Gas turbine simulation method and device based on multi-field coupling and transient heat exchange of gas compressor

Abstract

The invention relates to the technical field of heat energy machinery, in particular to a gas turbine simulation method and device based on multi-physics field coupling and gas compressor transient heat transfer, and the method comprises the steps: coupling one-dimensional complete machine model data with three-dimensional gas compressor model data to obtain coupling data; and an analysis tool based on the multi-physics field coupling transient numerical simulation technology is obtained through development according to the coupling data, simulation prediction is conducted on the performance condition of the gas compressor under the transient convective heat transfer condition based on the analysis tool, and a simulation prediction result is obtained. Therefore, the problems that in the prior art, simulation time is long, model building and solving are relatively complex, and numerical values are unstable due to the action between physical fields are solved.

Description

Technical Field

[0001] This application relates to the technical field of thermal energy machinery, and particularly relates to a gas turbine simulation method and device based on multi-physical field coupling and transient heat transfer of a compressor. Background Art

[0002] Existing research on multi-physical field coupling models mainly focuses on the coupling between fluid dynamics, heat transfer, and structural response. In the prior art, although there are methods combining CFD (Computational Fluid Dynamics) and FEA (Finite Element Analysis) to study the performance of compressors under different working conditions, the computational requirements for multi-physical field coupling and transient analysis are relatively high. Especially in three-dimensional models and complex boundary conditions, the simulation time may be very long. In addition, the model establishment and solution of the prior art are relatively complex, and the interaction between physical fields may lead to numerical instability. Therefore, how to improve the simulation accuracy and efficiency of gas turbines has become an urgent problem to be solved. Summary of the Invention

[0003] This application provides a gas turbine simulation method and device based on multi-physical field coupling and transient heat transfer of a compressor to solve the problems in the related art, such as long simulation time, relatively complex model establishment and solution, and numerical instability caused by the interaction between physical fields.

[0004] The first aspect of the embodiments of this application provides a gas turbine simulation method based on multi-physical field coupling and transient heat transfer of a compressor, including the following steps: obtaining one-dimensional whole-machine model data and three-dimensional compressor model data of the gas turbine, where the whole-machine model data includes at least one of the thermodynamic parameters, flow parameters, and mechanical parameters of the gas turbine, and the compressor model data includes at least one of the geometric structure, material properties, and boundary conditions of the compressor; coupling the whole-machine model data and the compressor model data to obtain coupling data; developing an analysis tool based on multi-physical field coupling transient numerical simulation technology according to the coupling data, and using the analysis tool to simulate and predict the performance of the compressor under transient convective heat transfer conditions to generate a simulation prediction result of the gas turbine.

[0005] Through the above technical solution, the embodiments of the present application can effectively couple the one-dimensional overall engine model data of the gas turbine and the three-dimensional compressor model data, comprehensively consider the thermodynamic, flow, and mechanical parameters of the gas turbine and the geometric structure, material properties, and boundary conditions of the compressor, so as to generate coupled data. Based on these data, a multi-physics coupled transient numerical simulation analysis tool is developed to accurately simulate and predict the performance of the compressor under transient convective heat transfer conditions. This method improves the operating stability, efficiency, and safety of the gas turbine in the new power system environment, and provides technical support for the reform of China's power system and the construction of a clean and low-carbon energy system.

[0006] Optionally, in an embodiment of the present application, before simulating and predicting the performance of the compressor under transient convective heat transfer conditions, it further includes: constructing a compressor component characteristic correction model based on the digital intelligence fusion technology; using the compressor component characteristic correction model to obtain the performance under the transient convective heat transfer conditions.

[0007] Through the above technical solution, the embodiments of the present application can effectively extract the performance characteristics in the historical operation data by combining machine learning algorithms and data mining technologies, so as to accurately reflect the influence of transient convective heat transfer on the performance of the compressor. This method not only improves the accuracy of component performance prediction, reduces the experimental cost, but also provides a scientific basis for the optimization design of the gas turbine under complex working conditions, thereby improving the overall operating efficiency and safety.

[0008] Optionally, in an embodiment of the present application, constructing the compressor component characteristic correction model based on the digital intelligence fusion technology includes: extracting at least one performance characteristic of the compressor component based on the historical operation data of the compressor; using the at least one performance characteristic to construct the compressor component characteristic correction model.

[0009] Through the above technical solution, the embodiments of the present application can extract key performance characteristics by analyzing the historical operation data of the compressor, accurately reflect the actual performance of the compressor component under transient convective heat transfer conditions, and improve the accuracy of performance prediction.

[0010] Optionally, in an embodiment of the present application, it further includes: developing a system characteristic prediction software for the gas turbine, and evaluating and / or optimizing the operating performance of the gas turbine based on the simulation and prediction results.

