Turbine disc baffle structure optimization method, device, equipment, medium and product

Abstract

The invention discloses a turbine disc baffle structure optimization method and device, equipment, a medium and a product and relates to the field of turbine rotors, and the method comprises the steps that actual structure information of a turbine disc-baffle rotor system is obtained; performing finite element modeling on the actual structure information to obtain a finite element model; transient thermal analysis and transient stress analysis are sequentially carried out according to the finite element model, and the most dangerous time step where the maximum equivalent stress and the maximum contact stress are located is obtained; establishing a response surface model based on a Kriging model according to the most dangerous time step where the maximum equivalent stress and the maximum contact stress are located and actual structure information; according to the response surface model, a multi-target genetic algorithm is used for optimization, and optimized turbine disc baffle structure information is obtained. Stress concentration is effectively reduced, and the fatigue life is prolonged.

Description

Technical Field

[0001] This application relates to the field of turbine rotors, and in particular to a method, apparatus, equipment, medium, and product for optimizing turbine disk baffle structure. Background Technology

[0002] As a typical hot-end component in aero-engines, the gas turbine rotor mainly consists of turbine blades, a turbine disk, and turbine baffles. The turbine rotor operates under harsh conditions of high temperature, high pressure, and high speed for extended periods, enduring extremely complex and demanding coupled thermal stresses and mechanical loads. The turbine baffles not only provide axial restraint for the turbine blades but also contribute to the insulation and cooling channels within the turbine disk cavity, effectively protecting critical components such as the tenons and grooves at the disk rim from corrosion by the high-temperature combustion gases.

[0003] Most turbine baffles employ a boltless structure, axially fixed to the turbine disk via retaining rings, forming a turbine disk-baffle rotor system. The baffle relies on axial pre-interference to generate axial clamping force, preventing axial movement of the blades during engine operation and preventing high-temperature combustion gases from entering the tenons and grooves through the gaps between the baffle and turbine disk, thus reducing the risk of rotor system failure. Furthermore, the baffle achieves radial positioning with the turbine disk rim via its cylindrical surface and transfers its own centrifugal load to the turbine disk.

[0004] However, with the continuous increase in turbine inlet temperature in aero-engines and the increasingly stringent requirements for long service life and high reliability, the design of turbine rotor systems needs to comprehensively consider the influence of more factors. Compared to the turbine disk, the turbine baffle is a thin-walled structure with low thermal inertia and rapid thermal response. During actual acceleration and deceleration of the engine, there is a significant difference between the transient and steady-state temperature fields of the turbine disk and the baffle. This change in the transient temperature field may cause gaps in the radial fit between the baffle and the turbine disk, thereby compromising its centering function; it may also increase the radial interference fit, leading to increased contact stress and volume stress in the components, thus reducing fatigue life. Furthermore, since radial centering between the baffle and the turbine disk is achieved through cylindrical surface contact, the centrifugal load of the baffle is transferred to the turbine disk through the contact surface. This structure is similar to the tenon joint between the turbine disk and the blade, which can cause significant thermal stress and fatigue damage at the contact surface. Therefore, a thorough analysis of the contact state and contact stress between the baffle and the turbine disk is necessary.

[0005] Extensive research has been conducted on the structural optimization of turbine disk rotor systems. However, few studies have reported on the structural optimization of turbine disk-baffle rotor systems considering transient temperature response. Summary of the Invention

[0006] The purpose of this application is to provide a method, apparatus, equipment, medium, and product for optimizing the structure of a turbine disk baffle, which can effectively reduce stress concentration and improve fatigue life.

[0007] To achieve the above objectives, this application provides the following solution:

[0008] In a first aspect, this application provides a method for optimizing the structure of a turbine disk baffle, including:

[0009] Obtain the actual structural information of the turbine disk-baffle rotor system;

[0010] Finite element modeling is performed on the actual structural information to obtain a finite element model;

[0011] Based on the finite element model, transient thermal analysis and transient stress analysis are performed sequentially to obtain the most dangerous time step where the maximum equivalent stress and maximum contact stress occur;

[0012] Based on the most critical time step where the maximum equivalent stress and maximum contact stress occur, and the actual structural information, a response surface model is established using the Kriging model.

[0013] The optimized turbine disk baffle structure information is obtained by optimizing the response surface model using a multi-objective genetic algorithm.

[0014] In one embodiment, finite element modeling is performed on the actual structural information to obtain a finite element model, specifically including:

[0015] Based on the actual structural information, a model is created using finite element software to obtain an initial model.

[0016] The initial model is divided into a network and boundary conditions are set to obtain a finite element model. The constraints of the finite element model include frictional contact constraints, axial deformation coupling constraints, axial displacement constraints applied to the turbine disk end, boundary heat transfer constraints, and centrifugal load constraints between the turbine disk and the baffle.

[0017] In one embodiment, based on the finite element model, transient thermal analysis and transient stress analysis are performed sequentially to obtain the most critical time step where the maximum equivalent stress and maximum contact stress occur, specifically including:

[0018] Transient thermal analysis was performed on the finite element model based on transient boundary conditions to obtain the temperature field at each moment.

[0019] Extract the average temperature value and rotation speed function of the set area based on the temperature field at each moment;

[0020] The time step at which the maximum stress occurs is determined based on the average temperature value and the rotational speed function.

