A method for constructing performance model of axial flow compressor

Abstract

The present invention discloses a method for constructing an axial flow compressor performance model, which relates to the field of simulation and design of axial flow compressors, including: S1, modeling each component of an elementary-level axial flow compressor separately; S2, calculating the efficiency loss of each component to obtain the actual pressure rise coefficient of the elementary-level axial flow compressor by inverse calculation; S3, calculating the outlet gas parameters of the elementary-level axial flow compressor model based on the actual pressure rise coefficient to complete parameter evaluation and performance prediction of the elementary-level axial flow compressor; S4, configuring parameters for the combination of each component based on the results of parameter evaluation and performance prediction to complete the encapsulation of the base pressure-level axial flow compressor model; The present invention provides a method for constructing an axial flow compressor performance model, which solves the problem that traditional axial flow compressor simulation models cannot perform inter-stage analysis, can only perform overall equipment analysis, and have a rough performance prediction method.

Description

Technical Field

[0001] The invention relates to the field of simulation design of axial flow compressors, and in particular to a method for constructing a performance model of an axial flow compressor. Background Art

[0002] A wind tunnel is an experimental device used to simulate flight conditions in the atmosphere. It tests models in a controlled laboratory environment to evaluate their performance, aerodynamic characteristics, and safety. It plays a vital role in the fields of machinery, aerospace, etc. Axial compressors are key equipment in wind tunnels. They compress airflow through moving blades to increase the speed and pressure of airflow in order to achieve the required experimental conditions in the wind tunnel.

[0003] In the detailed design stage of axial compressors, two methods are usually combined to analyze the compressor performance. One is to directly derive the import and export parameters of the axial compressor from the relationship between specific speed, flow rate, pressure ratio and efficiency, but it often ignores the state parameters between the compressor stages and only considers the overall performance analysis of the compressor. The corresponding results often have certain limitations. When it is necessary to analyze the inter-stage parameters of the compressor, it is difficult to judge its local performance and it is difficult to improve the overall performance of the compressor by improving the single-stage performance of the compressor. One is to use the speed triangle calculation method combined with the map interpolation method to correct the compressor inter-stage performance, but a large amount of data in the map has not been verified, and there are problems of poor applicability and large errors. Summary of the invention

[0004] An object of the present invention is to solve at least the above problems and / or disadvantages and to provide at least the advantages which will be described hereinafter.

[0005] In order to achieve these objectives and other advantages of the present invention, a method for constructing an axial compressor performance model is provided, comprising:

[0006] S1. Separately model each component of the elementary axial compressor;

[0007] S2. Calculate the efficiency loss of each component to obtain the actual pressure rise coefficient of the elementary axial compressor by reverse calculation;

[0008] S3. Calculate the outlet gas parameters of the primitive-level axial flow compressor model based on the actual pressure rise coefficient to complete parameter evaluation and performance prediction of the primitive-level axial flow compressor;

[0009] S4. Based on the results of parameter evaluation and performance prediction, parameters of the combination of each component are configured to complete the packaging of the base pressure level axial flow compressor model;

[0010] In S2, the components of the elementary-level axial compressor include: an inlet guide vane assembly, a moving blade assembly, a stationary blade assembly and a tail fairing assembly.

[0011] Preferably, in S1, the split modeling is obtained based on a performance model architecture of the compressor, and the performance model architecture includes:

[0012] The core method layer that provides principle input for component and part modeling at the abstract layer;

[0013] A basic resource layer for defining reusable resources;

[0014] An abstract model for expressing the overall architecture, components, assemblies, and interface relationships of the compressor, and an abstract layer that supports rapid reconstruction for different objects;

[0015] The instance layer is used to truly characterize specific models or specific design solutions and integrate actual design parameters and composition relationships with the abstract layer;

[0016] The run case layer is used to provide specific cases for compressor performance simulation verification.

