Compressor non-design point calculation method based on gas turbine multi-physical domain simulation platform
By constructing a compressor model using the SysTides module and the Modelica language, the problems of performance prediction error and model universality in compressor non-design point modeling and simulation were solved. Multi-physics domain coupled simulation was realized, improving the accuracy and efficiency of simulation calculation.
Patent Information
- Application Number
- CN202511732720.1
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-11-24
- Publication Date
- 2026-01-13
AI Technical Summary
Existing compressor non-design point modeling and simulation technologies suffer from large performance prediction errors, inaccurate control strategies, high surge risk, and difficulty in rapidly traversing multiple operating conditions and parameter spaces due to multi-physics domain coupled modeling, resulting in poor model versatility.
The SysTides module of the domestic gas turbine multi-system integration platform was adopted. The compressor model was constructed using the Modelica language, standard physical ports were designed, user input parameters and variables were defined, a robust characteristic plot interpolation algorithm was developed, and the compressor non-design point solution calculation was performed to realize steady-state and dynamic response simulation.
It improves the accuracy and model reusability of compressor performance prediction under multiple operating conditions outside the design point, and significantly enhances simulation calculation efficiency and stability.
Smart Images
Figure CN121328031A_ABST
Abstract
Description
TECHNICAL FIELD
[0001] The present application relates to the technical field of compressor off-design point simulation calculation, and particularly relates to a compressor off-design point calculation method based on a gas turbine multi-physical domain simulation platform. BACKGROUND
[0002] A compressor is a key component in a thermal system such as a gas turbine, an aero-engine, and an industrial compressor, and its performance directly affects the efficiency and stability of the system. In actual operation, the compressor often works at off-design point conditions (such as the gas turbine is often used in peak regulation and variable load scenes; the compressor needs to be quickly adapted during the operation processes such as starting, stopping, and load jumping), and its flow characteristics present high nonlinearity and strong coupling. Under the above conditions, the traditional design point parameters cannot accurately reflect the actual working state of the compressor, which may lead to an increase in performance prediction error, inaccurate control strategy setting, and even cause stability problems such as surge. In addition, the operation process of the compressor involves multiple physical domains such as thermodynamics, fluid mechanics, mechanical structure, and control system. Therefore, under the mechanism of multi-physical domain coupling modeling, the performance modeling and simulation calculation of the compressor at off-design points become an important technical means for efficient and reliable simulation calculation of the compressor.
[0003] The current common compressor off-design point modeling and simulation technology mainly includes: a performance map lookup table method, which constructs a compressor performance map (such as four-dimensional data of flow rate-rotational speed-pressure ratio-efficiency) through experiments or high-precision simulation data, and obtains a target performance point through interpolation calculation under actual working conditions. The performance map lookup table method relies on existing map data, cannot give an effective and reasonable extension method when crossing the map boundary, and the interpolation result may be distorted or unsolvable, leading to simulation failure, so it is difficult to handle topology structure changes or cross-working interval calculation, and has poor support for boundary extrapolation and multi-condition steady-state prediction; a CFD simulation method, which solves the three-dimensional Reynolds time-averaged Navier-Stokes equation set in the control volume, combines a proper turbulence model and a grid division method, and finely simulates the internal flow of the compressor to analyze the detailed three-dimensional flow structure, loss distribution, backflow, leakage, and stall development process of the compressor. The CFD simulation method needs modeling and grid division, requires a relatively large amount of computing resources, and cannot be embedded in a system-level simulation framework to carry out dynamic response calculation. In addition, when the geometric parameters of the compressor change, the modeling and grid division need to be re-performed, which is difficult to realize modularization and reuse, cannot quickly traverse the multi-condition and parameter space, and has poor model universality. SUMMARY
[0004] The main purpose of the present application is to provide a compressor off-design point calculation method based on a gas turbine multi-physical domain simulation platform, which can effectively solve the problems in the two common methods of compressor off-design point modeling and simulation in the background art.
