A method, device, equipment and medium for predicting normal pulsating Reynolds normal stress

Abstract

The present application discloses a normal pulsating Reynolds normal stress prediction method, device, equipment and medium, which relates to the field of transition prediction technology, including: closing the items to be closed in the initial Reynolds stress transport equation according to the Boussinesq hypothesis and the preset standard K equation transition model to obtain a first Reynolds stress transport equation; modeling the items to be modeled in the first Reynolds stress transport equation based on a preset modeling method to obtain a second Reynolds stress transport equation; comparing the second Reynolds stress transport equation with the normal pulsating Reynolds normal stress transport equation in the form of a k equation. T ‑k L The coupled model is coupled with the ω-ω model to obtain the coupled model, and the coupled model is used to predict the transition of the target transition flow field to obtain the normal pulsating Reynolds normal stress distribution results of the laminar section, transition section and turbulent section. In this way, the application can achieve accurate prediction of the normal pulsating Reynolds normal stress through the coupled model.

Description

Technical Field

[0001] The present invention relates to the technical field of transition prediction, and in particular to a method, device, equipment and medium for predicting normal pulsating Reynolds normal stress. Background Art

[0002] Among the commonly used transition prediction methods, the most valuable prediction method for engineering applications is the transition model based on the Reynolds Averaged Navier-Stokes equation (RANS), namely transition modeling. Existing modeling methods are mainly divided into two categories: the first category is the coupling of the transition empirical relationship and the turbulence model, and the second category is to add the transport equation on the basis of the original RANS-based turbulence model. Due to the limitations of the method technology itself, the first type of method does not have the ability to accurately simulate the Reynolds stress of the transition process. Due to the progress of experimental and theoretical research, the second type of method has been continuously developed. The RANS-based transport equation model shows remarkable efficiency and robustness, making it a widely used method in engineering practice. Representative transition modeling work includes the γ-Reθ model (using the empirical correlation method, not simulating the physical mechanism of transition; using the strain rate Reynolds number to trigger the transition, and avoiding the use of non-local variables by solving two additional transport equations), the k-ω-γ model (which can reflect the influence of head purity, incoming flow Reynolds number, and incoming flow turbulence on the transition of hypersonic cone boundary layer) and the k-ζ model (assuming that the flow is completely turbulent and the influence of molecular viscosity is negligible). However, systematic testing has shown that the above models lack the ability to describe the anisotropy of Reynolds stress in the transition process and the transition stress transport mechanism.

[0003] It can be seen that how to accurately describe the transitional Reynolds stress and achieve accurate prediction of the transitional flow field is a problem to be solved in this field. Summary of the invention

[0004] In view of this, the purpose of the present invention is to provide a normal pulsation Reynolds normal stress prediction method, device, equipment and storage medium, which can be based on the Boussinesq hypothesis and the preset standard K model to perform closed modeling on several items in the initial Reynolds stress transport equation, determine the normal pulsation Reynolds normal stress transport equation that can accurately describe the generation, development, and cross-diffusion of transition normal pulsation, and couple it to k T -k L -ω transition model, through the coupled model, the normal pulsating Reynolds normal stress can be accurately predicted. The specific scheme is as follows:

[0005] In a first aspect, the present application provides a method for predicting normal pulsating Reynolds normal stress, comprising:

[0006] According to the Boussinesq hypothesis and the preset standard K equation transition model, the items to be closed in the initial Reynolds stress transport equation are closed to obtain the corresponding semi-closed first Reynolds stress transport equation; the initial Reynolds stress transport equation includes items to be closed and items to be modeled;

[0007] Modeling the items to be modeled in the first Reynolds stress transport equation based on a preset modeling method to obtain a corresponding fully closed second Reynolds stress transport equation;

[0008] The second Reynolds stress transport equation is expressed in the form of the normal pulsating Reynolds normal stress transport equation and k T -k L -ω model is coupled to obtain a coupled model, and the coupled model is used to predict the transition of the target transition flow field to obtain the normal pulsating Reynolds normal stress distribution results of the corresponding laminar section, transition section and turbulent section.