[0021] Based on the time step of the maximum stress, transient stress analysis is performed on the mechanical load history to obtain the most dangerous time step where the maximum equivalent stress and maximum contact stress are located.

[0022] In one embodiment, a response surface model is established based on the Kriging model according to the most critical time step where the maximum equivalent stress and maximum contact stress occur, as well as the actual structural information. Specifically, this includes:

[0023] Based on the actual structural information, test samples are generated using the optimal space-filling method.

[0024] Based on the test samples and the most dangerous time steps where the maximum equivalent stress and maximum contact stress are located, a response surface model is established using the Kriging model.

[0025] In one embodiment, the expression for the multi-objective genetic algorithm is:

[0026]

[0027] Among them, L i For dimensional design parameters, σ eqv，max σ is the maximum equivalent stress of the baffle. pre，max For the maximum contact angle stress in radial fit, σ pre，ave The radial fit average contact stress is given by ΔY, which is the axial displacement of the outer edge of the baffle relative to the outer side of the turbine disk.

[0028] In one embodiment, the expression for the frictional contact constraint is:

[0029]

[0030] Where R is the structural residual; λ is the Lagrange multiplier; g is the contact gap; ∈ is the penalty parameter, R aug The system residuals are augmented, and T is the transpose sign;

[0031] The expression for the boundary heat transfer constraint is:

[0032] q=h(T surface -T ∞ );

[0033] Where q is the heat flux density; T surface T∞ is the surface temperature of the structure; T∞ is the ambient temperature; h is the convective heat transfer coefficient.

[0034] Secondly, this application provides a turbine disk baffle structure optimization device, comprising:

[0035] The acquisition module is used to acquire the actual structural information of the turbine disk-baffle rotor system;

[0036] The first modeling module is used to perform finite element modeling on the actual structural information to obtain a finite element model.

[0037] The analysis module is used to perform transient thermal analysis and transient stress analysis sequentially based on the finite element model to obtain the most dangerous time step where the maximum equivalent stress and maximum contact stress are located.

[0038] The second modeling module is used to establish a response surface model based on the Kriging model according to the most dangerous time step where the maximum equivalent stress and maximum contact stress are located, as well as the actual structural information.

[0039] The optimization module is used to optimize the response surface model using a multi-objective genetic algorithm to obtain the optimized turbine disk baffle structure information.

[0040] Thirdly, this application provides a computer device, including: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the turbine disk baffle structure optimization method described above.

[0041] Fourthly, this application provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the turbine disk baffle structure optimization method described above.

[0042] Fifthly, this application provides a computer program product, including a computer program that, when executed by a processor, implements the turbine disk baffle structure optimization method described above.

[0043] According to the specific embodiments provided in this application, the following technical effects are disclosed:

[0044] This application provides a method, apparatus, equipment, medium, and product for optimizing turbine disk baffle structures. The method involves performing finite element modeling on the actual structural information to obtain a finite element model; based on the finite element model, performing transient thermal analysis and transient stress analysis sequentially to obtain the most critical time steps where the maximum equivalent stress and maximum contact stress occur; establishing a response surface model based on the Kriging model using the most critical time steps of the maximum equivalent stress and maximum contact stress, and the actual structural information; and optimizing the response surface model using a multi-objective genetic algorithm to obtain optimized turbine disk baffle structure information. By establishing a response surface model using the Kriging model and then optimizing it using a multi-objective genetic algorithm, the optimized turbine disk baffle structure information can be obtained, which can reduce stress concentration and improve fatigue life. Attached Figure Description

[0045] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, 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.

[0046] Figure 1 A flowchart for obtaining the most dangerous time step;

[0047] Figure 2 Schematic diagram of turbine disk baffle structure optimization;

[0048] Figure 3 This is a geometric model diagram of the turbine disk-rotor system;

[0049] Figure 4 Temperature history diagram of the rotor system;

[0050] Figure 5 This is a stress history diagram of the rotor system;

[0051] Figure 6 A response surface plot for setting parameters and output parameters;

[0052] Figure 7 Flowchart of the method for optimizing turbine disk baffle structure;

[0053] Figure 8 A functional module schematic diagram of a turbine disk baffle structure optimization device provided in another embodiment of this application;

[0054] Figure 9 This is a schematic diagram of the structure of a computer device provided in an embodiment of this application. Detailed Implementation

[0055] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0056] This application establishes a finite element model of a turbine disk-baffle rotor assembly and parametrically processes the turbine disk-baffle model by adjusting its contour dimensions. Based on this, a stress state analysis of the turbine disk-baffle considering the influence of transient temperature is conducted, and a response surface optimization model is constructed. With radial centering and axial pre-compression of the turbine disk-baffle as constraints, the dimensional optimization of the turbine disk-baffle is performed by minimizing the equivalent stress and contact stress of the baffle as the objective function.

[0057] To make the above-mentioned objectives, features and advantages of this application more apparent and understandable, the application will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0058] In one exemplary embodiment, such as Figure 7 As shown, a method for optimizing the structure of a turbine disk baffle is provided. This method is executed by a computer device, specifically by a terminal or server alone, or by both a terminal and a server. The method includes the following steps:

[0059] Step 701: Obtain the actual structural information of the turbine disk-baffle rotor system.