[0005] To achieve the above object, the technical scheme adopted by the present application is as follows: The present application provides a compressor non-design point calculation method based on a gas turbine multi-physical domain simulation platform, and the steps are as follows: S1, using the SysTides module in the domestic gas turbine multi-system integrated platform, a compressor model is constructed through the Modelica language; S2, designing standard compressor physical ports, including aerodynamic ports, mechanical rotating ports and control input interfaces, for integrating with the models of the combustor and turbine, to realize the multi-physical domain characteristics of compressor modeling; S3, defining user input parameters required for non-design point calculation of the compressor model; S4, defining variables required for non-design point calculation of the compressor model; S5, constructing key physical equations of the model; S6, developing a high-robustness characteristic map interpolation algorithm, S7, compressor characteristic map and bleed characteristic map data processing and storage; S8, performing non-design point solving calculation of the compressor, and through dragging the compressor icon, compressor testing or gas turbine system modeling is performed; after starting the solving, the SysTides module will perform model translation, analysis, optimization, C code generation, compilation and simulation on the defined variables and equations, and the embedded solver can solve differential algebraic equations to realize steady-state solving and dynamic response. The accurate prediction of the compressor at the non-design point is realized, and the reusability and system coupling ability of the model are improved.
[0006] Further, in step S3, the user input parameters include working medium, IGV angle, reference pressure, reference temperature, characteristic map, compressor stage number, bleed stage number and bleed performance map; when defining the parameters, the parameter type, physical unit, Modelica annotation syntax, display of the parameter configuration interface, and display and hiding of the physical ports in the model icon need to be specified. The user can set whether the compressor performs bleed operation in the interface, improve the reusability and expansion ability of the model in the whole machine modeling process, and enhance the flexibility and adaptability of system modeling.
[0007] Further, in step S4, the variables required for non-design point calculation of the compressor model include pressure ratio, efficiency, corrected speed, corrected flow, inlet / outlet temperature, bleed pressure ratio, bleed temperature ratio and bleed flow; the type and physical unit of the variable need to be specified when defining the variable.
[0008] Further, in step S5, the key physical equations of the model include mass conservation, momentum conservation and energy conservation equations; the pressure ratio, the inlet flow and the efficiency of each stage of the compressor are obtained by interpolation according to the compressor performance map, and the extraction amount, the extraction pressure and the extraction temperature of each stage are obtained by interpolation according to the extraction performance map of each stage.
[0009] Further, in step S6, the method for developing a characteristic map interpolation algorithm with high robustness is as follows: The general characteristics of the compressor are expressed by the function expression of equation 1: , wherein, is the pressure ratio, is the efficiency, is the corrected rotational speed, is the corrected inlet flow; The pressure ratio function of a certain boost ratio on a certain corrected rotational speed line is defined as which is expressed by equation 2: , wherein, and are the minimum value and the maximum value of the boost ratio on the current corrected rotational speed line, respectively; After introducing the pressure ratio function , the characteristic curve of the compressor characteristic map can be evolved from equation 1 and equation 2 into the expression of equation 3: , As long as the values of the corrected rotational speed and the pressure ratio function are known during the calculation process, the performance parameters of the compressor can be obtained by one-time interpolation.
[0010] Further, in step S6, the specific characteristic map interpolation calculation process is as follows: 1) According to the current igv angle value, find the adjacent two igv values: igvL and igvH in the characteristic map, and calculate the IGV linear interpolation ratio igvRatio=(igv-igvL) / (igvH-igvL); 2) According to the IGV linear interpolation ratio igvRatio, perform linear interpolation on the performance map data under the igvL and igvH angles to obtain the pressure ratio, flow and efficiency performance data under the current igv angle value, which are PRTable, WTable and EtaTable, respectively; 3) : According to the current modified speed value rpm, find the adjacent two speed lines: rpmL and rpmH, calculate the modified speed linear interpolation ratio rpmRatio = (rpm-rpmL) / (rpmH-rpmL); 4) : According to rpmRatio, linearly interpolate the performance map data under rpmL and rpmH speed lines, obtain the pressure ratio, flow and efficiency performance data at current rpm speed, respectively recorded as PRTab, WTab and EtaTab; 5) : According to the definition of pressure ratio function , calculate the corresponding pressure ratio value PR = PRMin+Z*(PRMax-PRMin) on the current speed line, usually PRMin = PRTab[1], PRMax = PRTab[N]; 6) : Find the adjacent pressure ratio: PRValL and PRValH, and the position information of PR on the speed line, calculate the pressure ratio linear interpolation ratio PRRatio = (PRVal-PRValL) / (PRValH-PRValL), here PRValL = PRTab[InxL], PRValH = PRTab[InxH]; 7) : According to the position information and the pressure ratio linear interpolation ratio PRRatio, calculate the flow and efficiency: W = WTab(InxL) + PRRatio*(WTab(InxH)-WTab(InxL)), Eta = EtaTab(InxL) + PRRatio*(EtaTab(InxH)-EtaTab(InxL)), Thus, the characteristic map interpolation calculation is completed.