[0009] Optionally, the to-be-closed terms in the initial Reynolds stress transport equation are closed according to the Boussinesq hypothesis and the preset standard K equation transition model to obtain the corresponding semi-closed first Reynolds stress transport equation, including:

[0010] According to the Boussinesq hypothesis and the preset standard K-equation transition model, the laminar viscous diffusion term and the generation term in the initial Reynolds stress transport equation are closed, and the target parameters are obtained according to the turbulent kinetic energy and the turbulent motion viscosity coefficient in the processing process to achieve the closed processing of the laminar viscous diffusion term and the generation term, and obtain the corresponding semi-closed first Reynolds stress transport equation.

[0011] Optionally, the modeling process of the to-be-modeled item in the first Reynolds stress transport equation based on a preset modeling method to obtain a corresponding fully closed second Reynolds stress transport equation includes:

[0012] Based on the fact that the diffusion velocity is proportional to the stress gradient, the turbulence diffusion term and the pressure diffusion term in the initial Reynolds stress transport equation are anisotropically modeled using the target parameter to obtain a first result;

[0013] Using the target parameter, the viscous dissipation term in the initial Reynolds stress transport equation is isotropically modeled to obtain a second result;

[0014] Using the target parameter to model the pressure strain term in the initial Reynolds stress transport equation to obtain a third result;

[0015] A completely closed second Reynolds stress transport equation is obtained based on the first result, the second result and the third result.

[0016] Optionally, the second result is:

[0017] ;

[0018] Among them, ν is the laminar viscosity coefficient, k is the turbulent kinetic energy, is the specific dissipation rate of turbulent kinetic energy, x k is the rectangular coordinate system, and is the pulsation speed, is the Kronecker symbol, and the overline represents the Reynolds mean.

[0019] Optionally, the normal pulsating Reynolds normal stress transport equation is:

[0020] ;

[0021] in, is the total differential of the normal pulsating Reynolds stress, To generate items, is the dissipation term, is the pressure strain term, is the normal pulsating Reynolds stress, is the specific dissipation rate of turbulent kinetic energy, ν is the laminar flow viscosity coefficient, t is time, x j is the rectangular coordinate system, c 3 is the constant coefficient to be calibrated.

[0022] Optionally, the dissipation term is:

[0023] ;

[0024] Where k is the turbulent kinetic energy, is the specific dissipation rate of turbulent kinetic energy, ν is the laminar flow viscosity coefficient, x k is the rectangular coordinate system, is the normal pulsating Reynolds stress.

[0025] Optionally, the pressure strain term is:

[0026] ;

[0027] in, is the normal pulsating Reynolds stress, , is the Reynolds shear stress, c 1 and c 2 are constant coefficients to be calibrated, x, y, z are the coordinates of the rectangular coordinate system, is the average velocity in the coordinate direction, k is the turbulent kinetic energy, is the specific dissipation rate of turbulent kinetic energy.

[0028] In a second aspect, the present application provides a normal pulsation Reynolds normal stress prediction device, comprising:

[0029] A closing module is used to close the items to be closed in the initial Reynolds stress transport equation according to the Boussinesq hypothesis and the preset standard K equation transition model to obtain the corresponding semi-closed first Reynolds stress transport equation; the initial Reynolds stress transport equation includes items to be closed and items to be modeled;

[0030] A modeling module, used for modeling the items to be modeled in the first Reynolds stress transport equation based on a preset modeling method to obtain a corresponding fully closed second Reynolds stress transport equation;

[0031] A coupling solution module is used to solve the second Reynolds stress transport equation in the form of a normal pulsating Reynolds normal stress transport equation with k T -k L -ω model is coupled to obtain a coupled model, and the coupled model is used to predict the transition of the target transition flow field to obtain the normal pulsating Reynolds normal stress distribution results of the corresponding laminar section, transition section and turbulent section.

[0032] In a third aspect, the present application provides an electronic device, including:

[0033] Memory, used to store computer programs;

[0034] A processor is used to execute the computer program to implement the normal pulsation Reynolds normal stress prediction method as described above.

[0035] In a fourth aspect, the present application provides a computer-readable storage medium for storing a computer program, wherein the computer program, when executed by a processor, implements the normal pulsation Reynolds normal stress prediction method as described above.