[0060] Step 702: Perform finite element modeling on the actual structural information to obtain a finite element model.

[0061] Step 703: Based on the finite element model, perform transient thermal analysis and transient stress analysis in sequence to obtain the most dangerous time step where the maximum equivalent stress and maximum contact stress are located.

[0062] Step 704: Based on the maximum equivalent stress and the maximum contact stress at the most critical time step and the actual structural information, establish a response surface model using the Kriging model.

[0063] Step 705: Optimize the response surface model using a multi-objective genetic algorithm to obtain the optimized turbine disk baffle structure information.

[0064] By implementing the above steps, a response surface model is established using the Kriging model, and then a multi-objective genetic algorithm is used for optimization, thereby obtaining the optimized turbine disk baffle structure information, which can reduce stress concentration and improve fatigue life.

[0065] In an exemplary embodiment, finite element modeling is performed on the actual structural information to obtain a finite element model. Specifically, this includes: modeling based on the actual structural information using finite element software to obtain an initial model; performing network partitioning and boundary condition setting on the initial model to obtain a finite element model; the constraints of the finite element model include frictional contact constraints, axial deformation coupling constraints, axial displacement constraints applied to the turbine disk end, boundary heat transfer constraints, and centrifugal load constraints between the turbine disk and the baffle. The actual structural information refers to the geometric dimensions of the actual structure.

[0066] In practical applications, the expression for the frictional contact constraint is:

[0067]

[0068] Where R is the structural residual; λ is the Lagrange multiplier; g is the contact gap; ∈ is the penalty parameter, Raug The system residual is the augmented system residual, and T is the transpose sign.

[0069] The expression for the boundary heat transfer constraint is:

[0070] q=h(T surface -T ∞ );

[0071] Where q is the heat flux density; T surface T∞ is the surface temperature of the structure; T∞ is the ambient temperature; h is the convective heat transfer coefficient.

[0072] In an exemplary embodiment, transient thermal analysis and transient stress analysis are performed sequentially on the finite element model to obtain the most dangerous time step where the maximum equivalent stress and maximum contact stress are located. Specifically, this includes: performing transient thermal analysis on the finite element model based on transient boundary conditions to obtain the temperature field at each moment; extracting the average temperature value and rotational speed function of a set area based on the temperature field at each moment; determining the time step where the maximum stress is located based on the average temperature value and the rotational speed function; and performing transient stress analysis based on the mechanical load history at the time step where the maximum stress is located to obtain the most dangerous time step where the maximum equivalent stress and maximum contact stress are located.

[0073] In an exemplary embodiment, a response surface model is established based on the Kriging model according to the most dangerous time step where the maximum equivalent stress and maximum contact stress are located, as well as the actual structural information. Specifically, this includes: generating test samples using the optimal space-filling method based on the actual structural information; and establishing a response surface model based on the Kriging model according to the test samples and the most dangerous time step where the maximum equivalent stress and maximum contact stress are located.

[0074] In an exemplary embodiment, the expression of the multi-objective genetic algorithm is:

[0075]

[0076] Among them, L i For dimensional design parameters, such as Figure 3 As shown, L iIt includes nine adjustable dimensional design parameters: X1, X2, H, X4, Y1, Y2, Y3, Y4, and Y5. X1 and Y1 define the upper left reference point of the baffle profile, where X1 represents the radial distance from this point to the turbine disk rim reference surface, and Y1 represents the axial distance from this point to the stacking centerline. X2 and Y2 define the upper right reference point of the baffle profile, where X2 represents the radial distance from this point to the rim reference surface, and Y2 represents the axial distance from this point to the stacking centerline. X3 and Y3 define the lower right reference point of the baffle profile, where X3 represents the radial distance from this point to the rim reference surface, and Y3 represents the axial distance from this point to the stacking centerline. X4 and Y4 define the lower left reference point of the baffle profile, where X4 represents the radial distance from this point to the rim reference surface, and Y4 represents the axial distance from this point to the stacking centerline. H defines the thickness of the baffle neck. Y5 defines the length of the contact surface between the baffle and the disk body. ρ eqv，max σ is the maximum equivalent stress of the baffle. pre，max For the maximum contact angle stress in radial fit, σ pre，ave The radial fit average contact stress is given by ΔY, which is the axial displacement of the outer edge of the baffle relative to the outer side of the turbine disk.

[0077] This application primarily addresses the thermal stress coupling problem of aero-engine rotor systems under transient conditions, with a particular focus on fatigue damage caused by thermal stress between the turbine disk and the baffle. Because the baffle heats up rapidly while the disk heats up slowly, fit failure is easily triggered during non-steady-state phases such as startup / acceleration, leading to a significant decrease in fatigue life. The method described in this application can effectively reduce stress concentration and significantly improve fatigue life.

[0078] In another exemplary embodiment, a specific process for the turbine disk baffle structure optimization method in practical application is also provided:

[0079] Step 1: Perform finite element modeling of the turbine disk-baffle rotor system using finite element software.

[0080] The specific sub-steps are as follows:

[0081] Step 1.1 Model Establishment. A turbine disk-baffle rotor system model is established in finite element software. The finite element software is not limited to commercial finite element software such as Ansys and Abaqus. If the transient calculation of the rotor system is large, a two-dimensional axisymmetric model can be used. If accurate calculation results are required, a three-dimensional model is used. Then, material properties are defined, including elastic-plastic parameters, thermal conductivity, specific heat capacity, and density. Specifically, in this embodiment, the turbine disk-baffle rotor system model is a two-dimensional axisymmetric model established based on the geometric dimensions of the actual structure, such as... Figure 3 As shown.

