Turbine guide vane comprehensive cooling efficiency prediction method and system based on numerical simulation

Abstract

The application discloses a turbine guide vane comprehensive cooling efficiency prediction method and system based on numerical simulation, relates to the field of gas turbines, and can calculate the average comprehensive cooling efficiency of a turbine guide vane under given geometric parameters and flow parameters. The method comprises the following steps: extracting geometric parameters and aerodynamic parameters that affect the comprehensive cooling efficiency of the turbine guide vane, using the geometric parameters to construct a plurality of guide vane models, using the aerodynamic parameters to set different boundary conditions for the plurality of guide vane models, and constructing a plurality of working conditions; performing numerical simulation and simulation calculation according to the plurality of working conditions to obtain the comprehensive cooling efficiency under each working condition; taking the above parameters as a data set, inputting a preset empirical formula and a to-be-solved parameter into function fitting software, setting preset items of a function fitting software algorithm, executing the set function fitting software algorithm to obtain the to-be-solved parameter, substituting the to-be-solved parameter into the preset empirical formula, and obtaining a predicted turbine guide vane comprehensive cooling efficiency model.

Description

Technical Field

[0001] This invention relates to the field of gas turbine guide vane technology, and in particular to a method and system for predicting the comprehensive cooling efficiency of turbine guide vanes based on numerical simulation. Background Technology

[0002] Gas turbines are widely used in shipbuilding, aerospace, power generation, chemical industry, metallurgy, energy and power engineering, and are hailed as the "crown jewel of industry." As a symbol of national defense, industrial, and technological strength, advanced countries worldwide prioritize them as a strategic industry. The gas turbine, one of the most crucial components of a gas turbine, not only generates power but also drives the compressor. Currently, the turbine inlet temperature of advanced aero engines has reached approximately 2000K, exceeding the temperature resistance limit of turbine blade metal materials, thus necessitating the use of advanced cooling technologies.

[0003] There are many cooling methods for guide vanes, which can be broadly classified into internal cooling, film cooling, impingement cooling, and divergent cooling. The simplest internally cooled vanes use multiple independent radial cooling holes or multiple cooling holes connected in series. Another type uses internal rough surfaces such as ribs, bosses, or turbulence columns to increase turbulence and heat transfer coefficient. Film cooling has several design schemes, including single-row film cooling holes, multi-row film cooling holes, and full film cooling, which can effectively prevent direct contact between high-temperature combustion gases and the blade wall. Internal impingement cooling is mainly used for cooling the leading edge, blade base, and blade back of the blade. It can increase the local cooling effect in these areas. Its main disadvantage is that the pressure loss of airflow passing through the impingement cooling holes is relatively large. Divergent cooling has a higher cooling efficiency than other cooling methods, but it has not yet been directly applied to aero-gas turbines. The main reason is that divergent blades are prone to clogging and oxidation, have a very limited service life, insufficient mechanical strength, and are also very difficult to manufacture. Modern aero-engine high-temperature turbine blades almost never employ a single cooling structure, but rather a composite cooling approach. External cooling is mostly film cooling, while internal cooling utilizes a combination of convection, impingement cooling, multi-pass ribbed channels, and turbulence columns. To measure the cooling effect of turbine blades under the combined effects of external film cooling, internal cooling, and thermal coupling, the concept of integrated cooling efficiency is introduced, and its calculation formula is as follows:

[0004]

[0005] Among them, T g T w T c,in These represent the mainstream temperature, the wall temperature under coupled heat exchange conditions, and the cold air inlet temperature, respectively. The overall cooling efficiency reflects the dimensionless temperature distribution of the wall under coupled heat exchange conditions.

[0006] In practical hot-end component design, the most important parameter is the wall temperature, which determines the service life and reliability of the hot-end component. The overall cooling efficiency, reflecting the dimensionless temperature of the hot-end component, provides direct analytical data for cooling design. The overall cooling effect of turbine blades directly affects the effectiveness of the blade cooling structure and has significant guiding significance for turbine blade design. Turbine blade design, in turn, directly affects the length of the engine's overall development cycle, cost, and the success of the development plan. Therefore, accurate and rapid prediction of the overall cooling efficiency of turbine blades under certain known geometric and flow parameters is crucial for the early design of turbine blades. Summary of the Invention

[0007] This invention provides a method and system for predicting the comprehensive cooling efficiency of turbine guide vanes based on numerical simulation, which is used to solve the problem of predicting the comprehensive cooling efficiency of gas turbine guide vanes and to calculate the average comprehensive cooling efficiency of turbine guide vanes under given geometric and flow parameters.