[0036] It can be seen that the present application firstly performs a closing process on the items to be closed in the initial Reynolds stress transport equation according to the Boussinesq hypothesis and the preset standard K equation transition model, and obtains the corresponding semi-closed first Reynolds stress transport equation; the initial Reynolds stress transport equation includes items to be closed and items to be modeled; the items to be modeled in the first Reynolds stress transport equation are modeled based on the preset modeling method to obtain the corresponding fully closed second Reynolds stress transport equation; the second Reynolds stress transport equation is combined with the k T -k L-ω model is coupled to obtain a coupled model, and the coupled model is used to predict the transition of the target transition flow field to obtain the normal pulsation Reynolds normal stress distribution results of the corresponding laminar section, transition section and turbulent section. In this way, the present application can perform closed modeling on several items in the initial Reynolds stress transport equation based on the Boussinesq hypothesis and the preset standard K model, determine the normal pulsation Reynolds normal stress transport equation that can accurately describe the generation, development, and cross-diffusion of the transition normal pulsation, and couple it to k T -k L -ω transition model, the coupled model can achieve accurate prediction of normal pulsating Reynolds normal stress. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, 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 embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying creative work.

[0038] Figure 1 A flow chart of a normal pulsation Reynolds normal stress prediction method disclosed in this application;

[0039] Figure 2 A specific transition prediction result diagram disclosed in this application;

[0040] Figure 3 A schematic diagram of a specific laminar flow section disclosed in this application;

[0041] Figure 4 A schematic diagram of a specific transition section disclosed in this application;

[0042] Figure 5 A schematic diagram of a specific turbulent section disclosed in this application;

[0043] Figure 6 This is a schematic diagram of the structure of a normal pulsation Reynolds normal stress prediction device disclosed in this application;

[0044] Figure 7 This is a structural diagram of an electronic device disclosed in this application. DETAILED DESCRIPTION

[0045] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0046] See also Figure 1 As shown, an embodiment of the present invention discloses a method for predicting normal pulsating Reynolds normal stress, comprising:

[0047] Step S11, closing the items to be closed in the initial Reynolds stress transport equation according to the Boussinesq hypothesis and the preset standard K equation transition model to obtain the corresponding semi-closed first Reynolds stress transport equation; the initial Reynolds stress transport equation includes items to be closed and items to be modeled.

[0048] In the embodiment of the present application, let time be t, and the three-dimensional velocity of a single point in the rectangular coordinate system xyz be uvw, where the former can be expressed as x k represents (x 1 =x,x 2 =y,x 3 =z), the latter can be used i or k Indicates (u 1 =u,u 2 =v,u 3 =w). The Reynolds mean of any physical quantity c is expressed as ,set up , the average speed can be expressed as or ( , , ), the three-way pulsation speed can be expressed as or ( , , ), pressure p is the same, and the laminar flow viscosity coefficient is recorded as , the turbulent viscosity coefficient is denoted as , turbulent kinetic energy is written as , the exact form of the turbulent kinetic energy transport equation is:

[0049] ;

[0050] The left term is the rate of change of turbulent kinetic energy migration, and the first term on the right is is the turbulent kinetic energy generation term. The three terms from left to right in the second term on the right are pressure diffusion term, turbulent diffusion term, and laminar viscous diffusion term. The third term on the right is the viscous dissipation term, which is equivalent to -ε. It can be understood that for fully developed infinitely extended flat plate / channel turbulent flow, the migration rate of the left-hand term is 0, and the x- and z-direction derivative terms on the right-hand term can be ignored. Therefore, the turbulent kinetic energy transport equation can be simplified to the following form:

[0051] ;

[0052] That is, the balance of generation, diffusion and dissipation. In the generation and diffusion terms, the normal pulsation The growth of turbulent kinetic energy is the mechanism and fundamental principle of the transition process. Therefore, the description of the transition process requires accurate modeling of the normal pulsation.

[0053] Furthermore, the exact form of the Reynolds stress transport equation is as follows:

[0054] ;

[0055] Similarly, the left side of the equation is the Reynolds stress migration change rate, the first total term on the right side is the diffusion term, and the three sub-terms are: ① turbulent diffusion term ② pressure diffusion term ③ laminar viscous diffusion term, the second total term on the right side is ④ generation term, the third term is ⑤ viscous dissipation term, and the fourth term is ⑥ pressure strain term.

