Compressor reduced scale influence assessment method and device, electronic equipment and storage medium

Abstract

The invention provides an evaluation method and device for the reduced scale influence of a gas compressor, electronic equipment and a storage medium. The method comprises the following steps: performing three-dimensional fluid dynamics (CFD) calculation on a prototype compressor model, and obtaining a first two-dimensional blade profile of a plurality of blade rows and blade height positions of the compressor according to a calculation result; calculating first loss before and after scale reduction of the first two-dimensional blade profile through the two-dimensional CFD; establishing a loss prediction model of the first two-dimensional blade profile based on the first loss, and obtaining second loss corresponding to different target blade rows and blade height positions based on the loss prediction model; based on the second loss and the calculation result, the scale efficiency of the compressor is determined, the influence of scale on the aerodynamic performance of the compressor is evaluated based on the scale efficiency, and a first evaluation result is obtained. According to the scheme, the influence of the reduced scale on the aerodynamic performance of the gas compressor can be rapidly and accurately evaluated.

Description

Technical Field

[0001] The present application relates to the technical field of gas turbines, and in particular to a method, device, electronic equipment, and storage medium for evaluating the impact of compressor scaling. Background Art

[0002] Heavy-duty gas turbine high-flow multi-stage axial-flow compressors are large in size and consume high power. Direct full-scale testing is costly and time-consuming. Conducting scaled-down compressor testing based on similarity principles can reduce testing cycles and costs. However, scaled-down compressors and full-scale compressors do not fully meet the aerodynamic similarity criteria. Scaling reduces the Reynolds number, affecting boundary layer conditions and losses, resulting in differences in aerodynamic performance between scaled-down and full-scale compressors. Summary of the Invention

[0003] The purpose of this application is to solve one of the technical problems in the related art at least to a certain extent.

[0004] To this end, the first objective of the present application is to propose a method for evaluating the impact of compressor scaling, so as to achieve a rapid and accurate evaluation of the impact of scaling on the aerodynamic performance of the compressor.

[0005] A second objective of the present application is to provide a device for evaluating the impact of compressor scaling.

[0006] The third objective of this application is to provide an electronic device.

[0007] The fourth object of this application is to provide a computer-readable storage medium.

[0008] A fifth object of this application is to provide a computer program product.

[0009] To achieve the above objectives, a first embodiment of the present application provides a method for evaluating the effects of compressor scaling, comprising: performing three-dimensional fluid dynamics calculations (CFD) on a prototype compressor model, and obtaining first two-dimensional blade profiles of multiple blade rows and blade height positions of the compressor based on the calculation results;

[0010] Calculating the first loss of the first two-dimensional blade profile before and after scaling by two-dimensional CFD;

[0011] establishing a loss prediction model for the first two-dimensional blade profile based on the first loss, and obtaining second losses corresponding to different target blade rows and blade height positions based on the loss prediction model;

[0012] Based on the second loss and the calculation result, the scaled efficiency of the compressor is determined, and based on the scaled efficiency, an impact of scale on the aerodynamic performance of the compressor is evaluated to obtain a first evaluation result.

[0013] To achieve the above-mentioned objectives, a second embodiment of the present application provides a device for evaluating the effects of compressor scaling, comprising: a generation module for performing three-dimensional fluid dynamics (CFD) calculations on a prototype compressor model, and obtaining a first two-dimensional blade profile for multiple blade rows and blade height positions of the compressor based on the calculation results;

[0014] a determination module, configured to calculate, by two-dimensional CFD, a first loss of the first two-dimensional blade profile before and after scaling;

[0015] a prediction module, configured to establish a loss prediction model for the first two-dimensional blade profile based on the first loss, and obtain second losses corresponding to different target blade rows and blade height positions based on the loss prediction model;

[0016] An evaluation module is configured to determine a scaled efficiency of the compressor based on the second loss and the calculation result, and evaluate an impact of scale on the aerodynamic performance of the compressor based on the scaled efficiency to obtain a first evaluation result.

[0017] To achieve the above-mentioned purpose, the third aspect embodiment of the present application proposes an electronic device, comprising: a processor; and a memory communicatively connected to the processor; the memory storing computer-executable instructions; the processor executing the computer-executable instructions stored in the memory, so that the processor can execute the method for evaluating the impact of compressor scaling as described in the first aspect embodiment above.

[0018] To achieve the above-mentioned purpose, the fourth embodiment of the present application proposes a computer-readable storage medium having a computer program stored thereon, wherein the computer instructions are used to enable the computer to execute the method for evaluating the impact of compressor scaling as described in the first embodiment above.

[0019] To achieve the above-mentioned purpose, the fifth embodiment of the present application proposes a computer program product, including a computer program, which, when executed by a processor, implements the method for evaluating the impact of compressor scaling as described in the first embodiment above.