[0011] Through the above technical solution, the embodiments of the present application can provide accurate performance prediction, help engineers identify potential problems in a timely manner, thereby improving the operating efficiency and safety of the gas turbine. Secondly, by optimizing the operating parameters, energy consumption and operating costs can be reduced, promoting the construction of a clean and low-carbon energy system.

[0012] Optionally, in an embodiment of the present application, the simulation prediction results include at least one of the compressor efficiency, pressure ratio, temperature distribution, and stress distribution.

[0013] Through the above technical solutions, the embodiments of the present application can simulate and predict key performance indicators such as the efficiency, pressure ratio, temperature distribution, and stress distribution of the compressor, providing a scientific basis for the design and optimization of gas turbines, and thus improving their operating efficiency and safety. This comprehensive analysis ability not only helps to better understand the performance of the compressor under different operating conditions, but also provides effective support for reducing test costs and improving reliability in engineering practice, promoting the construction of a clean and low-carbon energy system.

[0014] An embodiment of the second aspect of the present application provides a gas turbine simulation device based on multi-field coupling and transient heat transfer of the compressor, including: an acquisition module for acquiring one-dimensional overall machine model data and three-dimensional compressor model data of the gas turbine, where the overall machine model data includes at least one of the thermodynamic parameters, flow parameters, and mechanical parameters of the gas turbine, and the compressor model data includes at least one of the geometric structure, material properties, and boundary conditions of the compressor; a coupling module for coupling the overall machine model data and the compressor model data to obtain coupling data; a simulation module for developing an analysis strategy based on multi-physical field coupling transient numerical simulation technology according to the coupling data, and using the analysis strategy to simulate and predict the performance of the compressor under transient convective heat transfer conditions to generate simulation prediction results of the gas turbine.

[0015] Through the above technical solutions, the embodiments of the present application can effectively couple the one-dimensional overall machine model data and the three-dimensional compressor model data of the gas turbine, comprehensively considering the thermodynamic, flow, and mechanical parameters of the gas turbine and the geometric structure, material properties, and boundary conditions of the compressor, so as to generate coupling data. Based on these data, a multi-physical field coupling transient numerical simulation analysis tool is developed to accurately simulate and predict the performance of the compressor under transient convective heat transfer conditions. This method improves the operating stability, efficiency, and safety of gas turbines in the new power system environment, providing technical support for China's power system reform and the construction of a clean and low-carbon energy system.

[0016] Optionally, in an embodiment of the present application, it further includes: a construction module for constructing a compressor component characteristic correction model based on digital and intelligent fusion technology; an analysis module for using the compressor component characteristic correction model to obtain the performance under transient convective heat transfer conditions.

[0017] Through the above technical solution, the embodiments of the present application can effectively extract the performance characteristics in the historical operation data by combining machine learning algorithms and data mining technologies, so as to accurately reflect the impact of transient convective heat transfer on the performance of the compressor. This method not only improves the accuracy of component performance prediction, reduces the experimental cost, but also provides a scientific basis for the optimal design of gas turbines under complex working conditions, thereby improving the overall operation efficiency and safety.

[0018] Optionally, in an embodiment of the present application, the construction module includes: an extraction unit for extracting at least one performance characteristic of the compressor component based on the historical operation data of the compressor; a construction unit for constructing a characteristic correction model of the compressor component by using the at least one performance characteristic.

[0019] Through the above technical solution, the embodiments of the present application can extract key performance characteristics by analyzing the historical operation data of the compressor, accurately reflect the actual performance of the compressor component under transient convective heat transfer conditions, and improve the accuracy of performance prediction.

[0020] Optionally, in an embodiment of the present application, it further includes: a development module for developing system characteristic prediction software for the gas turbine, and evaluating and / or optimizing the operation performance of the gas turbine based on the simulation prediction results.

[0021] Through the above technical solution, the embodiments of the present application can provide accurate performance prediction, help engineers identify potential problems in a timely manner, thereby improving the operation efficiency and safety of the gas turbine. Secondly, by optimizing the operation parameters, energy consumption and operation costs can be reduced, promoting the construction of a clean and low-carbon energy system.

[0022] Optionally, in an embodiment of the present application, the simulation prediction results include at least one of the efficiency, pressure ratio, temperature distribution, and stress distribution of the compressor.

[0023] Through the above technical solution, the embodiments of the present application can provide a scientific basis for the design and optimization of gas turbines by simulating and predicting key performance indicators such as the efficiency, pressure ratio, temperature distribution, and stress distribution of the compressor, thereby improving its operation efficiency and safety. This comprehensive analysis ability not only helps to better understand the performance of the compressor under different working conditions, but also provides effective support for reducing test costs and improving reliability in engineering practice, promoting the construction of a clean and low-carbon energy system.

[0024] The third aspect embodiment of the present application provides an electronic device, including: a memory, a processor, and a computer program stored on the memory and executable on the processor, and the processor executes the program to implement the gas turbine simulation method based on multi-field coupling and compressor transient heat transfer as described in the above embodiments.

