A method and system for predicting average film cooling effectiveness of turbine vanes

Abstract

This invention proposes a method and system for predicting the average film cooling efficiency of turbine guide vanes. First, the main influencing parameters affecting film cooling efficiency are extracted as independent variables, and the average film cooling efficiency of the turbine blades is used as the dependent variable. Numerical simulations are conducted using calculation schemes for different structures and operating conditions to obtain the average film cooling efficiency under each condition. Then, a corresponding database is generated using the simulation results and independent variable parameters. Finally, a formula for predicting the average film cooling efficiency of the guide vanes is established using the obtained database and multivariate nonlinear function fitting, and the prediction error is analyzed. This invention obtains the predicted average film cooling efficiency of the turbine guide vanes through the geometric and aerodynamic parameters, and can be used to predict the average film cooling efficiency of gas turbine guide vanes.

Description

Technical Field

[0001] This invention belongs to the field of turbomachinery technology, specifically relating to a method and system for predicting the average film cooling efficiency of turbine guide vanes. 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] Film cooling (FS) is an effective cooling method. Lower-temperature compressor gas is introduced from the compressor and injected into the main combustion stream through film cooling orifices on the turbine blade surface. This cooling airflow, relatively cooler than the main combustion stream, bends in the direction of the main combustion stream under the combined influence of the main combustion stream pressure and the flow shear stress generated by Newton's law of internal friction. It adheres to a certain area of ​​the blade surface, isolating the blade surface from the main combustion stream and preventing direct convective heat transfer, thus protecting the turbine blade surface. Fluid dynamic parameters affecting FSD performance include air-to-air ratio, momentum ratio, density ratio, main combustion stream turbulence intensity, and main combustion stream Mach number. Geometric parameters include the downstream distance from the film cooling orifice, orifice spacing, orifice inclination angle, orifice compound angle, aspect ratio, orifice diameter, shape, and orifice arrangement. Therefore, FSD efficiency is the result of multiple coupled parameters, and accurately and comprehensively predicting FSD efficiency is a very difficult and complex task requiring extensive work. Accurately predicting the average FSD efficiency within a certain range and with a certain precision has significant practical implications.

[0004] Currently, commonly used methods for predicting film cooling efficiency include empirical formulas, neural networks, and computational fluid dynamics (CFD). Among these, empirical formulas have been studied and optimized extensively due to their early development. However, their applicability is narrow, focusing only on parameters with significant influence, and they are prone to large deviations in predicting film cooling efficiency for real turbine blades. With the recent surge in artificial intelligence, neural networks have also been applied to predicting film cooling efficiency, demonstrating good predictive results. However, neural networks require large datasets for training, and collecting sufficient datasets for training is a significant challenge. CFD has seen rapid development due to its substantial cost advantage over experimental research; however, its three-dimensional numerical simulation of complex cooling structures requires extremely large mesh sizes, leading to increased mesh generation workload and computation time, which pose significant obstacles to cooling structure design. Therefore, finding more efficient and accurate methods for predicting film cooling efficiency is urgently needed. Summary of the Invention

[0005] This invention proposes a method and system for predicting the average film cooling efficiency of turbine guide vanes. Based on the empirical formula for predicting film cooling efficiency summarized by predecessors, the empirical formula is improved by combining numerical simulation results to obtain a more accurate calculation formula for predicting the average film cooling efficiency. The predicted average film cooling efficiency of the turbine guide vane can be obtained through the geometric and aerodynamic parameters of the turbine guide vane.

[0006] This invention is achieved through the following technical solution:

[0007] A system for predicting the average film cooling efficiency of turbine guide vanes:

[0008] The system includes: a model building module, a working condition building module, a simulation calculation module, and a function fitting module;

[0009] The model building module is used to extract the geometric parameters that affect the average film cooling efficiency of the turbine guide vanes. Based on the extracted geometric parameters, different guide vane models are constructed, and the obtained guide vane models are meshed to calculate the required computational domain.

[0010] The operating condition establishment module is used to extract aerodynamic parameters that affect the average film cooling efficiency of the turbine guide vanes. Based on the aerodynamic influence parameters of the average film cooling efficiency, the boundary conditions of the computational domain of the model establishment module are set to construct different computational operating conditions.

[0011] The simulation calculation module is used to perform numerical simulation calculations on the calculation conditions constructed by the working condition establishment module, obtain the air film cooling efficiency distribution field under the corresponding working condition, and calculate the corresponding average air film cooling efficiency.

