Variable-speed power turbine meridian flow channel constraint optimization design method and device, electronic equipment and storage medium

Abstract

The invention discloses a variable-speed power turbine meridian flow channel constraint optimization design method and device, electronic equipment and a storage medium. The method comprises the steps that S1, a blade area is divided into n fluid units in the radial direction; s2, medium-diameter turbine inlet state parameters of all the fluid units are given according to radial distribution; s3, defining the comprehensive turbine efficiency of the optimization design; s4, parameter ranges of meridian flow channel molded line limiting conditions are set; and S5, combining a genetic optimization algorithm, taking the comprehensive turbine efficiency as a target function, taking stage power distribution, an outlet Mach number, the average section radius of each row of blades and the like as design variables, taking the target function as an iterative convergence target, and taking a constraint condition as a limit, and carrying out stage-by-stage iterative calculation on the design variables. The aerodynamic performance of the variable-speed power turbine in various states is better balanced in the design process, the reasonability of the one-dimensional design result of the variable-speed power turbine is improved, the design repeatability is reduced, and the design efficiency is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of aero-engines, and in particular to a method, device, equipment and storage medium for optimizing the constrained design of a meridian flow passage of a variable-speed power turbine. Background Art

[0002] High-speed helicopters have the characteristics of vertical take-off and landing, hovering and high maneuverability of conventional helicopters, and can also perform high-speed cruising flight, which greatly enhances their deployment, transportation and combat capabilities. They have become the focus of the country's new helicopter development, and corresponding model research and development work has been carried out.

[0003] However, when the speed of high-speed helicopters increases, they will face the problem of cross-sound of the forward rotor blades, resulting in a decrease in rotor propulsion efficiency and an increase in aerodynamic noise. Therefore, high-speed helicopters need to use a lower rotor speed when cruising at high speed. During vertical takeoff, landing, and single-engine emergency conditions, the high-speed rotation of the rotor will generate vertical thrust, thereby enabling the rotorcraft to achieve higher propulsion efficiency, so as to obtain higher propulsion efficiency within the entire flight envelope. Based on this working characteristic, new high-speed helicopters must require new power systems to meet their different work tasks or working mode needs. Among them, variable speed power turbines have the advantages of multi-state speed adjustment, simple mechanical structure, and no additional weight (which can avoid the complexity and weight of the variable speed transmission system and the transmission system shift mechanism). Therefore, they have become the focus of high-speed helicopter power development research.

[0004] Unlike conventional power turbines that work at a single main working point for a long time, the mission characteristics of variable speed power turbines determine that they need to work continuously under multiple working conditions with greatly different speeds. Changes in different speeds will cause a large range of changes in the angle of attack, which will cause the flow field environment to deteriorate, losses to increase, and efficiency to decline. In addition, in the cruising state, the load coefficient of the power turbine blades will increase significantly, resulting in a decrease in turbine stage efficiency. Low speed will also cause the power turbine to work in a low Reynolds range. The reduction in Reynolds number will weaken the anti-separation ability of the flow on the blade surface, especially the suction surface, resulting in a complex flow structure inside the channel. Therefore, the secondary flow loss and the total loss increase sharply and nonlinearly with the decrease in Reynolds number. At the same time, the low Reynolds effect will reduce the blade's resistance to angle of attack and load resistance, which has a great impact on the aerodynamic problems of the variable speed power turbine. This poses a greater challenge. If a single operating point is simply selected as the design point like a conventional power turbine, and the design parameters of the turbine mid-diameter are used as the average design parameters for design, it is impossible to achieve turbine component performance that meets the full operating condition index requirements. Therefore, in the design of a variable-speed power turbine, in order to ensure that the variable-speed power turbine can maintain high performance in a wide speed range, multiple operating states and radial flow changes need to be considered during one-dimensional design, resulting in a more complicated one-dimensional design process for the variable-speed power turbine and requiring more reliance on design experience. In addition, for the one-dimensional design of a multi-stage turbine, calculating the flow path geometry after optimizing the design to obtain the aerodynamic performance parameters may very likely cause the flow path profile to appear uneven or even sawtooth-shaped. Therefore, it is particularly important to develop a method for optimizing the design of a variable-speed power turbine with meridian flow constraints.

[0005] Currently, there is limited research in China on the design of variable-speed power turbines for high-speed helicopters, and no research has yet been conducted on optimization design methods that use the quantization of the meridional flow path as a constraint. Due to the mission characteristics of variable-speed power turbines, they must operate continuously under multiple operating conditions with significantly different speeds. These speed variations can cause wide variations in the angle of attack. Low speeds also cause the turbine to operate in the low Reynolds range. A decrease in the Reynolds number weakens the flow's resistance to separation on the blade surface, particularly the suction side, leading to a complex flow structure within the channel. Consequently, secondary flow losses and total losses increase dramatically and nonlinearly with decreasing Reynolds number. Existing variable-speed power turbine designs often ignore the radial variations in the channel flow at low speeds and low Reynolds numbers, and employ a single operating state for design. This makes it difficult to balance the aerodynamic performance of the variable-speed power turbine under various conditions. Furthermore, the design process is prone to unreasonable flow path geometry, resulting in numerous design iterations and a reliance on extensive experience. This reduces design efficiency and impacts the design cycle. Summary of the Invention

[0006] On the one hand, the present application provides a method for constrained optimization design of a meridian flow channel of a variable speed power turbine, which is used to solve the technical problems that the existing technology cannot achieve the performance of variable speed power turbine components meeting the full operating condition index requirements, the design efficiency is low, and the design cycle is affected.