[0025] In the fourth aspect of the embodiments of the present application, a computer-readable storage medium is provided. The computer-readable storage medium stores a computer program, and when the program is executed by a processor, it implements the above-mentioned gas turbine simulation method based on multi-field coupling and transient heat transfer of the compressor.

[0026] In the fifth aspect of the embodiments of the present application, a computer program product is provided, including a computer program. When the computer program is executed, it is used to implement the above-mentioned gas turbine simulation method based on multi-field coupling and transient heat transfer of the compressor.

[0027] The embodiments of the present application can effectively couple the one-dimensional whole-machine model data of the gas turbine with the three-dimensional compressor model data, enabling comprehensive consideration of thermodynamic, flow, and mechanical parameters, as well as the geometric structure, material properties, and boundary conditions of the compressor, thereby generating accurate coupling data. The multi-physics field coupling transient numerical simulation analysis tool developed based on these data can accurately simulate and predict the performance of the compressor under transient convective heat transfer conditions, significantly improving the operating stability, efficiency, and safety of the gas turbine in the new power system environment, and providing important technical support for the reform of China's power system and the construction of a clean and low-carbon energy system. At the same time, by combining machine learning algorithms and data mining techniques, performance characteristics are effectively extracted from historical operation data, which not only improves the accuracy of component performance prediction, reduces experimental costs, but also provides a scientific basis for optimization design under complex operating conditions. This method enables engineers to timely identify potential problems, optimize operating parameters, reduce energy consumption and operating costs, and further promote the construction of a clean and low-carbon energy system. In addition, by simulating and predicting the key performance indicators of the compressor, such as efficiency, pressure ratio, temperature distribution, and stress distribution, a solid scientific basis is provided for the design and optimization of the gas turbine, enhancing its operating efficiency and safety. This comprehensive analysis ability not only improves the understanding of the compressor's performance under different operating conditions, but also provides effective support for reducing test costs and improving reliability in engineering practice, contributing to the sustainable development of a clean and low-carbon energy system.

[0028] Additional aspects and advantages of the present application will be given in part in the following description, become apparent in part from the following description, or be learned through the practice of the present application. Description of the Drawings

[0029] The above and / or additional aspects and advantages of the present application will become apparent and be readily understood from the following description of the embodiments in conjunction with the drawings, where:

[0030] Figure 1 It is a flowchart of a gas turbine simulation method based on multi-field coupling and transient heat transfer of the compressor according to an embodiment of the present application;

[0031] Figure 2Schematic structural diagram of a gas turbine simulation device based on multi-field coupling and transient heat transfer of a compressor according to an embodiment of the present application;

[0032] Figure 3 Schematic structural diagram of an electronic device according to an embodiment of the present application. Detailed implementation manners

[0033] Embodiments of the present application will be described in detail below. Examples of the embodiments are shown in the accompanying drawings, where the same or similar reference numerals denote the same or similar elements or elements with the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to explain the present application and should not be construed as limiting the present application.

[0034] The gas turbine simulation method and device based on multi-field coupling and transient heat transfer of a compressor according to an embodiment of the present application will be described below with reference to the accompanying drawings. In view of the problems in the related art mentioned in the above background art, such as long simulation time, relatively complex model establishment and solution, and numerical instability caused by the interaction between physical fields, the present application provides a gas turbine simulation method based on multi-field coupling and transient heat transfer of a compressor. In this method, the one-dimensional overall model data of the gas turbine and the three-dimensional compressor model data can be effectively coupled, comprehensively considering the thermodynamic, flow, and mechanical parameters of the gas turbine and the geometric structure, material properties, and boundary conditions of the compressor, so as to generate coupled data. Based on these data, a multi-physical-field coupling transient numerical simulation analysis tool is developed to accurately simulate and predict the performance of the compressor under transient convective heat transfer conditions. This method improves the operating stability, efficiency, and safety of gas turbines in the new power system environment, and provides technical support for the reform of China's power system and the construction of a clean and low-carbon energy system. Thus, the problems in the related art, such as long simulation time, relatively complex model establishment and solution, and numerical instability caused by the interaction between physical fields, are solved.

[0035] Specifically, Figure 1 Schematic flow diagram of a gas turbine simulation method based on multi-physical-field coupling and transient heat transfer of a compressor provided by an embodiment of the present application.

[0036] As Figure 1 shown, the gas turbine simulation method based on multi-physical-field coupling and transient heat transfer of a compressor includes the following steps:

[0037] In step S101, one-dimensional overall model data of the gas turbine and three-dimensional compressor model data are obtained, where the overall model data includes at least one of the thermodynamic parameters, flow parameters, and mechanical parameters of the gas turbine, and the compressor model data includes at least one of the geometric structure, material properties, and boundary conditions of the compressor.