[0008] One embodiment of the present invention provides a method for predicting the comprehensive cooling efficiency of turbine guide vanes based on numerical simulation, comprising: step S1, extracting geometric parameters affecting the comprehensive cooling efficiency of turbine guide vanes, constructing multiple different guide vane models based on the geometric parameters, and meshing them; step S2, extracting aerodynamic parameters affecting the comprehensive cooling efficiency of turbine guide vanes, setting different boundary conditions for the multiple different guide vane models based on the aerodynamic parameters to construct multiple different operating conditions; step S3, performing numerical simulation calculations based on the multiple different operating conditions to obtain the comprehensive cooling efficiency under each operating condition; step S4, taking the geometric parameters and aerodynamic parameters as inputs, taking the comprehensive cooling efficiency under each operating condition as outputs, and inputting a preset empirical formula and the parameters to be solved into function fitting software, setting the type, convergence judgment index, maximum number of iterations, and mode of the function fitting software algorithm; step S5, executing step S4 to obtain the parameters to be solved, substituting the parameters to be solved into the preset empirical formula to obtain a model for predicting the comprehensive cooling efficiency of turbine guide vanes.

[0009] Another embodiment of the present invention provides a numerical simulation-based system for predicting the comprehensive cooling efficiency of turbine guide vanes, comprising: an extraction module for extracting geometric parameters affecting the comprehensive cooling efficiency of turbine guide vanes, constructing multiple different guide vane models based on the geometric parameters, and meshing them; a construction module for extracting aerodynamic parameters affecting the comprehensive cooling efficiency of turbine guide vanes, setting different boundary conditions for the multiple different guide vane models based on the aerodynamic parameters to construct multiple different operating conditions; a simulation module for performing numerical simulation calculations based on the multiple different operating conditions to obtain the comprehensive cooling efficiency under each operating condition; a setting module for taking the geometric parameters and the aerodynamic parameters as inputs, taking the comprehensive cooling efficiency under each operating condition as outputs, and inputting a preset empirical formula and the parameters to be solved into a function fitting software, setting the type, convergence criterion, maximum number of iterations, and mode of the function fitting software algorithm; and a prediction model construction module for executing the setting module to obtain the parameters to be solved, substituting the parameters to be solved into the preset empirical formula to obtain a model for predicting the comprehensive cooling efficiency of turbine guide vanes.

[0010] Another aspect of the present invention provides a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the method for predicting the comprehensive cooling efficiency of turbine guide vanes based on numerical simulation as described in the above embodiments.

[0011] Another aspect of the present invention provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the method for predicting the comprehensive cooling efficiency of turbine guide vanes based on numerical simulation as described in the above embodiments.

[0012] The technical solution of the present invention achieves at least the following beneficial technical effects:

[0013] Using the comprehensive cooling efficiency data of turbine guide vanes obtained from numerical simulation, combined with the experimental relationship, the empirical formula with undetermined parameters was fitted using function fitting software to obtain the undetermined parameters. The average error was about 8%, and the average coefficient of determination reached 0.96, achieving excellent prediction results.

[0014] Predicting the overall cooling efficiency of turbine guide vanes using empirical formulas is highly efficient. However, since the results are based on numerical simulations, they may differ from experimental results. Using the experimental formulas presented here, predicting the overall cooling efficiency of turbine guide vanes under new parameters takes only a few seconds.

[0015] 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

[0016] The above and / or additional aspects and advantages of the present invention will become apparent and readily understood from the following description of the embodiments taken in conjunction with the accompanying drawings, wherein:

[0017] Figure 1 This is a flowchart of a method for predicting the comprehensive cooling efficiency of turbine guide vanes based on numerical simulation, according to an embodiment of the present invention.

[0018] Figure 2 This is a schematic diagram of a method for predicting the comprehensive cooling efficiency of turbine guide vanes based on numerical simulation, according to an embodiment of the present invention.

[0019] Figure 3 The graph shows the comparison between the predicted results and the CFD calculation results. The x-axis represents the experimental condition number, the y-axis represents the blade cooling effect, the black solid line represents the numerical simulation result, and the gray dashed line represents the experimental relationship prediction result.