[0082] Step 1.2 Mesh Generation. For 2D models, quadrilateral meshes can be used, and for 3D models, hexahedral meshes can be used. A coarser mesh is used inside the model, while a finer mesh is used in the contact area between the turbine disk and the baffle. A smooth, gradual transition is set to ensure the computational accuracy and reliability of the contact surface.

[0083] In finite element mesh generation, a coarse mesh is used inside the model, and a fine mesh is used in the contact area. A smooth transition region for mesh size is set between the two, i.e., a "smooth and gradual transition," which is achieved by controlling the rate of change of element size in the mesh transition region. Its physical manifestation is mainly to avoid stress distortion at the coarse and fine meshes.

[0084] Step 1.3 Boundary Condition Setting. To simulate the assembly constraints of the rotor system, frictional contact is set at the contact surfaces, and the augmented Lagrangian contact algorithm is used for solving. The nodes at the bottom of the baffle and the nodes of the turbine disk slot are axially deformably coupled to prevent the baffle from detaching from the turbine disk, and an axial displacement constraint is applied to the mesh nodes at the shaft end of the turbine disk. A third type of heat transfer boundary condition is applied to the finite element model boundary for temperature loading. The centrifugal loads of the turbine disk and baffle are applied to the model in the form of rotational speed, and the centrifugal loads of the blades are applied to the turbine disk rim in the form of equivalent pressure.

[0085] The turbine disk-baffle system is a hot-end component of an aero-engine. The turbine disk is connected to the main shaft and rotates at high speed. Turbine blades are mounted on the turbine disk, which is the core of the entire impeller structure. The baffle is a boltless, thin-walled structural component that is installed on the back of the turbine disk by preload, forming a semi-sealed cavity to prevent high-temperature combustion gases from entering the turbine disk tenons / grooves. The baffle is not bolted but uses an interference fit structure with retaining rings for a boltless self-holding connection: the baffle is axially pre-interferenced into a positioning groove on the turbine disk, generating axial clamping force to prevent axial detachment during flight.

[0086] The constraints are the boundary conditions, including:

[0087] 1. Frictional Contact Constraints: Create surface-to-surface contact in the interaction module, selecting the turbine disk contact surface as the primary surface and the baffle contact surface as the secondary surface. In the contact properties, select hard contact for normal behavior (allowing contact surface separation but prohibiting penetration), select augmented Lagrangian algorithm for tangential behavior, and set the friction coefficient. The augmented Lagrangian method achieves contact by introducing a penalty term and iteratively adjusting the contact force. The mathematical expression of the frictional contact constraint is as follows:

[0088]

[0089] Where R is the structural residual; λ is the Lagrange multiplier; g is the contact gap; and ∈ is the penalty parameter.

[0090] 2. Axial deformation coupling constraint (bottom node of baffle and turbine disk slot node):

[0091] Use binding constraints in the constraint module to bind the bottom surface of the baffle to the slot surface.

[0092] 3. Apply axial displacement constraint to the turbine disk shaft end:

[0093] In the loading module, select the node at the end of the turbine disk shaft and apply a fixed constraint in the axial direction, i.e., the displacement U2 in the Y direction is 0. This is mainly to eliminate rigid body displacement and ensure that the model is statically determinate in the axial direction.

[0094] 4. Boundary heat transfer constraint: Type III boundary condition (convective boundary).

[0095] In the loading module, select the outer surfaces of the turbine disk and baffle, apply a convective heat transfer boundary, and input the convective heat transfer coefficient and ambient temperature. The formula is:

[0096] q=h(T surface -T ∞ );

[0097] Where q is the heat flux density, Tsurface is the surface temperature of the structure (calculated by the solver), and T∞ is the ambient temperature.

[0098] 5. The centrifugal load constraint of the turbine disk and baffle is applied in the form of rotational speed.

[0099] In the loading module, select Rotary Body Load, enter the rotational speed, and specify the central axis (rotation axis) of the turbine disk.

[0100] Step 2: Obtain the most critical time step where the maximum equivalent stress and maximum contact stress occur.

[0101] like Figure 1 As shown, the specific sub-steps are as follows:

[0102] Step 2.1: Temperature Field Analysis. Based on the finite element model from Step 1, transient calculations are performed to extract the changes in rotor speed and the average temperature of the turbine disk rim and baffle over time. When the rotor system's speed undergoes a sudden change in a very short time, the response speed of the temperature change in the turbine disk rim and baffle is much lower than the change in speed, and the temperature field requires a significant amount of time to stabilize.

[0103] This process is completed using the transient thermal-structural coupling analysis module in commercial finite element software such as ANSYS or ABAQUS. The workflow is as follows:

[0104] 1. Input transient boundary conditions, i.e. Figure 1 The heat transfer boundary conditions process (such as heat flux, heat transfer coefficient, rotational speed, etc.) in the process.

[0105] 2. Perform transient thermal analysis on the finite element model to obtain the temperature field at each moment.