[0011] Further, in step S7, the data of the characteristic map needs to be processed as follows: 1) : Record each modified speed value; 2) : Draw several auxiliary lines intersecting the modified speed line; 3) : Record the pressure ratio, modified flow and efficiency of the intersection points of each auxiliary line and the modified speed line, respectively form three arrays of the same size; 4) : The data of the bleeder performance map also refer to the above method; 5) : The compressor records each IGV angle value, 6) : Store the processed data into the record type model set through the compressor interface parameters.
[0012] Further, in step S8, the non-design point solving calculation of the compressor is carried out, and the process of steady-state solving and dynamic response is as follows: 1) : The Modelica model code is flattened by a translator, the hierarchical structure of the model is eliminated, and all equations are expanded into a flat, non-nested equation set, i.e. a flattened differential algebraic equation set, which contains differential equations for describing the change of variables over time and algebraic equations for describing the constraint relationship between variables; 2) : The flattened differential algebraic equation set is analyzed and sorted by an analyzer to determine the calculation order of the equations, and the sorted equation set is obtained, the analysis identifies the causal relationship between equations by constructing a variable-equation graph, and detects the index and high index problems of the equation set, and uses an algorithm for index reduction if necessary; the sorting is based on the analysis results, and the equations are sorted to convert the equation set into a form that can be sequentially calculated; the sorted equations have the same content as the flattened equations, but the numerical stability and solving efficiency are improved after the calculation order is optimized; 3) : The redundant variables are eliminated by an optimizer using symbolic processing techniques to simplify the equation set, and the simplified equation set is obtained, which is mathematically equivalent to the original equation set; the symbolic processing techniques used by the optimizer include: a. Symbolic simplification, applying mathematical rules to simplify expressions; b. Variable elimination, using substitution or elimination method to eliminate redundant variables; c. Equation rewriting, rewriting complex equations into equivalent simple forms; 4) : The simplified equation set is converted into C code; 5) : The C code is compiled and linked by a C compiler to generate an executable program; 6) : Perform simulation calculation by executing the executable program.
[0013] Compared with the prior art, the SysTides module in the domestic gas turbine multi-system integration platform is adopted, the compressor model is constructed by the Modelica language, the coupling simulation and response simulation between multiple physical domains are realized, the accuracy of performance prediction of the compressor under non-design point multi-working conditions is improved, the model reuse and expansion capability are good, and the simulation calculation efficiency and stability are significantly improved. BRIEF DESCRIPTION OF DRAWINGS
[0014] Fig. 1 It is a schematic diagram of the physical port of the compressor of the application.
[0015] Fig. 2 It is a calculation process diagram of the compressor characteristic graph interpolation algorithm of the application.
[0016] Fig. 3 It is a process diagram for completing non-design point solving calculation of the compressor by the compressor model constructed by the Modelica language of the application, realizing steady-state solving and dynamic response. DETAILED DESCRIPTION
[0017] To make the objectives, technical means and advantages of the present invention readily understood, the present invention will be further described below in conjunction with specific embodiments.
[0018] like Figs. 1 to 3 As shown, this invention provides a method for calculating the compressor non-design point based on a gas turbine multi-physics domain simulation platform, the steps of which are as follows: S1. The compressor model is constructed using the SysTides module in the domestic gas turbine multi-system integration platform and the Modelica language. Modelica is a physical system modeling language with features such as object-oriented and equation-based non-causal modeling, which can support various forms of model construction. S2. Design standard compressor physical ports, including pneumatic ports (such as intake ports, extraction ports, exhaust ports, etc.), mechanical rotary ports, and control input interfaces, for integration with combustion chamber and turbine models to achieve multi-physics domain characteristics of compressor modeling; such as Fig. 1 As shown, ①-⑦ are pneumatic ports used for fluid flow calculations; ⑧-⑨ are mechanical ports used to connect coaxial turbines or generators, etc.; ⑩ is the IGV input control interface. This is the compressor power output interface; physical ports, which can directly use the physical domain ports in the Modelica standard library, or can be independently developed according to the port definition rules to enable multi-physical domain connection of compressor physical ports; thereby realizing multi-physical domain compressor modeling and computational simulation based on the gas turbine multi-system integration platform; S3. Define the user input parameters required for non-design point calculations of the compressor model; S4. Define the variables needed for non-design point calculations of the compressor model; S5. Key physical equations for building the model; S6. Develop a robust feature map interpolation algorithm; S7. Data processing and storage of compressor characteristic diagrams and extraction characteristic diagrams; S8. Perform compressor non-design point calculations. By dragging the compressor icon, you can test the compressor or model the gas turbine system. After the solution starts, the SysTides module will translate, analyze, optimize, generate C code, compile and simulate the defined variables and equations. The embedded solver can solve differential algebraic equations to achieve steady-state solutions and dynamic responses.