[0020] Figure 4 This is a schematic diagram of a turbine guide vane integrated cooling efficiency prediction system based on numerical simulation, according to an embodiment of the present invention. Detailed Implementation

[0021] Embodiments of the present invention are described in detail below, examples of which are illustrated in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and intended to explain the present invention, and should not be construed as limiting the present invention.

[0022] The following describes, with reference to the accompanying drawings, a method and system for predicting the comprehensive cooling efficiency of turbine guide vanes based on numerical simulation, according to an embodiment of the present invention. First, the method for predicting the comprehensive cooling efficiency of turbine guide vanes based on numerical simulation, according to an embodiment of the present invention, will be described with reference to the accompanying drawings.

[0023] Figure 1 This is a flowchart of a method for predicting the overall cooling efficiency of turbine guide vanes based on numerical simulation, according to an embodiment of the present invention.

[0024] like Figure 1 As shown, the method for predicting the overall cooling efficiency of turbine guide vanes based on numerical simulation includes the following steps:

[0025] In step S1, the geometric parameters that affect the overall cooling efficiency of the turbine guide vane are extracted, and multiple different guide vane models are constructed based on the geometric parameters and meshed.

[0026] Furthermore, in one embodiment of the present invention, the geometric parameters include the gas-side heat exchange area, the cold-side heat exchange area, the gas-side characteristic length, and the cold-side characteristic length.

[0027] Specifically, the geometric parameters affecting the overall cooling efficiency of the turbine guide vanes are extracted: the heat transfer area F on the gas side. g , Cooling side heat exchange area F c , characteristic length d of the gas side g and the characteristic length d of the cold air side c The feature length is calculated using the following formula:

[0028]

[0029] Where A represents the channel inlet area and L represents the channel inlet wetted perimeter. ANSYS ICEM was used for mesh generation.

[0030] Based on the above parameters, different guide vane models are constructed in the modeling software, and these models are meshed in the mesh generation software to obtain the computational domain required for the calculation.

[0031] In step S2, aerodynamic parameters affecting the overall cooling efficiency of the turbine guide vane are extracted, and different boundary conditions are set for multiple different guide vane models based on the aerodynamic parameters to construct a variety of different working conditions.

[0032] Furthermore, in one embodiment of the present invention, the aerodynamic parameters include flow ratio, temperature ratio, and mainstream Reynolds number.

[0033] In other words, we extract the aerodynamic parameters that affect the overall cooling efficiency of the turbine guide vanes: these aerodynamic parameters include the flow ratio K. G Wenbi K T and the mainstream Reynolds number Re g The flow ratio is defined as m c This refers to the mass flow rate of the air conditioner inlet, expressed in kg / s or m³. g The mass flow rate of the gas inlet is expressed in kg / s, and the temperature ratio is defined as follows: T g Total gas inlet temperature, in Kelvin (K) and temperature (T). c The total temperature of the cooling gas inlet is expressed in K. Based on these aerodynamic parameters, different boundary conditions are set for different models to construct various calculation conditions.

[0034] In step S3, numerical simulation calculations are performed based on various operating conditions to obtain the comprehensive cooling efficiency under each operating condition.

[0035] Specifically, numerical simulation calculations are performed on the various operating condition models described in step S2 to obtain the calculation results for each operating condition. The expression for the comprehensive cooling efficiency is then input into the post-processing software, and the comprehensive cooling efficiency of the guide vanes under each operating condition is calculated to obtain the output for each condition. The numerical simulation and post-processing software used is ANSYS CFX, and the expression for the comprehensive cooling efficiency is:

[0036]

[0037] In step S4, geometric parameters and aerodynamic parameters are used as inputs, the comprehensive cooling efficiency under each working condition is used as output, and the preset empirical formula and the parameters to be solved are input into the function fitting software. The type of the function fitting software algorithm, the convergence judgment index, the maximum number of iterations, and the mode are set.

[0038] In other words, geometric parameters, aerodynamic parameters, and the comprehensive cooling efficiency under various operating conditions are used as the dataset for function fitting. The dataset is then input into the function fitting software 1stOpt, and the form of the fitting function (and the preset empirical formula) and the parameters to be solved are specified. At the same time, the type of algorithm, convergence judgment index, maximum number of iterations, and mode of the function fitting software are also specified in advance.

