Turbine blade optimization design method and device based on fluid topological optimization

Abstract

The invention discloses a turbine blade optimization design method and device based on fluid topological optimization, and the method comprises the steps: carrying out the fluid topological optimization based on the initial configuration of a to-be-optimized turbine blade, and obtaining the optimized topological configuration of the turbine blade; the optimized topological configuration based on the turbine blade is stacked in the geometric modeling software in the spanwise direction, and a three-dimensional configuration of the turbine blade is obtained through reconstruction; carrying out accompanying optimization on the three-dimensional configuration of the turbine blade to obtain an optimized three-dimensional configuration of the turbine blade, and carrying out fluid topological optimization based on the blade top of the optimized three-dimensional configuration of the movable blade to obtain an optimized topological configuration of the blade top of the movable blade; and reconstructing the blade top of the optimized three-dimensional configuration of the movable blade in geometric modeling software based on the optimized topological configuration of the blade top of the movable blade to obtain a final optimized configuration of the movable blade, and forming a final optimized configuration of the turbine blade to be optimized by the final optimized configuration of the movable blade and the optimized three-dimensional configuration of the stationary blade. And a complete process from generation of a two-dimensional blade grid to reconstruction of a three-dimensional blade is provided.

Description

Technical Field

[0001] This invention relates to the field of turbine blade design, and more specifically to a turbine blade optimization design method and apparatus based on fluid topology optimization. Background Technology

[0002] Currently, the mainstream approach to aerodynamic design of typical aero-engine flow channel components involves optimizing dimensions and shapes on a pre-defined initial geometry. Related research largely focuses on improving optimization algorithms or optimizing initial geometry, with few breakthroughs in design concepts. Although extensive optimization research has been conducted both domestically and internationally on typical aero-engine flow channel components, performance improvements are often limited. Compared to traditional dimension and shape optimization, fluid topology optimization methods exhibit unique advantages in theoretical research. This method does not require pre-defined initial surfaces and geometric information, representing a "from scratch" design paradigm. Introducing it into the aerodynamic optimization design of typical aero-engine flow channel components holds promise for constructing entirely new design methods. Its core lies in rationally distributing design variables within the design domain to achieve the desired goals, thereby fundamentally avoiding dependence on the initial geometry. As a highly flexible aerodynamic design tool, fluid topology optimization can not only optimize dimensions and shapes but also reconstruct the topological layout of the research object, forming innovative aerodynamic configurations distinct from conventional designs. Applying fluid topology optimization to the design of typical turbine flow channel components theoretically has the potential to achieve breakthrough topology layouts within the design space. Based on this, it can be further combined with traditional optimization methods for refined design to meet the future requirements of my country's aerospace power devices for high performance and high adaptability of flow channel components.

[0003] Domestic and international experts and scholars have conducted preliminary research on this issue. Sá et al. applied an optimization method based on the variable density method to the design of small-sized pumps and verified the performance of the designed product. Pietropaoli et al. conducted aerodynamic and heat transfer topology optimization on the internal cooling channels of turbines, using the combination of minimizing flow loss and minimizing channel wall temperature as dual objectives to optimize the serpentine channel design. Maesschalck et al. conducted research on fluid topology optimization of turbine blade tip structures, proposing that fluid topology optimization has great potential in tip structure design. In 2021, Zhang Min et al. conducted preliminary research on the clearance structure design of turbine rotor blade tips based on fluid topology optimization methods, obtaining a tip structure optimized by fluid topology. In 2024, Alonso et al. used two-dimensional rotating machinery as the research object and achieved efficiency improvements. It can be seen that the above research is basically limited to exploring optimization methods for simplified models or conducting local optimization design of turbine blades, and has not proposed topology optimization for the overall structure of turbine blades. Summary of the Invention

[0004] The purpose of this application is to propose a turbine blade optimization design method and device based on fluid topology optimization to address the aforementioned technical problems.

[0005] In a first aspect, the present invention provides a turbine blade optimization design method based on fluid topology optimization, comprising the following steps:

[0006] The initial configuration of the turbine blade to be optimized is obtained, which includes stationary blades and moving blades. Based on the initial configuration of the turbine blade to be optimized, fluid topology optimization is carried out to obtain the optimized topology configuration of the turbine blade. In the CFD calculation process of fluid topology optimization, an energy equation is added to the incompressible Navier-Stokes equation, a penalty term constructed by the design variables of variable density is added to the momentum equation, and a density term is added to the mass equation.

[0007] The optimized topological configuration of the turbine blade is reconstructed by stacking along the spanwise direction in geometric modeling software to obtain the three-dimensional configuration of the turbine blade. Adjoint optimization is performed on the three-dimensional configuration of the turbine blade to obtain the optimized three-dimensional configuration of the turbine blade, which includes the optimized three-dimensional configuration of the stationary blade and the optimized three-dimensional configuration of the moving blade.

[0008] Fluid topology optimization is performed on the blade tip based on the optimized three-dimensional configuration of the moving blade to obtain the optimized topology configuration of the blade tip.