[0017] Preferably, the core method layer constructs the compressor performance model by combining a one-dimensional stable isentropic flow model, a mean radius model, and a free vortex method;

[0018] Among them, the one-dimensional stable isentropic flow model assumes that the process of gas from the compressor inlet to the outlet through each stage of compression is isentropic compression, satisfying the continuity equation and energy conservation equation;

[0019] The mean radius model defines the mean radius of the compressor blades to characterize the compressor stage parameters with different blade lengths and numbers through steady-state parameters on the mean radius;

[0020] The free vortex method assumes that the axial velocity of the incoming flow is equal everywhere, and that the pressure rise at different radial heights after the airflow passes through the fan is equal, so as to deduce that the rotational velocity distribution at different positions of the airflow is inversely proportional to the distance of the blade section from the fan axis.

[0021] Preferably, the abstract layer is used to separate the model framework and model parameters in the Modelica system simulation model, and the abstract layer includes:

[0022] An overall architecture model with hierarchical characteristics, based on the overall principle architecture of a megawatt-class compressor;

[0023] Component-level models that decompose the overall architecture model;

[0024] A component-level model that decomposes the part-level model;

[0025] An abstract connector model that connects component-level models.

[0026] Preferably, the instance layer instantiates the relevant models of the abstract layer, and at the same time, by supplementing the mechanism equations of the incomplete models, adjusts the design parameters of the models at each level, realizes the instantiation of the models at each level, expands and improves the current various modeling objects, and constitutes the model library of the instance layer;

[0027] Among them, the instance layer has connector and interface models, as well as interface relationship forms, so as to instantiate the port model in the product, part, and component models according to the product model composition and coding information, generate the parameter grouping required for specific simulation, and create the port connection relationship between different parts and components in combination with the interface relationship form.

[0028] Preferably, the operation case layer identifies the corresponding architecture model template from top to bottom according to the simulation working conditions, environment, and medium requirements based on the compressor model composition or coding information, or re-parses and generates the compressor overall model framework based on the series-parallel relationship in the configuration.

[0029] Preferably, it also includes:

[0030] S5. Connect multiple primitive-level axial flow compressor models in series to construct an arbitrary-level axial flow compressor model.

[0031] Preferably, in S2,

[0032] In the above formula, C D is the total drag coefficient, s Indicates the density of moving blades, f r Indicates the advancing angle of the moving blade;

[0033] The inlet guide vane assembly efficiency loss K P Obtained by the following formula:

[0034]

[0035] In the above formula, K th0 represents the ideal pressure rise coefficient, l represents the moving blade flow coefficient, C Dp represents the inlet guide vane resistance coefficient, CL p represents the inlet guide vane lift coefficient, f p Indicates the inlet guide vane advance angle;

[0036] The stationary blade assembly efficiency lossK S Obtained by the following formula:

[0037]

[0038] In the above formula, e s represents the stator blade swirl coefficient, f s Indicates the stator blade advance angle;

[0039] The tail fairing assembly efficiency loss K D Obtained by the following formula:

[0040]

[0041] In the above formula, or D represents the efficiency of the tail fairing, x b Indicates the hub ratio.

[0042] Preferably, the actual pressure rise coefficient K th Obtained by the following formula:

[0043]

[0044] In the above formula, or T represents the actual fan efficiency, and , or T0 represents the design compressor stage efficiency.

[0045] Preferably, the outlet gas parameters include outlet parameters p 1 and the shaft power P of the axial compressor:

[0046] Among them, the export parameters p 1 is obtained by the following formula:

[0047] p 1= p 0+ dp

[0048] In the above formula, dp represents the compressor stage pressure rise, and , p 0 represents the compressor stage inlet pressure, r Indicates the density of the working fluid in the compressor;

[0049] The shaft power P is obtained by the following formula:

[0050]

[0051] In the above formula, m flow Indicates the mass flow rate of the compressor working fluid.