[0038] It should be noted that the calculation accuracy of the zero-dimensional model of the whole machine mainly depends on the accuracy of component characteristics. Obtaining component characteristics through experimental methods is costly. However, due to its modeling being based on a large number of simplified assumptions, it cannot independently predict component characteristics and their flow fields, and it is difficult to accurately evaluate the influence of various complex flow phenomena on the performance of components and the whole machine. Therefore, the calculation accuracy is limited. To balance the contradiction between calculation resources and calculation accuracy, a multi-dimensional simulation model based on multi-physics field coupling and transient heat transfer of the compressor is proposed, that is, a whole machine hybrid-dimensional simulation with local high dimensions and low dimensions of the whole machine. By integrating the high-dimensional simulation model of components or component characteristics obtained from high-dimensional simulation into the zero-dimensional simulation of the whole machine, the calculation accuracy of the performance of the whole machine can be improved under limited calculation resources. Specifically, the low-dimensional coupling model is the gas engine cycle model; the high-dimensional coupling model is the compressor characteristic curve model established by using neural network considering the cold storage and heat storage effects of blades and shafts under loss conditions.

[0039] In the embodiment of the present application, by constructing a multi-dimensional simulation model of multi-physics field coupling and transient heat transfer of the compressor, the calculation accuracy of the performance of the whole machine can be effectively improved under limited calculation resources, and the problem of insufficient calculation accuracy caused by simplified assumptions in the traditional model is solved. At the same time, by using the combination of the low-dimensional coupling model and the high-dimensional coupling model, the influence of complex flow phenomena on the performance of the gas turbine can be evaluated more accurately.

[0040] In step S102, the whole machine model number and the compressor model data are coupled to obtain coupled data.

[0041] The core steps of the present application include coupling the one-dimensional whole machine model and the three-dimensional compressor model data to obtain coupled data, thereby providing a data basis for subsequent development of analysis tools. Optionally, the multi-physics field coupling calculation method includes:

[0042] (1) Establish a numerical model: Specifically, it can simulate the temperature and stress fields in a mechanical system and consider the mutual influence of the two fields. The temperature field can be modeled as a heat transfer equation, and the stress field can be modeled as an elastic mechanics equation. Then, these two models are connected to each other in time and space using coupling technology.

[0043] (2) Discretize the model: Specifically, it can use the finite element method to discretize the temperature field and the stress field, divide the grid, and convert it into a discrete equation. For example, the entire calculation domain can be divided into multiple elements, and the equations on each element are solved to finally obtain the temperature and stress field distributions on the entire calculation domain. It should be noted that appropriate modeling methods and mathematical models are selected to facilitate the conversion of the problem description into a quantifiable model. Factors including but not limited to the type of problem, data source, characteristics, and whether the proposed problem can be converted into a quantifiable model need to be considered. At the same time, the accuracy requirements and calculation efficiency of numerical calculations are considered when selecting modeling methods and mathematical models to facilitate subsequent model solving.

[0044] (3) Solution Model: In the solution process, corresponding numerical methods and software tools are required for solution. For the solution of heat transfer equations and elastic mechanics equations, numerical algorithms including but not limited to steady-state or unsteady-state, implicit or explicit ones can be used. For example, computational fluid dynamics software or finite element software can be used to solve the equations. Specifically, when performing iterative calculations in terms of time, numerical solutions can be obtained using numerical methods including but not limited to explicit or implicit Euler method, Runge-Kutta method, Levenberg Marquardt method, etc.

[0045] It should be noted that the solution process not only depends on the corresponding numerical methods and software tools, but also requires the use of various mathematical formulas for calculation. The relationship between the discretization model and the solution model is reflected in the quality and efficiency of problem-solving. The correct selection of the mathematical model helps to obtain more accurate simulation results, while the correct implementation of numerical methods and solution can provide more efficient calculation methods, thus obtaining results in a shorter time. The discretization model and the solution model obtain more reliable and higher-precision solutions through continuous iterative solutions.

[0046] (4) Coupling Different Physical Fields: Multiphysics coupling includes but not limited to the coupling of thermal field, flow field and structural field. The temperature field and stress field can be coupled, considering the influence of the thermal expansion coefficient on the elastic modulus, and establishing the relationship between physical properties. Specifically, the thermal expansion coefficient of the temperature field can be used as the elastic mechanics modulus in the stress field, or the temperature-physical relationship of the material can be used as part of the elastic modulus, and the corresponding mathematical formula is used to describe the relationship.

[0047] It should be noted that when solving the model, numerical solutions of physical fields can be obtained by including but not limited to solving partial differential equations and boundary conditions, including but not limited to numerical approximation, difference scheme, iterative solution, etc. These numerical solutions are used as inputs for coupling different physical fields, that is, coupling the solved temperature field and stress field. Before coupling, the boundary conditions of each field need to be defined to ensure that the interfaces between all fields match each other. Different mathematical models and methods need to be used, including but not limited to coupled differential equations, optimization algorithms, mathematical sciences, etc.