[0009] Based on the optimized topological configuration of the moving blade tip, the blade tip of the optimized three-dimensional configuration of the moving blade is reconstructed in the geometric modeling software to obtain the final optimized configuration of the moving blade. The final optimized configuration of the moving blade and the optimized three-dimensional configuration of the stationary blade constitute the final optimized configuration of the turbine blade to be optimized.

[0010] Preferably, fluid topology optimization is performed based on the initial configuration of the turbine blade to be optimized to obtain the optimized topology configuration of the turbine blade, specifically including:

[0011] The initial configuration of the turbine blade to be optimized is cut along the spanwise S1 flow surface to obtain several two-dimensional blade cascade flow channels corresponding to different blade heights. The middle arc of the blade profile obtained by the intersection of the two-dimensional blade cascade flow channel and the blade is taken as the geometric boundary of the design domain. The geometric boundary of the design domain is translated up and down to obtain the design domain of the blade. The periodic boundary is extended along the upstream and downstream of the design domain of the blade respectively.

[0012] Based on the periodic boundary and the blade design domain, fluid topology optimization is performed on the two-dimensional blade cascade flow channels corresponding to different blade heights to obtain the optimized topology configuration of the turbine blade.

[0013] Preferably, fluid topology optimization is performed on the blade tip based on the optimized three-dimensional configuration of the moving blade, resulting in an optimized topology configuration of the blade tip, specifically including:

[0014] The tip of the optimized three-dimensional configuration of the moving blade is divided into different sections along the X-axis of the turbine rotation axis and used as the design domain of the tip. The area at a distance from the preset height of the casing is cut off on the side of the different sections as the research area. The height of the design domain of the tip is twice the tip clearance. The inlet and outlet of the design domain of the tip are represented by a square with a side length equal to the tip clearance, which represents the blade wall thickness.

[0015] Fluid topology optimization was performed on the blade tip for different cross sections based on the study region and the blade tip design domain.

[0016] Preferably, in the process of fluid topology optimization, the objective function of the design domain is the total pressure loss, which is expressed as:

[0017] ;

[0018] in, Indicates total pressure loss. Indicates the total import pressure. Indicates the total export pressure. Indicates the outlet static pressure;

[0019] The boundary objective function of the design domain is 0.

[0020] Preferably, the governing equations used in the CFD calculation process of fluid topology optimization include the mass equation, momentum equation, and energy equation. The mass equation is expressed as:

[0021] ;

[0022] The momentum equation is expressed as:

[0023] ;

[0024] The energy equation is expressed as:

[0025] ;

[0026] in, The density of the fluid is expressed in kg / m³. 3 ; Pressure, unit is N / m 2 ; Viscous stress, unit is N / m 2 ; The Darcy force applied in the design domain is used as a penalty term in the momentum equation. For gradient; Total enthalpy, in J; Thermal conductivity of the fluid, expressed in W / (m·K). The temperature is represented in Kelvin (K), and U is a velocity vector. For time;

[0027] Darcy force is represented as:

[0028] ;

[0029] in, For the fluid domain within the design domain, For the fluid domain outside the design domain, The permeability coefficient is the coefficient of performance. The relationship between the permeability coefficient and the design variables is determined by the RAMP interpolation method, as defined below:

[0030] ;

[0031] in, Design variables with a range of 0 to 1 Indicates solid. Indicates fluid; The permeability coefficient of the solid medium region; The permeability coefficient of the fluid medium region; Indicates the optimization parameters;

[0032] Total enthalpy Represented as:

[0033] ;

[0034] ;

[0035] Viscous stress Represented as:

[0036] ;

[0037] in, enthalpy (e) is the internal energy (J); e is the volume (m³). 3 ; Let be the Kronecker function, and μ be the dynamic viscosity.

[0038] As a preferred approach, during the optimization process, the objective function of the design domain is the turbine isentropic efficiency, defined as follows:

[0039] ;

[0040] in, For turbine isentropic efficiency, T z Where n is the torque, n is the number of blades, and C is the torque.p For the specific heat capacity at constant pressure, T 1,r The total temperature at the rotor inlet is m. 1,r This is the rotor inlet flow rate. Where k is the pressure ratio and k is the specific heat ratio.

[0041] Secondly, the present invention provides a turbine blade optimization design device based on fluid topology optimization, comprising:

[0042] The blade optimization module is configured to obtain the initial configuration of the turbine blade to be optimized, which includes stationary blades and moving blades; based on the initial configuration of the turbine blade to be optimized, fluid topology optimization is performed to obtain the optimized topology configuration of the turbine blade; in the CFD calculation process of fluid topology optimization, an energy equation is added to the incompressible Navier-Stokes equations, a penalty term constructed from design variables of variable density is added to the momentum equation, and a density term is added to the mass equation;

[0043] The accompanying optimization module is configured to stack the optimized topology configuration of the turbine blade along the spanwise direction in the geometric modeling software to reconstruct the three-dimensional configuration of the turbine blade; the accompanying optimization is performed on the three-dimensional configuration of the turbine blade to obtain the optimized three-dimensional configuration of the turbine blade, which includes the optimized three-dimensional configuration of the stationary blade and the optimized three-dimensional configuration of the moving blade.