[0020] The present application provides a method, device, electronic device, and storage medium for evaluating the effects of compressor scaling. The method performs three-dimensional CFD on a prototype compressor model to obtain calculation results, and determines a first two-dimensional blade profile based on the calculation results. The first two-dimensional blade profile is then subjected to two-dimensional CFD to calculate a first loss. A loss prediction model is established based on the first loss, and the second loss corresponding to different target blade rows and blade height positions is predicted based on the loss prediction model. The scaling efficiency of the compressor can be determined based on the second loss, and the effect of scaling on the aerodynamic performance of the compressor can be evaluated based on the scaling efficiency. Therefore, this solution uses a CFD method to calculate the loss of the two-dimensional blade profile before and after scaling, which can achieve fast and high-precision loss calculations, thereby enabling a fast and accurate evaluation of the effect of scaling on the aerodynamic performance of the compressor.

[0021] Additional aspects and advantages of the present application will be given in part in the description below, and in part will become apparent from the description below, or will be learned through practice of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] The above and / or additional aspects and advantages of the present application will become apparent and easily understood from the following description of the embodiments in conjunction with the accompanying drawings, in which:

[0023] Figure 1 A flow chart of a method for evaluating the impact of compressor scaling provided in an embodiment of the present application;

[0024] Figure 2 A flow chart of another method for evaluating the impact of compressor scaling provided by an embodiment of the present application;

[0025] Figure 3 A schematic diagram of a process for evaluating the impact of compressor scaling based on a two-dimensional blade profile provided in an embodiment of the present application;

[0026] Figure 4 A schematic structural diagram of a device for evaluating the effects of compressor scaling provided in an embodiment of the present application. DETAILED DESCRIPTION

[0027] The following describes in detail embodiments of the present application, examples of which are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to be used to explain the present application, and should not be construed as limiting the present application.

[0028] The following describes a method and apparatus for evaluating the impact of compressor scaling according to an embodiment of the present application with reference to the accompanying drawings.

[0029] Figure 1 is a flow chart of a method for evaluating the impact of compressor scaling provided by an embodiment of the present application, such as Figure 1 As shown, the method for evaluating the impact of compressor scaling in an embodiment of the present application includes but is not limited to the following steps:

[0030] S101, performing three-dimensional fluid dynamics calculation (CFD) on the prototype compressor model, and obtaining a first two-dimensional blade profile of multiple blade rows and blade height positions of the compressor based on the calculation results.

[0031] It should be noted that the execution subject of the compressor scaling effect evaluation method provided in the embodiment of the present application is an electronic device, which can be a terminal device. Optionally, the terminal device can be a mobile electronic device or a non-mobile electronic device. For example, the mobile electronic device can be a mobile phone, a tablet computer, a laptop computer, a PDA, an in-vehicle electronic device, a wearable device, an ultra-mobile personal computer (UMPC), a netbook or a personal digital assistant (PDA), etc., and the non-mobile electronic device can be a personal computer (PC), a television, etc. The embodiment of the present application does not make any specific limitations.

[0032] In some embodiments, the prototype compressor model refers to a three-dimensional model of a full-scale compressor, and the prototype compressor model is the same size as the full-scale compressor. In other words, the prototype compressor model can be obtained by performing three-dimensional modeling on the full-scale compressor.

[0033] In some embodiments, the prototype compressor model may be meshed to obtain a mesh model, and three-dimensional fluid dynamics (CFD) calculations may be performed based on the mesh model to obtain calculation results.

[0034] In some embodiments, performing three-dimensional CFD on the prototype compressor model may include performing numerical simulation on the prototype compressor model using three-dimensional CFD to simulate the fluid flow state inside the compressor, thereby obtaining calculation results.

[0035] Optionally, the calculation results may include parameters such as velocity, pressure, temperature, and flow direction of the fluid at the airfoil inlet.

[0036] In some embodiments, the inlet relative Mach number and angle of attack may be determined based on the calculation results, and a first two-dimensional blade profile of multiple blade rows and blade height positions of the compressor may be generated based on the inlet relative Mach number and angle of attack.

[0037] In some embodiments, a range of inlet relative Mach numbers and angles of attack within which a two-dimensional airfoil profile can be generated can be determined, and a set number of inlet relative Mach numbers and angles of attack can be selected from the range. Furthermore, a first two-dimensional airfoil profile can be generated based on the set number of inlet relative Mach numbers and angles of attack, with multiple blade rows and blade height positions. In other words, multiple blade rows and blade height positions can be determined based on different inlet relative Mach numbers and angles of attack.

[0038] Optionally, the inlet relative Mach number can be calculated based on the speed parameters in the calculation results and the current sound speed, and the angle of attack can be calculated based on the airflow direction of the fluid at the blade inlet and the tangent direction of the blade profile in the calculation results.

[0039] S102 , calculating first losses of the first two-dimensional blade profile before and after scaling using two-dimensional CFD.

[0040] In some embodiments, a first two-dimensional airfoil can be numerically simulated at different scales using two-dimensional CFD to obtain first losses of the first two-dimensional airfoil before and after scaling. The first losses before and after scaling can be determined by numerically simulating fluid flow on a two-dimensional plane based on the first two-dimensional airfoil. The different scales refer to actual size and scaled size, i.e., before scaling refers to actual size, and after scaling refers to scaled size.

[0041] In some embodiments, the flow loss of the first two-dimensional airfoil before scaling and the flow loss of the first two-dimensional airfoil after scaling can be calculated using two-dimensional CFD, and the difference between the flow loss before scaling and the flow loss after scaling can be calculated to obtain the first loss.