[0048] Furthermore, a new coupled field is obtained after coupling. This new field is essentially a function of the temperature field and the stress field, but is also affected by the interaction between the temperature field and the stress field, and this new coupled field can in turn be used as an input for a higher-level coupled system.

[0049] (5) Verify and correct the model: The model obtained through solution needs to be verified by experimental data or previous practical data. If there are deviations, the model needs to be identified and corrected, including but not limited to adjusting model parameters or re - optimizing the modeling process.

[0050] Specifically, mathematical metrics are used to compare the degree of difference between the model prediction results and experimental data. For example, in regression analysis, the coefficient of determination R2 (also known as the goodness - of - fit measure) can be used to evaluate the correlation between the time - delay data and the model prediction results. The value of R2 ranges from 0 to 1, and the closer the value is to 1, the higher the correlation between the experimental data and the model prediction results.

[0051] Furthermore, when the model is basically correct and verified, the model can be used for iterative calculations and optimization design of the temperature and stress fields, including but not limited to parameter scanning and optimization algorithms. Optimization includes but not limited to changing material properties, adjusting structural shapes, and other factors.

[0052] In the embodiments of the present application, a one - dimensional whole - machine model can be coupled with three - dimensional compressor model data to form coupled data, laying a foundation for the subsequent development of analysis tools. The method includes establishing a numerical model to simulate the mutual influence of the temperature and stress fields, discretizing the model for numerical solution, coupling different physical fields to consider the influence of thermal expansion on the elastic modulus, and verifying and correcting the model through experimental data. This process effectively improves the accuracy and efficiency of the simulation.

[0053] In step S103, an analysis tool based on multi - physical - field coupled transient numerical simulation technology is developed according to the coupled data, and the performance of the compressor under transient convective heat transfer conditions is simulated and predicted using the analysis tool to generate simulation prediction results of the gas turbine.

[0054] The simulation prediction results include at least one of the efficiency, pressure ratio, temperature distribution, and stress distribution of the compressor.

[0055] Optionally, in the post - processing of the transient heat transfer experiment, the data of the temperature change of each pixel point over time can be derived into a three - dimensional tensor, where the first dimension represents the number of pixel rows, the second dimension represents the number of pixel columns, and the third dimension represents the depth of temperature data. Using the form of three - dimensional tensor operations instead of pixel - point traversal in the traditional method, the processing efficiency of experimental data can be improved.

[0056] Specifically, on the premise of meeting the assumption of a semi-infinite body, the relationship between the temperature of the thermochromic liquid crystal on the test surface and the convective heat transfer coefficient is tested. Since the heating of the fluid during the experiment is not an ideal temperature step, it is first necessary to identify the pixel point A with the longest thermochromic liquid crystal coloring time. The thermochromic liquid crystal coloring time is tLC1, and the corresponding number of small-amplitude ideal temperature steps is N1. For any pixel point B, its liquid crystal coloring time is tLC2 (≤tLC1), and the corresponding number of small-amplitude ideal temperature steps is N2 (≤N1). Therefore, a three-dimensional tensor ΔTg can be established. The first dimension of this tensor is the number of pixel rows m in the shooting area, the second dimension is the number of pixel columns n in the shooting area, and the value of the third dimension is N1. For pixel point A, the data on its third dimension are N1 small-amplitude ideal temperature steps. For any pixel point B, the data on its third dimension are first N2 small-amplitude ideal temperature steps, and then the subsequent N1 - N2 data are assigned 0 to avoid the problem that a certain pixel point has reached the coloring time but is still superimposed during the operation. Thus, not only the dimensional requirements of tensor operations are met, but also the synchronous numerical solution of the convective heat transfer coefficient for all pixel points is achieved, thereby improving the efficiency of post-processing.

[0057] In the actual execution process, before simulating and predicting the performance of the compressor under transient convective heat transfer conditions, it also includes: constructing a compressor component characteristic correction model based on digital and intelligent fusion technology; using the compressor component characteristic correction model to obtain the performance under transient convective heat transfer conditions. The digital and intelligent fusion technology includes, but is not limited to, machine learning algorithms and data mining technologies, which can more accurately reflect the influence of transient convective heat transfer on the performance of the compressor, thereby improving the accuracy and reliability of the simulation.

[0058] Specifically, constructing a compressor component characteristic correction model based on digital and intelligent fusion technology includes extracting at least one performance characteristic of the compressor component based on the historical operation data of the compressor; using at least one performance characteristic to construct a compressor component characteristic correction model.