[0007] This application is implemented through the following scheme:

[0008] A method for constrained optimization design of a meridian flow passage of a variable speed power turbine comprises the following steps:

[0009] S1. Divide the blade area into n fluid units along the radial direction. There is no radial gap between the fluid units and no intersection is allowed.

[0010] S2. Given the turbine inlet state parameters of the mid-diameter of each fluid unit according to radial distribution, and taking the design parameters of the mid-diameter of each fluid unit as the average design parameters of each fluid unit;

[0011] S3. Define the comprehensive turbine efficiency of the optimized design: η=λ1η1+λ2η2+...+λ i η i , λi is the weighted parameter of each working point, which is used to set the importance of each working point in the objective function;

[0012] S4. Setting the parameter ranges for the meridian flow path profile constraint conditions, including the maximum outer diameter of the turbine outlet casing, the expansion angle of the turbine inlet guide vane flow path profile, and the expansion angle increment of each blade discharge flow path profile, where the expansion angle refers to the angle θ formed by the hub or casing profile and the axial direction;

[0013] S5. Combined with the genetic optimization algorithm, with the comprehensive turbine efficiency as the objective function, the stage power distribution, the outlet Mach number, the average cross-sectional radius of each row of blades, the outlet airflow angle of each stage of stator blades and the angle of attack as the design variables, and the product of the turbine outlet area and the turbine speed, the power index requirements of each state, the turbine outlet airflow angle and the meridian flow channel profile restriction conditions as the constraint conditions, the optimization design process is to iteratively solve the flow control equations and related relationships, with the objective function as the iterative convergence target and the constraint conditions as the restrictions, and the design variables are iteratively calculated step by step to realize the constrained optimization design of the meridian flow channel of the variable speed power turbine.

[0014] Furthermore, in step S1, the radial balance equation is used between each fluid unit. where p is the local static pressure, r is the distance from the median diameter of each fluid unit to the axis of rotation, and v is the distance from the median diameter of each fluid unit to the axis of rotation. θ is the absolute circumferential velocity of the local airflow, and ρ is the local airflow density.

[0015] Furthermore, in step S2, the inlet state parameters include the median mass flow rate m of the inlet of the i-th fluid unit 1i, the absolute velocity v of the median diameter of the inlet of the i-th fluid unit 1i , static pressure P at the inlet diameter of the i-th fluid unit 1i , static temperature of the middle diameter of the inlet of the i-th fluid unit T 1i , the absolute airflow angle α of the inlet median diameter of the i-th fluid unit 1i , the relative airflow angle β of the inlet median diameter of the i-th fluid unit 1i , the distance r from the median diameter of the i-th fluid unit to the axis of rotation i .

[0016] Furthermore, in step S3, the weighted parameter of each operating point is determined by analyzing the importance of each operating point, specifically defined by the operating time of the aircraft at the corresponding operating point.

[0017] Furthermore, in step S4, setting the parameter ranges of the meridian runner profile restriction conditions specifically includes the following steps:

[0018] The expansion angle range of the first-stage guide vane flow channel is set, and the incremental expansion angle of the hub and casing profile of the subsequent blade row compared to the previous blade row is controlled within a certain range to control the flow channel development and ensure the continuity of the flow channel profile. The following mathematical model is used to limit it:

[0019] g1(x)=θ min -θ≤0

[0020] g2(x)=θ-θ max ≤0

[0021] g3(x)=Δθ min -Δθ≤0

[0022] g4(x)=Δθ-Δθ max ≤0 ...

[0024] g j (x) = D min -D≤0

[0025] g j+1 (x) = DD max ≤0;

[0026] Among them, g j (x) is the meridian flow channel profile constraint function, j is determined by the number of turbine stages. If the number of turbine stages is x, then j = 4x + 2; θ is the inlet guide vane flow channel expansion angle; Δθ is the flow channel expansion angle increment; θ max is the maximum value of the expansion angle of the inlet guide vane flow passage; θ min is the minimum value of the expansion angle of the inlet guide vane flow channel; Δθ min is the minimum value of the flow channel expansion angle increment limit; Δθ maxis the maximum limit of the flow channel expansion angle increment; D is the outer diameter of the outlet casing; D min D is the minimum value of the outer diameter of the outlet casing; max The maximum outer diameter of the outlet casing is limited.