[0019] In a preferred embodiment, in step S3, the user input parameters include working fluid, IGV angle, reference pressure, reference temperature, characteristic diagram, number of compressor stages, number of pumping stages, and pumping performance diagram. When defining parameters, the parameter type and physical unit must be specified, Modelica annotation syntax must be added, and the display of the parameter configuration interface and the display and hiding of physical ports in the model icon must be customized.
[0020] As a preferred embodiment, in step S4, the variables required for the calculation of the off-design point of the compressor model are defined, including the pressure ratio, the efficiency, the corrected rotational speed, the corrected flow rate, the inlet / outlet temperature, the bleed air pressure ratio, the bleed air temperature ratio, and the bleed air flow rate; the type and physical unit of the variable are defined when the variable is defined, so as to ensure the normalization and consistency of the model calculation, and the visibility of the variable can be set through the public or protected keyword, so as to control the display of the variable in the user interface and realize the flexibility and safety of the model parameter management.
[0021] As a preferred embodiment, in step S5, the key physical equations of the model include the mass conservation equation, the momentum conservation equation, and the energy conservation equation; the pressure ratio, the inlet flow rate, and the efficiency of each stage of the compressor are obtained by interpolation according to the compressor performance map, and the bleed air amount, the bleed air pressure, and the bleed air temperature of each stage are obtained by interpolation according to the bleed air performance map.
[0022] As a preferred embodiment, in step S6, the method for developing a characteristic map interpolation algorithm with high robustness is as follows: The general characteristic of the compressor is expressed by the function of equation 1: , wherein, is the pressure ratio, is the efficiency, is the corrected rotational speed, is the corrected inlet flow rate; The pressure ratio function of the pressure ratio of any point on a certain corrected rotational speed line is defined as which is expressed by equation 2: , wherein, and are the minimum value and the maximum value of the pressure ratio of the current corrected rotational speed line, respectively; After the pressure ratio function is introduced, the characteristic curve of the compressor characteristic map can be evolved from equation 1 and equation 2 into the expression of equation 3: , As long as the values of the corrected rotational speed and the pressure ratio function are known during the calculation process, the performance parameters of the compressor can be obtained through one-time interpolation, which has higher robustness. Thus, the calculation speed can be improved and the transmission error that may be caused by other methods can be reduced even under the condition of less calculation resources, and The numerical range of the value is monitored to ensure that it is always within the [0,1] interval, thereby effectively preventing the interpolation of the characteristic map from going out of bounds, enhancing the convergence of iteration, and improving the computational efficiency. The above method is not only applicable to the calculation of the entire compressor, but also to the calculation of the pumping characteristics.