[0042] Alternatively, flow loss refers to energy loss caused by friction, separation, turbulence, etc. during the flow of the fluid. Flow loss includes friction loss, separation loss, and turbulence loss.

[0043] In some embodiments, the flow field distribution of the first two-dimensional blade profile before and after scaling can be obtained by performing numerical simulation using two-dimensional CFD, and the flow loss can be calculated based on the flow field distribution.

[0044] S103 , establishing a loss prediction model for the first two-dimensional blade profile based on the first loss, and obtaining second losses corresponding to different target blade rows and blade height positions based on the loss prediction model.

[0045] In some embodiments, the loss prediction model is used to predict losses based on the inlet relative Mach number and angle of attack. Specifically, based on the first loss and the inlet relative Mach number and angle of attack corresponding to the first loss, a correlation between the first loss, the inlet relative Mach number, and the angle of attack can be obtained, and a loss prediction model can be established based on the correlation.

[0046] In some embodiments, by determining the target blade row and blade height position, and inputting the target blade row and blade height position into the loss prediction model, the loss prediction model determines the inlet relative Mach number and angle of attack corresponding to the target blade row and blade height position based on the target blade row and blade height position, and then based on the correlation relationship, determines the second loss and outputs it.

[0047] For example, the target blade row and blade height position is blade row 1, blade height position A. By inputting blade row 1, blade height position A into the loss prediction model, the loss prediction model determines the inlet relative Mach number and angle of attack corresponding to blade row 1, blade height position A, and thus the second loss is determined based on the inlet relative Mach number and angle of attack.

[0048] S104: Determine the scaled efficiency of the compressor based on the second loss and the calculation result, and evaluate the impact of scaled efficiency on the aerodynamic performance of the compressor based on the scaled efficiency to obtain a first evaluation result.

[0049] In some embodiments, an aerodynamic performance estimation method may be used to calculate the second loss and the calculation result to obtain the scaled efficiency of the compressor, thereby evaluating the impact of scale on the aerodynamic performance of the compressor based on the scaled efficiency of the compressor to obtain a first evaluation result.

[0050] Optionally, a set calculation condition may be determined, and under the set calculation condition, the aerodynamic performance estimation calculation may be performed on the second loss and the calculation result to obtain the scaled efficiency of the compressor.

[0051] Alternatively, the performance parameter changes of the compressor can be evaluated based on the scaled efficiency, and the scaled impact can be evaluated based on the changes in the performance parameters. For example, the performance parameters include flow coefficient, pressure ratio, Reynolds number, and other parameters.

[0052] In the evaluation method for the effect of compressor scaling provided in the embodiment of the present application, a three-dimensional CFD is performed on the prototype compressor model to obtain a calculation result, and a first two-dimensional blade profile is determined based on the calculation result. The first two-dimensional blade profile is further subjected to two-dimensional CFD to calculate the first loss. A loss prediction model is established based on the first loss, and the second loss corresponding to different target blade rows and blade height positions is predicted based on the loss prediction model, so that the scaling efficiency of the compressor can be determined based on the second loss, and the effect of scaling on the aerodynamic performance of the compressor can be evaluated based on the scaling efficiency. Therefore, this solution uses the CFD method to calculate the loss of the two-dimensional blade profile before and after scaling, which can achieve fast and high-precision loss calculation, thereby achieving a fast and accurate evaluation of the effect of scaling on the aerodynamic performance of the compressor.

[0053] Figure 2 is a flow chart of a method for evaluating the impact of compressor scaling provided by an embodiment of the present application, such as Figure 2 As shown, the method for evaluating the impact of compressor scaling in an embodiment of the present application includes but is not limited to the following steps:

[0054] S201, performing three-dimensional fluid dynamics calculation (CFD) on the prototype compressor model, and obtaining a first two-dimensional blade profile of multiple blade rows and blade height positions of the compressor based on the calculation results.

[0055] In the embodiment of the present application, the implementation method of step S201 can be implemented by any method in the various embodiments of the present application, which is not limited here and will not be repeated.

[0056] S202 : Based on the calculation results, determine and generate a candidate inlet relative Mach number range and a candidate angle of attack range corresponding to the first two-dimensional blade profile.

[0057] In some embodiments, different inlet relative Mach numbers and angles of attack may be determined based on the calculation results, and based on the different inlet relative Mach numbers and angles of attack, a candidate inlet relative Mach number range and a candidate angle of attack range corresponding to the first two-dimensional blade profile may be determined to be generated.

[0058] In some embodiments, a reference two-dimensional blade profile may be obtained and, based on the reference two-dimensional blade profile, a candidate inlet relative Mach number range and a candidate angle of attack range may be determined. For example, a historically generated two-dimensional blade profile may be obtained, and the inlet relative Mach number and angle of attack corresponding to the historically generated two-dimensional blade profile may be determined. Based on the inlet relative Mach number and angle of attack, a candidate inlet relative Mach number range and a candidate angle of attack range may be generated.