[0027] Furthermore, in step S5, the mathematical model for the step-by-step iterative calculation of the design variables is defined as follows:

[0028]

[0029] maxη is the objective function, g i (x) is the constraint function, i is determined by the number of turbine stages and the number of working points involved in the design. If the number of turbine stages is x and the number of working points involved in the design is n, then i = 1, 2, 3...5x+n+3.

[0030] On the other hand, the present application also provides a variable speed power turbine meridian flow channel constraint optimization design device, comprising:

[0031] The fluid unit segmentation module is used to divide the blade area into n fluid units along the radial direction, with no radial gaps between the fluid units and no crossover is allowed;

[0032] The state parameter setting module is used to set the turbine inlet state parameters of the mid-diameter of each fluid unit according to radial distribution, and use the design parameters of the mid-diameter of each fluid unit as the average design parameters of each fluid unit;

[0033] Comprehensive turbine efficiency definition module, used to define the comprehensive turbine efficiency of the optimized design: η=λ1η1+λ2η2+ 。。。 +λ i η i , λi is the weighted parameter of each working point, which is used to set the importance of each working point in the objective function;

[0034] The parameter range setting module is used to set the parameter ranges of the meridian flow channel profile constraint conditions, including the maximum outer diameter of the turbine outlet casing, the expansion angle of the turbine inlet guide vane flow channel profile, and the expansion angle increment of each blade discharge flow channel profile. The expansion angle refers to the angle θ formed by the hub or casing profile and the axial direction.

[0035] The iterative calculation module is used to combine the genetic optimization algorithm, with the comprehensive turbine efficiency as the objective function, the stage power distribution, the outlet Mach number, the average cross-sectional radius of each row of blades, the outlet airflow angle of each stage of stator blades and the angle of attack as the design variables, and the product of the turbine outlet area and the turbine speed, the power index requirements of each state, the turbine outlet airflow angle and the meridian flow channel profile restriction conditions as the constraint conditions. The optimization design process is to iteratively solve the flow control equations and related relationships, with the objective function as the iterative convergence target and the constraint conditions as the restrictions, and the design variables are iteratively calculated step by step to realize the constrained optimization design of the meridian flow channel of the variable speed power turbine.

[0036] On the other hand, the present application also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the variable speed power turbine meridian flow channel constraint optimization design method when executing the computer program.

[0037] On the other hand, the present application also provides a storage medium, which includes a stored program, and when the program is running, controls the device where the storage medium is located to execute the steps of the variable speed power turbine meridian flow channel constraint optimization design method.

[0038] Compared with the existing technology, this application has the following beneficial effects:

[0039] The present application provides a method, device, electronic device and storage medium for constrained optimization design of a meridian flow channel of a variable speed power turbine. Compared with the traditional variable speed power turbine design method, the variable speed power turbine meridian flow channel constraint optimization design method of the present application can better balance the aerodynamic performance of the variable speed power turbine under various conditions during the design process, improve the rationality of the one-dimensional design results of the variable speed power turbine, reduce design repetitions, and improve design efficiency. It mainly brings two effects: ①. By comparing the importance of each working point, the comprehensive turbine efficiency is defined as the objective function, and each blade row channel is divided into n fluid units along the radial direction. By executing the relevant connections between the fluid units , the radial flow changes inside the variable speed power turbine channel are analyzed, and the design parameters of the inlet and outlet of each fluid unit are given by the design parameters of the median diameter of the fluid unit as the average parameters. Combined with the genetic optimization algorithm with the constraints as the restrictions, the design variables are iteratively calculated step by step, which can accurately improve the full mission cycle performance of the variable speed power turbine and ensure that the variable speed power turbine meets the performance index requirements of all working conditions; ②. At the same time, a method for quantifying the constraints of the multi-stage turbine meridian flow channel is proposed. While the turbine performance indicators meet the requirements, the smoothness of the meridian flow channel profile design results of the variable speed power turbine is guaranteed. The meridian flow channel form generated by the optimized design does not deviate from reality and is in line with engineering applications.

[0040] In addition to the above-described purposes, features and advantages, the present application also has other purposes, features and advantages. The present application will be further described in detail below with reference to the drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0042] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, for those skilled in the art, other drawings can be obtained based on these drawings without inventive work. In the drawings:

[0043] Figure 1 This is a flow chart of a method for optimizing the meridian flow channel constraints of a variable speed power turbine according to a preferred embodiment of the present application;

[0044] Figure 2 This is a schematic diagram of the fluid unit division of the preferred embodiment of the present application;

[0045] Figure 3 is a schematic diagram of the characteristic expansion angle of the turbine stage flow channel;

[0046] Figure 4 It is a schematic diagram of the step-by-step iterative calculation process of design variables combined with genetic optimization algorithm;

[0047] Figure 5 This is a schematic diagram of a module of a variable speed power turbine meridian flow channel constraint optimization design device according to a preferred embodiment of the present application;

[0048] Figure 6 This is a schematic block diagram of an electronic device according to a preferred embodiment of the present application;

[0049] Figure 7 It is a diagram of the internal structure of a computer device according to a preferred embodiment of the present application. DETAILED DESCRIPTION

[0050] It should be understood that the specific embodiments described herein are merely used to explain the technical solutions of the present application and are not intended to limit the present application.