[0023] As a preferred embodiment, such as Fig. 2 As shown, the specific characteristic map interpolation calculation process in step S6 is as follows: 1): Based on the current igv angle value, find two adjacent igv values in the characteristic graph: igvL and igvH, and calculate the IGV linear interpolation ratio igvRatio=(igv-igvL) / (igvH-igvL); 2): Based on the IGV linear interpolation ratio igvRatio, perform linear interpolation on the performance graph data (pressure ratio, flow rate, and efficiency data blocks, each a matrix of size N×numRPM) at the igvL and igvH angles to obtain the pressure ratio, flow rate, and efficiency performance data at the current igv angle value, which are PRTable, WTable, and EtaTable (matrices of size N×numRPM). 3): Based on the current corrected speed (rpm) value, find two adjacent speed lines: rpmL and rpmH, and calculate the corrected speed linear interpolation ratio rpmRatio=(rpm-rpmL) / (rpmH-rpmL); 4): Based on rpmRatio, perform linear interpolation on the performance graph data (column vectors corresponding to rpmL and rpmH in PRTable, WTable and EtaTable) under the rpm speed line to obtain the pressure ratio, flow rate and efficiency performance data at the current rpm speed, which are denoted as PRTab, WTab and EtaTab (which are N×1 matrices, i.e. column vectors). 5): Based on the pressure ratio function The definition is to calculate the pressure ratio PR=PRMin+Z*(PRMax-PRMin) corresponding to the current speed line. Usually, PRMin=PRTab[1] and PRMax=PRTab[N]. 6): Find the adjacent pressure ratios PRValL and PRValH on the speed line, and their position information (InxL and InxH). Calculate the linear interpolation ratio PRRatio = (PRVal - PRValL) / (PRValH - PRValL), where PRValL = PRTab[InxL] and PRValH = PRTab[InxH]. 7) : Calculate the flow and efficiency according to the position information (InxL and InxH) and the linear interpolation ratio of pressure ratio (PRRatio) : W = WTab(InxL) + PRRatio * (WTab(InxH) - WTab(InxL)), Eta = EtaTab(InxL) + PRRatio * (EtaTab(InxH) - EtaTab(InxL)), thus the characteristic map interpolation calculation is completed. Eta = EtaTab(InxL) + PRRatio * (EtaTab(InxH) - EtaTab(InxL)), thus the characteristic map interpolation calculation is completed.
[0024] As a preferred embodiment, in step S7, the data of the characteristic map needs to be processed as follows: 1) : Record each modified speed value; 2) : Draw several auxiliary lines intersecting the modified speed line; 3) : Record the pressure ratio, modified flow and efficiency at the intersection points of each auxiliary line and the modified speed line, respectively forming three arrays of the same size; 4) : The data of the bleeder performance map is also referenced to the above method; 5) : Record each IGV angle value of the compressor; 6) : Store the processed data into the record type model set through the compressor interface parameters.
[0025] As a preferred embodiment, as shown in step S8, the non-design point solving calculation of the compressor is performed, and the process of steady-state solving and dynamic response is as follows: Fig. 3 1) : Through the interpreter, the Modelica model code is flattened to eliminate the hierarchical structure of the model (such as class inheritance, component connection), and all equations are expanded into a flat, non-nested equation set, i.e. a flattened differential algebraic equation set (DAE equation set), which contains differential equations for describing the change of variables over time and algebraic equations for describing the constraint relationship between variables, for example, the equation set of a damping system is as follows: Equation one: der(x) = v, Equation two: m * der(v) = -c * v - k * x, where der(x) : derivative of variable x (differential term), represents the rate of change of x over time, m, c, k: parameters, respectively representing mass, damping coefficient and elastic coefficient, x, v: variables, respectively representing position and velocity; 2) : analysis and ordering of the flattened differential algebraic equations by an analyzer to determine the calculation order of the equations, and to obtain the ordered equation set, the analysis identifies the causal relationship between equations by constructing a variable-equation graph (each node represents a variable or equation, and the edge represents the dependency relationship); on the other hand, the index (such as the differential index) and the high index problem of the equation set are detected, and if necessary, the index reduction algorithm (such as the Pantelides algorithm) is used; the ordering is based on the analysis results, and the equations are ordered, the commonly used methods include topological ordering (for acyclic dependency graph) or Tarjan algorithm (processing strongly connected components), and the equation set is converted into a form that can be sequentially calculated; the ordered equation has the same content as the flattened equation, but the numerical stability and solving efficiency are improved after the calculation order is optimized; 3) : by using symbolic processing techniques to eliminate redundant variables, the optimizer simplifies the equation set to obtain the simplified equation set, which is mathematically equivalent to the original equation set; the symbolic processing techniques used by the optimizer include: a. symbolic simplification, applying mathematical rules to simplify expressions, such as combining like terms, etc.; b. variable elimination, using substitution or elimination method to eliminate redundant variables; c. equation rewriting, rewriting complex equations into equivalent simple forms; for example, the original equation: a = der (v); m * a = -c * v-k*x, eliminate a through symbolic processing, and the simplified equation set is m*der(v)=-c*v-k*x; the simplified equation set is mathematically equivalent to the original equation set, and is more compact, which is convenient for code generation; 4) : converting the simplified equation set into C code; 5) : compiling and linking the C code through the C compiler to generate an executable program; 6) : executing the executable program to perform simulation calculation. Through the above method, the SysTides module in the domestic gas turbine multi-system integrated platform is adopted, the compressor model is constructed by using the Modelica language, the coupling simulation and response simulation between multiple physical domains are realized, the accuracy of performance prediction of the compressor under non-design point multi-working conditions is improved, the model reuse and expansion ability are good, and the simulation calculation efficiency and stability are significantly improved.
