Method for calculating film cooling effectiveness based on k-epsilon turbulent flow model and mixing mass transfer function

Abstract

The present application provides a kind of gas film cooling efficiency calculation method based on k-epsilon turbulent flow model and mixing mass transfer function, first, establish gas film cooling efficiency calculation model;Then using the CFD solver embedded with k-epsilon turbulent flow model and mixing mass transfer function calculation module to the gas film cooling efficiency calculation model established in step 1 Iterative solution is carried out, the mass fraction distribution of secondary flow gas component is obtained;Finally, using post-processing software, according to the mass fraction distribution of secondary flow gas component obtained, the three-dimensional model wall surface adiabatic cooling efficiency distribution is calculated and obtained.The method introduces Gaussian three-parameter control mixing mass transfer function, with local secondary flow gas mass fraction as independent variable, and dynamically fine corrects the turbulent viscosity of mixing area through three empirical parameters, so as to significantly improve the simulation accuracy of complex mixing process, especially the simulation accuracy of gas film cooling flow field of special-shaped hole under the premise of not excessively increasing the calculation resources and complexity.

Description

Technical Field

[0001] This invention relates to the field of film cooling efficiency calculation, specifically a method based on k- A method for calculating the film cooling efficiency using turbulence models and mixing mass transfer functions. Background Technology

[0002] Gas turbines, as highly efficient energy conversion devices, are widely used in aviation, power generation, and ship propulsion. Turbine blades operate in harsh environments of high temperature, high pressure, and high speed for extended periods. To ensure their safe and reliable operation, effective cooling measures are essential. Film cooling technology, due to its advantages of good cooling effect, simple structure, and ease of implementation, has been widely used in modern gas turbines.

[0003] In recent years, with the continuous development of computational fluid dynamics (CFD) and experimental techniques, the research on film cooling mechanisms has become increasingly in-depth. CFD methods, by solving the Navier-Stokes equations to obtain flow field information, have become an efficient research tool. In CFD simulations of film cooling, the RANS method is commonly used, which requires the introduction of a turbulence model to close the equation set. The standard k-ε turbulence model is widely used due to its good performance in wall-attached flows. However, when simulating the mixing process between the main flow and the cooling secondary flow, the standard k-ε turbulence model exhibits significant deviations in predicting the turbulence intensity in the mixing region, leading to inaccurate flow field distribution calculations and thus affecting the overall accuracy of numerical simulations of film cooling efficiency.

[0004] To address the aforementioned problem of inaccurate turbulence intensity calculations, existing technologies primarily focus on parameter correction of the standard k-ε model or the adoption of more precise turbulence models. For example, invention patent CN116204989A discloses an enhanced mixing correction method for the k-ε turbulence model suitable for film cooling, which corrects turbulent viscosity by introducing a trigonometric mixing function. This method aims to improve simulation accuracy. However, the mixing function used in this method is relatively simple and is controlled by only a single empirical parameter, making it difficult to accurately correct the turbulent viscosity. As a result, its correction effect is limited in the numerical simulation of film cooling in irregularly shaped holes, and it cannot accurately capture the details of complex mixed flow fields.

[0005] Furthermore, invention patent CN116362027A discloses a porous film cooling calculation method based on an adaptive turbulence model and the source term method. This method defines a resolution control function, enabling the calculation model to adaptively switch between unsteady RANS, large eddy simulation (LES), and direct numerical simulation (DNS) modes. While this method theoretically achieves higher accuracy, its implementation relies on a strict match between the computational grid and the turbulence mode. Since the LES and DNS modes require far more grids than the RANS mode, switching modes necessitates extremely fine mesh generation and significantly increases computation time, computational complexity, and resource requirements, hindering rapid analysis and design in practical engineering applications.

[0006] In summary, existing numerical calculation methods for film cooling efficiency mainly suffer from the following technical problems:

[0007] Standard turbulence model methods based on simple mixing function corrections lack sufficient accuracy in simulating complex mixing processes in irregularly shaped film cooling orifices, making it difficult to accurately predict flow field details and cooling efficiency distributions. While employing higher-order turbulence models or multi-mode adaptive methods can improve accuracy, they suffer from drawbacks such as high computational grid requirements, excessive computation time, and complex implementation procedures, resulting in poor engineering practicality and computational economy. Therefore, there is an urgent need to develop a turbulence model correction method that can significantly improve the calculation accuracy of film cooling efficiency in irregularly shaped orifices while maintaining low computational cost and implementation complexity. Summary of the Invention

[0008] To address the technical problems existing in the prior art, this invention proposes a method based on k- A method for calculating film cooling efficiency using turbulence models and mixing mass transfer functions, this method is applicable to standard k- Within the framework of the turbulence model, a Gaussian three-parameter control mixing mass transfer function is introduced. This function uses the local secondary gas mass fraction as the independent variable and dynamically and finely corrects the turbulent viscosity of the mixing region through three empirical parameters. This significantly improves the simulation accuracy of complex mixing processes, especially the cooling flow field of irregularly shaped orifice film, without excessively increasing computational resources and complexity.