[0052] The present invention has at least the following beneficial effects: the present invention solves the problem that the traditional axial compressor simulation model cannot perform inter-stage analysis, can only perform overall equipment analysis, and the performance prediction method is rough. At the same time, it also solves the problem that the traditional compressor simulation method has poor versatility and is difficult to take into account a variety of different configuration products. The primitive level compressor model of the present invention has the following advantages:

[0053] (1) Ease of use: Users can directly simulate multi-stage compressors by dragging and dropping to obtain the overall compressor and each stage parameter.

[0054] (2) High reusability: Users can replace the compressor medium, modify the structural parameters and boundary parameters at will, and simulate the axial flow compressor under different working conditions.

[0055] (3) Configurable: A multi-level compressor performance simulation model library can be formed. The abstract layer provides templates for each level. The instance layer can quickly generate architecture templates, call related components or primitive models according to the specific product technical solutions, and regenerate the overall performance evaluation model.

[0056] (4) High computational efficiency: The simulation time required for the present invention to calculate 200 seconds in the real physical world is 0.797 seconds. The axial compressor model of the present invention can meet the requirements of ultra-real-time performance.

[0057] Other advantages, objectives and features of the present invention will be embodied in part through the following description, and in part will be understood by those skilled in the art through study and practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0058] Figure 1 It is a schematic diagram of a two-stage axial flow compressor model;

[0059] Figure 2 It is a schematic diagram of the development and packaging diagram of the elementary compressor of the present invention;

[0060] Figure 3 It is a schematic diagram of a simulation case of a two-stage axial flow compressor model of the present invention. DETAILED DESCRIPTION

[0061] The present invention is further described in detail below in conjunction with the accompanying drawings so that those skilled in the art can implement the invention with reference to the description.

[0062] The present invention proposes a method and device for constructing a compressor performance model based on the Modelica language. By combining a one-dimensional stable isentropic flow model, a mean radius model and a free vortex method, and replacing the map diagram with a correction correlation formula of the resistance coefficients of stationary blades and moving blades calibrated with a large amount of test data, the problem of large map diagram errors is solved. At the same time, the coefficients in the resistance system formula can be further corrected through the test data of the actual compressor to ensure the simulation accuracy of the compressor model under different types and different working conditions, and the parameter evaluation and performance prediction of the axial flow compressor can be accurately completed. Through a hierarchical technical solution, the model can be reusable and meet the requirements of scalability and consistency with the actual performance.

[0063] The present invention designs a performance model architecture including a core method layer, a basic resource layer, an abstract layer, an instance layer, and an operation case layer. The core method layer defines the core key algorithm for compressor performance modeling, and provides principle input for component and part modeling of the abstract layer; the basic resource layer is a basic reuse model of the environment, medium, working conditions, etc., which is a common basic resource for compressor performance simulation verification; the abstract layer expresses the abstract model of the overall architecture, components, assemblies, and interface relationships of the compressor, and has the characteristics of separation of incentives and data, flexible and configurable architecture, and supports rapid reconstruction for different objects; the instance layer is a real representation for specific models or specific design schemes, and is a fusion of actual design parameters, composition relationships and the abstract layer; the operation case layer provides specific cases for compressor performance simulation verification, which is a specific reference for business applications. The present invention takes into account both the general architecture of compressors and model-specific technical solutions, defines the abstraction and instantiation process of the performance model, satisfies the top-down decomposition and bottom-up integration of multidisciplinary simulation of compressors, and realizes automatic modeling generation driven by compressor composition schemes through connector models and interface relationship forms.

[0064] Specifically, a compressor performance model architecture includes:

[0065] 1. Construction of the core method layer: The compressor performance model is constructed by combining the one-dimensional stable isentropic flow model, the average radius model, and the free vortex method.

[0066] The one-dimensional stable isentropic flow model assumes that the process of gas from the compressor inlet to the outlet through each stage of compression is isentropic compression, satisfying the continuity equation and energy conservation equation.

[0067] The mean radius model defines the mean radius of the compressor blades and is one of the important design parameters. The steady-state parameters on the mean radius are used to characterize the compressor stage parameters with different blade lengths and numbers.

