A method for designing and optimizing a low-pressure turbine rear casing strut based on split blades

Abstract

The application provides a low-pressure turbine rear casing support plate design optimization method based on split blades, and relates to the field of aeroengines.The application adopts a parameterized modeling method to describe a blade profile;in the first stage, the number of main blades is increased, a multi-objective optimization algorithm is used to optimize main blade modeling parameters, CFD is used to evaluate outlet airflow angles and total pressure recovery coefficients, and the feasibility of the main blades is judged according to a preset threshold value;after the first stage, the number of main blades is reduced, split blades are introduced between adjacent main blades, and main blade parameters, split blade parameters and relative positions are jointly optimized to maximize the total pressure recovery coefficient under the condition of meeting the outlet airflow angle deviation constraint; and the best candidate configuration is output as the final design result.The application adopts a staged design process, reduces the weight of the rear casing while maintaining the flow guiding capacity, improves the comprehensive aerodynamic performance, and is suitable for the design optimization of the low-pressure turbine rear casing support plate of an aeroengine.

Description

Technical Field

[0001] This invention relates to the field of aero-engine technology, and specifically to a design optimization method for the rear casing support plate of a low-pressure turbine based on a splitter blade. Background Technology

[0002] The low-pressure turbine rear casing, located after the low-pressure turbine and before the afterburner of an aero-engine, is a crucial stator component connecting the low-pressure turbine outlet and the engine's rear structure. This component performs multiple functions, including load-bearing and flow rectification: on the one hand, its inner and outer rings and connecting plates need to support the rear bearing and transfer loads from the engine's rear components; on the other hand, the airflow at the low-pressure turbine outlet typically has significant swirling and a large circumferential velocity component. The guide plates or rectifier blades in the rear casing need to weaken the swirling with minimal total pressure loss, reorganizing the airflow into a more axial flow to reduce exhaust distortion and provide more uniform inlet conditions for downstream components such as the afterburner and exhaust nozzle.

[0003] As modern aero engines develop towards higher thrust-to-weight ratios and lower fuel consumption, the design constraints faced by the low-pressure turbine rear casing are becoming increasingly complex. To reduce engine weight and cost, modern engines often employ low-pressure turbines with fewer stages and higher loads, causing the exhaust airflow from the low-pressure turbine to deviate further from the axial direction. This places higher demands on the rectification capabilities of the rear casing. At the same time, the need for engine compactness further compresses the axial length, requiring the guide vanes of the rear casing to achieve better rectification within a shorter axial distance. Coupled with the strong secondary flow effects brought about by high inlet Mach numbers and large airflow deflection angles, efficient flow organization within the rear casing becomes increasingly difficult.

[0004] Existing low-pressure turbine rear casing support plates generally exhibit two typical technical approaches. The first approach favors large-chord-length blades to reduce the flow deflection intensity per unit axial length, thus mitigating the risk of flow separation. However, this method results in a larger rear casing size and higher structural weight, hindering engine component compactness and thrust-to-weight ratio improvements. The second approach shortens the blade chord length to achieve a shorter and lighter structure; however, this method faces the challenge of achieving large-angle airflow deflection within a shorter axial length. Existing solutions generally suffer from the following shortcomings: to ensure sufficient flow guidance capacity, it is often necessary to increase the number of blades and lengthen the flow channel, increasing the size and weight of the rear casing, while shortening the blade chord length limits flow guidance capacity.

[0005] To improve the aerodynamic performance of blade cascades or rectifying components, existing technologies employ design approaches that redistribute local aerodynamic loads, reduce wake intensity, or improve the exit flow field by combining blades of different sizes. While some publicly available research has applied splitter blades to the transition section, these studies largely treat the splitter blades as a predetermined configuration for layout, parameter design, or combined styling. This approach generally lacks a more universal design method that meets the lightweight rectification requirements of the aft casing support plate. Specifically, it should explore a basic blade layout that meets aerodynamic design requirements by increasing the number of main blades, then reduce the number of main blades and increase the number of smaller blades, further optimizing the position and airfoil parameters of the smaller blades. This would allow the smaller blades to replace the larger blades while maintaining rectification effects, achieving structural weight reduction and flow loss control. Furthermore, in many existing schemes, the smaller blades are typically derived from and scaled around predetermined parameters of the larger blades, acting more as auxiliary components than as active design variables that independently participate in flow field reconstruction and load redistribution in the second stage. For the rear casing support plate, this design approach makes it difficult to fully utilize the potential of small blades in local flow control and loss suppression, and it is also not conducive to further reducing the number of large blades while meeting design requirements such as rectification and load bearing, so as to achieve a lightweight design of the turbine rear casing.