[0051] In order to better understand the technical solution of the present application, a detailed description will be given below in conjunction with the accompanying drawings and specific implementation methods.

[0052] It should be noted that the execution subject of this embodiment may be a computing service device with data processing, network communication, and program execution capabilities, such as a tablet computer, personal computer, or mobile phone, or a device capable of optimizing the meridian flow path constraints of a variable-speed power turbine capable of performing the aforementioned functions. This embodiment and the following embodiments will be described below using the optimization design control device as the execution subject.

[0053] like Figure 1 As shown, the preferred embodiment of the present application provides a method for optimizing the design of a meridian flow channel constraint of a variable speed power turbine, comprising the steps of:

[0054] S1. Divide the blade area into n fluid units along the radial direction. There is no radial gap between each fluid unit and no intersection is allowed. For example Figure 2 As mentioned above, this embodiment divides the blade area into seven fluid units a to g along the radial direction, where ① represents the blade discharge inlet section and ② represents the blade discharge outlet section;

[0055] S2. Given the turbine inlet state parameters of the mid-diameter of each fluid unit according to radial distribution, and taking the design parameters of the mid-diameter of each fluid unit as the average design parameters of each fluid unit;

[0056] S3. Define the comprehensive turbine efficiency of the optimized design: η=λ1η1+λ2η2+...+λ i η i , λi is the weighted parameter of each working point, which is used to set the importance of each working point in the objective function;

[0057] S4. Set the parameter ranges of the meridian flow path profile restriction conditions, including the maximum outer diameter of the turbine outlet casing, the expansion angle of the turbine inlet guide vane flow path profile, and the value range of the expansion angle increment of each blade discharge flow path profile, where the expansion angle refers to the angle θ between the wheel hub or casing profile and the axial direction (see Figure 3 );

[0058] S5. Combined with the genetic optimization algorithm, with the comprehensive turbine efficiency as the objective function, the stage power distribution, the outlet Mach number, the average cross-sectional radius of each row of blades, the outlet airflow angle of each stage of stator blades and the angle of attack as the design variables, and the product of the turbine outlet area and the turbine speed, the power index requirements of each state, the turbine outlet airflow angle and the meridian flow channel profile restriction conditions as the constraint conditions, the optimization design process is to iteratively solve the flow control equations and related relationships, with the objective function as the iterative convergence target and the constraint conditions as the restrictions, and the design variables are iteratively calculated step by step to realize the constrained optimization design of the meridian flow channel of the variable speed power turbine.

[0059] The present embodiment provides a method for optimizing the meridian flow path constraints of a variable speed power turbine. Compared with the traditional method for optimizing the meridian flow path constraints of a variable speed power turbine, the method for optimizing the meridian flow path constraints of a variable speed power turbine of the present embodiment can better balance the aerodynamic performance of the variable speed power turbine under various conditions during the design process, improve the rationality of the one-dimensional design results of the variable speed power turbine, reduce design repetitions, and improve design efficiency. It mainly brings two effects: ①. By comparing the importance of each working point, the comprehensive turbine efficiency is defined as the objective function, and each blade row channel is divided into n fluid units along the radial direction. By executing the correlation between the fluid units, the variable speed power is optimized. The radial flow changes inside the turbine channel are analyzed. The design parameters of the median diameter of each fluid unit are used as the average parameters to give the inlet and outlet design parameters. Combined with the genetic optimization algorithm and the constraints as the limit, the design variables are iteratively calculated step by step. This can accurately improve the full mission cycle performance of the variable speed power turbine and ensure that the variable speed power turbine meets the performance index requirements under all working conditions. ② At the same time, a method for quantifying the constraints of the multi-stage turbine meridian flow channel is proposed. While meeting the turbine performance requirements, the smoothness of the meridian flow channel profile design results of the variable speed power turbine is guaranteed. The meridian flow channel form generated by the optimized design does not deviate from reality and is suitable for engineering applications.

[0060] Specifically, in step S1, the radial balance equation is used between each fluid unit. where p is the local static pressure, r is the distance from the median diameter of each fluid unit to the axis of rotation, and v is the distance from the median diameter of each fluid unit to the axis of rotation. θ is the absolute circumferential velocity of the local airflow, and ρ is the local airflow density.

[0061] In this embodiment, the radial balance equations are used between the fluid units. The benefits and purposes thereof include: enabling the present invention to better consider the flow changes in the radial direction within the turbine channel, and to refine and improve the comprehensive performance of the variable speed power turbine under multiple working conditions.