[0009] The technical solution of this invention is as follows:

[0010] Based on k- The method for calculating the film cooling efficiency using turbulence models and mixing mass transfer functions includes the following steps:

[0011] Step 1: Establish a three-dimensional model of the computational domain for film cooling efficiency calculation, and create a computational mesh suitable for fluid calculation based on the three-dimensional model to obtain the film cooling efficiency calculation model;

[0012] Step 2: Utilize embedded... The CFD solver of the turbulence model and the mixed mass transfer function calculation module iteratively solves the gas film cooling efficiency calculation model established in step 1 to obtain the mass fraction distribution of the secondary gas components.

[0013] In the a-th iteration of the solution process for the film cooling efficiency calculation model, the first step is to... The turbulent viscosity obtained in step In the standard Solving using the turbulence model yields the first... Mass fraction of secondary gas components in step iteration ;according to And the three-parameter mixing mass transfer function was used to calculate the first... Iterative turbulent viscosity correction factor Reuse Correcting the turbulent viscosity, we obtain the first... Iterative turbulent viscosity ;

[0014] The three-parameter mixing mass transfer function is:

[0015]

[0016] in , , These are the set mixing constants, and e is the natural constant;

[0017] Step 3: Using post-processing software, calculate and obtain the distribution of adiabatic cooling efficiency of the three-dimensional model wall based on the mass fraction distribution of the secondary gas components obtained in Step 2.

[0018] Furthermore, the mixing mass transfer function satisfies: [the following conditions apply to the mass fraction of the secondary gas component]. When the value is 0 or 1, the function takes the value of 1; and the mixing mass transfer function is related to Symmetry, mixing function in The value is maximized at that time.

[0019] Furthermore, the first mixing constant This is used to control the maximum value of the mixing mass transfer function, i.e., the correction value for turbulent viscosity at the point of strongest mixing; the second mixing constant. Used to control the degree of correction in the unmixed core region; third mixing constant With the second mixing constant The size of the core mixing region is controlled jointly.

[0020] Furthermore, the mixing constant takes the value of , , .

[0021] Furthermore, the specific formula for correcting turbulent viscosity using the turbulent viscosity correction coefficient is as follows:

[0022]

[0023] Calculate to obtain the first Iterative turbulent viscosity ;in For the first Fluid density in step iteration, For the first Turbulent kinetic energy in step iteration For the first Turbulent kinetic energy dissipation rate in step iteration This is the wall surface coefficient.

[0024] Furthermore, the present invention also proposes an electronic device and a computer-readable storage medium:

[0025] An electronic device includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the method described above.

[0026] A computer-readable storage medium having a computer program stored thereon that, when executed by a processor, implements the above-described method.

[0027] Beneficial effects:

[0028] Compared with the prior art, the present invention has the following significant advantages:

[0029] 1. The three-parameter Gaussian mixing function proposed in this invention can precisely characterize the correction requirements of turbulent viscosity in regions with different mixing intensities. Through the coordinated adjustment of the three parameters, high-precision correction of the spatial distribution of turbulent viscosity is achieved, thereby greatly improving the film cooling efficiency, especially the numerical prediction accuracy of the downstream flow field and cooling efficiency of irregular orifices. Examples show that the error between the traditional k-ε model and experimental results in most computational regions can be reduced from approximately 10% to less than 2%.

[0030] 2. This invention only makes local modifications to the standard k-ε turbulence model, without switching to higher-order LES or DNS models. Therefore, the requirements for the computational grid are comparable to those for standard RANS simulations, and the number of grids is far less than that required for higher-order models. This significantly saves computation time and hardware resources, reduces the complexity and cost for engineers to implement numerical simulations, and has good practical engineering value.

[0031] 3. The method of this invention provides a more reasonable physical description of the mixing process, and is applicable not only to standard cylindrical film cooling holes, but also, especially, to the numerical simulation of irregularly shaped film cooling holes with complex geometries (such as fan-shaped holes, expansion holes, etc.). Furthermore, this method effectively improves calculation accuracy under flow conditions ranging from low speed to high subsonic speeds, making it widely applicable.