[0006] Therefore, for the rear casing, a key component of aero-engines, it is still necessary to propose a more universal design method that fully leverages the potential of the new configuration of the splitter blade in terms of flow control and structural lightweighting, so as to provide technical support for the next generation of advanced aero-engines. Summary of the Invention

[0007] In view of this, this application provides a design optimization method for the rear casing support plate of a low-pressure turbine based on the splitter blade, in order to solve the problem that the prior art is unable to simultaneously meet the requirements of high rectification and low aerodynamic loss under the requirements of lightweight and compact rear casing.

[0008] This application provides the following technical solution: a method for optimizing the design of a low-pressure turbine rear casing support plate based on a splitter blade, comprising the following steps:

[0009] S1: Define design parameters, including turbine rear casing operating parameters, target outlet airflow angle, target total pressure recovery coefficient, and blade geometric boundaries; S2: Based on the aforementioned design parameters, construct candidate configurations for the first-stage enhanced guide vanes, and optimize the vane design parameters using a multi-objective optimization algorithm, including: increasing the number of vanes N. t Increase to n·N t The flow field of each candidate main blade configuration is obtained by solving computational fluid dynamics, and the outlet airflow angle of the flow field is extracted. and total pressure recovery coefficient Calculate the airflow angle deviation Deviation of total pressure recovery coefficient ,in For the target outlet airflow angle, N is the target total pressure recovery coefficient. t To satisfy the load-bearing capacity of the support plate, the number of main blades, n, is an integer greater than 1; S3: Determine if there exists a satisfying condition. and Candidate individuals for the main leaf configuration. To preset the deflection angle deviation threshold, A preset total pressure recovery coefficient deviation threshold is set; if it exists, the first stage is considered passed, and the target is selected. The blade configuration with the highest value is selected as the main blade configuration for the second stage; if it does not exist, the design space is expanded. S4: Based on the main blade configuration of the second stage, the number of main blades n·N t Reduce to N t At least one shunting blade is introduced between adjacent main blades to establish a candidate configuration for the rear casing combining main blades and shunting blades. S5: An optimization algorithm is used to jointly optimize the main blade parameters, splitter blade parameters, and relative position parameters between the splitter blades and the main blades of the candidate rear casing configurations. Specifically, computational fluid dynamics is used to evaluate the flow field of each candidate rear casing configuration, and the outlet airflow angle of this flow field is extracted. and total pressure recovery coefficient The optimization objective is to maximize the total pressure recovery coefficient while satisfying the outlet airflow angle deviation constraint. S6: Output the candidate configuration of the rear casing with the highest total pressure recovery coefficient that meets the outlet flow direction requirements, as the final design result of the rear casing blade cascade.

[0010] According to one embodiment of this application, the multi-objective optimization algorithm in step S2 is a genetic algorithm, and the optimization objective is... and .

[0011] According to one embodiment of this application, the target outlet airflow angle =90°.

[0012] According to one embodiment of this application, in step S1, the geometric parameters of the rear casing blade are defined using the following parametric modeling method: the blade profile is divided into two segments, a leading edge segment and a trailing edge segment; the blade leading edge segment profile parameters include: leading edge radius. Trailing edge radius Leading edge structural angle Tail margin structural angle Leading edge wedge angle Angle connecting the centers Parameters of control point 1 Parameters of control point 2 Control point 3 parameters Control point 4 parameters and axial chord length The blade's trailing section profile is extended in a straight line along the trailing edge construction angle, starting from the point of tangency of the trailing edge circle of the preceding section. The axial chord length of the extended section is... The suction and pressure sides of the front profile are both shaped using third-order Bézier curves. The four control points of the Bézier curve on the suction side are the upper tangent point A1 of the leading edge circle, control point 1, control point 2, and the upper tangent point B1 of the trailing edge circle. The four control points of the Bézier curve on the pressure side are the lower tangent point A2 of the leading edge circle, control point 3, control point 4, and the lower tangent point B2 of the trailing edge circle. The control point parameters are the coordinates of the control points, with A1 having coordinates of... The coordinates of A2 are .for B1 coordinates are B2 coordinates are ;for B1 coordinates are B2 coordinates are .