[0106] 3. Based on the temperature field at each moment, the average temperature value of the unit in a specific area (such as baffle or disk edge) is extracted by the post-processing module.

[0107] This is a standard yet advanced technical process in the current CAE field, implemented based on existing ANSYS / ABAQUS functions.

[0108] Step 2.2: Transient Stress Analysis. Based on the analysis results of Step 2.1, it can be seen that the rotor speed and temperature change asynchronously with time history; therefore, the transient stress will also differ from the rotor speed change over time history. Using the element average temperature value calculated in Step 2.1 as the initial boundary condition for the transient finite element calculation, a speed history is applied to the turbine disk to calculate the transient stress field of the rotor system, extracting the maximum equivalent stress and maximum contact stress of the rotor system. When the equivalent stress and contact stress reach their maximum at a certain moment, that moment is the most critical time step. Generally, the moment of maximum stress occurs after the time point of highest relative speed. At this time, the mechanical stress of the rotor system is at its maximum, and the thermal stress is also more significant due to the unstable temperature field.

[0109] Step 3: Optimize the structure based on the response surface model

[0110] like Figure 2 As shown, the specific sub-steps are as follows:

[0111] Step 3.1: Response Surface Optimization Process. The response surface optimization process consists of experimental design, establishing the response surface model, and multi-objective optimization solution. First, the experimental design is generated using the optimal space-filling method. The optimal space-filling design is a post-processed Latin hypercube sampling to obtain a uniform spatial distribution of design parameters. The design type uses the maximum-minimum distance, and the number of experimental samples is set to 100 to balance the computational cost and fitting accuracy of the experimental design samples. A response surface model is established based on the Kriging model between the design parameters and the output parameters. The design parameters are the geometric dimensions of the turbine disk-baffle rotor system, and the output parameters are the maximum stress or fatigue life corresponding to the most critical time step in Step 2. During response surface optimization, only the temperature field and rotational speed values ​​corresponding to this time point are selected for steady-state load input, thereby reducing the computational load of the optimization analysis; these are used to input the loading boundary conditions of the response surface model, rather than for full-process optimization. The maximum stress is directly extracted from the finite element post-processing, and the fatigue life is calculated using the following formula:

[0112]

[0113] Where, d t The fatigue injury occurs once per week, and its reciprocal is the fatigue life, Δσ.eqv and Δε eqv Equivalent stress and equivalent strain can be obtained from the finite element calculation results of the rotor structure; a1 and b1 are material constants.

[0114] Step 3.2: Optimization Solution Using a Multi-Objective Genetic Algorithm. Based on the generated response surface optimization model, optimization is performed using a multi-objective genetic algorithm. This method supports all types of input parameters, and the constraint handling uses the same non-dominant principle as the objective function. It does not require setting penalty functions or Lagrange factors for constraints and objectives. Generally, multiple global optimal solutions exist in the design space, forming an effective solution set for multi-objective optimization. Based on the dimensional constraints of the design parameters, the range of dimensional variations must ensure that the rotor system geometric model can be generated normally without turbine disk-baffle interference.

[0115] The optimization process of a multi-objective genetic algorithm specifically includes:

[0116] 1. Experimental Design: Using the optimal space-filling method (improved Latin hypercube sampling), multiple sets of sample data (including multiple input size design parameters) are generated to establish the response surface;

[0117] 2. Response surface methodology: The Kriging model is used to fit the nonlinear mapping relationship between the input parameters and the output target;

[0118] 3. Optimization solution: Based on the nonlinear mapping relationship, MOGA (multi-objective genetic algorithm) is adopted, and the optimization objectives are to minimize the baffle equivalent stress and minimize the contact stress.

[0119] 4. Filter the optimal solution set and select the optimal structural parameter set that satisfies the functional constraints. The optimal structural parameter set is the size of the structure, and it is evaluated using the optimized maximum equivalent stress, maximum contact stress, axial displacement, average contact stress, and fatigue life.

[0120] Step 3.3: Optimization Target Setting. The optimization target can be set to minimize the maximum stress of the baffle, the maximum radial contact stress, or maximize fatigue life. Furthermore, considering the reliability of the turbine disk-baffle assembly, the radial mating surfaces of the turbine disk-baffle rotor system must not loosen; therefore, a constraint condition of an average radial contact stress greater than 100 MPa is set. The baffle also needs to maintain axial compression against the turbine disk, and the axial displacement of the baffle's outer edge relative to the outer side of the turbine disk is set to be less than 0.1 mm. For a specific model of turbine disk-baffle rotor system, specific average radial contact stress and axial displacement of the baffle's outer edge relative to the outer side of the turbine disk are set.

[0121] The multi-objective genetic algorithm for optimization focuses on the stress distribution and contact fit state of the baffle. The optimization objective is to minimize the maximum equivalent stress σ of the baffle.eqv，max Maximum contact stress σ in radial fit pre，max .

[0122] Furthermore, considering the reliability of the turbine disk-baffle assembly, the radial mating surfaces of the turbine disk-baffle rotor system must not become loose; therefore, an average radial mating contact stress σ is set. pre，ave The constraint condition is ≥100MPa. The baffle also needs to maintain axial compression of the turbine disk, with the axial displacement ΔY of the outer edge of the baffle relative to the outer side of the turbine disk set to ≤0.1mm. Based on the above analysis, the structural optimization mathematical model of the turbine disk-baffle rotor system is obtained as follows:

[0123]

[0124] As an exemplary embodiment, a specific data processing procedure for the turbine disk baffle structure optimization method is also provided.