[0012] The function fitting module takes the geometric parameters extracted by the model building module and the aerodynamic parameters extracted by the operating condition building module as inputs, and the average film cooling efficiency obtained by the numerical simulation of the simulation calculation module as output. It obtains the values ​​of the parameters in the function expression through function fitting, and substitutes the obtained values ​​into the empirical formula to obtain the empirical formula for predicting the average film cooling efficiency of the turbine guide vane.

[0013] A prediction method for a turbine guide vane average film cooling efficiency prediction system:

[0014] The method specifically includes the following steps:

[0015] Step 1: Extract the geometric parameters that affect the average film cooling efficiency of the turbine guide vanes. Based on the extracted geometric parameters, construct different guide vane models, mesh the obtained guide vane models, and calculate the required computational domain.

[0016] Step 2: Extract the aerodynamic parameters that affect the average film cooling efficiency of the turbine guide vanes, and set the boundary conditions of the calculation domain in Step 1 based on the aerodynamic parameters affecting the average film cooling efficiency, thereby constructing different calculation conditions.

[0017] Step 3: Perform numerical simulation calculations on the calculation conditions constructed in Step 2 to obtain the air film cooling efficiency distribution field under the corresponding conditions, and calculate the corresponding average air film cooling efficiency.

[0018] Step 4: Using the geometric parameters extracted in Step 1 and the aerodynamic parameters extracted in Step 2 as inputs, and the average film cooling efficiency obtained from the numerical simulation in Step 3 as output, the values ​​of the parameters in the function expression are obtained through the function fitting module, and the obtained values ​​are substituted into the empirical formula to obtain the empirical formula for predicting the average film cooling efficiency of the turbine guide vane.

[0019] Furthermore, in step one,

[0020] The geometric parameters affecting the average film cooling efficiency of the turbine guide vanes include the diameters of the film cooling holes d1 and d2, the lateral spacing of the film cooling holes s1 and s2, and the distances from the film cooling holes to the blade tip l1 and l2.

[0021] Furthermore, in step two,

[0022] The aerodynamic parameters affecting the average film cooling efficiency of the turbine guide vanes include the Reynolds number at the jet outlet. jet,1 Re jet,2 Blowing ratio M, density ratio DR.

[0023] Furthermore, in step three,

[0024] The average film cooling efficiency was obtained by numerical simulation using ANSYS CFX and CFD-POST calculation.

[0025] Furthermore, the function expression described in step four is:

[0026]

[0027] In the formula, The average film cooling efficiency is given by A, B, C, D, E, F, G, H, and I, which are undetermined coefficients / exponents. The function fitting software used is 1stOpt, R. ejet,1 R ejet,2 , M and DR are independent variables and dependent variables.

[0028] An electronic device includes a memory and a processor, the memory storing a computer program, the processor executing the computer program to implement the steps of the above method.

[0029] A computer-readable storage medium for storing computer instructions that, when executed by a processor, implement the steps of the above-described method.

[0030] Beneficial effects of the invention

[0031] This invention can be used to predict the average film cooling efficiency of gas turbine guide vanes, solving the problems that existing empirical formulas for predicting film cooling efficiency have limited accuracy and cannot predict the average film cooling efficiency.

[0032] This invention, based on the average film cooling efficiency data of turbine guide vanes obtained through numerical simulation, constructs a new empirical formula by combining it with previously summarized empirical formulas. The new empirical formula is then fitted using function fitting software to obtain the parameters to be determined. The standard deviation reaches 1.64%, and the average coefficient of determination reaches 0.98, achieving excellent prediction results.

[0033] This invention uses an empirical formula to predict the average film cooling efficiency of turbine guide vanes with very high efficiency. The results obtained based on numerical simulation can guarantee a certain degree of accuracy. Using this empirical formula to predict the average film cooling efficiency of new parameters only takes a few seconds. Attached Figure Description

[0034] Figure 1 This is a flowchart illustrating the implementation process of the present invention;

[0035] Figure 2 This is a graph showing the fitting results of the suction surface function of the present invention;

[0036] Figure 3This is a graph showing the fitting results of the pressure surface function in this invention. Detailed Implementation

[0037] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0038] Combination Figures 1 to 3 .

[0039] A system for predicting the average film cooling efficiency of turbine guide vanes, characterized in that:

[0040] The system includes: a model building module, a working condition building module, a simulation calculation module, and a function fitting module;

[0041] The model building module is used to extract the geometric parameters that affect the average film cooling efficiency of the turbine guide vanes. Based on the extracted geometric parameters, different guide vane models are constructed in the modeling software, and the obtained guide vane models are meshed to calculate the required computational domain.