[0013] According to one embodiment of this application, in step S4, the parameters of the diverter blades satisfy: ; ; ; in, , These are the leading edge radius and trailing edge radius of the splitter blade, respectively. , These are the axial chord lengths of the front section and the extended rear section of the splitter blade, respectively. , These are the leading edge radius and trailing edge radius of the main blade, respectively. , These are the axial chord lengths of the leading section and the extended section of the trailing section of the main blade, respectively.

[0014] According to one embodiment of this application, in step S5, the optimization algorithm is a genetic algorithm, and the optimization variables include all geometric parameters Bs of the splitter blades, and , and γ; where, This indicates that the splitter blades are initially and evenly placed on one side of the suction surface of the main blade. Location, γ represents the axial distance between the position of the splitter blade and the center of the trailing edge of the main blade, and γ represents the rotation angle of the splitter blade.

[0015] According to one embodiment of this application, in step S5, the outlet airflow angle deviation constraint is: ,in This is the preset outlet airflow angle deviation margin.

[0016] According to one embodiment of this application, in step S5, if the optimized maximum total pressure recovery coefficient is... Then increase the number of splitter blades to We will continue to optimize using the optimization algorithm.

[0017] Compared with the prior art, the beneficial effects that at least one technical solution adopted in the embodiments of this specification can achieve include at least: 1. This invention proposes a phased design process of main blade feasibility verification and joint optimization, which can screen out obviously infeasible aerodynamic configurations before high-dimensional joint optimization, reduce invalid calculations, and improve design efficiency.

[0018] 2. In the first stage, the present invention constructs a physical feasibility criterion by presetting the total pressure recovery coefficient deviation threshold and the flow direction tolerance, which can prevent the optimization algorithm from staying in the design area of ​​severe separation or obviously unable to meet the flow guidance requirements for a long time.

[0019] 3. In the second stage, the present invention adopts a configuration reorganization method of reducing the main blades and introducing the splitter blades, which can reduce the weight of the rear casing and enhance the flow guidance capability while maintaining or restoring the target flow guidance capability, thereby helping to improve the compactness of engine components and reduce friction loss.

[0020] 4. The present invention uses the diverter blades to reguide and reshape the local low-energy fluid region, wake region or potential separation region generated after the reduction of the main blade, which is beneficial to improving the flow field structure and improving the overall aerodynamic performance of the rear casing.

[0021] 5. This invention combines parametric leaf shape modeling with optimization algorithms, giving each optimization variable a clear geometric meaning, which helps improve the controllability of the design process and the feasibility of engineering implementation. Attached Figure Description

[0022] To more clearly illustrate the technical solutions of the embodiments of this application, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0023] Figure 1This is a schematic diagram of the blade parametric modeling method according to an embodiment of the present invention; Figure 2 This is a schematic diagram of the splitter blade architecture according to an embodiment of the present invention. Detailed Implementation

[0024] The embodiments of this application will now be described in detail with reference to the accompanying drawings.

[0025] The following specific examples illustrate the implementation of this application. Those skilled in the art can easily understand other advantages and effects of this application from the content disclosed in this specification. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of them. This application can also be implemented or applied through other different specific embodiments, and the details in this specification can also be modified or changed based on different viewpoints and applications without departing from the spirit of this application. It should be noted that, in the absence of conflict, the following embodiments and features in the embodiments can be combined with each other. Based on the embodiments in this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0026] This invention provides a method for optimizing the design of a low-pressure turbine rear casing support plate based on a splitter blade, comprising the following steps: Step S1: Define design parameters, including turbine rear casing operating parameters, target outlet airflow angle, target total pressure recovery coefficient, and blade geometric boundaries.

[0027] Specifically, such as Figure 1 As shown, the geometric parameters of the rear casing blades are defined using the following parametric modeling method: the blade profile is divided into two segments, the leading edge and the trailing edge; the leading edge profile parameters include: leading edge radius. Trailing edge radius Leading edge structural angle Tail margin structural angle Leading edge wedge angle Angle connecting the centers Parameters of control point 1 Parameters of control point 2 Control point 3 parameters Control point 4 parameters and axial chord length The blade's trailing section profile is extended in a straight line along the trailing edge construction angle, starting from the point of tangency of the trailing edge circle of the preceding section. The axial chord length of the extended section is... The suction and pressure sides of the front profile are both shaped using third-order Bézier curves. The four control points of the Bézier curve on the suction side are the upper tangent point A1 of the leading edge circle, control point 1, control point 2, and the upper tangent point B1 of the trailing edge circle. The four control points of the Bézier curve on the pressure side are the lower tangent point A2 of the leading edge circle, control point 3, control point 4, and the lower tangent point B2 of the trailing edge circle. The control point parameters are the coordinates of the control points, with A1 having coordinates of... The coordinates of A2 are .for B1 coordinates are B2 coordinates are ;for B1 coordinates are B2 coordinates are .