[0059] For example, by determining the inlet relative Mach number and angle of attack corresponding to the historically generated two-dimensional blade profile, and determining the maximum inlet relative Mach number and angle of attack and the minimum inlet relative Mach number and angle of attack, and increasing the maximum inlet relative Mach number and angle of attack, and reducing the minimum inlet relative Mach number and angle of attack, the reduced minimum inlet relative Mach number and the increased maximum inlet relative Mach number and angle of attack can be used as the candidate inlet relative Mach number range and the candidate angle of attack range.

[0060] S203 : Generate a first two-dimensional blade profile based on the candidate inlet relative Mach number range and the candidate angle of attack range.

[0061] In some embodiments, a target inlet relative Mach number may be determined from a range of candidate inlet relative Mach numbers, and a target angle of attack may be determined from a range of candidate angles of attack. Alternatively, a set number of target inlet relative Mach numbers and target angles of attack may be randomly obtained from the range of candidate inlet relative Mach numbers and the range of candidate angles of attack, thereby generating a first two-dimensional airfoil profile based on the target inlet relative Mach numbers and the target angles of attack.

[0062] For example, five target inlet relative Mach numbers are randomly determined from the candidate inlet relative Mach number range, and five target angles of attack are determined from the candidate angle of attack range. Then, the five target inlet relative Mach numbers and the five target angles of attack are combined respectively to generate 25 first two-dimensional blade profiles.

[0063] In some embodiments, generating the first two-dimensional airfoil profile may include determining an inlet condition position based on a target inlet relative Mach number and a target angle of attack, thereby generating the first two-dimensional airfoil profile based on the inlet condition position. Optionally, the inlet condition position includes a blade row position and a blade height position corresponding to the blade row position. A three-dimensional blade of a prototype compressor model may be determined, and the three-dimensional blade at the blade row position may be intercepted at the blade height position using a surface of revolution to generate the first two-dimensional airfoil profile.

[0064] Optionally, the three-dimensional blades of the prototype compressor model include blade row 1, blade row 2 and blade row 3. The blade row position is determined to be blade row 2 through the inlet condition position, and the blade height position is blade height A. The first two-dimensional blade profile of blade height position A can be intercepted on blade row 2 through the rotating surface.

[0065] In some embodiments, the inlet condition may be determined based on the target inlet relative Mach number and the target angle of attack, so that the blade row position and blade height position that meet the inlet condition are used as the inlet condition position.

[0066] S204 , calculating first losses of the first two-dimensional blade profile before and after scaling using two-dimensional CFD.

[0067] S205 , establishing a loss prediction model for the first two-dimensional blade profile based on the first loss, and obtaining second losses corresponding to different target blade rows and blade height positions based on the loss prediction model.

[0068] S206 , determining the scaled efficiency of the compressor based on the second loss and the calculation result, and evaluating the effect of scaled efficiency on the aerodynamic performance of the compressor based on the scaled efficiency to obtain a first evaluation result.

[0069] In the embodiment of the present application, steps S204-S206 can be implemented by any of the methods in the embodiments of the present application, which is not limited here and will not be described in detail.

[0070] On the basis of the above embodiment, after obtaining the second losses corresponding to different blade rows and blade height positions, it can also be determined whether the loss prediction model needs to be adjusted based on the second losses to improve the accuracy of the loss prediction model.

[0071] In some embodiments, by determining the second two-dimensional blade profile corresponding to the second loss, that is, according to the target blade row and blade height position corresponding to the second loss, a second two-dimensional blade profile can be generated, and the third loss of the second two-dimensional blade profile can be calculated by two-dimensional CFD, and the loss difference between the second loss and the third loss can be obtained.

[0072] Furthermore, whether the loss prediction model needs to be adjusted can be determined based on the loss difference and the difference threshold. In response to the loss difference being greater than the difference threshold, the loss prediction model is adjusted until the loss difference is less than or equal to the difference threshold.

[0073] That is to say, when the loss difference is greater than the difference threshold, the loss prediction model is adjusted, and the adjusted loss prediction model is used to re-obtain the second loss and the second two-dimensional blade shape corresponding to the second loss, and then the third loss is determined based on the second two-dimensional blade shape, and the loss difference between the second loss and the third loss is determined. If the loss difference is less than or equal to the difference threshold, there is no need to adjust the loss prediction model, otherwise continue to adjust the loss prediction model until the loss difference is less than or equal to the difference threshold.

[0074] Based on the above embodiment, after evaluating the effect of scale on the aerodynamic performance of the compressor based on the scale efficiency, the process of determining the scale efficiency of the compressor can be adjusted to improve the efficiency and accuracy of evaluating the effect of scale on the aerodynamic performance of the compressor.

[0075] In some embodiments, the blade geometry model, tip clearance, and computational grid of the prototype compressor model may be kept unchanged. By controlling the Reynolds number change of the prototype compressor model and calculating the effect of the Reynolds number change on the aerodynamic performance of the compressor through three-dimensional CFD during the change process, a second evaluation result is obtained, thereby simulating the effect of scale on the aerodynamic performance of the compressor, and verifying the accuracy of the first evaluation result based on the second evaluation result.