[0042] The operating condition establishment module is used to extract aerodynamic parameters that affect the average film cooling efficiency of the turbine guide vanes. Based on the aerodynamic influence parameters of the average film cooling efficiency, the boundary conditions of the computational domain of the model establishment module are set to construct different computational operating conditions.

[0043] The simulation calculation module is used to perform numerical simulation calculations on the calculation conditions constructed by the working condition establishment module, obtain the air film cooling efficiency distribution field under the corresponding working condition, and calculate the corresponding average air film cooling efficiency in the post-processing software.

[0044] The function fitting module takes the geometric parameters extracted by the model building module and the aerodynamic parameters extracted by the operating condition building module as inputs, and the average film cooling efficiency obtained by the numerical simulation of the simulation calculation module as output. The function fitting software inputs the function expression and the parameters to be calculated in the expression, runs the function fitting module, obtains the values ​​of the parameters in the function expression through function fitting, and substitutes the obtained values ​​into the empirical formula to obtain the empirical formula for predicting the average film cooling efficiency of the turbine guide vane.

[0045] A prediction method for a turbine guide vane average film cooling efficiency prediction system:

[0046] The method specifically includes the following steps:

[0047] Step 1: A total of 10 parameters, including geometric parameters and flow parameters, were extracted and used as input parameters for the fitting formula, corresponding to the average film cooling efficiency obtained from the numerical simulation.

[0048] Extract the geometric parameters that affect the average film cooling efficiency of the turbine guide vane. Based on the extracted geometric parameters, construct different guide vane models, mesh the obtained guide vane models, and calculate the required computational domain.

[0049] Step 2: After determining the values ​​of geometric and flow parameters, establish corresponding numerical simulation models and use the commercial computational fluid dynamics software ANSYS to perform numerical simulations on the models to obtain the distribution of the film cooling efficiency field for each model.

[0050] Extract the aerodynamic parameters that affect the average film cooling efficiency of the turbine guide vanes, and set the boundary conditions of the calculation domain in step one based on the aerodynamic parameters affecting the average film cooling efficiency, thereby constructing different calculation conditions.

[0051] Step 3: In post-processing, calculate the average film cooling efficiency of the suction surface and the pressure surface respectively, and use it as the output of the fitting function;

[0052] Numerical simulation calculations were performed on the calculation conditions constructed in step two to obtain the distribution field of the air film cooling efficiency under the corresponding conditions, and the corresponding average air film cooling efficiency was calculated.

[0053] Step 4: The resulting dataset for function fitting is input into the function fitting software 1stOpt. The form of the fitting function and the parameters to be determined are specified, and the program is run to obtain the result of the average film cooling efficiency prediction formula. This empirical formula can replace traditional finite element analysis software to predict the average film cooling efficiency of turbine guide vanes under new aerodynamic and geometric parameters.

[0054] The geometric parameters extracted in step one and the aerodynamic parameters extracted in step two are used as inputs, and the average film cooling efficiency obtained from the numerical simulation in step three is used as output. The values ​​of the parameters in the function expression are obtained through the function fitting module, and the obtained values ​​are substituted into the empirical formula to obtain the empirical formula for predicting the average film cooling efficiency of the turbine guide vane.

[0055] In step one,

[0056] The geometric parameters affecting the average film cooling efficiency of the turbine guide vanes include the diameters of the film cooling holes d1 and d2, the lateral spacing of the film cooling holes s1 and s2, and the distances from the film cooling holes to the blade tip l1 and l2.

[0057] In step two,

[0058] The aerodynamic parameters affecting the average film cooling efficiency of the turbine guide vanes include the Reynolds number at the jet outlet. jet,1 Re jet,2 Blowing ratio M, density ratio DR.

[0059] In step three,

[0060] The average film cooling efficiency was obtained by numerical simulation using ANSYS CFX and CFD-POST calculation.

[0061] The function expression mentioned in step four is:

[0062]

[0063] In the formula, The average film cooling efficiency is given by A, B, C, D, E, F, G, H, and I, which are undetermined coefficients / exponents. The function fitting software used is 1stOpt, R. ejet,1 R ejet,2 , M and DR are independent variables and dependent variables. Running the program yields the values ​​of each parameter in the function expression.