[0028] In practice, the following parameters are input: inlet total temperature, inlet total pressure, inlet airflow angle, outlet flow rate, target outlet airflow angle, and target total pressure recovery coefficient of the turbine rear casing. The geometric boundaries, minimum thickness constraints, and maximum dimension constraints of the blades are also set. Simultaneously, the population size, maximum number of iterations, crossover probability, mutation probability, and elite retention ratio of the genetic algorithm are also set.

[0029] The main blades are described parametrically using the above-described parametric modeling method, given the number of main blades as follows: All geometric parameters of the main blade : .in, The leading edge radius of the main blade. The radius of the trailing edge of the main blade. The leading edge structural angle of the main blade. The main blade trailing edge structural angle, The leading edge wedge angle of the main blade, The angle between the centers of the leading and trailing edges of the main blades. The axial chord length of the leading section of the main blade. The axial chord length of the extended rear section of the main blade. The control point 1 parameters for the main blades, The control point 2 parameters for the main blade The three control points for the main blades are: The four control points for the main blades are:

[0030] Step S2: First stage: Construct candidate configurations for the first stage enhanced guide vanes and optimize the parameters of the main vanes using a genetic algorithm.

[0031] Based on the aforementioned design parameters, candidate configurations for the first-stage enhanced guide vanes are constructed, and a multi-objective optimization algorithm is used to optimize the vane design parameters, including: increasing the number of vanes N.t Increase to n·N t The flow field of each candidate main blade configuration is obtained by solving computational fluid dynamics, and the outlet airflow angle of the flow field is extracted. and total pressure recovery coefficient Calculate the airflow angle deviation Deviation of total pressure recovery coefficient ,in For the target outlet airflow angle, N is the target total pressure recovery coefficient. t To satisfy the load-bearing capacity of the support plate, the number of main blades, n, is an integer greater than 1; Specifically, in the first stage of optimization, the main blade optimizer is activated to perform a preliminary evaluation of the performance parameters. First, based on the baseline aft casing design, the main blade arrangement density is increased to form candidate main blade configurations for enhancing aerodynamic performance in the first stage. Only the main blade parameters are considered. The blades are used as variables in a genetic algorithm for optimization. Increasing the number of main blades improves their arrangement density and enhances their guiding capacity when relying solely on them. The goal of this stage is not to directly obtain the final design, but rather to explore the blade layout that meets design requirements under given operating conditions when relying solely on the main blades.

[0032] In the first stage, a multi-objective optimization algorithm is used to optimize the main blade design parameters to obtain acceptable aerodynamic losses and flow guidance capabilities. Initially, the number of blades is increased to n·N. t For each candidate main blade configuration, its flow field is obtained by computational fluid dynamics (CFD), and at least the following performance indicators are extracted: outlet airflow angle (angle between the outlet and the crest line). Total pressure recovery coefficient , Due to export pressure, This is to control import pressure. And this indicator is then compared with the target outlet airflow angle. Target total pressure recovery coefficient Compare them.

[0033] Define the airflow angle deviation as:

[0034] The target outlet airflow angle of the rear casing 90°.

[0035] Define the deviation of the total pressure recovery coefficient as:

[0036] The smaller the deviation of the total pressure recovery coefficient, the higher the total pressure recovery coefficient of the main blade. The performance of the designed main blades exceeded the required specifications.

[0037] The optimization objective of the multi-objective optimization algorithm is: and .

[0038] Step S3: Determine the feasibility of the main blade.

[0039] Determine if there exists a satisfying condition. and Candidate individuals for the main leaf configuration. To preset the deflection angle deviation threshold, A preset total pressure recovery coefficient deviation threshold is set; if it exists, the first stage is considered passed, and the target is selected. The blade configuration with the highest value is selected as the main blade configuration for the second stage; if it does not exist, the design space is expanded. Specifically, the first-stage deflection angle deviation threshold is defined as: The total pressure recovery coefficient deviation threshold is .