[0044] The blade tip optimization module is configured to perform fluid topology optimization based on the optimized three-dimensional configuration of the moving blade tip, and obtain the optimized topology configuration of the moving blade tip.

[0045] The reconstruction module is configured to reconstruct the tip of the optimized three-dimensional configuration of the moving blade in the geometric modeling software based on the optimized topology configuration of the moving blade tip, so as to obtain the final optimized configuration of the moving blade. The final optimized configuration of the moving blade and the optimized three-dimensional configuration of the stationary blade constitute the final optimized configuration of the turbine blade to be optimized.

[0046] Thirdly, the present invention provides an electronic device including one or more processors; and a storage device for storing one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors implement the method as described in any implementation of the first aspect.

[0047] Fourthly, the present invention provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the method as described in any of the implementations of the first aspect.

[0048] Fifthly, the present invention provides a computer program product, including a computer program that, when executed by a processor, implements the method as described in any of the implementations in the first aspect.

[0049] Compared with the prior art, the present invention has the following beneficial effects:

[0050] (1) The turbine blade optimization design method based on fluid topology optimization proposed in this invention innovatively introduces the compressible Navier-Stokes equation into engineering applications, treats fluid density as a variable and couples it with the energy equation, and the energy equation takes into account the effect of temperature change, which can more realistically reflect the flow effect under the actual working conditions of the turbine during the optimization process.

[0051] (2) The turbine blade optimization design method based on fluid topology optimization proposed in this invention realizes the reconstruction of two-dimensional blade cascade to three-dimensional blade in the flow channel “from nothing to something”. Based on the blade adjoint optimization, the aerodynamic design of the innovative fluid topology configuration of the moving blade tip is further carried out, which reflects the innovative design idea of ​​turbine components. Attached Figure Description

[0052] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0053] Figure 1 This is a schematic flowchart of a turbine blade optimization design method based on fluid topology optimization, which is an embodiment of this application.

[0054] Figure 2 This is a schematic diagram illustrating the construction of the design domain for a turbine blade using a fluid topology optimization-based turbine blade optimization design method according to an embodiment of this application.

[0055] Figure 3 This diagram illustrates the iterative process of two-dimensional blade flow channel fluid topology optimization in the turbine blade optimization design method based on fluid topology optimization, as an embodiment of this application.

[0056] Figure 4 A comparison diagram of the blade configuration before and after optimization in the turbine blade optimization design method based on fluid topology optimization, which is an embodiment of this application;

[0057] Figure 5 This is a schematic diagram illustrating the construction of the blade tip design domain in the turbine blade optimization design method based on fluid topology optimization, as an embodiment of this application.

[0058] Figure 6This diagram illustrates the iterative process of tip fluid topology optimization for a moving blade in an embodiment of the turbine blade optimization design method based on fluid topology optimization, as described in this application.

[0059] Figure 7 The diagram shows the blade tip configuration and streamline distribution before and after optimization of the turbine blade based on the fluid topology optimization optimization design method according to an embodiment of this application.

[0060] Figure 8 This is a schematic diagram of a turbine blade optimization design device based on fluid topology optimization, as an embodiment of this application.

[0061] Figure 9 This is a schematic diagram of the hardware structure of an electronic device provided in an embodiment of the present invention. Detailed Implementation

[0062] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this invention, and not all of them. Based on the embodiments of this invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this invention.

[0063] Figure 1 An embodiment of this application illustrates a turbine blade optimization design method based on fluid topology optimization, comprising the following steps:

[0064] S1. Obtain the initial configuration of the turbine blade to be optimized, which includes stationary blades and moving blades. Based on the initial configuration of the turbine blade to be optimized, perform fluid topology optimization to obtain the optimized topology configuration of the turbine blade. In the CFD calculation process of fluid topology optimization, the governing equations used are supplemented with an energy equation on the basis of the incompressible Navier-Stokes equation, and a penalty term constructed by the design variables of variable density is added to the momentum equation, and a density term is added to the mass equation.

[0065] In a specific embodiment, fluid topology optimization is performed based on the initial configuration of the turbine blade to be optimized to obtain the optimized topology configuration of the turbine blade, specifically including:

[0066] The initial configuration of the turbine blade to be optimized is cut along the spanwise S1 flow surface to obtain several two-dimensional blade cascade flow channels corresponding to different blade heights. The middle arc of the blade profile obtained by the intersection of the two-dimensional blade cascade flow channel and the blade is taken as the geometric boundary of the design domain. The geometric boundary of the design domain is translated up and down to obtain the design domain of the blade. The periodic boundary is extended along the upstream and downstream of the design domain of the blade respectively.

[0067] Based on the periodic boundary and the blade design domain, fluid topology optimization is performed on the two-dimensional blade cascade flow channels corresponding to different blade heights to obtain the optimized topology configuration of the turbine blade.