[0039] The preset empirical formula is as follows:

[0040]

[0041] Where C, n, z, and k are the parameters to be solved, and F g F represents the heat exchange area on the gas side. c d represents the heat exchange area on the cold air side. g d is the characteristic length of the gas-side gas. c K represents the characteristic length of the cold air side. G For the flow ratio, K T For the temperature ratio, Re g The Reynolds number is the mainstream imported number, Θ represents the blade cooling effect, and its relationship with the overall cooling efficiency is calculated using the following formula:

[0042]

[0043] In step S5, the parameters to be solved are obtained by executing step S4. The parameters to be solved are then substituted into the preset empirical formula to obtain the model for predicting the comprehensive cooling efficiency of the turbine guide vane.

[0044] Based on the foregoing, such as Figure 2As shown, the specific working process of this embodiment of the invention can be as follows: To estimate the comprehensive cooling efficiency of the turbine guide vane using this experimental relationship, it is first necessary to extract the main factors affecting the comprehensive cooling efficiency. This embodiment of the invention extracts a total of 7 parameters, including geometric parameters and flow parameters, which are used as input parameters for the experimental relationship to be determined, and the comprehensive cooling efficiency obtained from numerical simulation is used as the output.

[0045] After determining the values ​​of geometric and flow parameters, a corresponding numerical simulation model is established. The model is then simulated using ANSYS, a commercial computational fluid dynamics software, to obtain the overall cooling efficiency field distribution for each model. The overall cooling efficiency is then calculated in post-processing.

[0046] This yields a dataset for function fitting. By inputting this dataset into the function fitting software 1stOpt and specifying the form of the fitting function and the parameters to be determined, the program can be run to obtain the result of the comprehensive cooling efficiency prediction formula. The empirical formula obtained can replace the traditional finite element analysis software and achieve the comprehensive cooling efficiency prediction of turbine guide vanes under new aerodynamic and geometric parameters.

[0047] Furthermore, combined Figure 3 As shown in Table 1 below, a comparison between the CFD numerical calculation results and the prediction results obtained using the embodiments of the present invention shows that the blade cooling effect prediction model obtained by the method of the present invention can quickly and accurately obtain the blade cooling effect under any geometry and flow parameters. Then, the comprehensive cooling efficiency of the turbine guide vane is obtained through the relationship between the blade cooling effect and the comprehensive cooling efficiency. The cooling effect prediction results are quite close to the CFD numerical calculation results, with an average relative error of about 8%, indicating that the prediction model obtained by this embodiment has good accuracy.

[0048] Table 1

[0049] Node number Numerical calculation value y Predicted value y 1 1.3312 1.3651636 2 2.1356 1.9104348 3 2.6632 2.4555059 4 2.9111 3.0004251 5 3.3687 3.5452109 6 0.8089 0.9441456 7 1.2594 1.3212401 8 1.8493 1.6981664 9 2.274 2.0749735 10 2.264 2.4517005 11 0.6518 0.8975277 12 1.0598 1.2560332 13 1.5832 1.6144101 14 2.0526 1.9726775

[0050] In summary, the numerical simulation-based method for predicting the comprehensive cooling efficiency of turbine guide vanes proposed in this embodiment of the invention, based on experimental relationships summarized from domestic and international research and computational fluid dynamics simulation results, and combined with function fitting software, constructs a comprehensive cooling efficiency prediction model applicable to different geometric structures and flow parameters. This enables rapid preliminary prediction of the comprehensive cooling efficiency of novel turbine blade geometry under certain operating parameters, providing a preliminary estimate of its cooling structure design and heat transfer characteristics, and offering some reference value for subsequent turbine blade design.

[0051] Next, referring to the accompanying drawings, a numerical simulation-based prediction system for the integrated cooling efficiency of turbine guide vanes according to an embodiment of the present invention is described.

[0052] Figure 4 This is a schematic diagram of a turbine guide vane integrated cooling efficiency prediction system based on numerical simulation, according to an embodiment of the present invention.

[0053] like Figure 4 As shown, the system 10 includes: an extraction module 100, a construction module 200, a simulation module 300, a setting module 400, and a prediction model construction module 500.