[0040] The rule for determining whether the optimized leaf shape passes in the first stage can be expressed as follows: Select candidate individuals from the optimal solution set of the multi-objective optimization algorithm that meet the following conditions; if such individuals exist, the first stage is considered passed: and ; If no candidate individual that meets the above conditions is found within the preset number of algebras, it is determined that under the current operating conditions and target outlet airflow angle requirements, this type of main blade configuration alone cannot meet the design requirements, and the design space needs to be expanded.

[0041] Among the blades that meet the conditions output by the optimization algorithm in this stage, select... The largest individual leaf is used as the main leaf configuration in the second stage.

[0042] Step S4: Initialize the splitter blade configuration.

[0043] Based on the main blade configuration of the second stage, the number of main blades n·N t Reduce to N t At least one shunting blade is introduced between adjacent main blades to establish a candidate configuration for the rear casing that combines the main blades and the shunting blades.

[0044] Specifically, this invention uses the leaf shape optimized in the first stage as the main blade configuration, reducing the number of main blades to [number missing]. Increase the number of splitter blades to .

[0045] The size of the splitter blades is constrained so that their weight is significantly less than that of the main blades. The main blades are then parametrically described using the aforementioned parametric modeling method, and all geometric parameters Bs of the splitter blades are defined. The following requirements must be met: ; ; ; in, , These are the leading edge radius and trailing edge radius of the splitter blade, respectively. , These are the axial chord lengths of the front section and the extended rear section of the splitter blade, respectively. , These are the leading edge radius and trailing edge radius of the main blade, respectively. , These are the axial chord lengths of the leading section and the extended section of the trailing section of the main blade, respectively. The leading edge construction angle of the splitter blade. The trailing edge construction angle of the splitter blade. The leading edge wedge angle of the splitter blade. The angle is the line connecting the centers of the leading and trailing edges of the splitter blades. For the control point 1 parameters of the splitter blades, For the control point 2 parameters of the splitter blades, For the control point 3 parameters of the splitter blade, The four parameters are the control points for the splitter blades.

[0046] The diverter blades are initially and evenly placed on one side away from the suction surface of the main blades. At this location, the axial distance between the splitter blade and the center of the trailing edge of the main blade is... The rotation angle of the splitter blade is γ.

[0047] S5: Second stage: Joint optimization of main blades and shunting blades.

[0048] An optimization algorithm is used to jointly optimize the main blade parameters, splitter blade parameters, and relative position parameters between the splitter blades and main blades of the candidate rear casing configurations. Specifically, computational fluid dynamics is used to evaluate the flow field of each candidate rear casing configuration, and the outlet airflow angle of this flow field is extracted. and total pressure recovery coefficient The optimization objective is to maximize the total pressure recovery coefficient while satisfying the outlet airflow angle deviation constraint. The maximum total pressure recovery coefficient obtained after optimization is still... Then increase the number of splitter blades to Repeat step S5 using a genetic algorithm for optimization until the number of splitter blades reaches a certain threshold. .

[0049] In the second stage of joint optimization, the joint optimizer is activated to perform joint optimization design on the aft casing blades. If the first stage of optimization is passed, it means that under the current operating conditions, the target flow direction control can be basically achieved by enhancing the main blades' guiding capacity. However, its configuration is usually not the final optimal solution because too many main blades and too dense arrangement may bring greater friction loss and weight, while limiting its flow capacity.

[0050] Therefore, in the second stage, the number of main blades is reduced to improve flow capacity and reduce the weight of the rear casing; simultaneously, at least one diverter blade is introduced between adjacent main blades to form a rear casing configuration with multiple blades working together, such as... Figure 2 As shown. Splitter blades are used to redirect the local flow field that may deteriorate after the number of main blades is reduced, to reshape low-energy fluid regions, to suppress or delay flow separation, and to reduce the wake loss of the main blades.

[0051] Specifically, a genetic algorithm is used to optimize the parameters of the candidate rear casing configuration. The optimization variables include all geometric parameters Bs of the splitter blades, and , And γ. For each candidate configuration, its flow field is evaluated by computational fluid dynamics, and the outlet airflow angle is extracted. Total pressure recovery coefficient The optimization objective for the second stage is:

[0052] in, This represents the outlet airflow angle deviation margin.

[0053] If the maximum total pressure recovery coefficient obtained after optimization does not meet the design requirements, the number of splitter blades will be increased to [a certain value]. We will continue to use a genetic algorithm for optimization.

[0054] S6: Output the best candidate configuration of the rear casing with the highest total pressure recovery coefficient that meets the outlet flow direction requirements, as the final design result of the rear casing blade cascade.