[0026] The basic principles and main features of the present application and the advantages of the present application are shown and described. It should be understood by those skilled in the art that the present application is not limited by the above examples, the above examples and descriptions in the specification are only to illustrate the principles of the present application, and various changes, equivalent replacements, improvements, etc. of the present application fall within the scope of the present application without departing from the spirit and scope of the present application. The scope of protection of the present application is defined by the appended claims and their equivalents.
Claims
1. A method for calculating the non-design point of a compressor based on a gas turbine multi-physics domain simulation platform, characterized in that, The steps are as follows: S1. The compressor model is constructed using the SysTides module in the domestic gas turbine multi-system integration platform and the Modelica language. S2. Design standard compressor physical ports, including pneumatic ports, mechanical rotary ports, and control input interfaces, for integration with combustion chamber and turbine models to achieve multi-physics domain characteristics of compressor modeling; S3. Define the user input parameters required for non-design point calculations of the compressor model; S4. Define the variables needed for non-design point calculations of the compressor model; S5. Key physical equations for building the model; S6. Develop a robust feature map interpolation algorithm; S7. Data processing and storage of compressor characteristic diagrams and extraction characteristic diagrams; S8. Perform compressor non-design point calculations. By dragging the compressor icon, you can perform compressor testing or gas turbine system modeling. After the solution starts, the SysTides module will translate, analyze, optimize, generate C code, compile and simulate the defined variables and equations. The embedded solver solves the differential algebraic equations to achieve steady-state solution and dynamic response.
2. The method for calculating the compressor non-design point based on a gas turbine multi-physics domain simulation platform according to claim 1, characterized in that, In step S3, the user input parameters include working fluid, IGV angle, reference pressure, reference temperature, characteristic diagram, number of compressor stages, number of pumping stages, and pumping performance diagram. When defining parameters, the parameter type and physical unit must be specified, Modelica annotation syntax must be added, and the display of the parameter configuration interface and the display and hiding of physical ports in the model icon must be customized.
3. The method for calculating the compressor non-design point based on a gas turbine multi-physics domain simulation platform according to claim 1, characterized in that... In step S4, the variables required for non-design point calculation of the compressor model are defined, including pressure ratio, efficiency, corrected speed, corrected flow rate, inlet / outlet temperature, extraction pressure ratio, extraction temperature ratio, and extraction flow rate; the type and physical unit of the variable must be clearly defined when defining the variable.
4. The method for calculating the compressor non-design point based on a gas turbine multi-physics domain simulation platform according to claim 1, characterized in that, In step S5, the key physical equations of the model include the equations for conservation of mass, momentum, and energy. The pressure ratio, inlet flow rate, and efficiency of each stage compressor at the non-design point are obtained by interpolation based on the compressor performance diagram, while the pumping volume, pumping pressure, and pumping temperature of each stage are obtained by interpolation based on the pumping performance diagram of each stage.
5. The method for calculating the compressor non-design point based on a gas turbine multi-physics domain simulation platform according to claim 4, characterized in that, In step S6, the method for developing a robust feature map interpolation algorithm is as follows: The general characteristics of the compressor are expressed as a function of Equation 1: ， in, For pressure ratio, For efficiency, To correct the rotational speed, To correct the inbound traffic; Define the boost ratio at any point on a certain corrected speed line. pressure ratio function The expression for equation 2 is: ， in, and These are the minimum and maximum values of the boost ratio at the current corrected speed line, respectively. Introducing the pressure ratio function Subsequently, the compressor characteristic curve can be transformed from Equations 1 and 2 into Equation 3, and the expression for Equation 3 is: , During the calculation process, it is only necessary to know the corrected rotational speed. and pressure ratio function The compressor's performance parameters can be obtained by interpolation using the value of .