[0076] In some embodiments, a process of determining the scaled efficiency of the compressor is adjusted by obtaining a difference between the first evaluation result and the second evaluation result and in response to the difference being greater than a difference threshold.

[0077] In some embodiments, through three-dimensional CFD calculation verification of the effect of compressor scaling, the Reynolds number is changed through inlet throttling without changing the blade geometry and blade tip clearance, and the effect of scaling on aerodynamic performance is simulated. This saves the time of scaling the geometric model and regenerating the mesh, and the impact of the Reynolds number change can be considered separately.

[0078] In the compressor scaling impact assessment method provided in an embodiment of the present application, a candidate inlet relative Mach number range and a candidate angle of attack range are determined based on three-dimensional CFD calculation results. From these candidate inlet relative Mach number ranges and candidate angle of attack ranges, a target inlet relative Mach number and a target angle of attack are determined, thereby generating a first two-dimensional airfoil profile. Thus, generating a two-dimensional airfoil profile based on the three-dimensional CFD calculation results can improve the efficiency and accuracy of two-dimensional airfoil generation.

[0079] It should be noted that there are different ways to generate the first two-dimensional blade profile in the embodiments of the present application. When determining the first loss based on the first two-dimensional blade profile generated in different ways and generating a loss prediction model, the corresponding methods are also different.

[0080] Generating the first two-dimensional airfoil may include:

[0081] Method 1: Select a first set number of first target inlet relative Mach numbers from a range of candidate inlet relative Mach numbers, and select a first set number of first target angles of attack from a range of candidate angles of attack, thereby determining an inlet condition position based on the first target inlet relative Mach numbers and the first target angles of attack, so as to obtain a first two-dimensional blade profile by intercepting the three-dimensional blade based on the inlet condition position.

[0082] Method 2: Generate a two-dimensional blade profile based on the inlet relative Mach number and the inlet relative Mach number and angle of attack within the candidate inlet relative Mach number range and the candidate angle of attack range, select a second set number of two-dimensional blade profiles from the generated two-dimensional blade profiles, and determine the second target inlet relative Mach number and second target angle of attack corresponding to the two-dimensional blade profile, thereby determining the inlet condition position, and obtain the first two-dimensional blade profile by intercepting the three-dimensional blade at the inlet condition position.

[0083] In some embodiments, obtaining a first loss using the first two-dimensional blade profile determined in Method 1 and generating a loss prediction model based on the first loss may include: determining a target inlet relative Mach number and a target angle of attack corresponding to the first two-dimensional blade profile, and performing interpolation calculations on the target inlet relative Mach number, the target angle of attack, and the first loss to obtain an enhanced inlet relative Mach number and the enhanced angle of attack, as well as the first loss corresponding to the enhanced inlet relative Mach number and the enhanced angle of attack. Furthermore, performing linear fitting on the target inlet relative Mach number, the target angle of attack, the first loss, and the first loss corresponding to the enhanced inlet relative Mach number and the enhanced angle of attack to obtain the loss prediction model.

[0084] In some embodiments, obtaining a first loss using the first two-dimensional blade profile determined by Method 2 and generating a loss prediction model based on the first loss may include: obtaining an initial neural network model and determining a target inlet relative Mach number, a target angle of attack, and the first loss as training samples. The initial neural network model may then be trained based on the training samples until a training termination condition is satisfied, resulting in a target neural network model serving as a loss prediction model. The loss prediction model is used to reflect the correlation between the inlet relative Mach number, angle of attack, and loss. Establishing the loss prediction model through an artificial neural network allows for a highly accurate model to be created using a smaller number of samples.

[0085] In an embodiment of the present application, a loss prediction model is established by interpolation or neural network, and the losses of other scaled two-dimensional blade shapes are obtained based on the loss prediction model, so that the efficiency of each stage of the full-scale compressor can be corrected and the impact of scale reduction on the compressor can be evaluated.

[0086] Figure 3 The figure shows a schematic diagram of the process for evaluating the effect of compressor scaling based on two-dimensional blade profiles. Figure 3 As shown, a first loss of a first two-dimensional blade profile before and after scaling is calculated using two-dimensional CFD. Based on the first loss, a loss prediction model is established through interpolation or a neural network to obtain a second loss based on the loss prediction model. A second two-dimensional blade profile corresponding to the second loss is determined, and a third loss of the second two-dimensional blade profile is calculated using two-dimensional CFD. The loss prediction model can be verified using two-dimensional CFD. The loss difference between the second and third losses is obtained and compared with a loss threshold. If the loss difference is greater than the difference threshold, the loss prediction model is adjusted until the loss difference is less than or equal to the difference threshold.

[0087] Furthermore, a loss prediction model is used to obtain second losses corresponding to different target blade rows and blade height positions. An aerodynamic performance estimation method is then used to determine the compressor's scaled efficiency based on the second losses and the calculated results. The effect of scale on the compressor's aerodynamic performance is then evaluated based on the scaled efficiency, yielding a first evaluation result. By maintaining the blade geometry, tip clearance, and computational grid of the prototype compressor model unchanged and controlling the Reynolds number variation of the prototype compressor model, the process of determining the compressor's scaled efficiency is verified using three-dimensional CFD. By calculating the effect of Reynolds number variation on the compressor's aerodynamic performance using three-dimensional CFD, a second evaluation result is obtained, and the accuracy of the first evaluation result is verified based on the second evaluation result. By obtaining the difference between the first and second evaluation results, and in response to the difference being greater than a difference threshold, the process of determining the compressor's scaled efficiency is adjusted.