[0055] This invention adopts a phased design process to reduce the weight of the rear casing while maintaining the airflow guiding capability and improving the overall aerodynamic performance. It is applicable to the design optimization of the rear casing support plate of the low-pressure turbine of aero engines.

[0056] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A method for optimizing the design of a low-pressure turbine rear casing support plate based on splitter blades, characterized in that, Includes the following steps: S1: Define design parameters, including turbine rear casing operating parameters, target outlet airflow angle, target total pressure recovery coefficient, and blade geometric boundaries; In step S1, the blade geometry parameters of the rear casing are defined using the following parametric modeling method: the blade profile is divided into two segments, the front segment and the rear segment, for description; The blade leading edge profile parameters include: leading edge radius. Trailing edge radius Leading edge structural angle Tail margin structural angle Leading edge wedge angle Angle connecting the centers Parameters of control point 1 Parameters of control point 2 Control point 3 parameters Control point 4 parameters and axial chord length The blade's trailing section profile is extended in a straight line along the trailing edge construction angle, starting from the point of tangency of the trailing edge circle of the preceding section. The axial chord length of the extended section is... ; S2: Based on the aforementioned design parameters, construct candidate configurations for the first-stage enhanced guide vanes, and optimize the vane design parameters using a multi-objective optimization algorithm, including: increasing the number of vanes N. t Increase to n·N t The flow field of each candidate main blade configuration is obtained by solving computational fluid dynamics, and the outlet airflow angle of the flow field is extracted. and total pressure recovery coefficient Calculate the airflow angle deviation Deviation of total pressure recovery coefficient ,in For the target outlet airflow angle, N is the target total pressure recovery coefficient. t To satisfy the load-bearing capacity of the support plate, the number of main blades, n, is an integer greater than 1; S3: Determine if there exists a satisfying condition. and Candidate individuals for the main leaf configuration. To preset the deflection angle deviation threshold, A preset total pressure recovery coefficient deviation threshold is set; if it exists, the first stage is considered passed, and the target is selected. The blade configuration with the highest value is selected as the main blade configuration for the second stage; if it does not exist, the design space is expanded. S4: Based on the main blade configuration of the second stage, the number of main blades n·N t Reduce to N t At least one shunting blade is introduced between adjacent main blades to establish a candidate configuration for the rear casing combining main blades and shunting blades. S5: An optimization algorithm is used to jointly optimize the main blade parameters, splitter blade parameters, and relative position parameters between the splitter blades and the main blades of the candidate rear casing configurations. Specifically, computational fluid dynamics is used to evaluate the flow field of each candidate rear casing configuration, and the outlet airflow angle of this flow field is extracted. and total pressure recovery coefficient The optimization objective is to maximize the total pressure recovery coefficient while satisfying the outlet airflow angle deviation constraint. S6: Output the candidate configuration of the rear casing with the highest total pressure recovery coefficient that meets the outlet flow direction requirements, as the final design result of the rear casing blade cascade.

2. The method according to claim 1, characterized in that, The multi-objective optimization algorithm mentioned in step S2 is a genetic algorithm, and the optimization objective is... and .

3. The method according to claim 1, characterized in that, The target outlet airflow angle =90°.

4. The method according to claim 1, characterized in that, In step S4, the parameters of the splitter blades satisfy: ； ； ； in, , These are the leading edge radius and trailing edge radius of the splitter blade, respectively. , These are the axial chord lengths of the front section and the extended rear section of the splitter blade, respectively. , These are the leading edge radius and trailing edge radius of the main blade, respectively. , These are the axial chord lengths of the leading section and the extended section of the trailing section of the main blade, respectively.

5. The method according to claim 1, characterized in that, In step S5, the optimization algorithm is a genetic algorithm, and the optimization variables include all geometric parameters Bs of the splitter blade, and , and γ; where, This indicates that the splitter blades are initially and evenly placed on one side of the suction surface of the main blade. Location, γ represents the axial distance between the position of the splitter blade and the center of the trailing edge of the main blade, and γ represents the rotation angle of the splitter blade.

6. The method according to claim 1, characterized in that, In step S5, the outlet airflow angle deviation constraint is: ,in This is the preset outlet airflow angle deviation margin.

7. The method according to claim 1, characterized in that, In step S5, if the maximum total pressure recovery coefficient obtained after optimization is... Then increase the number of splitter blades to We will continue to optimize using the optimization algorithm.

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