[0032] Additional aspects and advantages of the invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. Attached Figure Description

[0033] The above and / or additional aspects and advantages of the present invention will become apparent and readily understood from the description of the embodiments taken in conjunction with the following drawings, in which:

[0034] Figure 1 This is a flowchart illustrating the implementation of the technical solution of this invention;

[0035] Figure 2 This is a schematic diagram of the simulation calculation domain for film cooling efficiency in an embodiment of the present invention;

[0036] Figure 3 This is a magnified view showing the details and dimensions of the irregularly shaped air film pores in an embodiment of the present invention;

[0037] Figure 4 These are comparative cloud maps of the air film cooling efficiency distribution on the lower wall of the main cavity in this embodiment of the invention; where (a) is the experimental result and (b) is... The calculation results of the turbulence model, (c) are the calculation results of the present invention;

[0038] Figure 5 This is a comparison diagram of the cooling efficiency of the central axis of the air film hole in the embodiments of the present invention;

[0039] Figure 6 This is a comparison chart of the numerical calculation cooling efficiency and the experimental results error in the embodiments of the present invention. Detailed Implementation

[0040] This invention discloses a method based on A method for calculating the film cooling efficiency using a turbulence model and a Gaussian three-parameter controlled mixing mass transfer function is proposed. This method is aimed at addressing the limitations of traditional methods. Turbulent viscosity in the mixing region of film cooling using turbulence models To address the problem of inaccurate predictions, a three-parameter controlled mixing mass transfer function is proposed, which is then used in conjunction with calculation standards. Turbulent viscosity in turbulence models The mixing mass transfer function is based on the mass fraction of the secondary gas components. The gas film cooling efficiency is a function of the independent variable, and its shape is adjusted by three key parameters. The values ​​of these key parameters are fixed by comparing numerical calculations with experimental results. Compared with traditional numerical calculation methods, the gas film cooling efficiency calculated using this invention has higher numerical accuracy, thus accurately predicting experimental results.

[0041] Specifically, the following steps are included:

[0042] Step 1: Establish a three-dimensional model of the computational domain for film cooling efficiency calculation. Based on the three-dimensional model, use commercial software to create a computational mesh suitable for fluid calculation to obtain the film cooling efficiency calculation model.

[0043] Step 2: Utilize embedded... The CFD solver of the turbulence model and the mixing mass transfer function calculation module solves the gas film cooling efficiency calculation model established in step 1 to obtain the mass fraction distribution of the secondary gas components.

[0044] The specific process is as follows:

[0045] Step 2.1: Set the boundary conditions of the flow field computational domain; assign the values ​​of the main inlet boundary conditions as initial values ​​to the fluid computational mesh;

[0046] Step 2.2: Iterative calculation of the Navier-Stokes equations, The standard equations consisting of the turbulence model equations and the supplementary component transport equations. Turbulence model, in which The turbulence model equations are:

[0047]

[0048]

[0049] Calculate and obtain the first The flow field information of step iteration, where For the first Fluid density in step iteration, For the first Turbulent kinetic energy in step iteration For time, Spatial coordinates, subscript Spatial dimension variable , For the first The velocity tensor in the step iteration, The molecular dynamic viscosity of laminar fluid. For the first The turbulent viscosity obtained by step-by-step iterative calculation The Prandtl number is the turbulent kinetic energy equation. For Favre mean turbulent stress, For the strain rate tensor, For the first Turbulent kinetic energy dissipation rate in step iteration; The Prandtl number is the equation for turbulent viscous dissipation. For explicit wall items; , These are the relevant constants of the turbulent viscous dissipation equation. , The correlation equations for the turbulent viscous dissipation equations are known to those skilled in the art, and the calculation methods and value ranges of the correlation constants and correlation equations are well known to those skilled in the art.

[0050] No. The component transport equations calculated by step-by-step iteration are as follows:

[0051]

[0052] in, The molecular diffusion coefficient of the secondary gas; denoted as the turbulent Schmidt number of the secondary gas.

[0053] Step 2.3: Calculate the mass fraction of the secondary gas components. Substituting into the three-parameter mixing mass transfer equation

[0054]

[0055] Calculate to obtain the first Iterative turbulent viscosity correction factor .