[0068] The free vortex method assumes that the axial velocity of the incoming flow is equal everywhere, and that the pressure rise at different radial heights after the airflow passes through the fan is equal. Therefore, it can be deduced that the rotational velocity distribution at different positions of the airflow is inversely proportional to the distance of the blade section from the fan axis.

[0069] 2. Construction of basic resource layer: define reusable resources such as medium characteristics, environmental parameters, task conditions, etc.

[0070] The medium characteristics should interact with the environmental model. Environmental parameters (such as temperature, pressure, and humidity) serve as built-in parameters of the medium characteristics model to drive the timing changes of the medium characteristics during the simulation process.

[0071] The temperature range, pressure range, and humidity range of environmental parameters are obtained through the analysis of task condition coding and described in the Modelica language to provide parameter input for various instance models and operation models.

[0072] The mission condition is an objective description of the actual operation and test scenario, which is encoded in combination with typical mission processes and test outline items, including pressure curves, medium change curves, environmental change processes, operating time, key monitoring parameters and parameter monitoring thresholds. All contents are encoded through data structures.

[0073] 3. Abstract layer construction: Separate the model framework and model parameters in the Modelica system simulation model. This layer includes:

[0074] Overall architecture model: With reference to the overall principle architecture of a megawatt-class compressor, it has hierarchical characteristics. The overall architecture is decomposed into a component-level model, and then further decomposed into a component-level model. The architecture layer model is the core of the abstract layer and has reconfigurable capabilities. Different models of products, parts, and component models have optional capabilities. Each modeling object can define a variety of different model templates based on its actual product technical solution, and its composition and interface relationship can be automatically configured according to the product code when used.

[0075] Component-level models: including rotor dynamics model, magnetic bearing model, medium model, inverter model, high-speed motor model, sensor model, compressor model, etc.

[0076] Component-level models: including shaft vibration model, displacement model, rotor model, electromagnet model, power amplifier model, motor body model, controller model, driver model, displacement sensor model, vibration sensor model, speed sensor model, current sensor model, inlet guide vane assembly, moving blade assembly, stationary blade assembly and tail fairing assembly, etc.

[0077] Abstract connector model: includes two types of connectors: general connector and special connector:

[0078] General connectors: including mechanical, electrical, control and other connector types.

[0079] Special connectors: including various cables, plugs, industrial bus protocols, special flanges, sealing pipe joints, etc. required by the model products. The various port parameters required by the connector also adopt a replaceable record format, so as to meet the reconfigurable requirements of the general architecture model and the component abstract model.

[0080] 4. Instance layer construction: Instantiate the abstract layer according to the specific simulation requirements and model object design scheme.

[0081] According to the model object architecture, the system architecture model in the abstract layer is obtained, and the architecture composition form is automatically adjusted according to the model object structure.

[0082] Adjust the connector and interface models, and regenerate various records in the connector and architecture interface models according to the model object and model granularity requirements.

[0083] Instantiate relevant models, supplement the mechanism equations of incomplete models, adjust the design parameters of models at all levels, realize the instantiation of models at all levels, expand and improve the current modeling objects of various types, and form a model library at the instance layer.

[0084] According to the test data, the swirl coefficients between the inlet guide vanes and the moving blades, and between the moving blades and the stationary blades are calculated, the moving blade flow coefficient, lift coefficient and drag coefficient are calculated, and then the pressure rise loss of each component is calculated. The actual pressure rise of the elementary axial compressor is obtained by reverse calculation, and the outlet gas parameters are calculated. Finally, the parameters are set and the model is packaged.

[0085] 5. Run case construction: Reconstruct the environment, working conditions, media, and system objects to form an operational simulation case to support virtual verification work.

[0086] According to the simulation conditions, environment, and medium requirements, the corresponding architecture model template is identified from top to bottom based on the compressor model composition or coding information, or the compressor overall model framework is re-analyzed and generated based on the series-parallel relationship in the configuration.