[0059] When implementing the gas turbine simulation, first, the performance of the compressor under different working conditions is simulated through a numerical model to obtain characteristic curves. Then, these characteristic curves are compared with the characteristic lines under the adiabatic state to evaluate the performance changes under different flow conditions. Through normalization processing, a deviation coefficient can be established, which is used to quantify the performance difference between the actual operating conditions and the ideal adiabatic conditions.

[0060] Furthermore, develop a system characteristic prediction software for gas turbines, and based on the simulation and prediction results, evaluate and / or optimize the operating performance of the gas turbines. The prediction software includes, but is not limited to, a user interface, a data processing module, a simulation calculation module, and a result analysis module.

[0061] The simulation and prediction of the performance of a compressor under transient convective heat transfer conditions based on an analysis tool include, but are not limited to, obtaining characteristic curves under transient conditions by dividing the grid and using methods such as CHT (Conjugate Heat Transfer) and thermo-mechanical coupling, and then using a neural network to obtain deviation coefficients under different full-load operations, and performing simulation and prediction based on the deviation coefficients.

[0062] In the embodiment of the present application, by developing an analysis tool based on multi-physics field coupling transient numerical simulation technology, the efficient simulation and prediction of the performance of a compressor under transient convective heat transfer conditions are realized, and simulation results including key indicators such as compressor efficiency, pressure ratio, temperature distribution, and stress distribution are generated. In addition, the efficiency of experimental data processing is improved by using three-dimensional tensor operations, ensuring the accuracy in the post-processing of transient heat transfer experiments. By constructing a correction model for the characteristics of compressor components based on digital and intelligent fusion technology, the influence of transient convective heat transfer on the performance of the compressor can be more accurately reflected, thereby improving the reliability and accuracy of the simulation. Finally, the developed gas turbine system characteristics prediction software can provide strong support for the operation performance evaluation and optimization of gas turbines, promoting the progress and application of gas turbine technology.

[0063] According to the gas turbine simulation method based on multi-physics field coupling and compressor transient heat transfer proposed in the embodiment of the present application, the one-dimensional whole-machine model data of the gas turbine and the three-dimensional compressor model data can be effectively coupled, comprehensively considering the thermodynamic, flow, and mechanical parameters of the gas turbine and the geometric structure, material properties, and boundary conditions of the compressor, so as to generate coupled data. Based on these data, a multi-physics field coupling transient numerical simulation analysis tool is developed to accurately simulate and predict the performance of the compressor under transient convective heat transfer conditions. This method improves the operation stability, efficiency, and safety of gas turbines in the new power system environment, providing technical support for the reform of China's power system and the construction of a clean and low-carbon energy system.

[0064] Next, a gas turbine simulation device based on multi-field coupling and compressor transient heat transfer proposed in the embodiment of the present application is described with reference to the accompanying drawings.

[0065] Figure 2 It is a block diagram of the gas turbine simulation device based on multi-field coupling and compressor transient heat transfer in the embodiment of the present application.

[0066] As Figure 2 shown, the gas turbine simulation device 10 based on multi-field coupling and compressor transient heat transfer includes: an acquisition module 100, a coupling module 200, and a simulation module 300.

[0067] Specifically, an acquisition module 100 is configured to acquire one-dimensional overall machine model data and three-dimensional compressor model data of a gas turbine, where the overall machine model data includes at least one of thermodynamic parameters, flow parameters, and mechanical parameters of the gas turbine, and the compressor model data includes at least one of the geometric structure, material properties, and boundary conditions of the compressor.

[0068] A coupling module 200 is configured to couple the overall machine model data and the compressor model data to obtain coupled data.

[0069] A simulation module 300 is configured to develop an analysis strategy based on a multi-physical field coupling transient numerical simulation technology according to the coupled data, and use the analysis strategy to simulate and predict the performance of the compressor under transient convective heat transfer conditions to generate a simulation prediction result of the gas turbine.

[0070] Optionally, in an embodiment of the present application, it further includes: a construction module 400 and an analysis module 500.

[0071] Specifically, the construction module 400 is configured to construct a compressor component characteristic correction model based on a digital intelligence fusion technology.

[0072] The analysis module 500 is configured to obtain the performance under transient convective heat transfer conditions by using the compressor component characteristic correction model.

[0073] Optionally, in an embodiment of the present application, the construction module 400 includes: an extraction unit and a construction unit.

[0074] Wherein, the extraction unit is configured to extract at least one performance characteristic of the compressor component based on the historical operation data of the compressor.

[0075] The construction unit is configured to construct a compressor component characteristic correction model by using at least one performance characteristic.

[0076] Optionally, in an embodiment of the present application, it further includes: a development module 600, which is configured to develop a system characteristic prediction software for the gas turbine, and evaluate and / or optimize the operating performance of the gas turbine based on the simulation prediction result.

[0077] Optionally, in an embodiment of the present application, the simulation prediction result includes at least one of the efficiency, pressure ratio, temperature distribution, and stress distribution of the compressor.