[0068] In a specific embodiment, during the fluid topology optimization process, the objective function of the design domain is the total pressure loss, which is expressed as:

[0069] ;

[0070] in, Indicates total pressure loss. Indicates the total import pressure. Indicates the total export pressure. Indicates the outlet static pressure;

[0071] The boundary objective function of the design domain is 0.

[0072] In a specific embodiment, the governing equations used in the CFD calculation process of fluid topology optimization include the mass equation, momentum equation, and energy equation. The mass equation is expressed as:

[0073] ;

[0074] The momentum equation is expressed as:

[0075] ;

[0076] The energy equation is expressed as:

[0077] ;

[0078] in, The density of the fluid is expressed in kg / m³. 3 ; Pressure, unit is N / m 2 ; Viscous stress, unit is N / m 2 ; The Darcy force applied in the design domain is used as a penalty term in the momentum equation. For gradient; Total enthalpy, in J; Thermal conductivity of the fluid, expressed in W / (m·K). The temperature is represented in Kelvin (K), and U is a velocity vector. For time;

[0079] Darcy force is represented as:

[0080] ;

[0081] in, For the fluid domain within the design domain, For the fluid domain outside the design domain, The permeability coefficient is the coefficient of performance. The relationship between the permeability coefficient and the design variables is determined by the RAMP interpolation method, as defined below:

[0082] ;

[0083] in, Design variables with a range of 0 to 1 Indicates solid. Indicates fluid; The permeability coefficient of the solid medium region; The permeability coefficient of the fluid medium region; Indicates the optimization parameters;

[0084] Total enthalpy Represented as:

[0085] ;

[0086] ;

[0087] Viscous stress Represented as:

[0088] ;

[0089] in, enthalpy (e) is the internal energy (J); e is the volume (m³). 3 ; Let be the Kronecker function, and μ be the dynamic viscosity.

[0090] Specifically, the initial configuration of the turbine blade to be optimized is imported into the geometric modeling tool. Several S1 flow surfaces are uniformly selected along different blade heights (corresponding to the spanwise direction). Each S1 flow surface represents a coaxial conical surface. The three-dimensional conical flow surface is unfolded into a two-dimensional plane. At the same time, the blade section (airfoil) is projected onto this two-dimensional plane to form a two-dimensional blade cascade flow channel. The turbine blade to be optimized includes stationary blades and moving blades. Among them, num_S S1 flow surfaces are uniformly selected along different blade heights for the stationary blades, and num_R S1 flow surfaces are uniformly selected along different blade heights for the moving blades.

[0091] The initial configuration of the turbine blade to be optimized is divided into two-dimensional blade cascade channels at several blade heights of the S1 flow surface. The middle arc of the blade profile at different blade heights is taken as the geometric boundary of the design domain and translated to form the upper and lower boundaries of the blade design domain. The two sides are appropriately extended along the upstream and downstream of the blade design domain to form periodic boundaries. The corresponding blade height working conditions of the calculation results of the initial configuration of the turbine blade to be optimized are used as the boundary conditions for optimization. Fluid topology optimization is carried out on the two-dimensional blade cascade channels at different blade heights.

[0092] In one embodiment, reference Figure 2 Each leaf-shaped profile projected onto a two-dimensional plane (corresponding to) Figure 2 (Left image) The arc is extracted using geometric modeling tools as the geometric boundary of the design domain (corresponding to...) Figure 2 The wall in the design domain is used to shift the grid pitch d(i) of each cross section vertically, which serves as the upper and lower boundaries of the blade's design domain. Extending the design domain upstream and downstream by a distance equal to the axial chord length x_chord allows the inflow and outflow to develop fully. The two sides are set as periodic boundaries (corresponding to...). Figure 2 The period is defined as follows: Inlet corresponds to the region of input fluid, and Outlet corresponds to the region of output fluid. Therefore, based on the fluid within the period boundary, fluid topology optimization is carried out on the design domain of the blade corresponding to different blade heights.

[0093] In the process of fluid topology optimization, a quasi-three-dimensional assumption is made regarding the flow within the two-dimensional blade cascade channel. The radial velocity component is ignored (i.e., Vr≈0), and the flow is assumed to develop tangentially along the flow surface. The flow within the two-dimensional blade cascade channel exhibits periodic repetition (a single channel represents the entire circumference). The initial configuration of the turbine blade to be optimized is meshed and CFD calculated. The blade height conditions corresponding to the num_S+num_R calculation results are extracted as the boundary conditions for optimization, including the total inlet pressure. wei(i), total imported temperature (i) Outlet static pressure (i) Inlet Mach number Ma_in(i), etc. Fluid topology optimization is performed on the two-dimensional blade cascade flow channels with num_S+num_R blade heights to be optimized, with the optimization objective being to minimize the total pressure loss of the flow. A schematic diagram of the iterative process of fluid topology optimization for the two-dimensional blade cascade flow channel is shown below. Figure 3 As shown, the optimized topology configuration of the turbine blades is finally obtained.