[0087] Decompose downwards, continue to retrieve the corresponding various parts model templates, continue to retrieve the component model templates, and complete the model composition definition that matches the actual product.

[0088] The instance layer model should also provide specific connector and interface models and interface relationship forms. According to the product model composition and coding information, the port model should be instantiated in the product, part, and component models to generate the parameter grouping required for specific simulation. Combined with the interface relationship form, the port connection relationship between different parts and components can be created.

[0089] For the created component model, according to the simulation requirements, combined with the basic model in the basic resource library, the mechanism equations are filled in to form a complete instance model, which is then checked and compiled.

[0090] Example 1

[0091] This embodiment provides a method for constructing a compressor performance model, which can realize the performance prediction of an axial flow compressor. By inputting boundary conditions such as inlet pressure, inlet temperature, and inlet flow, it is possible to predict parameters such as outlet pressure, outlet temperature, and outlet flow, thereby realizing performance prediction. In order to improve the reusability of the model, meet the requirements of scalability, and maintain consistency with the physical topological structure, the inlet guide vanes, single-stage stationary blades, single-stage moving blades, and tail fairing are constructed as a primitive level during the modeling process to form a primitive-level axial flow compressor model. For any level of compressor entity, any compressor equipment model can be built by directly dragging multiple primitive-level axial flow compressor models in series. Specifically, it includes:

[0092] Model construction: The primitive-level axial compressor model is constructed through simulation software, and then any level of axial compressor model is constructed by connecting multiple primitive-level axial compressor models in series. The primitive-level axial compressor model includes an inlet guide vane assembly, a moving blade assembly, a stationary blade assembly, and a tail fairing assembly;

[0093] Parameter setting: Calculate the swirl coefficients between the inlet guide vanes and moving blades, and between the moving blades and the stationary blades, calculate the moving blade flow coefficient, lift coefficient, and drag coefficient, and then calculate the pressure rise loss of each component, reversely calculate the actual pressure rise of the elementary axial compressor, and then calculate the outlet gas parameters. Finally, set the parameters and package the model.

[0094] In order to improve the reusability of the model, meet the requirements of scalability and maintain consistency with the physical topology, this embodiment constructs the inlet guide vane, single-stage stationary blade, single-stage moving blade and tail fairing into a primitive level during the modeling process to form a primitive level axial compressor model. For any level of compressor entity, you can directly drag multiple primitive level axial compressor models in series to build any compressor equipment model. For example, the established two-stage axial compressor model is as follows Figure 1 shown.

[0095] The primitive level can be composed of moving blades and stationary blade cascades. The primitive level cascades are the same as the cascades of plane flow. Therefore, this embodiment adopts a one-dimensional stable isentropic flow model. At the same time, the analysis process of the primitive level model uses the primitive level parameters at the average radius for calculation. In the development process of the primitive level model, the average radius of the blade is used as the calculation radius to simplify the complex compression process.

[0096] In summary, the axial compressor model of this embodiment combines the one-dimensional stable isentropic flow model, the average radius model and the free vortex model. First, the swirl coefficients between the guide vanes and the moving blades, the moving blades and the stationary blades are calculated, the flow coefficient, lift coefficient and drag coefficient within the stage are calculated, and then the pressure rise loss of each unit is calculated, and the actual pressure rise of the elementary stage is obtained by reverse calculation. Finally, the outlet gas parameters are calculated. The following is the detailed calculation process:

[0097] First calculate the inlet guide vane curvature angle i p :

[0098]

[0099] Where: x p Indicates the inlet guide vane installation angle.

[0100] Calculate the outlet lag angle of the inlet guide vane airflow d p :

[0101]

[0102] Where: s p represents the inlet guide vane pitch, c p Indicates the chord length of the inlet guide vane.