[0088] Corresponding to the evaluation methods for the effects of compressor scaling proposed in the above-mentioned embodiments, one embodiment of the present application further proposes an evaluation device for the effects of compressor scaling. Since the evaluation device for the effects of compressor scaling proposed in the embodiment of the present application corresponds to the evaluation methods for the effects of compressor scaling proposed in the above-mentioned embodiments, the implementation methods of the above-mentioned evaluation methods for the effects of compressor scaling are also applicable to the evaluation device for the effects of compressor scaling proposed in the embodiment of the present application, and will not be described in detail in the following embodiments.

[0089] In order to implement the above embodiment, the present application also proposes a device for evaluating the impact of compressor scaling.

[0090] Figure 4A schematic diagram of the structure of a device for evaluating the impact of compressor scaling provided in an embodiment of the present application.

[0091] like Figure 4 As shown, the compressor scaling effect evaluation device 400 includes:

[0092] A generation module 401 is configured to perform a three-dimensional fluid dynamics calculation (CFD) on the prototype compressor model and obtain a first two-dimensional blade profile of multiple blade rows and blade height positions of the compressor based on the calculation results;

[0093] A determination module 402 is configured to calculate a first loss of a first two-dimensional blade profile before and after scaling by using two-dimensional CFD;

[0094] A prediction module 403 is configured to establish a loss prediction model for the first two-dimensional blade profile based on the first loss, and obtain second losses corresponding to different target blade rows and blade height positions based on the loss prediction model;

[0095] The evaluation module 404 is configured to determine the scaled efficiency of the compressor based on the second loss and the calculation result, and evaluate the effect of scaled efficiency on the aerodynamic performance of the compressor based on the scaled efficiency to obtain a first evaluation result.

[0096] In a possible implementation of an embodiment of the present application, the generation module 401 is further used to: determine, based on the calculation results, a candidate inlet relative Mach number range and a candidate angle of attack range corresponding to the first two-dimensional blade profile; and generate the first two-dimensional blade profile based on the candidate inlet relative Mach number range and the candidate angle of attack range.

[0097] In a possible implementation of an embodiment of the present application, the generation module 401 is further used to: determine a target inlet relative Mach number from a range of candidate inlet relative Mach numbers; determine a target angle of attack from a range of candidate angles of attack; and generate a first two-dimensional blade profile based on the target inlet relative Mach number and the target angle of attack.

[0098] In a possible implementation of an embodiment of the present application, the generation module 401 is also used to: determine the inlet condition position based on the target inlet relative Mach number and the target angle of attack, the inlet condition position including the blade row position and the blade height position corresponding to the blade row position; determine the three-dimensional blades of the prototype compressor model, and intercept the three-dimensional blades of the blade row position through the rotating surface at the blade height position to obtain a first two-dimensional blade profile.

[0099] In a possible implementation of an embodiment of the present application, the prediction module 403 is further used to: perform interpolation calculations on the target inlet relative Mach number, the target angle of attack, and the first loss to obtain the enhanced inlet relative Mach number and the enhanced angle of attack, as well as the first loss corresponding to the enhanced inlet relative Mach number and the enhanced angle of attack; perform linear fitting on the target inlet relative Mach number, the target angle of attack, the first loss, and the first loss corresponding to the enhanced inlet relative Mach number and the enhanced angle of attack to obtain a loss prediction model.

[0100] In a possible implementation of an embodiment of the present application, the prediction module 403 is further used to: obtain an initial neural network model; determine the target inlet relative Mach number, target angle of attack and first loss as training samples; train the initial neural network model based on the training samples until the training end condition is met and the training is terminated, thereby obtaining a target neural network model as a loss prediction model, which is used to reflect the correlation between the inlet relative Mach number, angle of attack and loss.

[0101] In a possible implementation of an embodiment of the present application, the prediction module 403 is also used to: determine a second two-dimensional blade profile corresponding to the second loss; calculate the third loss of the second two-dimensional blade profile through two-dimensional CFD, and obtain the loss difference between the second loss and the third loss; in response to the loss difference being greater than a difference threshold, adjust the loss prediction model until the loss difference is less than or equal to the difference threshold.

[0102] In a possible implementation of an embodiment of the present application, the evaluation module 404 is further used to: control the change in the Reynolds number of the prototype compressor model, and calculate the impact of the change in the Reynolds number on the aerodynamic performance of the compressor through three-dimensional CFD during the change process to obtain a second evaluation result; obtain the difference between the first evaluation result and the second evaluation result; and in response to the difference being greater than a difference threshold, adjust the process of determining the scaled efficiency of the compressor.