[0062] Specifically, in step S2, the inlet state parameters include the median mass flow rate m of the inlet of the i-th fluid unit 1i , the absolute velocity v of the median diameter of the inlet of the i-th fluid unit 1i , static pressure P at the inlet diameter of the i-th fluid unit 1i , static temperature of the middle diameter of the inlet of the i-th fluid unit T 1i , the absolute airflow angle α of the inlet median diameter of the i-th fluid unit 1i , the relative airflow angle β of the inlet median diameter of the i-th fluid unit 1i , the distance r from the median diameter of the i-th fluid unit to the axis of rotation i .

[0063] In this embodiment, the inlet state parameters include the inlet median mass flow rate m of the i-th fluid unit 1i , the absolute velocity v of the median diameter of the inlet of the i-th fluid unit 1i , static pressure P at the inlet diameter of the i-th fluid unit 1i , static temperature of the middle diameter of the inlet of the i-th fluid unit T 1i , the absolute airflow angle α of the inlet median diameter of the i-th fluid unit 1i , the relative airflow angle β of the inlet median diameter of the i-th fluid unit 1i , the distance r from the median diameter of the i-th fluid unit to the axis of rotation i Its benefits and purposes include: if the design parameters of the turbine mid-diameter are simply used as average design parameters for design, it will be difficult to ensure that the performance of the turbine components meets the requirements of all operating conditions.

[0064] Preferably, in step S3, the weighted parameter of each operating point is determined by analyzing the importance of each operating point, specifically defined by the operating time of the aircraft at the corresponding operating point.

[0065] In this embodiment, when weighting parameters at each operating point, the weighted parameters are obtained based on an analysis of the importance of each operating point. Specifically, the weighted parameters are defined and determined based on the operating time of the aircraft at the corresponding operating point. The benefits and purposes of using the operating time of the corresponding operating point to define and determine the weighted parameters at each operating point include: this method can comprehensively consider the turbine efficiency indicators of a variable speed power turbine under multiple operating conditions.

[0066] Preferably, in step S4, setting the parameter ranges of the meridian runner profile restriction conditions specifically includes the steps of:

[0067] The expansion angle range of the first-stage guide vane flow channel is set, and the incremental expansion angle of the hub and casing profile of the subsequent blade row compared to the previous blade row is controlled within a certain range to achieve the purpose of controlling the flow channel development and ensuring the continuity of the flow channel profile. The following mathematical model is used to limit it:

[0068] g1(x)=θ min -θ≤0

[0069] g2(x)=θ-θ max ≤0

[0070] g3(x)=Δθ min -Δθ≤0

[0071] g4(x)=Δθ-Δθ max ≤0 ...

[0073] g j (x) = D min -D≤0

[0074] g j+1(x) = DD max ≤0;

[0075] Among them, g j (x) is the meridian flow channel profile constraint function, j is determined by the number of turbine stages. If the number of turbine stages is x, then j = 4x + 2; θ is the inlet guide vane flow channel expansion angle; Δθ is the flow channel expansion angle increment; θ max is the maximum value of the expansion angle of the inlet guide vane flow passage; θ min is the minimum value of the expansion angle of the inlet guide vane flow channel; Δθ min is the minimum value of the flow channel expansion angle increment limit; Δθ max is the maximum limit of the flow channel expansion angle increment; D is the outer diameter of the outlet casing; D min D is the minimum value of the outer diameter of the outlet casing; max The maximum outer diameter of the outlet casing is limited.

[0076] When setting the parameter ranges of the meridian flow channel profile restriction conditions in this embodiment, a mathematical model is used to limit the value ranges of the maximum outer diameter of the turbine outlet casing, the expansion angle of the turbine inlet guide vane flow channel profile, and the incremental expansion angle of each blade discharge flow channel profile. The benefits and purposes of this embodiment include: while the turbine performance indicators meet the requirements, the smoothness of the meridian flow channel profile design results of the variable speed power turbine is ensured, and the meridian flow channel form generated by the optimized design does not deviate from reality and is suitable for engineering applications.

[0077] Preferably, in step S5, the mathematical model for iterative calculation of the design variables is defined as follows:

[0078]

[0079] maxη is the objective function, g i (x) is the constraint function, i is determined by the number of turbine stages and the number of working points involved in the design. If the number of turbine stages is x and the number of working points involved in the design is n, then i = 1, 2, 3...5x+n+3.