[0103] Calculate the airflow deflection angle of the inlet guide vane α p :

[0104]

[0105] Calculate the swirl coefficient of the inlet guide vane e p :

[0106]

[0107] Calculate the inlet guide vane advance angle f p :

[0108]

[0109] Calculate the swirl coefficient of the stator blade e s :

[0110]

[0111] Where: e s represents the stator blade swirl coefficient, ss Indicates the inlet guide vane pitch, c s represents the chord length of the inlet guide vane, α s Indicates the stator blade advance angle.

[0112] Calculate the stator blade advance angle α s :

[0113]

[0114] Calculate the blade advance angle α r :

[0115]

[0116] In the formula ,l represents the moving blade flow coefficient;

[0117] Calculate the moving blade flow coefficient l :

[0118]

[0119] Where: c 1 represents the absolute speed at the compressor inlet, R m represents the average blade radius, n Indicates the compressor speed.

[0120] Calculate the density of moving blades s :

[0121]

[0122] Where: c r is the chord length of the blade, s r Indicates the radial clearance between blades.

[0123] Calculating the lift coefficient C L :

[0124] .

[0125] Calculating blade profile losses CDP :

[0126]

[0127] Where: a 1 and a 2 are blade loss correction coefficients, aThe default value of 1 is 0.38, and the range is 0.2~0.6, a The default value of 2 is 0.006, and the range is 0.001~0.01, which can be modified by design parameters or test data respectively;

[0128] Calculate the ring end loss CDW :

[0129]

[0130] Where: l represents the leaf height, α 3 express a 3 is the ring end loss correction coefficient, the default value is 0.001, the range is 0.001~0.01, and it can be corrected by design parameters or test data.

[0131] Calculating Secondary Flow Losses CDS :

[0132]

[0133] Where: α 4 It is the correction factor of secondary flow loss, the default value is 0.015, the range is 0.01~0.05, and it can be corrected by design parameters or test data;

[0134] Calculate the total drag coefficient C D :

[0135] .

[0136] Calculate the ideal pressure rise factor K th0 :

[0137]

[0138] Calculate efficiency loss of moving blade assembly K R :

[0139]

[0140] Where: f r Indicates the advancing angle of the moving blade;

[0141] Calculate the efficiency loss of the inlet guide vane assembly K P :

[0142]

[0143]

[0144]

[0145] Where: represents the inlet guide vane lift coefficient, Represents the inlet guide vane resistance coefficient.

[0146] Calculate the efficiency loss of the stator assembly K S :

[0147]

[0148] Where: f s Indicates the stator blade advance angle.

[0149] Calculating the efficiency loss of the tail fairing assembly K D :

[0150]

[0151] Where: represents the efficiency of the tail fairing, Indicates the hub ratio.

[0152] Calculating Actual Fan Efficiency or T :

[0153]

[0154] Calculate the actual pressure rise factor K th :

[0155]

[0156] Where: or T0 represents the design compressor stage efficiency.

[0157] Calculate export parameters p 1:

[0158]

[0159]

[0160] Where: dp represents the compressor stage pressure rise, p 0 represents the compressor stage inlet pressure, r Indicates the density of the working fluid in the compressor.

[0161] Calculate the shaft power P:

[0162]

[0163] Where: m flow Indicates the mass flow rate of the compressor working fluid;

[0164] The parameters obtained by the above calculations are all parameters that reflect the overall performance of the compressor. These parameters can be used to predict the performance of the compressor. Specifically, the basic resource layer defines reusable resources such as medium characteristics, environmental parameters, and task conditions. The core method layer obtains parameters that reflect the overall performance of the compressor through the above calculations. The abstract layer designs the model architecture based on the above parameters of the overall performance of the compressor, and then encapsulates the model through the instance layer. In actual use, users can identify the corresponding architecture model template from top to bottom according to the simulation conditions, environment, and medium requirements based on the compressor model composition or coding information, or re-parse and generate the compressor overall model framework based on the series-parallel relationship in the configuration, and then check and compile the established compressor through simulation.