[0094] The mathematical model of the fluid topology optimization method can be expressed as:

[0095] ;

[0096] Where J is the objective function of the flow field with respect to the design variables and the flow field variables; For design variables; For flow field variables, including velocity, pressure, temperature, etc.; U is the velocity vector; Represent the residual equation of the governing equation; This indicates an additional inequality constraint.

[0097] Typically, the optimization objective is expressed as the sum of the design domain objective value and the boundary objective value, as follows:

[0098] ;

[0099] in, For design domain; The boundary of the design domain; The objective function for the design domain; The objective function for designing the domain boundary.

[0100] The constraints are:

[0101] ;

[0102] Among them, V θ The set volume constraints.

[0103] In the embodiments of this application, the total pressure loss is used as the objective function of the design domain. The boundary objective function of the design domain is 0, i.e. =0.

[0104] The fluid / solid penalty function in fluid topology optimization is introduced using a variable density method. The basic idea is to arrange design variables with values ​​between 0 and 1 on the discrete grid cells of the design domain, and then introduce these design variables into the governing equations by constructing a penalty function. This causes the design variables to have no effect in the fluid region but generate significant resistance in the solid region, thus automatically separating the fluid and solid regions. The embodiments of this application utilize the application of a Darcy force on the design domain as a penalty method. This force represents the resistance experienced by the fluid when passing through a porous medium, typically exhibiting a linear relationship positively correlated with the fluid velocity. The Darcy force is used as a penalty term in the momentum equation. The fluid density is treated as a variable, and a density term is added to the mass equation and coupled to the energy equation. Therefore, the embodiments of this application add an energy equation to the incompressible Navier-Stokes equations, add a penalty term constructed from the variable density design variables to the momentum equation, and add a density term to the mass equation, thus obtaining the Navier-Stokes equations for a steady compressible fluid.

[0105] When permeability coefficient The larger the permeability coefficient, the greater the resistance the fluid experiences, the weaker the permeability in porous media, and the more difficult the flow. Typically, the permeability coefficient... In the formula Determined by the Darcy number, the two are inversely proportional. The Darcy number is defined as follows:

[0106] ;

[0107] Where Da is the Darcy number, μ is the dynamic viscosity, and l is the inlet height of the flow channel.

[0108] In the process of fluid topology optimization, solid regions are considered to have almost no fluid passage, therefore Usually, a larger value is chosen. Here we take 0.

[0109] Because of the high-temperature, high-speed compressible flow in the turbine channel, the energy equation in the governing equations must also be considered during CFD calculations. Furthermore, considering the influence of porous media flow, the governing equations should also include Darcy force as a penalty term. The other steps in the iterative process of fluid topology optimization are standard and will not be elaborated upon here.

[0110] S2, Based on the optimized topological configuration of the turbine blade, the turbine blade is reconstructed by stacking along the spanwise direction in the geometric modeling software to obtain the three-dimensional configuration of the turbine blade; the three-dimensional configuration of the turbine blade is then subjected to adjoint optimization to obtain the optimized three-dimensional configuration of the turbine blade, which includes the optimized three-dimensional configuration of the stationary blade and the optimized three-dimensional configuration of the moving blade.

[0111] In a specific embodiment, during the optimization process, the objective function of the design domain is the turbine isentropic efficiency, defined as follows:

[0112] ;

[0113] in, For turbine isentropic efficiency, T z Where n is the torque, n is the number of blades, and C is the torque. p For the specific heat capacity at constant pressure, T 1,r The total temperature at the rotor inlet is m. 1,r This is the rotor inlet flow rate. Where k is the pressure ratio and k is the specific heat ratio.

[0114] Specifically, referring to the optimized topology of the turbine blade, the blades are reconstructed into a 3D configuration by stacking along the spanwise direction in geometric modeling software, resulting in the 3D model turbine.igs. Sections are taken from the 3D model along different blade heights, and after format conversion, the stationary blade geometry file stator.curve and the rotating blade geometry file rotor.curve are obtained for mesh generation. These two geometry files are imported into the mesh generation software to generate a mesh. After format conversion, adjoint optimization is performed, with the optimization objective being the turbine's isentropic efficiency, resulting in the optimized 3D configuration of the turbine blade. During adjoint optimization, design variables are placed on the surface of the design object, and their effects on the design object are influenced by adjoint sensitivity, thereby controlling the position of the design variables. Control points move on the blade surface, causing deformation of the blade surface. The final optimized 3D configuration of the turbine blade is shown below. Figure 4 As shown.

[0115] S3. Based on the optimized three-dimensional configuration of the moving blade tip, fluid topology optimization is performed to obtain the optimized topology configuration of the moving blade tip.

[0116] In a specific embodiment, step S3 specifically includes:

[0117] The tip of the optimized three-dimensional configuration of the moving blade is divided into different sections along the X-axis of the turbine rotation axis and used as the design domain of the tip. The area at a distance from the preset height of the casing is cut off on the side of the different sections as the research area. The height of the design domain of the tip is twice the tip clearance. The inlet and outlet of the design domain of the tip are represented by a square with a side length equal to the tip clearance, which represents the blade wall thickness.