[0080] like Figure 4As shown, this embodiment combines the genetic optimization algorithm, takes the comprehensive efficiency as the objective function, takes the stage power distribution, the outlet Mach number, the average cross-sectional radius of each row of blades, the outlet airflow angle of each stage of the stator blades and the angle of attack as the design variables, takes the product of the turbine outlet area and the turbine speed, the power index requirements of each state, the power distribution coefficient range of each stage of the turbine (except the turbine outlet stage, given the power distribution coefficient range of the first few stages of the turbine, the turbine outlet stage power distribution coefficient can be accurately obtained by using the equation relationship), the turbine outlet airflow angle and the above-mentioned meridian flow channel restriction conditions as the constraint conditions, the optimization design process mainly involves iteratively solving the flow control equations and related relationships, taking the objective function maxη (comprehensive efficiency) as the iterative convergence target, and taking the constraint conditions as the limit, and iteratively calculating the design variables step by step. This embodiment performs iterative calculations on the design variables step by step. The mathematical model definition for stage-by-stage iterative calculations is detailed. The benefits and objectives of this embodiment's mathematical model definition for stage-by-stage iterative calculations of design variables include: using overall efficiency as the objective function, stage power distribution, exit Mach number, average cross-sectional radius of each blade row, exit flow angle and angle of attack of each stator blade stage as design variables, and the product of turbine outlet area and turbine speed (which reflects turbine blade strength), power requirements for each state, the range of turbine power distribution coefficients for each stage (except for the turbine exit stage, where the range of power distribution coefficients for the preceding stages is given and the turbine exit stage power distribution coefficient can be accurately determined using equations), turbine exit flow angle, and the aforementioned meridian flow channel constraints as constraints. This approach allows for better balancing of the aerodynamic performance of a variable-speed power turbine under various conditions during the design process, improving the rationality of the one-dimensional design results of a variable-speed power turbine, reducing design iterations, and increasing design efficiency.

[0081] like Figure 5 As shown, another preferred embodiment of the present application further provides a variable speed power turbine meridian flow channel constraint optimization design device, comprising:

[0082] The fluid unit segmentation module is used to divide the blade area into n fluid units along the radial direction, with no radial gaps between the fluid units and no crossover is allowed;

[0083] The state parameter setting module is used to set the turbine inlet state parameters of the mid-diameter of each fluid unit according to radial distribution, and use the design parameters of the mid-diameter of each fluid unit as the average design parameters of each fluid unit;

[0084] Comprehensive turbine efficiency definition module, used to define the comprehensive turbine efficiency of the optimized design: η=λ1η1+λ2η2+ 。。。 +λ i η i , λi is the weighted parameter of each working point, which is used to set the importance of each working point in the objective function;

[0085] The parameter range setting module is used to set the parameter ranges of the meridian flow channel profile constraint conditions, including the maximum outer diameter of the turbine outlet casing, the expansion angle of the turbine inlet guide vane flow channel profile, and the expansion angle increment of each blade discharge flow channel profile. The expansion angle refers to the angle θ formed by the hub or casing profile and the axial direction.

[0086] The iterative calculation module is used to combine the genetic optimization algorithm, with the comprehensive turbine efficiency as the objective function, the stage power distribution, the outlet Mach number, the average cross-sectional radius of each row of blades, the outlet airflow angle of each stage of stator blades and the angle of attack as the design variables, and the product of the turbine outlet area and the turbine speed, the power index requirements of each state, the turbine outlet airflow angle and the meridian flow channel profile restriction conditions as the constraint conditions. The optimization design process is to iteratively solve the flow control equations and related relationships, with the objective function as the iterative convergence target and the constraint conditions as the restrictions, and the design variables are iteratively calculated step by step to realize the constrained optimization design of the meridian flow channel of the variable speed power turbine.

[0087] The variable speed power turbine meridian flow channel constraint optimization design device provided in the present application adopts the variable speed power turbine meridian flow channel constraint optimization design method in the above-mentioned embodiment. It can solve the technical problems that the existing technology cannot achieve the performance of variable speed power turbine components to meet the full working condition index requirements, the design efficiency is low, and the design cycle is affected. Compared with the existing technology, the beneficial effects of the variable speed power turbine meridian flow channel constraint optimization design device provided in the present application are the same as the beneficial effects of the variable speed power turbine meridian flow channel constraint optimization design method provided in the above-mentioned embodiment, and the other technical features of the variable speed power turbine meridian flow channel constraint optimization design device are the same as the features disclosed in the above-mentioned embodiment method, which will not be repeated here.

[0088] like Figure 6 As shown, a preferred embodiment of the present application also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the variable speed power turbine meridian flow channel constraint optimization design method in the above-mentioned embodiment when executing the computer program.

[0089] The electronic device provided in the application adopts the variable speed power turbine meridian flow path constraint optimization design method in the above-mentioned embodiment, which can solve the technical problems of the existing technology that the performance of variable speed power turbine components cannot meet the full operating condition index requirements, the design efficiency is low, and the design cycle is affected. Compared with the existing technology, the beneficial effects of the electronic device provided in this application are the same as the beneficial effects of the variable speed power turbine meridian flow path constraint optimization design method provided in the above-mentioned embodiment, and the other technical features of the electronic device are the same as the features disclosed in the above-mentioned embodiment method, which will not be repeated here.

[0090] like Figure 7As shown, the preferred embodiment of the present application further provides a computer device, which can be a terminal or a liveness detection server, and its internal structure diagram can be as shown in FIG. Figure 7 As shown. The computer device includes a processor, a memory, and a network interface connected via a system bus. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The network interface of the computer device is used to communicate with other external computer devices via a network connection. When the computer program is executed by the processor, the steps of the above-mentioned variable speed power turbine meridian flow channel constraint optimization design method are implemented.