[0125] 1. Finite element modeling of the turbine disk-baffle rotor system was performed using finite element software.

[0126] by Figure 3 Taking the turbine disk-baffle rotor system shown as an example, structural optimization is performed. Nine adjustable dimensional design parameters are X1, X2, H, X4, Y1, Y2, Y3, Y4, and Y5. Finite element modeling of the turbine disk-baffle rotor system is performed using Ansys Workbench software. The material of the turbine disk-baffle rotor system is a nickel-based superalloy. Considering the large transient computational load of the rotor system, a two-dimensional axisymmetric model is adopted.

[0127] 2. Obtain the most critical time step where the maximum equivalent stress and maximum contact stress occur.

[0128] Figure 4 A typical history of the rotor system is presented, including the changes in rotor speed, turbine disk rim, and average baffle temperature over time. The results show that when the rotor system's speed changes abruptly within a very short time, the response speed of the turbine disk rim and baffle temperature changes is much slower than the speed change, and the temperature field requires a significant amount of time to stabilize.

[0129] Figure 5The variation of maximum stress in each component of the rotor system over time is presented. As can be seen from the figure, the maximum stress occurs at the initial stage (time point B) of time point A, when the relative speed is highest. At this point, the mechanical stress of the rotor system is at its maximum, and the thermal stress is also more significant due to the unstable temperature field. As the heat conduction process continues, the maximum stress in each component of the rotor system decreases significantly towards the end of the 100% relative speed steady-state period. Taking the maximum stress of the baffle as an example, during the 100% relative speed period, its value first rapidly increases from approximately 1000 MPa to 1200 MPa, then slowly decreases and stabilizes at approximately 800 MPa. This reflects that the maximum stress of the baffle considering the transient temperature response is about 50% higher than the result at steady-state temperature, indicating that the stress distribution of the rotor system is quite sensitive to changes in the temperature field. Furthermore, according to... Figure 5 The results of the change in maximum stress were analyzed. Time point B was selected as the moment when the stress was most critical. At this time, the maximum stress of the baffle and the maximum contact stress were the largest, while the change in maximum stress at the wheel center was not sensitive to the change in time.

[0130] 3. Optimize the structure based on the response surface model.

[0131] The response surface model was generated by initializing the experimental design data consisting of 11 factors (9 design parameters and 2 output parameters) and 100 samples. The 9 design parameters are X1, X2, H, X4, Y1, Y2, Y3, Y4 and Y5, and the 2 output parameters are the maximum equivalent stress σ of the baffle. eqv,max Maximum contact stress σ in radial fit pre,max First, a sensitivity analysis of the influence of design parameters on output parameters is conducted, including both positive and negative effects. This influences the maximum equivalent stress σ of the baffle. eqv,max The main design parameters are Y3 and Y4, which affect the maximum contact stress σ of the radial fit. pre,max The main design parameters are Y3 and Y5, respectively. Overall, changes in the dimensional design parameters Y3, Y4, and Y5 will affect σ. eqv,max and σ pre,max All of these factors have a significant impact. Secondly, the design parameters and output parameters are fitted with a Kriging response surface model to generate a response surface plot, which can reflect the continuous influence of changes in each design parameter on the output parameter. Because there are many design parameters, Figure 6 The paper only provides the impact of the design parameters Y3 / Y4 and Y3 / Y5, which have a significant influence, on the output value σ. eqv,max and σ pre,max The response surface, in which, Figure 6 (a) The design parameters Y3 and Y4 affect the output parameter σ eqv,max The effect diagram of response surface methodology. Figure 6 (b) The design parameters Y3 and Y5 affect the output parameter σ pre,maxThe influence diagram of the response surface methodology is shown. Meanwhile, the root mean square error (RMSE) is used to evaluate the error of the response surface model. The comparison between the fitted response surface values ​​and the sample output values ​​indicates that the σ value of the fitted response surface model is within acceptable limits. eqv,max and σ pre,max The root mean square errors were 20.6 MPa and 50.7 MPa, respectively, compared with the sample output value σ. eqv,max and σ pre,max The distribution range of 807–1268 MPa and 1067–2811 MPa is relatively small, which can meet the accuracy requirements of optimization.

[0132] 4. Optimization Results and Analysis.

[0133] The optimized geometric model of the turbine disk-baffle rotor system shows that the baffle's profile more closely resembles the gas turbine disk, and the radially mating annulus between the baffle and the turbine disk is thicker. Table 1 compares the design and output parameters before and after optimization. After optimization, the maximum equivalent stress σ of the baffle is... eqv,max The pressure decreased from 1229.7 MPa to 875.4 MPa, a reduction of 28.8%, and the maximum radial contact stress σ... pre,max The pressure decreased from 1990.9 MPa to 1588.2 MPa, a reduction of 20.0%. Simultaneously, the geometric area of ​​the back baffle was optimized from 74.93 mm². 2 Reduced to 72.0mm 2 Therefore, it will not cause additional centrifugal load on the turbine disk center, and the maximum stress on the turbine disk center will not increase after structural optimization. The axial displacement ΔY of the outer edge of the baffle relative to the outer edge of the turbine disk has increased by 0.06mm, which still meets the constraint requirements of axial clamping of the baffle and will not cause the axial mating surfaces to separate.

