel model from the three-dimensional model as a calculation model, where the single flow channel model is obtained by dividing according to the blades of the compressor;

[0257] The second construction module 803 is used to construct the fluid control equation of the air flow inside the calculation model;

[0258] The third construction module 804 is used to introduce the SA turbulence model into the fluid control equation to construct the turbulence control equation;

[0259] The solving module 805 is used to solve the fluid control equation and the turbulence control equation by using a multi-grid method to obtain the flow field value of the calculation model.

[0260] Optionally, the third building block 804 includes:

[0261] A time-average processing unit is used to perform time-average processing on the fluid control equation to obtain a time-averaged fluid control equation;

[0262] A construction unit is used to introduce the SA turbulence model into the time-averaged fluid control equation to construct the turbulence control equation;

[0263] The solution module 805 is used to:

[0264] The time-averaged fluid control equation and the turbulence control equation are solved to obtain the flow field values ​​of the calculation model.

[0265] Optionally, the time-averaged fluid control equations include a mass equation, a momentum equation and a state equation.

[0266] Optionally, the mass equation is:

[0267]

[0268] in, is the gradient, ρ is the air density, is the average speed of air;

[0269] The momentum equation is:

[0270]

[0271] in, is the gradient, p is the air pressure, is the time-averaged velocity of the air, τ is the viscosity of the air;

[0272] The state equation is:

[0273] p=ρRT

[0274] Where p is the air pressure, T is the air temperature, and R is the gas constant.

[0275] Optionally, the turbulence control equation is as follows:

[0276]

[0277] in, is the gradient, ρ is the air density, is the average speed of air, is the transport variable in the SA turbulence model, is the optimized vorticity size, d is the distance to the nearest surface, and f w is a function of d, σ, C b1 , C b2 , C w1 are all constants;

[0278] in, S is the vorticity size, v is the molecular viscosity, k, C v1 is a constant;

[0279] in, g=r+C w2 (r 6 -r), C w2 , C w3 is a constant.

[0280] Optionally, the device further comprises:

[0281] A fourth building block is used to build boundary conditions of the computational model;

[0282] The solution module 805 includes:

[0283] A discrete processing unit is used to discretize the fluid control equation, the turbulence control equation and the boundary condition to obtain a linear matrix;

[0284] The solving unit is used to solve the linear matrix by adopting the multi-grid method to obtain the flow field value of the calculation model.

[0285] Optionally, the boundary condition includes:

[0286] The inlet boundary conditions of the calculation model are:

[0287] U inlet = Speed ​​threshold

[0288]

[0289]

[0290] Among them, U inlet is the inlet air velocity, p 总 is the total inlet air pressure, p 静 is the inlet air static pressure, U is the outlet air velocity, T 总 is the total inlet air temperature, T 静 is the static temperature of the outlet air, γ is the specific heat capacity of the air, and Ma is the Mach number;

[0291] The outlet boundary conditions of the calculation model are:

[0292]

[0293]

[0294]

[0295] in, is the gradient, U outlet is the outlet air velocity, p outlet is the outlet air pressure, T outlet is the outlet air temperature.

[0296] Optionally, the boundary condition also includes:

[0297] The boundary conditions of the blade flow surface of this calculation model are periodic boundary conditions;

[0298] The boundary conditions of the blades, hub and casing of this calculation model are wall boundary conditions.

[0299] Optionally, the discrete processing unit is used to:

[0300] The velocity gradient term and the pressure gradient term in the fluid control equation, the turbulence control equation and the boundary condition are discretized in a restricted discretization manner;

[0301] The fluid control equation, the turbulence control equation and the velocity convection term in the boundary condition are discretized using a second-order central difference format;

[0302] The fluid control equation, the turbulence control equation and the pressure convection term in the boundary condition are discretized using a second-order upwind scheme.

[0303] Optionally, the device further comprises:

[0304] A gridding module is used to perform gridding processing on the calculation model to obtain a gridded calculation model;

[0305] The second building block 803 is used for:

[0306] Establish the fluid control equations within the gridded computational model.

[0307] Optionally, the device further comprises:

[0308] A partitioning module, used for partitioning the computational model into a rotational part and a non-rotational part;

[0309] A first speed conversion module, used for converting the absolute speed in the fluid control equation and the turbulence control equation of the rotating part into the sum of the relative speed and the coordinate system speed, where the coordinate system speed refers to the rotation speed of the rotating coordinate system constructed for the calculation model;

[0310] The second speed conversion module is used to convert the absolute speed in the fluid control equation and the turbulence control equation of the non-rotating part into the coordinate system speed.