6. The method for calculating the compressor non-design point based on a gas turbine multi-physics domain simulation platform according to claim 5, characterized in that, In step S6, the specific characteristic map interpolation calculation process is as follows: 1): Based on the current igv angle value, find two adjacent igv values in the characteristic graph: igvL and igvH, and calculate the IGV linear interpolation ratio igvRatio=(igv-igvL) / (igvH-igvL); 2): Based on the IGV linear interpolation ratio igvRatio, perform linear interpolation on the performance graph data under the igvL and igvH angles to obtain the pressure ratio, flow rate and efficiency performance data under the current igv angle value, which are PRTable, WTable and EtaTable respectively; 3): Based on the current corrected speed (rpm) value, find two adjacent speed lines: rpmL and rpmH, and calculate the corrected speed linear interpolation ratio rpmRatio=(rpm-rpmL) / (rpmH-rpmL); 4): Based on rpmRatio, perform linear interpolation on the performance graph data under rpmL and rpmH speed lines to obtain the pressure ratio, flow rate and efficiency performance data at the current rpm speed, which are denoted as PRTab, WTab and EtaTab respectively; 5): According to the definition of the pressure ratio function, calculate the pressure ratio value PR=PRMin+Z*(PRMax-PRMin) corresponding to the current speed line. Usually, PRMin=PRTab[1] and PRMax=PRTab[N]. 6): Find the adjacent pressure ratios PRValL and PRValH on the speed line, and their position information. Calculate the linear interpolation ratio PRRatio=(PRVal-PRValL) / (PRValH-PRValL), where PRValL=PRTab[InxL] and PRValH=PRTab[InxH]. 7): Calculate flow rate and efficiency based on location information and the pressure ratio linear interpolation ratio PRRatio. W=WTab(InxL)+PRRatio*(WTab(InxH)-WTab(InxL)), Eta= EtaTab(InxL)+PRRatio*(EtaTab(InxH)-EtaTab(InxL)), This completes the characteristic map interpolation calculation.
7. The method for calculating the compressor non-design point based on a gas turbine multi-physics domain simulation platform according to claim 6, characterized in that, In step S7, the data of the characteristic diagram needs to be processed as follows: 1) Record each corrected speed value; 2) Draw several auxiliary lines that intersect with the corrected speed lines; 3) Record the pressure ratio, corrected flow rate, and efficiency at the intersection points of each auxiliary line and the corrected speed line, forming three arrays of the same size; 4) Refer to the above method for the data of the pumping performance diagram; 5 6): The compressor records each IGV angle value. 7): The processed data is stored in a record type model that is set through the compressor interface parameters.
8. The method for calculating the compressor non-design point based on a gas turbine multi-physics domain simulation platform according to claim 7, characterized in that, In step S8, the compressor off-design point calculation is performed, and the process of achieving steady-state solution and dynamic response is as follows: 1): The Modelica model code is flattened by a translator to eliminate the hierarchical structure of the model and expand all equations into a flat, non-nested system of equations, namely the flattened differential-algebraic equation system. The flattened differential-algebraic equation system contains differential equations describing the changes of variables over time and algebraic equations describing the constraint relationships between variables. 2): The flattened differential-algebraic equation system is analyzed and sorted using an analyzer to determine the computational order of the equations, resulting in a sorted equation system. The analysis involves constructing a variable-equation graph to identify causal relationships between equations and detecting indexing and high-indexing issues in the equation system, using algorithms to reduce the index order when necessary. The sorting is based on the analysis results, converting the equation system into a form that can be computed sequentially. The sorted equations have the same content as the flattened equations, but the optimized computational order improves numerical stability and solution efficiency. 3): The optimizer uses symbolic processing techniques to eliminate redundant variables and simplify the system of equations, resulting in a simplified system of equations that is mathematically equivalent to the original system of equations. The symbolic processing techniques used by the optimizer include: a. symbolic simplification, which simplifies expressions by applying mathematical rules; b. variable elimination, which eliminates redundant variables by using substitution or elimination methods; and c. equation rewriting, which rewrites complex equations into equivalent simpler forms. 4): Convert the simplified system of equations into C code; 5): Compile and link C code using a C compiler to generate an executable program; 6): Execute the executable program to perform simulation calculations.