[0165] Furthermore, the compressor performance model construction method of this embodiment can be converted into Modelica language and the code can be written according to the syntax specification. The conversion steps are as follows:

[0166] (1) Development of imported guide vane components;

[0167] (2) Development of moving blade components;

[0168] (3) Development of stationary blade components;

[0169] (4) Tail fairing assembly development;

[0170] (5) Development of elementary compressor components;

[0171] (6) Elementary compressor model parameter panel settings;

[0172] (7) Primitive-level model encapsulation.

[0173] The final model developed is as follows Figure 2 As shown, the model parameter table parameters are shown in Table 1:

[0174] Table 1

[0175]

[0176] Furthermore, based on the above elementary axial compressor model, the following simulation calculation of the two-stage axial compressor model can be completed. The specific steps are as follows:

[0177] (1) Drag and drop two primitive-stage axial compressor models to connect them, and modify their corresponding parameters. In the parameter panel, select the inlet guide vanes and stator blades for the first stage of "Stage", and select the stator blades and tail fairing for the second stage. This will form a two-stage axial compressor structure of "inlet guide vanes - moving blades - stator blades - moving blades - stator blades - tail fairing";

[0178] (2) Select a boundary from the standard library, give the model appropriate boundary parameters, and connect the boundary to the compressor model;

[0179] (3) Click the Simulate button to complete the simulation of the two-stage axial compressor model.

[0180] The simulation diagram of the two-stage axial compressor model is shown below. Figure 3 shown.

[0181] Example 2

[0182] This embodiment is based on embodiment 1:

[0183] This embodiment provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the compressor performance model construction method of embodiment 1 is implemented. The computer program may be in source code form, object code form, executable file, or some intermediate form.

[0184] Example 3

[0185] This embodiment is based on embodiment 1:

[0186] The present embodiment provides a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the compressor performance model construction method of Embodiment 1. The computer program may be in source code form, object code form, executable file, or some intermediate form, etc. The storage medium includes: any entity or device capable of carrying computer program code, recording medium, computer memory, read-only memory (ROM), random access memory (RAM), electric carrier signal, telecommunication signal, and software distribution medium, etc. It should be noted that the content contained in the storage medium may be appropriately increased or decreased according to the requirements of legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, the storage medium does not include electric carrier signals and telecommunication signals.

[0187] Judging from the 200s time taken to simulate the real physical world, under the conditions of a simulation step size of 0.002 and a simulation accuracy of 1E-6, the steady-state calculation of the axial compressor was completed, and the CPU calculation time only took 0.797 seconds, indicating that the axial compressor model of the present invention can meet the requirements of super real-time performance.

[0188] The above solution is only an illustration of a preferred embodiment, but is not limited thereto. When implementing the present invention, appropriate replacement and / or modification can be performed according to user needs.

[0189] Although the embodiments of the present invention have been disclosed above, they are not limited to the applications listed in the specification and the embodiments. It can be fully applied to various fields suitable for the present invention. For those familiar with the art, additional modifications can be easily realized. Therefore, without departing from the general concept defined by the claims and equivalent scope, the present invention is not limited to the specific details and the illustrations shown and described here.