[0103] In the evaluation device for the effect of compressor scaling provided in the embodiment of the present application, a three-dimensional CFD is performed on the prototype compressor model to obtain a calculation result, and a first two-dimensional blade profile is determined based on the calculation result. The first two-dimensional blade profile is further subjected to two-dimensional CFD to calculate a first loss. A loss prediction model is established based on the first loss, and the second loss corresponding to different target blade rows and blade height positions is predicted based on the loss prediction model, so that the scaling efficiency of the compressor can be determined based on the second loss, and the effect of scaling on the aerodynamic performance of the compressor can be evaluated based on the scaling efficiency. Therefore, this solution uses the CFD method to calculate the loss of the two-dimensional blade profile before and after scaling, which can achieve fast and high-precision loss calculation, thereby achieving a fast and accurate evaluation of the effect of scaling on the aerodynamic performance of the compressor.

[0104] It should be noted that the explanation of the embodiment of the method for evaluating the effect of compressor scaling is also applicable to the device for evaluating the effect of compressor scaling in this embodiment, and will not be repeated here.

[0105] In order to implement the above embodiments, the present application also proposes an electronic device, comprising: a processor, and a memory communicatively connected to the processor; the memory stores computer-executable instructions; the processor executes the computer-executable instructions stored in the memory to implement the method provided by the above embodiments.

[0106] In order to implement the above embodiments, the present application also proposes a computer-readable storage medium, in which computer-executable instructions are stored. When the computer-executable instructions are executed by a processor, they are used to implement the methods provided by the above embodiments.

[0107] In order to implement the above embodiments, the present application also proposes a computer program product, including a computer program, which implements the methods provided by the above embodiments when executed by a processor.

[0108] The collection, storage, use, processing, transmission, provision and application of user personal information involved in this application are in compliance with relevant laws and regulations and do not violate public order and good morals.

[0109] It is important to note that personal information collected from users should be used for legitimate and reasonable purposes and should not be shared or sold beyond these legitimate uses. Furthermore, such collection / sharing should be conducted only after receiving the user's informed consent, including but not limited to notifying the user to read the user agreement / user notice and sign an agreement / authorization that includes the relevant user information before using the feature. Furthermore, any necessary steps must be taken to safeguard and secure access to such personal information and ensure that others with access to personal information comply with its privacy policy and procedures.

[0110] This application contemplates providing implementation options for users to selectively block the use or access of personal information data. Specifically, this application contemplates providing hardware and / or software to prevent or block access to such personal information data. Risks can be minimized by limiting data collection and deleting data once it is no longer needed. Furthermore, where applicable, such personal information can be de-identified to protect user privacy.

[0111] In the descriptions of the foregoing embodiments, the reference terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" mean that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present application. In this specification, the schematic expressions of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner. In addition, those skilled in the art may combine and combine the different embodiments or examples described in this specification and the features of the different embodiments or examples, unless they are mutually inconsistent.

[0112] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of the technical features being referred to. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of such features. Throughout the description of this application, "plurality" means at least two, for example, two, three, etc., unless otherwise specifically defined.

[0113] Any process or method description in a flowchart or otherwise described herein may be understood to represent a module, segment or portion of code comprising one or more executable instructions for implementing the steps of a custom logical function or process, and the scope of the preferred embodiments of the present application includes alternative implementations in which functions may be performed out of the order shown or discussed, including performing functions in a substantially simultaneous manner or in the reverse order depending on the functions involved, which should be understood by those skilled in the art to which the embodiments of the present application belong.

[0114] The logic and / or steps represented in the flowcharts or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing the logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (e.g., a computer-based system, a system including a processor, or other system that can fetch and execute instructions from an instruction execution system, apparatus, or device). For 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 with one or more wires (electronic devices), a portable computer disk cartridge (magnetic device), random access memory (RAM), read-only memory (ROM), erasable and programmable read-only memory (EPROM or flash memory), fiber optic devices, and a portable compact disc read-only memory (CDROM). Furthermore, the computer-readable medium may even be paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium and then editing, interpreting or processing it in another suitable manner if necessary, and then storing it in a computer memory.

[0115] It should be understood that various parts of the present application can be implemented using hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented using software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented using hardware, as in another embodiment, any one of the following technologies known in the art or a combination thereof can be used to implement: a discrete logic circuit having a logic gate circuit for implementing a logic function on a data signal, an application-specific integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0116] Those skilled in the art will understand that all or part of the steps in the method of the above embodiment can be completed by instructing related hardware through a program, and the 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.

[0117] In addition, the functional units in the various embodiments of the present application may be integrated into a processing module, or each unit may exist physically separately, or two or more units may be integrated into a module. The above-mentioned integrated module may be implemented in the form of hardware or in the form of a software functional module. If the integrated module is implemented in the form of a software functional module and sold or used as an independent product, it may also be stored in a computer-readable storage medium.

[0118] The storage medium mentioned above may be a read-only memory, a magnetic disk, or an optical disk, etc. Although the embodiments of the present application have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present application. Persons skilled in the art may make changes, modifications, substitutions, and variations to the above embodiments within the scope of the present application.