[0134] Table 1 Comparison of design parameters and output parameters before and after optimization

[0135]

[0136]

[0137] Under transient operating conditions (such as start-up, acceleration, deceleration, and shutdown), the turbine disk-baffle rotor system of aero-engines experiences varying rates of temperature rise, leading to inconsistent expansion between components. This results in significant thermal stress at the turbine disk-baffle interface, a cause of fatigue failure in aero-engines. Therefore, this application utilizes the Ansys Workbench platform and employs a Kriging response surface model combined with a multi-objective genetic algorithm to conduct structural optimization design of the turbine disk-baffle rotor system considering transient temperature response. Results show that, while ensuring axial preload and radial centering of the baffle, making the baffle profile more vertical and thickening its radial mating ring effectively reduces stress concentration in the rotor system and improves fatigue life. Compared to the original configuration, the optimized rotor system exhibits a 28.8% reduction in maximum equivalent stress and a 20.0% reduction in contact stress, with a 6.4-fold increase in fatigue life. The turbine disk-baffle rotor system optimization method considering transient temperature response proposed in this application can provide a reference for the life design of high-temperature rotating components in aero-engines.

[0138] This application addresses the structural optimization problem of a turbine disk-baffle rotor system considering transient temperature response. First, a typical geometric optimization model of the rotor system is established. Then, through finite element analysis of the temperature and stress fields throughout the transient full-process, the critical time point when the stress is maximum is identified. Finally, the transient temperature field at the critical time point is used as the initial boundary condition for steady-state finite element calculation. Multiple sets of steady-state finite element calculations are performed by applying the rotational speed history to obtain the maximum equivalent stress and contact stress of the rotor system. Furthermore, experimental samples are generated using the optimal space-filling design method, and a response surface model between the design parameters and output parameters is established based on the Kriging model. Finally, a multi-objective genetic algorithm is used to solve for the optimization results.

[0139] (1) For a certain type of turbine disk-baffle rotor system, due to the huge difference in thermal inertia between the turbine disk and the baffle, the maximum equivalent stress of the baffle based on the transient temperature field is 50% greater than the baffle stress under the loading steady-state temperature field, and the moment when the maximum equivalent stress of the baffle appears is delayed after the moment when the rotor accelerates to the maximum speed.

[0140] (2) After the rotor system was fitted by Kriging response surface and optimized by multi-objective genetic algorithm, the maximum equivalent stress of the baffle decreased from 1229.7MPa to 875.4MPa, the maximum principal stress decreased from 1256.3MPa to 978.6MPa, and the maximum contact stress decreased from 1990.0MPa to 1588.2MPa, and the assembly function requirements such as centering and clamping of the rotor system were met.

[0141] (3) The service life of the rotor system structure was calculated based on the damage model of total energy density. The fatigue life of the original rotor configuration was 8020 cycles, and the fatigue life after optimization was 56820 cycles, which increased the life by 6.1 times.

[0142] Based on the same inventive concept, this application also provides a turbine disk baffle structure optimization device for implementing the turbine disk baffle structure optimization method described above. The solution provided by this device is similar to the solution described in the above method; therefore, the specific limitations in one or more turbine disk baffle structure optimization device embodiments provided below can be found in the limitations of the turbine disk baffle structure optimization method described above, and will not be repeated here.

[0143] In one exemplary embodiment, such as Figure 8 As shown, a turbine disk baffle structure optimization device is provided, comprising:

[0144] The acquisition module is used to acquire the actual structural information of the turbine disk-baffle rotor system.

[0145] The first modeling module is used to perform finite element modeling on the actual structural information to obtain a finite element model.

[0146] The analysis module is used to perform transient thermal analysis and transient stress analysis sequentially based on the finite element model to obtain the most dangerous time step where the maximum equivalent stress and maximum contact stress are located.

[0147] The second modeling module is used to establish a response surface model based on the Kriging model, according to the most dangerous time step where the maximum equivalent stress and maximum contact stress are located, as well as the actual structural information.

[0148] The optimization module is used to optimize the response surface model using a multi-objective genetic algorithm to obtain the optimized turbine disk baffle structure information.

[0149] In one exemplary embodiment, a computer device is provided, which may be a server or a terminal, and its internal structure diagram may be as follows. Figure 9As shown, the computer device includes a processor, memory, input / output (I / O) interfaces, and a communication interface. The processor, memory, and I / O interfaces are connected via a system bus, and the communication interface is also connected to the system bus via the I / O interfaces. The processor provides computational and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system, computer programs, and a database. The internal memory provides the environment for the operating system and computer programs stored in the non-volatile storage media. The database stores turbine disk baffle structure optimization data. The I / O interfaces are used for information exchange between the processor and external devices. The communication interface is used for communication with external terminals via a network connection. When the computer program is executed by the processor, it implements a turbine disk baffle structure optimization method.

[0150] Those skilled in the art will understand that Figure 9 The structures shown are merely block diagrams of some structures related to the present application and do not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than shown in the figures, or combine certain components, or have different component arrangements. In an exemplary embodiment, a computer device is provided, including a memory and a processor. The memory stores a computer program, and the processor executes the computer program to implement the above-described method embodiments.