[0056] The mixed mass transfer function must meet the following requirements when it is constructed:

[0057] 1: In When the value is 0 or 1, the function takes the value of 1, that is, the equation identifies the computational domain where mixing has not occurred and maintains its original turbulence model properties;

[0058] 2: The mass transfer function of mixing with respect to Symmetry; the reason is that the mass fraction of the secondary gas components is The mixing intensity of the two gases (mainstream gas and secondary gas) and the mass fraction of the secondary gas component are as follows: Same time;

[0059] 3: The mass transfer function of mixing The value is maximized at time, because as... When the mass fraction of the two gases approaches 0.5, the mass fractions of the two gases are the same, and the mixing intensity is the strongest at this point.

[0060] The proposed mixing mass transfer function equation satisfies the above requirements, and this mixing mass transfer function equation includes three mixing constants. , , . , , Based on the summary of experimental data, it is possible to reasonably correct the turbulent viscosity under mixed conditions, thereby effectively improving the numerical calculation accuracy of film cooling efficiency.

[0061] Where the first mixing constant This determines the maximum value of the mixing mass transfer equation, that is, the correction value for turbulent viscosity at the point of strongest mixing; the second mixing constant This determines the degree of correction in the unmixed core region; the third mixing constant With the second mixing parameter These factors collectively determine the size of the mixing core region. Mixing mass transfer function. Different degrees of correction are applied to the turbulent viscosity in regions with varying degrees of mixing. In regions where no mixing occurs, the original turbulent viscosity is maintained. The correction value for turbulent viscosity increases with the intensity of mixing. This indicates that an mixing process has occurred, as... When the mass fraction of the two gases approaches 0.5, the mass fractions of the two gases are the same, and the mixing intensity is the most intense at this point.

[0062] Step 2.4: Substituting into the formula for calculating turbulent viscosity,

[0063]

[0064] Calculate to obtain the first Iterative turbulent viscosity ;in For the first Fluid density in step iteration, For the first Turbulent kinetic energy in step iteration For the first Turbulent kinetic energy dissipation rate in step iteration is the wall coefficient, taken as a constant of 0.09.

[0065] Step 2.5: Compare the first The flow field distribution results of the first iteration and the second iteration The flow field distribution results from each iteration are used to obtain the calculated residuals. When the calculated residuals are less than the convergence criterion, the iteration stops and the final secondary gas component mass fraction distribution is output; otherwise, the process returns to step 2.2. The flow field distribution results include the secondary gas component mass fractions.

[0066] The core innovation of the above scheme lies in proposing a three-parameter mixing mass transfer equation, which is applicable to... The turbulence model makes different corrections to the turbulent viscosity in regions with different mixing intensities during the calculation process, and uses the corrected turbulent viscosity to continue the iterative process of the fluid calculation equation.

[0067] Step 3: Using post-processing software, calculate and obtain the distribution of adiabatic cooling efficiency of the three-dimensional model wall based on the mass fraction distribution of the secondary gas components obtained in Step 2.

[0068] Specifically, the principle for obtaining the film cooling efficiency in step 3 is based on heat and mass transfer analogy, when the Lewis number... At this time, the solutions to the Navier-Stokes energy equation and mass transfer equation have the same form. For turbulent flow of pure gas and gas mixture, The assumption is reasonable. Therefore, based on the heat and mass transfer analogy, the film cooling efficiency equation can be written in the following form:

[0069]

[0070] in, For film cooling efficiency, The mainstream gas temperature, The mass fraction of the mainstream gas. The temperature of the insulating wall surface. This represents the gas mass fraction at the wall surface. The temperature of the secondary gas. Let represent the mass fraction of the secondary gas. It can be seen that the distribution of the mass fraction follows the same pattern as the temperature distribution, from which the cooling efficiency of the gas film can be obtained.

[0071] The embodiments of the present invention are described in detail below. These embodiments are exemplary and intended to explain the present invention, and should not be construed as limiting the present invention.

[0072] This embodiment takes the classic 7–7–7 fan-shaped cooling hole as an example, and adopts the method proposed in this invention based on... A method for calculating the film cooling efficiency using a turbulence model and a Gaussian-type three-parameter controlled mixing mass transfer function was proposed. Numerical simulations were performed on the experimental state of a 7–7–7 fan-shaped cooling hole. The film cooling efficiency was obtained from the numerical simulations and compared with the experimental results to verify the beneficial effects of the proposed method.

[0073] Specifically, such as Figure 1 The following is an implementation flow of the present invention. This embodiment is implemented through the following steps:

[0074] Step 1: Establish a three-dimensional model of the computational domain for film cooling efficiency calculation. Based on the three-dimensional model, use commercial software to create a computational mesh suitable for fluid calculation to obtain the film cooling efficiency calculation model.