Claims

1. A method for evaluating the impact of compressor scaling, characterized in that: The method comprises: Perform three-dimensional fluid dynamics calculations (CFD) on the prototype compressor model, and obtain the first two-dimensional blade profiles of multiple blade rows and blade height positions of the compressor based on the calculation results; Calculating the first loss of the first two-dimensional blade profile before and after scaling by two-dimensional CFD; establishing a loss prediction model for the first two-dimensional blade profile based on the first loss, and obtaining second losses corresponding to different target blade rows and blade height positions based on the loss prediction model; Based on the second loss and the calculation result, the scaled efficiency of the compressor is determined, and based on the scaled efficiency, an impact of scale on the aerodynamic performance of the compressor is evaluated to obtain a first evaluation result.

2. The method according to claim 1, characterized in that The step of obtaining a first two-dimensional blade profile of a plurality of blade rows and blade height positions of the compressor according to the calculation results includes: Based on the calculation results, determining a candidate inlet relative Mach number range and a candidate angle of attack range corresponding to the first two-dimensional blade profile; The first two-dimensional blade profile is generated based on the candidate inlet relative Mach number range and the candidate angle of attack range.

3. The method according to claim 2, characterized in that Generating the first two-dimensional blade profile based on the candidate inlet relative Mach number range and the candidate angle of attack range includes: determining a target inlet relative Mach number from the range of candidate inlet relative Mach numbers; determining a target angle of attack from the range of candidate angles of attack; The first two-dimensional blade profile is generated based on the target inlet relative Mach number and the target angle of attack.

4. The method according to claim 3, characterized in that Generating the first two-dimensional blade profile based on the target inlet relative Mach number and the target angle of attack includes: determining an inlet condition position based on the target inlet relative Mach number and the target angle of attack, the inlet condition position including a blade row position and a blade height position corresponding to the blade row position; The three-dimensional blades of the prototype compressor model are determined, and the three-dimensional blades at the blade row position are intercepted through the rotation surface at the blade height position to obtain the first two-dimensional blade profile.

5. The method according to claim 3, characterized in that The establishing of the loss prediction model of the first two-dimensional blade profile based on the first loss includes: performing interpolation calculation on the target inlet relative Mach number, the target angle of attack, and the first loss to obtain an enhanced inlet relative Mach number and an enhanced angle of attack, and a first loss corresponding to the enhanced inlet relative Mach number and the enhanced angle of attack; The target inlet relative Mach number, the target angle of attack, and the first loss, as well as the first loss corresponding to the enhanced inlet relative Mach number and the enhanced angle of attack, are linearly fitted to obtain the loss prediction model.

6. The method according to claim 3, characterized in that The step of establishing a loss prediction model for the first two-dimensional blade profile based on the first loss further includes: Get the initial neural network model; determining the target inlet relative Mach number, the target angle of attack, and the first loss as training samples; The initial neural network model is trained based on the training samples until the training end condition is met, and the target neural network model is obtained as the loss prediction model. The loss prediction model is used to reflect the correlation between the inlet relative Mach number, angle of attack and loss.

7. The method according to claim 1, characterized in that After obtaining the second losses corresponding to different target blade rows and blade height positions based on the loss prediction model, the method further includes: determining a second two-dimensional blade profile corresponding to the second loss; calculating a third loss of the second two-dimensional blade profile by two-dimensional CFD, and obtaining a loss difference between the second loss and the third loss; In response to the loss difference being greater than a difference threshold, the loss prediction model is adjusted until the loss difference is less than or equal to the difference threshold.

8. The method according to claim 1, characterized in that After evaluating the effect of scale reduction on the aerodynamic performance of the compressor based on the scale reduction efficiency, the method further includes: controlling a change in the Reynolds number of the prototype compressor model, and calculating, during the change, an effect of the change in the Reynolds number on the aerodynamic performance of the compressor using three-dimensional CFD to obtain a second evaluation result; Obtaining a difference between the first evaluation result and the second evaluation result; In response to the difference being greater than a difference threshold, a process for determining a scaled efficiency of the compressor is adjusted.

9. A device for evaluating the impact of compressor scaling, characterized in that: The device comprises: A generation module is used to perform three-dimensional fluid dynamics calculations (CFD) on the prototype compressor model and obtain the first two-dimensional blade profiles of multiple blade rows and blade height positions of the compressor based on the calculation results; a determination module, configured to calculate, by two-dimensional CFD, a first loss of the first two-dimensional blade profile before and after scaling; a prediction module, configured to establish a loss prediction model for the first two-dimensional blade profile based on the first loss, and obtain second losses corresponding to different target blade rows and blade height positions based on the loss prediction model; An evaluation module is configured to determine a scaled efficiency of the compressor based on the second loss and the calculation result, and evaluate an impact of scale on the aerodynamic performance of the compressor based on the scaled efficiency to obtain a first evaluation result.

10. An electronic device, characterized in that: include: a processor, and a memory communicatively connected to the processor; The memory stores computer-executable instructions; The processor executes the computer-executable instructions stored in the memory to implement the method according to any one of claims 1 to 8.

11. A computer-readable storage medium, characterized in that The computer-readable storage medium stores computer-executable instructions, which are used to implement the method according to any one of claims 1 to 8 when executed by a processor.

12. A computer program product, characterized in that The invention comprises a computer program, which implements the method according to any one of claims 1 to 8 when executed by a processor.

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