[0056] Accordingly, Boussinesq assumes the following:

[0057] ;

[0058] In a specific embodiment, the closing process of the to-be-closed items in the initial Reynolds stress transport equation according to the Boussinesq hypothesis and the preset standard K-equation transition model to obtain the corresponding semi-closed first Reynolds stress transport equation may include: closing the laminar viscosity diffusion term and the generation term in the initial Reynolds stress transport equation according to the Boussinesq hypothesis and the preset standard K-equation transition model, and obtaining the target parameters according to the turbulent kinetic energy and the turbulent motion viscosity coefficient in the processing process to achieve the closing process of the laminar viscosity diffusion term and the generation term to obtain the corresponding semi-closed first Reynolds stress transport equation. Specifically, the process of closing the to-be-closed items in the initial Reynolds stress transport equation is based on the Boussinesq hypothesis and combined with any turbulence model modeled around the turbulent kinetic energy k, which can achieve the closing of items ③④ (laminar viscosity diffusion term and generation term, i.e., to-be-closed items) in the Reynolds stress transport equation, such as the SST turbulence model, which already includes the turbulent kinetic energy k and the turbulent motion viscosity coefficient in the solution process. , can be directly obtained , that is, the target parameters are obtained. After the ③④ items are closed, the corresponding first Reynolds stress transport equation can be obtained.

[0059] Step S12: modeling the items to be modeled in the first Reynolds stress transport equation based on a preset modeling method to obtain a corresponding fully closed second Reynolds stress transport equation.

[0060] Further, after obtaining the first Reynolds stress transport equation with closed items ③④ through the above steps, items ①②⑤⑥ (i.e., items to be modeled) in the first Reynolds stress transport equation can be modeled; in a specific embodiment, the modeling of the items to be modeled in the first Reynolds stress transport equation based on a preset modeling method to obtain the corresponding fully closed second Reynolds stress transport equation can include: based on the diffusion velocity being proportional to the stress gradient, anisotropically modeling the turbulent diffusion item and the pressure diffusion item in the initial Reynolds stress transport equation using the target parameter to obtain a first result; isotropically modeling the viscous dissipation item in the initial Reynolds stress transport equation using the target parameter to obtain a second result; modeling the pressure strain item in the initial Reynolds stress transport equation using the target parameter to obtain a third result; and obtaining a fully closed second Reynolds stress transport equation based on the first result, the second result, and the third result. Specifically, in the process of closed modeling of the ①②⑤⑥ items in the Reynolds stress transport equation, the turbulent diffusion item ①+pressure diffusion item ② can be combined and anisotropically modeled based on the two consistencies and the diffusion rate is proportional to the stress gradient to obtain the first result, as shown below:

[0061] ;

[0062] By performing small-scale isotropic modeling on the viscous dissipation term ⑤, the second result can be obtained, which is shown as follows:

[0063] ;

[0064] Where ν is the laminar kinematic viscosity coefficient. For incompressible air, , k is the turbulent kinetic energy, which is obtained by solving any transition model containing the k equation, is the specific dissipation rate of turbulent kinetic energy, obtained by solving any transition model including the k equation, x k is a rectangular coordinate system. The subscript k ranges from 1, 2, and 3, representing the x, y, and z coordinates, respectively. According to the Einstein summation convention, when the same subscript appears in pairs in a certain item, all values ​​of the subscript must be traversed and summed; and is the pulsation speed, the value range of the subscripts i and j is 1, 2, and 3, corresponding to the pulsation speed in the x, y, and z directions respectively , , ; is the Kronecker symbol if and only if i=j, ,otherwise , the upper line represents the Reynolds average, that is, the average value of this term within a certain flow time. If i=j=2, this expression corresponds to the Reynolds normal stress Second result of the transport equation:

[0065] ;

[0066] For the pressure strain term ⑥, the third result can be obtained based on the divergence operation and Green's theorem modeling, as shown below:

[0067] .

[0068] Furthermore, after all the terms in the Reynolds stress transport equation are closed and modeled, the normal pulsating Reynolds normal stress can be derived based on the Reynolds stress transport equation, the Boussinesq hypothesis and the closed terms. Transport equation, the normal pulsating Reynolds normal stress transport equation is:

[0069] ;

[0070] in, is the total differential of the normal pulsating Reynolds stress, To generate items, is the dissipation term, is the pressure strain term, is the normal pulsating Reynolds stress, is the specific dissipation rate of turbulent kinetic energy, ν is the laminar flow viscosity coefficient, t is time, x j is the rectangular coordinate system, c 3 is the constant coefficient to be calibrated.