[0054] The module comprises the following components: Extraction module 100 extracts the geometric parameters affecting the overall cooling efficiency of the turbine guide vanes, constructs multiple guide vane models based on these parameters, and meshes them. Construction module 200 extracts the aerodynamic parameters affecting the overall cooling efficiency of the turbine guide vanes, sets different boundary conditions for each guide vane model based on these aerodynamic parameters, and constructs various operating conditions. Simulation module 300 performs numerical simulation calculations under various operating conditions to obtain the overall cooling efficiency under each condition. Setting module 400 takes the geometric and aerodynamic parameters as inputs, outputs the overall cooling efficiency under each operating condition, and inputs the preset empirical formula and the parameters to be solved into the function fitting software, setting the algorithm type, convergence criterion, maximum number of iterations, and mode of the function fitting software. Prediction model construction module 500 executes the setting module to obtain the parameters to be solved, substitutes these parameters into the preset empirical formula, and obtains a predicted model for the overall cooling efficiency of the turbine guide vanes.

[0055] Furthermore, in one embodiment of the present invention, the geometric parameters include the gas-side heat exchange area, the cold-side heat exchange area, the gas-side characteristic length, and the cold-side characteristic length, and the aerodynamic parameters include the flow ratio, the temperature ratio, and the mainstream Reynolds number.

[0056] Furthermore, in one embodiment of the present invention, the simulation module uses the commercial fluid dynamics software ANSYS CFX for numerical simulation.

[0057] Furthermore, in one embodiment of the present invention, the preset empirical formula is:

[0058]

[0059] Where C, n, z, and k are the parameters to be solved, and F g F represents the heat exchange area on the gas side. c d represents the heat exchange area on the cold air side. g d is the characteristic length of the gas-side gas. c K represents the characteristic length of the cold air side. G For the flow ratio, K T For the temperature ratio, Re g The standard is the Reynolds number imported from abroad, and Θ represents the blade cooling effect.

[0060] It should be noted that the foregoing explanation of the embodiment of the method for predicting the comprehensive cooling efficiency of turbine guide vanes based on numerical simulation also applies to the system of this embodiment, and will not be repeated here.

[0061] The turbine guide vane integrated cooling efficiency prediction system based on numerical simulation proposed in this embodiment of the invention, based on the form of experimental relationship of cooling effect, combined with the relatively mature and widely used CFD numerical simulation method, and then using function fitting tool, obtains an empirical formula for predicting the integrated cooling efficiency of turbine guide vanes based on numerical simulation. It can achieve a relatively accurate prediction of the integrated cooling efficiency of turbine guide vanes within a certain range, and provide a certain reference for subsequent turbine blade design.

[0062] To implement the above embodiments, the present invention also proposes a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the method for predicting the comprehensive cooling efficiency of turbine guide vanes based on numerical simulation as described in the foregoing embodiments.

[0063] To implement the above embodiments, the present invention also proposes a non-transitory computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements the method for predicting the comprehensive cooling efficiency of turbine guide vanes based on numerical simulation as described in the foregoing embodiments.

[0064] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., refer to specific features, structures, materials, or characteristics described in connection with that embodiment or example, which are included in at least one embodiment or example of the present invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

[0065] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of this invention, "N" means at least two, such as two, three, etc., unless otherwise explicitly specified.

[0066] Any process or method description in the flowchart or otherwise herein can be understood as representing a module, segment, or portion of code comprising one or more N executable instructions for implementing custom logic functions or processes, and the scope of preferred embodiments of the invention includes additional implementations in which functions may be performed not in the order shown or discussed, including substantially simultaneously or in reverse order depending on the functions involved, as should be understood by those skilled in the art to which embodiments of the invention pertain.

[0067] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (such as a computer-based system, a processor-included system, or other system that can fetch and execute instructions from, an instruction execution system, apparatus, or device). For the purposes of this specification, "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transmit programs for use by, or in conjunction with, an instruction execution system, apparatus, or device. More specific examples (a non-exhaustive list) of computer-readable media include: an electrical connection having one or more wires (electronic device), a portable computer disk drive (magnetic device), random access memory (RAM), read-only memory (ROM), erasable and editable read-only memory (EPROM or flash memory), fiber optic devices, and portable optical disc read-only memory (CDROM). Alternatively, the computer-readable medium may be paper or other suitable media on which the program can be printed, since the program can be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, interpreting, or otherwise processing as necessary, and then stored in a computer memory.

[0068] It should be understood that various parts of the present invention can be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, the N steps or methods can be implemented in software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware as in another embodiment, it can be implemented using any one or a combination of the following techniques known in the art: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.