[0311] In an embodiment of the present application, a three-dimensional model of a compressor can be constructed, and a single-channel model can be selected from the three-dimensional model as a calculation model. Then, a fluid control equation for the air flow inside the calculation model is constructed, and the SA turbulence model is introduced into the fluid control equation to construct the turbulence control equation. The fluid control equation and the turbulence control equation are then solved to obtain the flow field values ​​of the calculation model. In this way, only one single-channel model needs to be calculated for the three-dimensional model of the entire compressor, which reduces the amount of calculation. Moreover, by introducing the SA turbulence model into the fluid control equation to construct the turbulence control equation, and then solving the fluid control equation and the turbulence control equation to obtain the flow field values ​​of the calculation model, the accuracy of the calculated flow field values ​​is improved.

[0312] Fig. 9 1 is a structural block diagram of an electronic device 900 provided in an embodiment of the present application. The electronic device 900 may be a mobile phone, a tablet computer, a desktop computer, a server, or other electronic device. The electronic device 900 may be used to implement the method for determining the flow field value of a compressor provided in the above embodiment.

[0313] Typically, the electronic device 900 includes a processor 901 and a memory 902 .

[0314] The processor 901 may include one or more processing cores, such as a 4-core processor, an 8-core processor, and the like. The processor 901 may be implemented in at least one hardware form of DSP (Digital Signal Processing), FPGA (Field Programmable Gate Array), and PLA (Programmable Logic Array). The processor 901 may also include a main processor and a coprocessor. The main processor is a processor for processing data in an awake state, also known as a CPU (Central Processing Unit); the coprocessor is a low-power processor for processing data in a standby state. In some embodiments, the processor 901 may be integrated with a GPU (Graphics Processing Unit), which is responsible for rendering and drawing the content to be displayed on the display screen. In some embodiments, the processor 901 may also include an AI (Artificial Intelligence) processor, which is used to process computing operations related to machine learning.

[0315] The memory 902 may include one or more computer-readable storage media, which may be non-transitory. The memory 902 may also include a high-speed random access memory, and a non-volatile memory, such as one or more disk storage devices, flash memory storage devices. In some embodiments, the non-transitory computer-readable storage medium in the memory 902 is used to store at least one instruction, which is used to be executed by the processor 901 to implement the method for determining the flow field value of the compressor provided in the method embodiment of the present application.

[0316] In some embodiments, the electronic device 900 may further optionally include: a peripheral device interface 903 and at least one peripheral device. The processor 901, the memory 902 and the peripheral device interface 903 may be connected via a bus or a signal line. Each peripheral device may be connected to the peripheral device interface 903 via a bus, a signal line or a circuit board. Specifically, the peripheral device may include: at least one of a display screen 904, an audio circuit 905, a communication interface 906 and a power supply 907.

[0317] Those skilled in the art will understand that Fig. 9 The structure shown in the figure does not constitute a limitation on the electronic device 900, and may include more or less components than those shown in the figure, or combine some components, or adopt a different component arrangement.

[0318] In an exemplary embodiment, a computer-readable storage medium is also provided, on which instructions are stored, and when the instructions are executed by a processor, the method for determining the flow field numerical value of the compressor described above is implemented.

[0319] In an exemplary embodiment, a computer program product is also provided. When the computer program product is executed, it is used to implement the above-mentioned method for determining the flow field numerical value of the compressor.

[0320] Those skilled in the art can understand that all or part of the steps of implementing the above embodiments can be completed by hardware, or by a program to instruct the relevant hardware to complete, and the program can be stored in a computer-readable storage medium, and the above-mentioned storage medium can be a read-only memory, a disk or an optical disk, etc. The above description is only an optional embodiment of the present application and is not intended to limit the present application. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included in the protection scope of the present application.

Claims

1. A method for numerically determining the flow field of a compressor, It is characterized in that The method comprises: Construct a 3D model of the compressor; Selecting a single-channel model from the three-dimensional model as a calculation model, wherein the single-channel model is obtained by dividing according to the blades of the compressor; Constructing a fluid control equation for air flow inside the computational model; Introducing the SA turbulence model into the fluid control equation to construct the turbulence control equation; The fluid control equation and the turbulence control equation are solved to obtain the flow field value of the calculation model.

2. The method according to claim 1, It is characterized in that The SA turbulence model is introduced into the fluid control equation to construct the turbulence control equation, including: Performing time-average processing on the fluid control equation to obtain a time-averaged fluid control equation; Introducing the SA turbulence model into the time-averaged fluid control equation to construct the turbulence control equation; The step of solving the fluid control equation and the turbulence control equation to obtain the flow field value of the calculation model includes: The time-averaged fluid control equation and the turbulence control equation are solved to obtain the flow field value of the calculation model.