[0075] In this embodiment, the following is adopted: Figure 3 The 7–7–7 sector-shaped cooling hole structure model is shown. The air film hole consists of a section with a diameter D = 6.78 mm and a length L. m A cylindrical segment with a length of 16.95 mm and a length L diff It consists of an expansion section of 23.74 mm, with a total hole length of L = L m +L diff =40.69mm. The orifice expands symmetrically in both the flow and spanwise directions, with the forward expansion angle δ... fwd =7° and spanning angle δ lat =7° is the characteristic. The cross-sectional area of ​​the cylindrical segment is equal to the inlet area A. inlet =36.12mm 2 Export area A exit =90.36mm 2 The spanwise width t of the orifice outlet on the wall surface. breakout =14.34mm.

[0076] Step 2: Utilize embedded... The CFD solver of the turbulence model and the mixing mass transfer function calculation module solves the gas film cooling efficiency calculation model established in step 1 to obtain the mass fraction distribution of the secondary gas components.

[0077] In step 2 The specific implementation process of the turbulence model and the mixed mass transfer function calculation module in the CFD solver is as follows:

[0078] Step 2.1: Set the boundary conditions of the flow field computational domain; assign the values ​​of the main inlet boundary conditions as initial values ​​to the fluid computational mesh; in this embodiment, the computational domain schematic diagram and its boundary condition settings are as follows: Figure 2 As shown. The value of the velocity inlet is set to... The secondary flow is set as the mass flow inlet, with a value of [value missing]. The density ratio of the primary and secondary flows .

[0079] Step 2.2: Iterative calculation of the Navier-Stokes equations, The standard equations consisting of the turbulence model equations and the supplementary component transport equations. Turbulence model, in which The turbulence model equations are:

[0080]

[0081]

[0082] No. The component transport equations calculated in step 1 are as follows:

[0083]

[0084] The first The turbulent viscosity obtained in step Substitute the above standards The turbulence model solution yields the first Mass fraction of secondary gas components in step iteration .

[0085] In this embodiment, the relevant constants that need to be fixed in the turbulence model during numerical calculation are:

[0086] , , , , .

[0087] Step 2.3: Calculate the mass fraction of the secondary gas components. Substituting into the three-parameter mixing mass transfer equation

[0088]

[0089] Calculate to obtain the first Iterative turbulent viscosity correction factor This includes three mixing constants, the first mixing constant... The maximum value of the mixing mass transfer function is used to control the correction value of turbulent viscosity at the point of strongest mixing, characterizing the maximum correction factor of the mixing function to turbulent viscosity; the second mixing constant. The magnitude of the turbulent viscosity correction factor in the unmixed core region is determined when , ,different When, the mixing mass transfer function is The possible values ​​are shown in Table 1:

[0090] Table 1 , , At that time, turbulent viscosity correction factor With the second mixing constant Changes

[0091]

[0092] It can be seen that with As the value increases, the turbulent viscosity correction factor increases for the unmixed core region.

[0093] Third mixing constant The range of mass concentration in the core mixing region was defined, for , Different situations The value is in The range is shown in Table 2:

[0094] Table 2 , hour, The corresponding range of secondary gas component mass fractions

[0095]

[0096] It can be seen that with The larger the value, the larger the concentration range defined as the core mixing region.

[0097] Step 2.4: Substituting into the formula for calculating turbulent viscosity,

[0098]

[0099] Calculate to obtain the first Iterative turbulent viscosity ,in For the first Fluid density in step iteration, For the first Turbulent kinetic energy in step iteration For the first Turbulent kinetic energy dissipation rate in step iteration is the wall coefficient, taken as a constant of 0.09.

[0100] Step 2.5: Compare the first The flow field distribution results of the first iteration and the second iteration The flow field distribution results from each iteration are used to obtain the calculated residuals. When the calculated residuals are less than the convergence criterion, the iteration stops and the final secondary gas component mass fraction distribution is output; otherwise, the process returns to step 2.2. The flow field distribution results include the secondary gas component mass fractions.

[0101] Step 3: Using post-processing software, calculate and obtain the distribution of adiabatic cooling efficiency of the three-dimensional model wall based on the mass fraction distribution of the secondary gas components obtained in Step 2.