[0091] Those skilled in the art will understand that Figure 7 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than shown in the figure, or combine certain components, or have a different component arrangement.

[0092] The computer device provided in this application utilizes the variable-speed power turbine meridian flow path constraint optimization design method described in the aforementioned embodiment. This device can address the technical issues of the prior art, such as the inability to achieve full-scale performance requirements for variable-speed power turbine components, low design efficiency, and reduced design cycle time. Compared to the prior art, the computer device provided in this application offers the same beneficial effects as the variable-speed power turbine meridian flow path constraint optimization design method described in the aforementioned embodiment. Other technical features of the computer device are the same as those disclosed in the aforementioned embodiment and are not further elaborated here.

[0093] A preferred embodiment of the present application also provides a storage medium, which includes a stored program, and when the program is running, controls the device where the storage medium is located to execute the steps of the variable speed power turbine meridian flow channel constraint optimization design method in the above embodiment.

[0094] It should be noted that the steps shown in the flowcharts of the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions, and that, although a logical order is shown in the flowcharts, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0095] If the functions described in the method of this embodiment are implemented in the form of a software functional unit and sold or used as an independent product, they can be stored in a storage medium readable by one or more computing devices. Based on this understanding, the part of the embodiment of the present application that contributes to the prior art or the part of the technical solution can be embodied in the form of a software product, which is stored in a storage medium and includes a number of instructions for enabling a computing device (which can be a personal computer, server, mobile computing device or network device, etc.) to execute all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk and other media that can store program code.

[0096] Those skilled in the art will appreciate that the embodiments of the present application can be provided as methods, systems, or computer program products. Therefore, the application can adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the application can adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that contain computer-usable program code. The scheme in the embodiment of the present application can be implemented in various computer languages, for example, object-oriented programming language Java and literal translation scripting language JavaScript, etc.

[0097] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the steps in the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0098] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1The function specified in one or more boxes.

[0099] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0100] The present application also provides a computer program product, comprising a computer program, which, when executed by a processor, implements the steps of the above-mentioned variable speed power turbine meridian flow channel constraint optimization design method.

[0101] The computer program product provided in this application can address the technical issues of existing technologies, such as the inability to achieve full-scale performance requirements for variable-speed power turbine components, low design efficiency, and reduced design cycles. Compared to existing technologies, the computer program product provided in this application offers the same beneficial effects as the constrained optimization design method for a variable-speed power turbine meridian flow path provided in the aforementioned embodiments, and will not be further elaborated here.

[0102] Although the preferred embodiments of the present application have been described, those skilled in the art may make additional changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present application.

[0103] Obviously, those skilled in the art may make various changes and modifications to this application without departing from the spirit and scope of this application. Thus, if these modifications and variations of this application fall within the scope of the claims of this application and their equivalents, this application is intended to include these modifications and variations.

Claims

1. A method for constrained optimization design of a meridian flow passage of a variable speed power turbine, characterized in that: Including steps: S1. Divide the blade area into n fluid units along the radial direction. There is no radial gap between the fluid units and no intersection is allowed. S2. Given the turbine inlet state parameters of the mid-diameter of each fluid unit according to radial distribution, and taking the design parameters of the mid-diameter of each fluid unit as the average design parameters of each fluid unit; S3. Define the comprehensive turbine efficiency of the optimized design: η=λ1η1+λ2η2+...+λ i η i , λi is the weighted parameter of each working point, which is used to set the importance of each working point in the objective function; S4. Setting the parameter ranges for the meridian flow path profile constraint conditions, including the maximum outer diameter of the turbine outlet casing, the expansion angle of the turbine inlet guide vane flow path profile, and the expansion angle increment of each blade discharge flow path profile, where the expansion angle refers to the angle θ formed by the hub or casing profile and the axial direction; S5. Combined with the genetic optimization algorithm, with the comprehensive turbine efficiency as the objective function, the stage power distribution, the outlet Mach number, the average cross-sectional radius of each row of blades, the outlet airflow angle of each stage of stator blades and the angle of attack as the design variables, and the product of the turbine outlet area and the turbine speed, the power index requirements of each state, the turbine outlet airflow angle and the meridian flow channel profile restriction conditions as the constraint conditions, the optimization design process is to iteratively solve the flow control equations and related relationships, with the objective function as the iterative convergence target and the constraint conditions as the restrictions, and the design variables are iteratively calculated step by step to realize the constrained optimization design of the meridian flow channel of the variable speed power turbine.

2. The variable speed power turbine meridian flow channel constraint optimization design method according to claim 1, characterized in that: In step S1, the radial balance equation is used between each fluid unit. where p is the local static pressure, r is the distance from the median diameter of each fluid unit to the axis of rotation, and v is the distance from the median diameter of each fluid unit to the axis of rotation. θ is the absolute circumferential velocity of the local airflow, and ρ is the local airflow density.