3. The method according to claim 2, It is characterized in that The time-averaged fluid control equations include a mass equation, a momentum equation and a state equation.

4. The method according to claim 3, It is characterized in that The mass equation is: in, is the gradient, ρ is the air density, is the average speed of air; The momentum equation is: in, is the gradient, p is the air pressure, is the time-averaged velocity of the air, τ is the viscosity of the air; The state equation is: p=ρRT Where p is the air pressure, T is the air temperature, and R is the gas constant.

5. The method according to any one of claims 2 to 4, It is characterized in that The turbulence governing equation is as follows: in, is the gradient, ρ is the air density, is the average speed of air, is the transport variable in the SA turbulence model, is the optimized vorticity size, d is the distance to the nearest surface, and f w is a function of d, σ, C b1 , C b2 , C w1 are all constants; in, S is the vorticity size, v is the molecular viscosity, k, C v1 is a constant; in, g=r+C w2 (r 6 -r), C w2 , C w3 is a constant.

6. The method according to claim 1, It is characterized in that Before solving the fluid control equation and the turbulence control equation to obtain the flow field value of the calculation model, the method further includes: constructing boundary conditions of the computational model; The step of solving the fluid control equation and the turbulence control equation to obtain the flow field value of the calculation model includes: Discretizing the fluid control equation, the turbulence control equation and the boundary condition to obtain a linear matrix; The linear matrix is ​​solved by using a multi-grid method to obtain the flow field value of the calculation model.

7. The method according to claim 6, It is characterized in that The boundary conditions include: The inlet boundary conditions of the calculation model are: U inlet = Speed ​​threshold Among them, U inlet is the inlet air velocity, p 总 is the total inlet air pressure, p 静 is the inlet air static pressure, U is the outlet air velocity, T 总 is the total inlet air temperature, T 静 is the static temperature of the outlet air, γ is the specific heat capacity of the air, and Ma is the Mach number; The outlet boundary conditions of the calculation model are: in, is the gradient, U outlet is the outlet air velocity, p outlet is the outlet air pressure, T outlet is the outlet air temperature.

8. The method according to claim 7, It is characterized in that The boundary conditions also include: The boundary conditions of the blade flow path surface of the calculation model are periodic boundary conditions; The boundary conditions of the blades, hub and casing of the calculation model are wall boundary conditions.

9. The method according to claim 6, It is characterized in that The discretization of the fluid control equation, the turbulence control equation and the boundary condition comprises: The velocity gradient term and the pressure gradient term in the fluid control equation, the turbulence control equation and the boundary condition are discretized in a restricted discretization manner; The velocity convection term in the fluid control equation, the turbulence control equation and the boundary condition is discretized using a second-order central difference format; The fluid control equation, the turbulence control equation and the pressure convection term in the boundary condition are discretized using a second-order upwind scheme.

10. The method according to claim 1, It is characterized in that Before constructing the fluid control equation of the air flow inside the calculation model, the method further includes: Performing gridding processing on the calculation model to obtain a gridded calculation model; The fluid control equation for constructing the air flow inside the calculation model includes: Construct fluid control equations within the gridded computational model.

11. The method according to claim 1, It is characterized in that Before solving the fluid control equation and the turbulence control equation to obtain the flow field value of the calculation model, the method further includes: dividing the computational model into a rotational part and a non-rotational part; Converting the absolute speed in the fluid control equation and the turbulence control equation of the rotating part into the sum of the relative speed and the coordinate system speed, wherein the coordinate system speed refers to the rotation speed of the rotating coordinate system constructed for the calculation model; The absolute velocities in the fluid governing equations and turbulence governing equations of the non-rotating portion are converted into the coordinate system velocities.

12. A device for determining the flow field value of a compressor, It is characterized in that The device comprises: A first building module is used to build a three-dimensional model of the compressor; A selection module, used for selecting a single flow channel model from the three-dimensional model as a calculation model, wherein the single flow channel model is obtained by dividing according to the blades of the compressor; A second construction module is used to construct a fluid control equation for the air flow inside the calculation model; A third building block is used to introduce the SA turbulence model into the fluid control equation to construct the turbulence control equation; The solution module is used to solve the fluid control equation and the turbulence control equation by using a multi-grid method to obtain the flow field value of the calculation model.

13. An electronic device, It is characterized in that The electronic device includes a processor, a memory, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the method for determining the flow field numerical value of a compressor according to any one of claims 1 to 11 is implemented.

14. A computer-readable storage medium, It is characterized in that The computer-readable storage medium stores instructions, which, when executed on a computer, enable the computer to execute the method for determining the flow field numerical value of a compressor according to any one of claims 1 to 11.

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