[0071] The generated items are:

[0072] ;

[0073] The dissipative term is:

[0074] ;

[0075] Where k is the turbulent kinetic energy, is the specific dissipation rate of turbulent kinetic energy, ν is the laminar flow viscosity coefficient, x k is the rectangular coordinate system, is the normal pulsating Reynolds stress.

[0076] The pressure strain term is:

[0077] ;

[0078] in, is the average speed, c 1 and c 2 are constant coefficients to be calibrated, x, y, z are rectangular coordinate systems, is the average speed.

[0079] And, the constant coefficients in the above terms can be defined as: c 1 is 1.8, c 2 is 0.4, c 3 is 0.1.

[0080] Step S13: The second Reynolds stress transport equation is converted into a normal pulsating Reynolds normal stress transport equation and k T -k L -ω model is coupled to obtain a coupled model, and the coupled model is used to predict the transition of the target transition flow field to obtain the normal pulsating Reynolds normal stress distribution results of the corresponding laminar section, transition section and turbulent section.

[0081] Correspondingly, the normal pulsating Reynolds normal stress obtained through the above steps is The transport equation can be compared with the original k given by the OpenFOAM platform T -k L -ω model is coupled to obtain the coupled model. In a specific embodiment, the calculation object is the T3A flat plate transition flow field, where the original k T -k L The calculation results of the -ω model RANS are in good agreement with the experimental results EXP., such as Figure 2 As shown. On this basis, the normal pulsating Reynolds normal stress transport equation is solved. The calculated results are consistent with the experimental results. In the laminar flow section before the transition (x=395mm, as shown in Figure 3 As shown), transition section (x=495mm, as shown Figure 4 ), the turbulent section after the transition (x=1195mm, as shown in Figure 5 shown) are basically the same.

[0082] It can be seen that the present application can realize the normal pulsating Reynolds normal stress Compared with the traditional turbulence / transition model which is completely based on the Boussinesq hypothesis, This application can correctly reflect the normal pulsating Reynolds normal stress during the transition process. The computational robustness and computational complexity of this application are comparable to those of a single transport equation based on the RANS method (such as the k transport equation and the ω transport equation), and are significantly lower than the Reynolds stress model; the accurate prediction of the normal pulsating Reynolds normal stress can be achieved.

[0083] like Figure 6 As shown, the embodiment of the present application discloses a normal pulsation Reynolds normal stress prediction device, comprising:

[0084] A closing module 11 is used to close the items to be closed in the initial Reynolds stress transport equation according to the Boussinesq hypothesis and the preset standard K equation transition model to obtain a corresponding semi-closed first Reynolds stress transport equation; the initial Reynolds stress transport equation includes items to be closed and items to be modeled;

[0085] A modeling module 12, configured to perform modeling processing on the items to be modeled in the first Reynolds stress transport equation based on a preset modeling method, so as to obtain a corresponding fully closed second Reynolds stress transport equation;

[0086] The coupling solution module 13 is used to combine the second Reynolds stress transport equation with the k T -k L -ω model is coupled to obtain a coupled model, and the coupled model is used to predict the transition of the target transition flow field to obtain the normal pulsating Reynolds normal stress distribution results of the corresponding laminar section, transition section and turbulent section.

[0087] It can be seen that the present application can perform closed modeling on several items in the initial Reynolds stress transport equation based on the Boussinesq hypothesis and the preset standard K equation transition model, and determine the normal pulsation Reynolds normal stress transport equation that can accurately describe the generation, development, and cross-diffusion of the transition normal pulsation, and couple it to the k T -k L -ω transition model, the coupled model can achieve accurate prediction of normal pulsating Reynolds normal stress.

[0088] In a specific embodiment, the enclosed module 11 may include:

[0089] The closed unit is used to perform closed processing on the laminar viscous diffusion term and the generation term in the initial Reynolds stress transport equation according to the Boussinesq hypothesis and the preset standard K equation transition model, and obtain the target parameters according to the turbulent kinetic energy and the turbulent motion viscosity coefficient in the processing process to achieve the closed processing of the laminar viscous diffusion term and the generation term, and obtain the corresponding semi-closed first Reynolds stress transport equation.