[0151] In one exemplary embodiment, a computer-readable storage medium is provided storing a computer program that, when executed by a processor, implements the above-described method embodiments.

[0152] In one exemplary embodiment, a computer program product is provided, including a computer program that, when executed by a processor, implements the above-described method embodiments.

[0153] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of the relevant data must comply with relevant regulations.

[0154] In this application, all actions to acquire signals, information, or data are carried out in compliance with the relevant data protection laws and policies of the country where the location is situated, and with the authorization granted by the owner of the relevant device.

[0155] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM).

[0156] The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, etc., and are not limited to these.

[0157] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0158] This application uses specific examples to illustrate the principles and implementation methods of this application. The descriptions of the above embodiments are only for the purpose of helping to understand the method and core ideas of this application. At the same time, for those skilled in the art, there will be changes in the specific implementation methods and application scope based on the ideas of this application. In summary, the content of this specification should not be construed as a limitation of this application.

Claims

1. A method of optimizing a turbine disk baffle structure, characterized by, The method comprises the following steps: acquiring actual structure information of a turbine disc-baffle rotor system; performing finite element modeling on the actual structure information to obtain a finite element model; performing transient thermal analysis and transient stress analysis on the finite element model to obtain a most dangerous time step at which maximum equivalent stress and maximum contact stress are located; establishing a response surface model based on a Kriging model according to the most dangerous time step at which the maximum equivalent stress and the maximum contact stress are located and the actual structure information; performing optimization on the response surface model by using a multi-objective genetic algorithm to obtain optimized turbine disc-baffle structure information.

2. The turbine disk baffle structure optimization method of claim 1, wherein, The finite element modeling on the actual structure information to obtain the finite element model specifically comprises: modeling based on a finite element software according to the actual structure information to obtain an initial model; performing network division and boundary condition setting on the initial model to obtain the finite element model; the constraint conditions of the finite element model include friction contact constraint, axial deformation coupling constraint, axial displacement constraint applied by a turbine disc end, boundary heat transfer constraint and centrifugal load constraint of the turbine disc and the baffle.

3. The turbine disk baffle structure optimization method of claim 1, wherein, The transient thermal analysis and the transient stress analysis on the finite element model to obtain the most dangerous time step at which the maximum equivalent stress and the maximum contact stress are located specifically comprises: performing transient thermal analysis on the finite element model based on transient boundary conditions to obtain a temperature field at each time; extracting average temperature values and a rotating speed function of a set region according to the temperature field at each time; determining a time step at which maximum stress is located according to the average temperature values and the rotating speed function; performing transient stress analysis based on mechanical load history according to the time step at which the maximum stress is located to obtain the most dangerous time step at which the maximum equivalent stress and the maximum contact stress are located.

4. The turbine disk baffle structure optimization method of claim 1, wherein, The response surface model established based on the Kriging model according to the most dangerous time step at which the maximum equivalent stress and the maximum contact stress are located and the actual structure information specifically comprises: generating test samples by using an optimal space filling method according to the actual structure information; establishing the response surface model based on the Kriging model according to the test samples and the most dangerous time step at which the maximum equivalent stress and the maximum contact stress are located.

5. The turbine disk blocker structure optimization method of claim 1, wherein, The expression of the multi-objective genetic algorithm is: where L i is a dimensional design parameter, σ eqv，max is the maximum equivalent stress of the shroud, σ pre，max is the maximum contact angle stress of the radial fit, σ pre，max is the average contact stress of the radial fit, and ΔY is the axial displacement of the shroud outer edge relative to the turbine disk outer edge side surface.

6. The turbine disk baffle structure optimization method of claim 2, wherein, The expression of the friction contact constraint is: where R is the structural residual; λ is the Lagrange multiplier; g is the contact gap; ∈ is the penalty parameter, R aug is the augmented system residual, is the transpose symbol; The expression of the boundary heat transfer constraint is: q = h(T surface - T ∞ ); where q is the heat flux; T surface is the surface temperature of the structure; T∞ is the ambient temperature; and h is the convective heat transfer coefficient.

7. A turbine disk blocker structure optimization apparatus, characterized by, The method comprises the following steps: an acquiring module configured to acquire actual structure information of a turbine disc-baffle rotor system; a first modeling module configured to perform finite element modeling on the actual structure information to obtain a finite element model; an analysis module configured to perform transient thermal analysis and transient stress analysis on the finite element model to obtain a most dangerous time step at which maximum equivalent stress and maximum contact stress are located; a second modeling module configured to establish a response surface model based on a Kriging model according to the most dangerous time step at which the maximum equivalent stress and the maximum contact stress are located and the actual structure information; an optimization module configured to perform optimization on the response surface model by using a multi-objective genetic algorithm to obtain optimized turbine disc-baffle structure information.

8. A computer device comprising: A memory, a processor, and a computer program stored on the memory and loadable on the processor, characterized in that the processor executes the computer program to implement the turbine disk baffle structure optimization method of any one of claims 1-6.

9. A computer readable storage medium having stored thereon a computer program, characterized in that, The computer program is executed by the processor to implement the turbine disk baffle structure optimization method of any one of claims 1-6.

10. A computer program product comprising a computer program, characterized in that, The computer program is executed by the processor to implement the turbine disk baffle structure optimization method of any one of claims 1-6.

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