[0069] Those skilled in the art will understand that all or part of the steps of the methods in the above embodiments can be implemented by a program instructing related hardware. The program can be stored in a computer-readable storage medium, and when executed, the program includes one or a combination of the steps of the method embodiments.

[0070] Furthermore, the functional units in the various embodiments of the present invention can be integrated into a processing module, or each unit can exist physically separately, or two or more units can be integrated into a module. The integrated module can be implemented in hardware or as a software functional module. If the integrated module is implemented as a software functional module and sold or used as an independent product, it can also be stored in a computer-readable storage medium.

[0071] The storage medium mentioned above can be a read-only memory, a disk, or an optical disk, etc. Although embodiments of the present invention have been shown and described above, it is to be 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.

Claims

1. A method for predicting comprehensive cooling effectiveness of turbine vanes based on numerical simulation, characterized in that, Includes the following steps: Step S1: Extract the geometric parameters that affect the overall cooling efficiency of the turbine guide vanes, construct multiple different guide vane models based on the geometric parameters, and mesh them. Step S2: Extract the aerodynamic parameters that affect the overall cooling efficiency of the turbine guide vanes, and set different boundary conditions for the multiple different guide vane models according to the aerodynamic parameters to construct a variety of different working conditions; Step S3: Perform numerical simulation calculations based on the various different operating conditions to obtain the comprehensive cooling efficiency under each operating condition. Step S4: Take the geometric parameters and aerodynamic parameters as inputs, take the comprehensive cooling efficiency under each working condition as outputs, and input the preset empirical formula and the parameters to be solved into the function fitting software. Set the type, convergence judgment index, maximum number of iterations and mode of the function fitting software algorithm. Step S5: Execute step S4 to obtain the parameters to be solved, substitute the parameters to be solved into the preset empirical formula, and obtain the prediction model of the comprehensive cooling efficiency of the turbine guide vane.

2. The numerical simulation based comprehensive cooling effectiveness prediction method of turbine vanes according to claim 1, characterized in that, The geometric parameters include the heat exchange area on the gas side, the heat exchange area on the cold gas side, the characteristic length on the gas side, and the characteristic length on the cold gas side. The aerodynamic parameters include the flow ratio, the temperature ratio, and the mainstream Reynolds number.

3. The numerical simulation based comprehensive cooling effectiveness prediction method of turbine vanes according to claim 1, characterized in that, In step S3, the commercial fluid dynamics software ANSYS CFX is used for numerical simulation.

4. A numerical simulation based comprehensive cooling effectiveness prediction system for turbine vanes, characterized by, include: An extraction module is used to extract geometric parameters that affect the overall cooling efficiency of turbine guide vanes, construct multiple different guide vane models based on the geometric parameters, and perform mesh generation on them; The construction module is used to extract aerodynamic parameters that affect the overall cooling efficiency of turbine guide vanes, and set different boundary conditions for the multiple different guide vane models according to the aerodynamic parameters to construct a variety of different working conditions. The simulation module is used to perform numerical simulation calculations based on the various different operating conditions to obtain the comprehensive cooling efficiency under each operating condition. The setting module takes the geometric parameters and aerodynamic parameters as inputs, takes the comprehensive cooling efficiency under each working condition as output, and inputs the preset empirical formula and the parameters to be solved into the function fitting software, and sets the type, convergence judgment index, maximum number of iterations and mode of the function fitting software algorithm; A prediction model construction module is used to execute the setting module to obtain the parameters to be solved, and substitute the parameters to be solved into the preset empirical formula to obtain a prediction model of the comprehensive cooling efficiency of the turbine guide vane.

5. The turbine guide vane integrated cooling efficiency prediction system based on numerical simulation according to claim 4, characterized in that, The geometric parameters include the heat exchange area on the gas side, the heat exchange area on the cold gas side, the characteristic length on the gas side, and the characteristic length on the cold gas side. The aerodynamic parameters include the flow ratio, the temperature ratio, and the mainstream Reynolds number.

6. The turbine guide vane integrated cooling efficiency prediction system based on numerical simulation according to claim 4, characterized in that, The simulation module uses the commercial fluid dynamics software ANSYS CFX for numerical simulation.

7. A computer device, characterized in that, It includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the method for predicting the comprehensive cooling efficiency of turbine guide vanes based on numerical simulation as described in any one of claims 1-3.

8. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the method for predicting the comprehensive cooling efficiency of turbine guide vanes based on numerical simulation as described in any one of claims 1-3.

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