[0064] Substituting the values ​​of each undetermined parameter into the empirical formula yields a method for predicting the average film cooling efficiency of turbine guide vanes. Substituting the new geometric parameters and flow parameters into the predicted empirical formula yields the average film cooling efficiency under any geometric and flow conditions.

[0065] Table 1 (in conjunction with) Figure 2 The fitting results for the average film cooling efficiency of the suction surface show that the root mean square error between the predicted value and the numerical simulation value is 0.012, the coefficient of determination is 0.984, and the average relative error of the prediction is about 1.75%. This indicates that the average film cooling efficiency prediction model obtained in this embodiment can accurately predict the average film cooling efficiency of the suction surface. The line graph between the actual value and the predicted value shows that the predicted value is very close to the actual value, and the prediction result is good.

[0066]

[0067] Table 1. Fitting results of the suction surface function.

[0068] Table 2 combined Figure 3The fitting results for the average film cooling efficiency of the pressure surface show that the root mean square error between the predicted value and the numerical simulation value of the fitting function is 0.016, the coefficient of determination is 0.982, and the average relative error of the prediction is about 3.46%. This indicates that the average film cooling efficiency prediction model obtained in this embodiment can accurately predict the average film cooling efficiency of the pressure surface. The line graph between the actual value and the predicted value shows that the predicted value is very close to the actual value, and the prediction result is good.

[0069]

[0070]

[0071] Table 2. Fitting results of pressure surface function

[0072] An electronic device includes a memory and a processor, the memory storing a computer program, the processor executing the computer program to implement the steps of the above method.

[0073] A computer-readable storage medium for storing computer instructions that, when executed by a processor, implement the steps of the above-described method.

[0074] The memory in this application embodiment can be volatile memory or non-volatile memory, or it can include both volatile and non-volatile memory. The non-volatile memory can be read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), or flash memory. The volatile memory can be random access memory (RAM), which is used as an external cache. By way of example, but not limitation, many forms of RAM are available, such as static random access memory (SRAM), dynamic random access memory (DRAM), synchronous dynamic random access memory (SDRAM), double data rate synchronous dynamic random access memory (DDRSDRAM), enhanced synchronous dynamic random access memory (ESDRAM), synchronous linked dynamic random access memory (SLDRAM), and direct rambus RAM (DR RAM). It should be noted that the memory used in the methods described in this invention is intended to include, but is not limited to, these and any other suitable types of memory.

[0075] In the above embodiments, implementation can be achieved, in whole or in part, through software, hardware, firmware, or any combination thereof. When implemented in software, it can be implemented, in whole or in part, as a computer program product. The computer program product includes one or more computer instructions. When the computer instructions are loaded and executed on a computer, all or part of the processes or functions described in the embodiments of this application are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another via wired (e.g., coaxial cable, fiber optic, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium accessible to a computer or a data storage device such as a server or data center that integrates one or more available media. The available media may be magnetic media (e.g., floppy disks, hard disks, magnetic tapes), optical media (e.g., high-density digital video discs (DVDs)), or semiconductor media (e.g., solid-state disks (SSDs)).

[0076] In implementation, each step of the above method can be completed by integrated logic circuits in the processor's hardware or by instructions in software. The steps of the method disclosed in the embodiments of this application can be directly implemented by a hardware processor, or by a combination of hardware and software modules in the processor. The software modules can reside in random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, registers, or other mature storage media in the art. This storage medium is located in memory, and the processor reads information from the memory and, in conjunction with its hardware, completes the steps of the above method. To avoid repetition, detailed descriptions are omitted here.

[0077] It should be noted that the processor in the embodiments of this application can be an integrated circuit chip with signal processing capabilities. During implementation, each step of the above method embodiments can be completed by the integrated logic circuits in the processor's hardware or by instructions in software form. The processor can be a general-purpose processor, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components. It can implement or execute the methods, steps, and logic block diagrams disclosed in the embodiments of this application. The general-purpose processor can be a microprocessor or any conventional processor. The steps of the methods disclosed in the embodiments of this application can be directly embodied as being executed by a hardware decoding processor, or executed by a combination of hardware and software modules in the decoding processor. The software modules can be located in random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, registers, or other mature storage media in the art. This storage medium is located in memory, and the processor reads the information in the memory and, in conjunction with its hardware, completes the steps of the above methods.