[0102] Comparison of experimental results:

[0103] Figure 4 For the results of the flat-plate film cooling experiment, using traditional The numerical calculation results of the turbulence model and the distribution cloud map of the film cooling efficiency calculated using the method disclosed in this invention are shown, where (a) is the experimental result and (b) is the result of the numerical calculation. The calculation results of the turbulence model are shown in (c), which represents the calculation results of this invention. As can be seen in the figure, the wall distribution of the film cooling efficiency calculated after supplementing the mixing mass transfer equation is significantly better than that of the traditional method. The turbulence model's calculation results are closer to the experimental results. It improves the accuracy of numerical calculations in both the spanwise and flowwise directions of the air film distribution. Figure 5 For the results of the film cooling experiment, using traditional Comparison of film cooling efficiency on the central axis of the cooling plane between numerical calculation results of the turbulence model and numerical calculation results using the method disclosed in this invention; Figure 5 As can be seen, the distribution of the simulated film cooling efficiency data obtained using the method disclosed in this invention along the central axis basically coincides with the experimental data. This further verifies that the method disclosed in this invention can improve the accuracy of film cooling efficiency calculation. Figure 6 To adopt traditional A comparison chart of the numerical calculation results of the turbulence model, the film cooling efficiency calculated using the method disclosed in this invention, and the experimental results is presented. It can be seen that the method disclosed in this invention can minimize the error between the numerical calculation and experimental results. The percentage of areas affected decreased from 10% to below 2%. All of the above demonstrates that the modified turbulence model disclosed in this invention can effectively improve the accuracy of numerical calculations for film cooling efficiency.

[0104] Although embodiments of the present invention have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present invention. Those skilled in the art can make changes, modifications, substitutions and variations to the above embodiments within the scope of the present invention without departing from the principles and spirit of the present invention.

Claims

1. A k-based A method for calculating the film cooling efficiency using turbulence models and mixing mass transfer functions, characterized in that... Includes the following steps: Step 1: Establish a three-dimensional model of the computational domain for film cooling efficiency calculation, and create a computational mesh suitable for fluid calculation based on the three-dimensional model to obtain the film cooling efficiency calculation model; Step 2: Utilize embedded... The CFD solver of the turbulence model and the mixed mass transfer function calculation module iteratively solves the gas film cooling efficiency calculation model established in step 1 to obtain the mass fraction distribution of the secondary gas components. In the a-th iteration of the solution process for the film cooling efficiency calculation model, the turbulent viscosity obtained in the (a-1)-th step is first... In the standard Solving using the turbulence model yields the first... Mass fraction of secondary gas components in step iteration ;according to And the three-parameter mixing mass transfer function was used to calculate the first... Iterative turbulent viscosity correction factor Reuse Correcting the turbulent viscosity, we obtain the first... Iterative turbulent viscosity ; The three-parameter mixing mass transfer function is: in , , These are the set mixing constants, and e is the natural constant; Step 3: Using post-processing software, calculate and obtain the distribution of adiabatic cooling efficiency of the three-dimensional model wall based on the mass fraction distribution of the secondary gas components obtained in Step 2.

2. A k-based method according to claim 1 A method for calculating the film cooling efficiency using turbulence models and mixing mass transfer functions, characterized in that... The mixing mass transfer function satisfies: [the following condition is met by] the mass fraction of the secondary gas component. When the value is 0 or 1, the function takes the value of 1; and the mixing mass transfer function is related to Symmetry, mixing function in The value is maximized at that time.

3. A k-based method according to claim 1 A method for calculating the film cooling efficiency using turbulence models and mixing mass transfer functions, characterized in that... First mixing constant This is used to control the correction value for turbulent viscosity at the point of most intense mixing; the second mixing constant. Used to control the degree of correction in the unmixed core region; third mixing constant With the second mixing constant The size of the core mixing region is controlled jointly.

4. A k-based method according to claim 3 A method for calculating the film cooling efficiency using turbulence models and mixing mass transfer functions, characterized in that... The mixing constant takes the value of , , .

5. A k-based method according to claim 1 A method for calculating the film cooling efficiency using turbulence models and mixing mass transfer functions, characterized in that... The specific formula for correcting turbulent viscosity using a turbulent viscosity correction factor is as follows: Calculate to obtain the first Iterative turbulent viscosity ;in For the first Fluid density in step iteration, For the first Turbulent kinetic energy in step iteration For the first Turbulent kinetic energy dissipation rate in step iteration This is the wall surface coefficient.

6. An electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the program, it implements the method of any one of claims 1 to 5.

7. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by the processor, it implements the method described in any one of claims 1 to 5.

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