[0078] It should be noted that the foregoing explanation of the embodiments of the gas turbine simulation method based on multi-field coupling and compressor transient heat transfer also applies to the gas turbine simulation device based on multi-field coupling and compressor transient heat transfer of this embodiment, and will not be repeated here.

[0079] The gas turbine simulation device based on multi-field coupling and transient heat transfer of the compressor according to the embodiments of the present application can effectively couple the one-dimensional whole-machine model data of the gas turbine and the three-dimensional compressor model data, comprehensively consider the thermodynamic, flow and mechanical parameters of the gas turbine and the geometric structure, material properties and boundary conditions of the compressor, so as to generate coupling data. Based on these data, a multi-physical field coupling transient numerical simulation analysis tool is developed to accurately simulate and predict the performance of the compressor under transient convective heat transfer conditions. This method improves the operation stability, efficiency and safety of gas turbines in the environment of new power systems, and provides technical support for the reform of China's power system and the construction of a clean and low-carbon energy system.

[0080] Figure 3 The structural schematic diagram of the electronic device provided by the embodiment of the present application. The electronic device may include:

[0081] A memory 301, a processor 302, and a computer program stored on the memory 301 and executable on the processor 302.

[0082] When the processor 302 executes the program, it implements the gas turbine simulation method based on multi-field coupling and transient heat transfer of the compressor provided in the above embodiments.

[0083] Further, the electronic device further includes:

[0084] A communication interface 303 for communication between the memory 301 and the processor 302.

[0085] The memory 301 is used to store a computer program executable on the processor 302.

[0086] The memory 301 may include a high-speed RAM memory, and may also include a non-volatile memory, such as at least one disk memory.

[0087] If the memory 301, the processor 302, and the communication interface 303 are independently implemented, the communication interface 303, the memory 301, and the processor 302 may be interconnected through a bus and complete communication with each other. The bus may be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, an Extended Industry Standard Architecture (EISA) bus, etc. The bus may be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 3It is represented by only a thick line, but it does not mean that there is only one bus or one type of bus.

[0088] Optionally, in a specific implementation, if the memory 301, the processor 302, and the communication interface 303 are integrated on a chip, the memory 301, the processor 302, and the communication interface 303 can communicate with each other through an internal interface.

[0089] The processor 302 may be a central processing unit (CPU for short), or an application specific integrated circuit (ASIC for short), or one or more integrated circuits configured to implement the embodiments of the present application.

[0090] The embodiments of the present application also provide a computer-readable storage medium, on which a computer program is stored. When the program is executed by a processor, the above-mentioned gas turbine simulation method based on multi-field coupling and compressor transient heat transfer is implemented.

[0091] The embodiments of the present application also provide a computer program product, including a computer program. When the computer program is executed, it is used to implement the above-mentioned gas turbine simulation method based on multi-field coupling and compressor transient heat transfer.

[0092] In the description of this specification, the descriptions with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples", etc. mean that the specific features, structures, materials, or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present application. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials, or characteristics described can be combined in a suitable manner in any one or N embodiments or examples. In addition, without conflict, those skilled in the art can combine and combine the different embodiments or examples described in this specification and the features of different embodiments or examples.

[0093] In addition, the terms "first" and "second" are only used for descriptive purposes, and cannot be understood as indicating or implying relative importance or implicitly specifying the quantity of the indicated technical features. Thus, the features defined with "first" and "second" can explicitly or implicitly include at least one of the features. In the description of the present application, the meaning of "N" is at least two, such as two, three, etc., unless otherwise specifically defined.

[0094] Any process or method description represented in a flowchart or otherwise described herein can be understood to represent a module, segment, or portion of code including one or N executable instructions for implementing a customized logical function or process. The scope of the preferred embodiments of this application includes additional implementations, where functions may be executed in a substantially simultaneous manner or in a reverse order according to the functions involved, rather than in the order shown or discussed, which should be understood by those skilled in the art to which the embodiments of this application pertain.

[0095] Logic and / or steps represented in a flowchart or otherwise described herein, for example, can be considered a sequenced list of executable instructions for implementing a logical function, and can be specifically implemented in any computer-readable medium for use by an instruction execution system, apparatus, or device (such as a computer-based system, a system including a processor, or other systems that can fetch and execute instructions from the instruction execution system, apparatus, or device), or in conjunction with such instruction execution systems, apparatus, or devices. For the purposes of this specification, a "computer-readable medium" can be any device that can contain, store, communicate, propagate, or transport a program 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 the following: an electrical connection portion with one or N wirings (electronic device), a portable computer diskette case (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disc read-only memory (CDROM). Additionally, the computer-readable medium can even be paper or other suitable media on which the program can be printed, because the program can be obtained electronically by optically scanning the paper or other media, followed by editing, interpretation, or otherwise processing as appropriate, and then stored in a computer memory.