[0078] The present invention provides a detailed description of a method and system for predicting the average film cooling efficiency of turbine guide vanes, and elucidates the principles and implementation methods of the invention. The descriptions of the embodiments above are only for the purpose of helping to understand the method and core ideas of the invention. At the same time, those skilled in the art will recognize that there will be changes in the specific implementation methods and application scope based on the ideas of the invention. Therefore, the content of this specification should not be construed as a limitation of the invention.

Claims

1. A system for predicting the average film cooling efficiency of turbine guide vanes, characterized in that: The system includes: a model building module, a working condition building module, a simulation calculation module, and a function fitting module; The model building module is used to extract geometric parameters affecting the average film cooling efficiency of turbine guide vanes. Based on the extracted geometric parameters, different guide vane models are constructed, and the obtained guide vane models are meshed to calculate the required computational domain. The geometric parameters affecting the average film cooling efficiency of turbine guide vanes include the diameter of the film cooling orifice. d 1, d 2. Lateral spacing of air film pores s 1, s 2. Distance from the film pore to the blade tip l 1, l 2; The operating condition establishment module is used to extract aerodynamic parameters affecting the average film cooling efficiency of the turbine guide vanes. Based on these aerodynamic parameters influencing the average film cooling efficiency, the boundary conditions of the computational domain in the model establishment module are set to construct different computational operating conditions. The aerodynamic parameters affecting the average film cooling efficiency of the turbine guide vanes include the Reynolds number at the jet outlet. Re jet,1 , Re jet,2 blower M density ratio DR ; The simulation calculation module is used to perform numerical simulation calculations on the calculation conditions constructed by the working condition establishment module, obtain the air film cooling efficiency distribution field under the corresponding working condition, and calculate the corresponding average air film cooling efficiency. The function fitting module takes the geometric parameters extracted by the model building module and the aerodynamic parameters extracted by the working condition building module as inputs, and the average film cooling efficiency obtained by the numerical simulation of the simulation calculation module as output. The module obtains the values ​​of the parameters in the function expression through function fitting, and substitutes the obtained values ​​into the empirical formula to obtain the empirical formula for predicting the average film cooling efficiency of the turbine guide vane. The function expression described in the function fitting module is: In the formula, The average film cooling efficiency is given by A, B, C, D, E, F, G, H, and I, which are undetermined coefficients / exponents. The function fitting software used is 1stOpt. , , , , , , M , DR Independent variable, dependent variable .

2. A prediction method for the turbine guide vane average film cooling efficiency prediction system according to claim 1, characterized in that: The method specifically includes the following steps: Step 1: Extract the geometric parameters affecting the average film cooling efficiency of the turbine guide vanes. Based on the extracted geometric parameters, construct different guide vane models, mesh the obtained guide vane models, and calculate the required computational domain. The geometric parameters affecting the average film cooling efficiency of the turbine guide vanes include the diameter of the film cooling orifice. d 1, d 2. Lateral spacing of air film pores s 1, s 2. Distance from the film pore to the blade tip l 1, l 2; Step 2: Extract the aerodynamic parameters affecting the average film cooling efficiency of the turbine guide vanes. Based on these aerodynamic parameters, set the boundary conditions of the calculation domain from Step 1 to construct different calculation conditions. The aerodynamic parameters affecting the average film cooling efficiency of the turbine guide vanes include the Reynolds number at the jet outlet. Re jet,1 , Re jet,2 blower M density ratio DR ; Step 3: Perform numerical simulation calculations on the calculation conditions constructed in Step 2 to obtain the air film cooling efficiency distribution field under the corresponding conditions, and calculate the corresponding average air film cooling efficiency. Step 4: Take the geometric parameters extracted in Step 1 and the aerodynamic parameters extracted in Step 2 as inputs, and take the average film cooling efficiency obtained from the numerical simulation in Step 3 as output. Use the function fitting module to obtain the values ​​of the parameters in the function expression, and substitute the obtained values ​​into the empirical formula to obtain the empirical formula for predicting the average film cooling efficiency of the turbine guide vane. The function expression mentioned in step four is: In the formula, The average film cooling efficiency is given by A, B, C, D, E, F, G, H, and I, which are undetermined coefficients / exponents. The function fitting software used is 1stOpt. , , , , , , M , DR Independent variable, dependent variable .

3. The method according to claim 2, characterized in that: In step three, The average film cooling efficiency was obtained by numerical simulation using ANSYS CFX and CFD-POST calculation.

4. An electronic device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method of claim 2 or 3.

5. A computer-readable storage medium for storing computer instructions, characterized in that, When the computer instructions are executed by the processor, they implement the steps of the method of claim 2 or 3.

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