[0090] In a specific embodiment, the modeling module 12 may include:

[0091] A first modeling unit is used for performing anisotropic modeling on the turbulence diffusion term and the pressure diffusion term in the initial Reynolds stress transport equation based on the diffusion velocity being proportional to the stress gradient and using the target parameter to obtain a first result;

[0092] A second modeling unit is used to perform isotropic modeling on the viscous dissipation term in the initial Reynolds stress transport equation using the target parameter to obtain a second result;

[0093] A third modeling unit is used to model the pressure strain term in the initial Reynolds stress transport equation using the target parameter to obtain a third result;

[0094] A model closing unit is used to obtain a completely closed second Reynolds stress transport equation based on the first result, the second result and the third result.

[0095] Furthermore, the present application also discloses an electronic device. Figure 7 This is a structural diagram of an electronic device 20 according to an exemplary embodiment. The content in the diagram cannot be regarded as any limitation on the scope of use of the present application.

[0096] Figure 7 A schematic diagram of the structure of an electronic device 20 provided in an embodiment of the present application. The electronic device 20 may specifically include: at least one processor 21, at least one memory 22, a power supply 23, a communication interface 24, an input / output interface 25, and a communication bus 26. The memory 22 is used to store a computer program, which is loaded and executed by the processor 21 to implement the relevant steps in the normal pulsation Reynolds normal stress prediction method disclosed in any of the aforementioned embodiments. In addition, the electronic device 20 in this embodiment may specifically be an electronic computer.

[0097] In this embodiment, the power supply 23 is used to provide working voltage for each hardware device on the electronic device 20; the communication interface 24 can create a data transmission channel between the electronic device 20 and the external device, and the communication protocol it follows is any communication protocol that can be applied to the technical solution of the present application, and is not specifically limited here; the input and output interface 25 is used to obtain external input data or output data to the outside world, and its specific interface type can be selected according to specific application needs and is not specifically limited here.

[0098] In addition, the memory 22, as a carrier for storing resources, can be a read-only memory, a random access memory, a disk or an optical disk, etc. The resources stored thereon can include an operating system 221, a computer program 222, etc., and the storage method can be temporary storage or permanent storage.

[0099] The operating system 221 is used to manage and control the hardware devices and computer program 222 on the electronic device 20, and can be Windows Server, Netware, Unix, Linux, etc. In addition to including a computer program that can be used to complete the normal pulsation Reynolds normal stress prediction method performed by the electronic device 20 disclosed in any of the aforementioned embodiments, the computer program 222 can further include a computer program that can be used to complete other specific tasks.

[0100] Furthermore, the present application also discloses a computer-readable storage medium for storing a computer program; wherein, when the computer program is executed by a processor, the above-disclosed normal pulsation Reynolds normal stress prediction method is implemented. The specific steps of the method can refer to the corresponding contents disclosed in the above-disclosed embodiments, and will not be repeated here.

[0101] In this specification, each embodiment is described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same or similar parts between the embodiments can be referred to each other. For the device disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant parts can be referred to the method part.

[0102] Professionals may further appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of the two. In order to clearly illustrate the interchangeability of hardware and software, the composition and steps of each example have been generally described in the above description according to function. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professionals and technicians may use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0103] The steps of the method or algorithm described in conjunction with the embodiments disclosed herein may be implemented directly using hardware, a software module executed by a processor, or a combination of the two. The software module may be placed in a random access memory (RAM), a memory, a read-only memory (ROM), an electrically programmable ROM, an electrically erasable programmable ROM, a register, a hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art.

[0104] Finally, it should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the sentence "comprise a ..." do not exclude the presence of other identical elements in the process, method, article or device including the elements.

[0105] The technical solution provided by the present application is introduced in detail above. Specific examples are used in this article to illustrate the principles and implementation methods of the present application. The description of the above embodiments is only used to help understand the method of the present application and its core idea. At the same time, for general technicians in this field, according to the idea of ​​the present application, there will be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as a limitation on the present application.