[0118] Based on the research region and the blade tip design domain, fluid topology optimization is performed on the blade tip corresponding to different cross sections.

[0119] In one embodiment, the blade tip of the optimized moving blade is taken as the research object. The area along the turbine rotation axis (X-axis) is divided into num_T sections, simplifying it to a two-dimensional blade tip design domain. The region 10 times the blade tip clearance (10δ) at a distance of 10 times the distance from the casing is selected as the research area. The height of the blade tip design domain is twice the blade tip clearance (2δ). The inlet and outlet of the blade tip design domain are each represented by a square with a side length of δ, indicating the blade wall thickness. Figure 5 The diagram on the left shows the design domain of the blade tip. Using the operating conditions of the corresponding cross-section of the optimized three-dimensional configuration of the moving blade as the boundary conditions, fluid topology optimization is performed on the design domain of the moving blade tip. The optimization process is the same as in step S1, resulting in the optimized topology configuration of the moving blade tip. Figure 5 The right side shows the optimized topological configuration of the blade tip of the moving blade.

[0120] In one embodiment, the operating conditions of the corresponding num_T cross sections of the optimized moving blade are used as the boundary conditions for optimization, including the total inlet pressure. wei(i), total imported temperature (i) Outlet static pressure (i) The inlet Mach number Ma_T_in(i) is used to perform fluid topology optimization on the design domain of the blade tip. The optimization objective is to minimize the total pressure loss of the flow. The optimization process is the same as in step S1. The configuration changes during the iteration process are as follows: Figure 6 As shown, num_T cross-sectional configurations are obtained.

[0121] S4. Based on the optimized topological configuration of the blade tip of the moving blade, the blade tip of the optimized three-dimensional configuration of the moving blade is reconstructed in the geometric modeling software to obtain the final optimized configuration of the moving blade. The final optimized configuration of the moving blade and the optimized three-dimensional configuration of the stationary blade constitute the final optimized configuration of the turbine blade to be optimized.

[0122] Specifically, referring to the optimized topological configuration of the blade tip, geometric modeling software is used to draw the blade tip section profile in each blade tip design section. The blade tip section profile is then combined with the blade tip outline to reconstruct a three-dimensional curved blade tip, resulting in the final optimized configuration of the moving blade, such as... Figure 7 As shown, the final optimized configuration of the moving blade and the optimized three-dimensional configuration of the stationary blade constitute the final optimized configuration of the turbine blade to be optimized.

[0123] Further reference Figure 8 As an implementation of the methods shown in the above figures, this application provides an embodiment of a turbine blade optimization design device based on fluid topology optimization. This device embodiment is similar to... Figure 1 Corresponding to the method embodiments shown, this device can be specifically applied to various electronic devices.

[0124] This application provides a turbine blade optimization design device based on fluid topology optimization, including:

[0125] Blade optimization module 1 is configured to obtain the initial configuration of the turbine blade to be optimized, which includes stationary blades and moving blades; based on the initial configuration of the turbine blade to be optimized, fluid topology optimization is performed to obtain the optimized topology configuration of the turbine blade; in the CFD calculation process of fluid topology optimization, an energy equation is added to the incompressible Navier-Stokes equation, a penalty term constructed by the design variables of variable density is added to the momentum equation, and a density term is added to the mass equation;

[0126] The accompanying optimization module 2 is configured to stack the optimized topology configuration of the turbine blade along the spanwise direction in the geometric modeling software to reconstruct the three-dimensional configuration of the turbine blade; the accompanying optimization is performed on the three-dimensional configuration of the turbine blade to obtain the optimized three-dimensional configuration of the turbine blade, which includes the optimized three-dimensional configuration of the stationary blade and the optimized three-dimensional configuration of the moving blade.

[0127] Blade tip optimization module 3 is configured to perform fluid topology optimization based on the optimized three-dimensional configuration of the moving blade tip to obtain the optimized topology configuration of the moving blade tip.

[0128] Reconstruction module 4 is configured to reconstruct the tip of the optimized three-dimensional configuration of the moving blade in the geometric modeling software based on the optimized topology configuration of the moving blade tip, so as to obtain the final optimized configuration of the moving blade. The final optimized configuration of the moving blade and the optimized three-dimensional configuration of the stationary blade constitute the final optimized configuration of the turbine blade to be optimized.

[0129] Figure 9 This is a schematic diagram of the hardware structure of an electronic device provided in an embodiment of the present invention. For example... Figure 9 As shown, the electronic device in this embodiment includes a processor 901 and a memory 902; wherein the memory 902 is used to store computer execution instructions; and the processor 901 is used to execute the computer execution instructions stored in the memory to implement the various steps performed by the electronic device in the above embodiment. For details, please refer to the relevant descriptions in the foregoing method embodiments.