Claims

1. A method for constructing an axial flow compressor performance model, characterized in that: include: S1. Separately model each component of the elementary axial compressor; S2. Calculate the efficiency loss of each component to obtain the actual pressure rise coefficient of the elementary axial compressor by reverse calculation; S3. Calculate the outlet gas parameters of the primitive-level axial flow compressor model based on the actual pressure rise coefficient to complete parameter evaluation and performance prediction of the primitive-level axial flow compressor; S4. Based on the results of parameter evaluation and performance prediction, parameters of the combination of each component are configured to complete the packaging of the base pressure level axial flow compressor model; In S2, the components of the elementary-level axial compressor include: an inlet guide vane assembly, a moving blade assembly, a stationary blade assembly and a tail fairing assembly; In S1, the split modeling is obtained based on the performance model architecture of the compressor, and the performance model architecture includes: The core method layer that provides principle input for component and part modeling at the abstract layer; A basic resource layer for defining reusable resources; An abstract model for expressing the overall architecture, components, assemblies, and interface relationships of the compressor, and an abstract layer that supports rapid reconstruction for different objects; The instance layer is used to truly characterize specific models or specific design solutions and integrate actual design parameters and composition relationships with the abstract layer; The operation case layer is used to provide specific cases for compressor performance simulation verification; The core method layer constructs a compressor performance model by combining a one-dimensional stable isentropic flow model, a mean radius model, and a free vortex method; Among them, the one-dimensional stable isentropic flow model assumes that the process of gas from the compressor inlet to the outlet through each stage of compression is isentropic compression, satisfying the continuity equation and energy conservation equation; The mean radius model defines the mean radius of the compressor blades to characterize the compressor stage parameters with different blade lengths and numbers through steady-state parameters on the mean radius; The free vortex method assumes that the axial velocity of the incoming flow is equal everywhere, and that the pressure rise of the airflow at different radial heights after passing through the fan is equal, so as to deduce that the rotational velocity distribution at different positions of the airflow is inversely proportional to the distance of the blade section from the fan axis. The abstract layer separates the model framework and model parameters in the Modelica system simulation model, and the abstract layer includes: An overall architecture model with hierarchical characteristics, based on the overall principle architecture of a megawatt-class compressor; Component-level models that decompose the overall architecture model; A component-level model that decomposes the part-level model; An abstract connector model that connects component-level models; The instance layer instantiates the relevant models of the abstract layer, and at the same time, by supplementing the mechanism equations of the incomplete models, adjusts the design parameters of the models at each level, realizes the instantiation of the models at each level, expands and improves the current various modeling objects, and constitutes the model library of the instance layer; The instance layer has connector and interface models, and interface relationship forms, so as to instantiate the port model in the product, component, and assembly model according to the product model composition and coding information, generate the parameter grouping required for the specific simulation, and create the port connection relationship between different components and assemblies in combination with the interface relationship form; The operation case layer identifies the corresponding architecture model template from top to bottom according to the simulation working conditions, environment, and medium requirements based on the compressor model composition or coding information, or re-parses and generates the compressor overall model framework based on the series-parallel relationship in the configuration.

2. The method for constructing an axial flow compressor performance model according to claim 1, characterized in that: In S2, the efficiency loss of the moving blade assembly is K R Obtained by the following formula: In the above formula, C D is the total drag coefficient, σ Indicates the density of moving blades, φ r Indicates the advancing angle of the moving blade; The inlet guide vane assembly efficiency loss K P Obtained by the following formula: In the above formula, K th0 represents the ideal pressure rise coefficient, λ represents the moving blade flow coefficient, C Dp represents the inlet guide vane resistance coefficient, CL p represents the inlet guide vane lift coefficient, φ p Indicates the inlet guide vane advance angle; The stationary blade assembly efficiency loss K S Obtained by the following formula: In the above formula, ε s represents the stator blade swirl coefficient, φ s Indicates the stator blade advance angle; The tail fairing assembly efficiency loss K D Obtained by the following formula: In the above formula, η D represents the efficiency of the tail fairing, x b Indicates the hub ratio.

3. The method for constructing an axial flow compressor performance model according to claim 2, characterized in that: Actual pressure rise coefficient K th Obtained by the following formula: In the above formula, η T represents the actual fan efficiency, and , η T0 represents the design compressor stage efficiency.

4. The method for constructing an axial flow compressor performance model according to claim 1, characterized in that: The outlet gas parameters include outlet parameters p 1 and the shaft power P of the axial compressor: Among them, the export parameters p 1 is obtained by the following formula: p 1= p 0+ dp In the above formula, dp represents the compressor stage pressure rise, and , p 0 represents the compressor stage inlet pressure, ρ Indicates the density of the working fluid in the compressor; The shaft power P is obtained by the following formula: In the above formula, m flow Indicates the mass flow rate of the compressor working fluid.

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