3. The variable speed power turbine meridian flow channel constraint optimization design method according to claim 1, characterized in that: In step S2, the inlet state parameters include the mass flow rate m of the inlet diameter of the i-th fluid unit 1i , the absolute velocity v of the median diameter of the inlet of the i-th fluid unit 1i , static pressure P at the inlet diameter of the i-th fluid unit 1i , static temperature of the middle diameter of the inlet of the i-th fluid unit T 1i , the absolute airflow angle α of the inlet median diameter of the i-th fluid unit 1i , the relative airflow angle β of the inlet median diameter of the i-th fluid unit 1i , the distance r from the median diameter of the i-th fluid unit to the axis of rotation i .

4. The variable speed power turbine meridian flow channel constraint optimization design method according to claim 3, characterized in that: In step S3, the weighted parameters of each operating point are determined by analyzing the importance of each operating point, specifically defined by the operating time of the aircraft at the corresponding operating point.

5. The variable speed power turbine meridian flow channel constraint optimization design method according to claim 3, characterized in that: In step S4, setting the parameter ranges of the meridian runner profile restriction conditions specifically includes the following steps: The expansion angle range of the first-stage guide vane flow channel is set, and the incremental expansion angle of the hub and casing profile of the subsequent blade row compared to the previous blade row is controlled within a certain range to control the flow channel development and ensure the continuity of the flow channel profile. The following mathematical model is used to limit it: g1(x)=θ min -θ≤0 g2(x)=θ-θ max ≤0 g3(x)=Δθ min -Δθ≤0 g4(x)=Δθ-Δθ max ≤0 ... g j (x)=D min -D≤0 g j+1 (x)=D-D max ≤0; Among them, g j (x) is the meridian flow channel profile constraint function, j is determined by the number of turbine stages. If the number of turbine stages is x, then j = 4x + 2; θ is the inlet guide vane flow channel expansion angle; Δθ is the flow channel expansion angle increment; θ max is the maximum value of the expansion angle of the inlet guide vane flow passage; θ min is the minimum value of the expansion angle of the inlet guide vane flow channel; Δθ min is the minimum value of the flow channel expansion angle increment limit; Δθ max is the maximum limit of the flow channel expansion angle increment; D is the outer diameter of the outlet casing; D min D is the minimum value of the outer diameter of the outlet casing; max The maximum outer diameter of the outlet casing is limited.

6. The variable speed power turbine meridian flow channel constraint optimization design method according to claim 5, characterized in that: In step S5, the mathematical model for the step-by-step iterative calculation of the design variables is defined as follows: maxη is the objective function, g i (x) is the constraint function, i is determined by the number of turbine stages and the number of working points involved in the design. If the number of turbine stages is x and the number of working points involved in the design is n, then i = 1, 2, 3...5x+n+3.

7. A variable speed power turbine meridian flow channel constraint optimization design device, characterized in that: include: The fluid unit segmentation module is used to divide the blade area into n fluid units along the radial direction, with no radial gaps between the fluid units and no crossover is allowed; The state parameter setting module is used to set the turbine inlet state parameters of the mid-diameter of each fluid unit according to radial distribution, and use the design parameters of the mid-diameter of each fluid unit as the average design parameters of each fluid unit; Comprehensive turbine efficiency definition module, used to define the comprehensive turbine efficiency of the optimized design: η=λ1η1+λ2η2+ 。。。 +λ i η i , λi is the weighted parameter of each working point, which is used to set the importance of each working point in the objective function; The parameter range setting module is used to set the parameter ranges of the meridian flow channel profile constraint conditions, including the maximum outer diameter of the turbine outlet casing, the expansion angle of the turbine inlet guide vane flow channel profile, and the expansion angle increment of each blade discharge flow channel profile. The expansion angle refers to the angle θ formed by the hub or casing profile and the axial direction. The iterative calculation module is used to combine the genetic optimization algorithm, with the comprehensive turbine efficiency as the objective function, the stage power distribution, the outlet Mach number, the average cross-sectional radius of each row of blades, the outlet airflow angle of each stage of stator blades and the angle of attack as the design variables, and the product of the turbine outlet area and the turbine speed, the power index requirements of each state, the turbine outlet airflow angle and the meridian flow channel profile restriction conditions as the constraint conditions. The optimization design process is to iteratively solve the flow control equations and related relationships, with the objective function as the iterative convergence target and the constraint conditions as the restrictions, and the design variables are iteratively calculated step by step to realize the constrained optimization design of the meridian flow channel of the variable speed power turbine.

8. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the computer program, the steps of the variable speed power turbine meridian flow channel constraint optimization design method according to any one of claims 1 to 6 are implemented.

9. A storage medium comprising a stored program, which controls the device where the storage medium is located to execute the steps of the variable speed power turbine meridian flow channel constraint optimization design method as claimed in any one of claims 1 to 6 when the program is executed.

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