[0096] It should be understood that various parts of this application can be implemented using hardware, software, firmware, or a combination thereof. In the above embodiments, the N steps or methods can be implemented using software or firmware stored in a memory and executed by a suitable instruction execution system. If implemented in hardware, as in another embodiment, any one or a combination of the following techniques known in the art can be used: discrete logic circuits having logic gate circuits for implementing logical functions on data signals, application-specific integrated circuits having suitable combinational logic gate circuits, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.

[0097] Those of ordinary skill in the art can understand that all or part of the steps carried out in implementing the above-mentioned embodiment methods can be completed by instructing relevant hardware through a program. The said program can be stored in a computer-readable storage medium. When the program is executed, it includes one or a combination of the steps of the method embodiment.

[0098] In addition, in each of the embodiments of the present application, the functional units can be integrated into a processing module, or each unit can exist physically alone, or two or more units can be integrated into one module. The above-mentioned integrated module can be implemented in the form of hardware or in the form of a software functional module. When the above-mentioned integrated module is implemented in the form of a software functional module and sold or used as an independent product, it can also be stored in a computer-readable storage medium.

[0099] The above-mentioned storage medium can be a read-only memory, a magnetic disk, an optical disc, etc. Although the embodiments of the present application have been shown and described above, it can be understood that the above embodiments are exemplary and should not be construed as limiting the present application. Those of ordinary skill in the art can make changes, modifications, substitutions, and variations to the above embodiments within the scope of the present application.

Claims

1. A gas turbine simulation method based on multi-field coupling and transient heat transfer of a compressor, characterized in that, It includes the following steps: Obtain one-dimensional overall machine model data and three-dimensional compressor model data of a gas turbine. Among them, the overall machine model data includes at least one of the thermodynamic parameters, flow parameters, and mechanical parameters of the gas turbine, and the compressor model data includes at least one of the geometric structure, material properties, and boundary conditions of the compressor; Couple the overall machine model data and the compressor model data to obtain coupled data; Develop an analysis tool based on multi-physical-field coupled transient numerical simulation technology according to the coupled data, and use the analysis tool to simulate and predict the performance of the compressor under transient convective heat transfer conditions to generate a simulation prediction result of the gas turbine.

2. The method according to claim 1, characterized in that, Before simulating and predicting the performance of the compressor under transient convective heat transfer conditions, it further includes: Construct a compressor component characteristic correction model based on digital and intelligent fusion technology; Use the compressor component characteristic correction model to obtain the performance under transient convective heat transfer conditions.

3. The method according to claim 2, characterized in that The construction of the compressor component characteristic correction model based on digital and intelligent fusion technology includes: Extract at least one performance characteristic of the compressor component based on the historical operation data of the compressor; Use the at least one performance characteristic to construct the compressor component characteristic correction model.

4. The method according to claim 1, wherein It also includes: Develop system characteristic prediction software for the gas turbine, and evaluate and / or optimize the operating performance of the gas turbine based on the simulation prediction result.

5. The method according to any one of claims 1-4, characterized in that, The simulation prediction result includes at least one of the efficiency, pressure ratio, temperature distribution, and stress distribution of the compressor.

6. A gas turbine simulation device based on multi-field coupling and transient heat transfer of a compressor, characterized in that, It includes: An acquisition module for obtaining one-dimensional overall machine model data and three-dimensional compressor model data of a gas turbine. Among them, the overall machine model data includes at least one of the thermodynamic parameters, flow parameters, and mechanical parameters of the gas turbine, and the compressor model data includes at least one of the geometric structure, material properties, and boundary conditions of the compressor; A coupling module for coupling the overall machine model data and the compressor model data to obtain coupled data; A simulation module for developing an analysis tool based on multi-physical-field coupled transient numerical simulation technology according to the coupled data, and using the analysis tool to simulate and predict the performance of the compressor under transient convective heat transfer conditions to generate a simulation prediction result of the gas turbine.

7. The device according to claim 6, wherein, It also includes: A construction module for constructing a compressor component characteristic correction model based on digital and intelligent fusion technology; An analysis module for using the compressor component characteristic correction model to obtain the performance under transient convective heat transfer conditions.

8. An electronic device, characterized in that, It includes: A memory, a processor, and a computer program stored on the memory and executable on the processor. The processor executes the program to implement the gas turbine simulation method based on multi-field coupling and compressor transient heat transfer as described in any one of claims 1-5.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, The program is executed by the processor to be used to implement the gas turbine simulation method based on multi-field coupling and compressor transient heat transfer as described in any one of claims 1-5.

10. A computer program product comprising a computer program, characterized in that, The computer program is executed to implement the gas turbine simulation method based on multi-field coupling and compressor transient heat transfer as described in any one of claims 1-5.

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