[0130] Alternatively, the memory 902 can be either standalone or integrated with the processor 901.

[0131] When the memory 902 is set up independently, the electronic device also includes a bus 903 for connecting the memory 902 and the processor 901.

[0132] This invention also provides a computer storage medium storing computer execution instructions, which, when executed by processor 901, implement the above method.

[0133] This invention also provides a computer program product, including a computer program that, when executed by a processor 901, implements the above-described method.

[0134] In the embodiments provided by this invention, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative; for instance, the division of modules is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple modules may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be indirect coupling or communication connection through some interfaces, devices, or modules, and may be electrical, mechanical, or other forms.

[0135] The modules described as separate components may or may not be physically separate. The components shown as modules may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to implement the solution of this embodiment according to actual needs.

[0136] Furthermore, the functional modules in the various embodiments of this invention can be integrated into one processing unit, or each module can exist physically separately, or two or more modules can be integrated into one unit. The unit formed by the above modules can be implemented in hardware or in the form of hardware plus software functional units.

[0137] The integrated modules described above, implemented as software functional modules, can be stored in a computer-readable storage medium. These software functional modules, stored in a storage medium, include several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) or processor 901 to execute some steps of the methods of the various embodiments of this application.

[0138] It should be understood that the processor 901 described above can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), etc. The general-purpose processor can be a microprocessor, or the processor 901 can be any conventional processor 901. The steps of the method disclosed in this invention can be directly manifested as execution by the hardware processor 901, or execution by a combination of hardware and software modules within the processor 901.

[0139] The memory 902 may include high-speed RAM memory, and may also include non-volatile memory NVM, such as at least one disk storage device, and may also be a USB flash drive, portable hard drive, read-only memory, disk or optical disc, etc.

[0140] Bus 903 can be an Industry Standard Architecture (ISA), a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus, etc. Bus 903 can be divided into address bus, data bus, control bus, etc. For ease of illustration, the bus 903 in the accompanying drawings of this application is not limited to only one bus 903 or one type of bus 903.

[0141] The aforementioned storage medium can be implemented from any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk. The storage medium can be any available medium accessible to general-purpose or special-purpose computers.

[0142] An exemplary storage medium is coupled to a processor 901, enabling the processor 901 to read information from and write information to the storage medium. Alternatively, the storage medium can be an integral part of the processor 901. The processor 901 and the storage medium can reside in an application-specific integrated circuit (ASIC). Alternatively, the processor 901 and the storage medium can exist as discrete components in an electronic device or a host device.

[0143] Those skilled in the art will understand that all or part of the steps of the above-described method embodiments can be implemented by hardware related to program instructions. The aforementioned program can be stored in a computer-readable storage medium. When executed, the program performs the steps of the above-described method embodiments; and the aforementioned storage medium includes various media capable of storing program code, such as ROM, RAM, magnetic disks, or optical disks.

[0144] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A turbine blade optimization design method based on fluid topology optimization, characterized in that, Includes the following steps: The initial configuration of the turbine blade to be optimized is obtained, which includes stationary blades and moving blades; based on the initial configuration of the turbine blade to be optimized, fluid topology optimization is carried out to obtain the optimized topology configuration of the turbine blade; in the CFD calculation process of the fluid topology optimization, an energy equation is added to the incompressible Navier-Stokes equation, a penalty term constructed by the design variable of variable density is added to the momentum equation, and a density term is added to the mass equation; Based on the optimized topological configuration of the turbine blade, the turbine blade is reconstructed by stacking along the spanwise direction in the geometric modeling software. The three-dimensional configuration of the turbine blade is then subjected to adjoint optimization to obtain the optimized three-dimensional configuration of the turbine blade, which includes the optimized three-dimensional configuration of the stationary blade and the optimized three-dimensional configuration of the moving blade. Based on the optimized three-dimensional configuration of the moving blade, fluid topology optimization is performed on the blade tip to obtain the optimized topology configuration of the moving blade tip. Based on the optimized topological configuration of the blade tip of the moving blade, the blade tip of the optimized three-dimensional configuration of the moving blade is reconstructed in the geometric modeling software to obtain the final optimized configuration of the moving blade. The final optimized configuration of the moving blade and the optimized three-dimensional configuration of the stationary blade constitute the final optimized configuration of the turbine blade to be optimized.

2. The turbine blade optimization design method based on fluid topology optimization according to claim 1, characterized in that, Based on the initial configuration of the turbine blade to be optimized, fluid topology optimization is performed to obtain the optimized topology configuration of the turbine blade, specifically including: The initial configuration of the turbine blade to be optimized is cut along the spanwise S1 flow surface to obtain several two-dimensional blade cascade flow channels corresponding to different blade heights. The middle arc line of the blade profile obtained by the intersection of the two-dimensional blade cascade flow channel and the blade is taken as the geometric boundary of the design domain. The geometric boundary of the design domain is translated up and down to obtain the design domain of the blade. The periodic boundary is extended along the upstream and downstream of the design domain of the blade respectively. Based on the periodic boundary and the blade design domain, fluid topology optimization is performed on the two-dimensional blade cascade flow channels corresponding to different blade heights to obtain the optimized topology configuration of the turbine blade.