Claims

1. A method for predicting normal pulsation Reynolds normal stress, characterized in that: include: According to the Boussinesq hypothesis and the preset standard K equation transition model, the items to be closed in the initial Reynolds stress transport equation are closed to obtain the corresponding semi-closed first Reynolds stress transport equation; the initial Reynolds stress transport equation includes items to be closed and items to be modeled; Modeling the items to be modeled in the first Reynolds stress transport equation based on a preset modeling method to obtain a corresponding fully closed second Reynolds stress transport equation; The second Reynolds stress transport equation is expressed in the form of the normal pulsating Reynolds normal stress transport equation and k T -k L -ω model to obtain a coupled model, and use the coupled model to predict the transition of the target transition flow field to obtain the normal pulsating Reynolds normal stress distribution results of the corresponding laminar section, transition section and turbulent section; The modeling process of the items to be modeled in the first Reynolds stress transport equation based on the preset modeling method to obtain the corresponding fully closed second Reynolds stress transport equation includes: Based on the fact that the diffusion velocity is proportional to the stress gradient, the turbulence diffusion term and the pressure diffusion term in the initial Reynolds stress transport equation are anisotropically modeled using target parameters to obtain a first result; the target parameters are parameters obtained according to the turbulence kinetic energy and the turbulence kinematic viscosity coefficient during the closed processing process; Using the target parameter, the viscous dissipation term in the initial Reynolds stress transport equation is isotropically modeled to obtain a second result; Using the target parameter to model the pressure strain term in the initial Reynolds stress transport equation to obtain a third result; Obtaining a completely closed second Reynolds stress transport equation based on the first result, the second result and the third result; Wherein, the first result is: ； in, , and is the pulsation speed, is the specific dissipation rate of turbulent kinetic energy, x k is the rectangular coordinate system, the upper line represents the Reynolds average, c3 is the constant coefficient to be calibrated, and is the Kronecker symbol, is the pulsating pressure, is the density; The second result is: ； Among them, v is the laminar viscosity coefficient, k is the turbulent kinetic energy, is the Kronecker symbol; Wherein, the third result is: ； Among them, c1 and c2 are constant coefficients to be calibrated, x i and x j is the rectangular coordinate system; Among them, the normal pulsating Reynolds normal stress transport equation is: ； in, is the total differential of the normal pulsating Reynolds stress, To generate items, is the dissipation term, is the pressure strain term, is the normal pulsating Reynolds stress, and t is the time.

2. The normal pulsation Reynolds normal stress prediction method according to claim 1, characterized in that: The Boussinesq hypothesis and the preset standard K equation transition model are used to close the items to be closed in the initial Reynolds stress transport equation to obtain the corresponding semi-closed first Reynolds stress transport equation, including: According to the Boussinesq hypothesis and the preset standard K-equation transition model, the laminar viscous diffusion term and the generation term in the initial Reynolds stress transport equation are closed, and the target parameters are obtained according to the turbulent kinetic energy and the turbulent motion viscosity coefficient in the processing process to achieve the closed processing of the laminar viscous diffusion term and the generation term, and obtain the corresponding semi-closed first Reynolds stress transport equation.

3. The normal pulsation Reynolds normal stress prediction method according to claim 1, characterized in that: The dissipation term is: ； in, is the normal pulsating Reynolds stress.

4. The normal pulsation Reynolds normal stress prediction method according to claim 1, characterized in that: The pressure strain term is: ； in, is the normal pulsating Reynolds stress, , is the Reynolds shear stress, x, y, z are the coordinates of the rectangular coordinate system, is the average velocity in the coordinate direction.

5. A normal pulsation Reynolds normal stress prediction device, characterized in that: The normal pulsation Reynolds normal stress prediction device is used to implement the normal pulsation Reynolds normal stress prediction method according to any one of claims 1 to 4, and the device comprises: A closing module is used to close the items to be closed in the initial Reynolds stress transport equation according to the Boussinesq hypothesis and the preset standard K equation transition model to obtain the corresponding semi-closed first Reynolds stress transport equation; the initial Reynolds stress transport equation includes items to be closed and items to be modeled; A modeling module, used for modeling the items to be modeled in the first Reynolds stress transport equation based on a preset modeling method to obtain a corresponding fully closed second Reynolds stress transport equation; A coupling solution module is used to solve the second Reynolds stress transport equation in the form of a normal pulsating Reynolds normal stress transport equation with k T -k L -ω model is coupled to obtain a coupled model, and the coupled model is used to predict the transition of the target transition flow field to obtain the normal pulsating Reynolds normal stress distribution results of the corresponding laminar section, transition section and turbulent section.

6. An electronic device, characterized in that: include: Memory, used to store computer programs; A processor, configured to execute the computer program to implement the normal pulsation Reynolds normal stress prediction method as claimed in any one of claims 1 to 4.

7. A computer-readable storage medium, characterized in that: Used to store a computer program, which, when executed by a processor, implements the normal pulsation Reynolds normal stress prediction method as described in any one of claims 1 to 4.

Images