3. The turbine blade optimization design method based on fluid topology optimization according to claim 2, characterized in that, Based on the optimized three-dimensional configuration of the moving blade, fluid topology optimization is performed at the blade tip to obtain the optimized topology configuration of the moving blade tip, specifically including: The blade tip of the optimized three-dimensional configuration of the moving blade is divided into different sections along the X-axis of the turbine rotation axis and used as the design domain of the blade tip. The area at a preset height from the casing is cut off on the side of the different sections as the research area. The height of the design domain of the blade tip is twice the blade tip clearance. The inlet and outlet of the design domain of the blade tip are respectively represented by a square with a side length equal to the blade tip clearance to represent the blade wall thickness. Based on the research region and the blade tip design domain, fluid topology optimization is performed on the blade tip corresponding to different cross sections.

4. The turbine blade optimization design method based on fluid topology optimization according to claim 3, characterized in that, In the fluid topology optimization process, the objective function of the design domain is the total pressure loss, which is expressed as: ； in, Indicates total pressure loss. Indicates the total import pressure. Indicates the total export pressure. Indicates the outlet static pressure; The boundary objective function of the design domain is 0.

5. The turbine blade optimization design method based on fluid topology optimization according to claim 1, characterized in that, The governing equations used in the CFD calculation process of the fluid topology optimization include the mass equation, momentum equation, and energy equation. The mass equation is expressed as: ； The momentum equation is expressed as: ； The energy equation is expressed as: ； in, The density of the fluid is expressed in kg / m³. 3 ; Pressure, unit is N / m 2 ; Viscous stress, unit is N / m 2 ; The Darcy force applied in the design domain is used as a penalty term in the momentum equation. For gradient; Total enthalpy, in J; Thermal conductivity of the fluid, expressed in W / (m·K). The temperature is represented in Kelvin (K), and U is a velocity vector. For time; Darcy force is represented as: ； in, For the fluid domain within the design domain, For the fluid domain outside the design domain, The permeability coefficient; the relationship between the permeability coefficient and the design variables is determined by the RAMP interpolation method, defined as follows: ； in, Design variables with a range of 0 to 1 Indicates solid. Indicates fluid; The permeability coefficient of the solid medium region; The permeability coefficient of the fluid medium region; Indicates the optimization parameters; Total enthalpy Represented as: ； ； Viscous stress Represented as: ； in, enthalpy (e) is the internal energy (J); e is the volume (m³). 3 ; Let be the Kronecker function, and μ be the dynamic viscosity.

6. The turbine blade optimization design method based on fluid topology optimization according to claim 1, characterized in that, In the accompanying optimization process, the objective function of the design domain is the turbine isentropic efficiency, defined as follows: ； in, For turbine isentropic efficiency, T z Where n is the torque, n is the number of blades, and C is the torque. p For the specific heat capacity at constant pressure, T 1,r The total temperature at the rotor inlet is m. 1,r This is the rotor inlet flow rate. Where k is the pressure ratio and k is the specific heat ratio.

7. A turbine blade optimization design device based on fluid topology optimization, characterized in that, include: The blade optimization module is configured to obtain the initial configuration of the turbine blade to be optimized, which includes stationary blades and moving blades. Based on the initial configuration of the turbine blade to be optimized, fluid topology optimization is carried out to obtain the optimized topology configuration of the turbine blade. In the CFD calculation process of the fluid topology optimization, an energy equation is added to the incompressible Navier-Stokes equation, a penalty term constructed by the design variable of variable density is added to the momentum equation, and a density term is added to the mass equation. The accompanying optimization module is configured to stack the optimized topology of the turbine blade along the spanwise direction in the geometric modeling software to reconstruct the three-dimensional configuration of the turbine blade; and to perform accompanying optimization on the three-dimensional configuration of the turbine blade to obtain the optimized three-dimensional configuration of the turbine blade, which includes the optimized three-dimensional configuration of the stationary blade and the optimized three-dimensional configuration of the moving blade. The blade tip optimization module is configured to perform fluid topology optimization based on the optimized three-dimensional configuration of the moving blade tip to obtain the optimized topology configuration of the moving blade tip. The reconstruction module is configured to reconstruct the tip of the optimized three-dimensional configuration of the moving blade in the geometric modeling software based on the optimized topological configuration of the blade tip, so as to obtain the final optimized configuration of the moving blade. The final optimized configuration of the moving blade and the optimized three-dimensional configuration of the stationary blade constitute the final optimized configuration of the turbine blade to be optimized.

8. An electronic device, comprising: One or more processors; Storage device for storing one or more programs. When the one or more programs are executed by the one or more processors, the one or more processors implement the method as described in any one of claims 1-6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the program is executed by the processor, it implements the method as described in any one of claims 1-6.

10. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by a processor, it implements the method as described in any one of claims 1-6.

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