A design method for cooling structure of porous foam ribbed plate applied to turbine blades

Abstract

The present invention discloses a method for designing a porous foam rib plate cooling structure for turbine blades, comprising the following steps: Step 1: parameterizing the porous foam rib plate cooling structure and extracting geometric characteristic parameters; Step 2: determining the geometric parameters to be optimized, giving upper and lower intervals of the design variables; Step 3: determining the optimization target and constructing a sample space of test points; Step 4: establishing a surrogate model between multi-objective optimization parameter values and geometric characteristic parameters; Step 5: optimizing under the optimization target using the surrogate model and the NSGA-II non-dominated genetic multi-objective optimization algorithm to obtain geometric parameter design values of the porous foam rib plate structure that meet the optimization target, thereby obtaining the optimal porous foam rib plate cooling structure. This method solves the problems of existing design methods that make it difficult to find the optimal design and have low design efficiency.

Description

Technical field

[0001] The invention belongs to the technical field of layer plate cooling structure design methods, and in particular relates to a porous foam rib layer plate cooling structure design method applied to turbine blades. [Background Technology]

[0002] Currently, the turbine inlet temperature of advanced gas turbine engines is showing a trend of continuous increase. To ensure the safe and reliable operation of turbine blades under high thermal load conditions, efficient cooling measures must be taken. The porous medium foam rib double-wall cooling structure integrates internal cooling and external film cooling, with the advantages of low cooling air consumption and high cooling efficiency. The flow resistance and heat transfer characteristics of the porous medium foam rib double-wall structure are closely related to the pore / rib structure parameters such as the porosity, pore density, and rib height of the porous foam ribs. In order to fully utilize the porous foam ribs to improve the comprehensive cooling effect of the double-wall structure, improve the unevenness of its surface temperature, and reduce the level of thermal stress without significantly increasing the flow resistance, and to avoid problems such as excessive resistance loss and lack of cooling air flow caused by unreasonable porous medium pore parameters, it is necessary to carry out the optimization design of the porous foam rib double-wall cooling structure.

[0003] Currently, the design of porous media spoiler plate structures remains at the conceptual level and theoretical feasibility, with no specific structural design, including the pore pattern, pore density, and parameter design of the porous media ribs. Traditional trial-and-error exhaustive design methods, which repeatedly vary the geometry, struggle to find the optimal design and are inefficient. Furthermore, improper porous media pore parameter design can lead to excessive resistance losses and the inability to maintain cool air flow. [Summary of the invention]

[0004] The purpose of the present invention is to provide a method for designing a porous foam rib plate cooling structure for turbine blades, so as to solve the problem that the existing design methods are difficult to find the optimal design and have low design efficiency.

[0005] The present invention adopts the following technical solution: a method for designing a porous foam rib plate cooling structure for turbine blades, comprising the following contents:

[0006] Step 1: Extract the minimum unit cooling structure of the double-wall configuration of the turbine guide blade under real working conditions, parameterize the porous foam rib plate cooling structure, and obtain its characteristic geometric parameters;

[0007] Step 2: Select an optimizable characteristic geometric parameter from the characteristic geometric parameters as an optimized design variable, and set an upper and lower range of the design variable;

[0008] Step 3: Determine the optimization target of the porous foam ribbed plate composite cooling structure, change the design value within the upper and lower ranges of the design variables, and construct a test point sample space;

[0009] Among them, the maximum average comprehensive cooling efficiency and the minimum pressure loss coefficient C p As a multi-objective optimization function;

[0010] Step 4: Perform numerical calculations on the test points to obtain the multi-objective optimization parameter values at different sample points, and establish a proxy model between the multi-objective optimization parameter values and the geometric feature parameters based on the sample space;

[0011] By increasing the number of test sample points, performing numerical simulations and comparing the results with those predicted by the proxy model, the numerical accuracy of the proxy model is verified:

[0012] If the accuracy of the proxy model is less than the set value, the number of sample points is increased and the proxy model is rebuilt until the accuracy of the proxy model meets the design requirements;

[0013] Step 5: When the minimum pressure loss coefficient Cp is less than or equal to the limit value and the maximum surface average comprehensive cooling efficiency is achieved Under the highest optimization goal, the agent model and the NSGA-II non-dominated genetic multi-objective optimization algorithm are used to search for the optimal solution, and the geometric parameter design values of the porous foam rib plate structure that meet the optimization goal are obtained, thereby obtaining the optimal porous foam rib plate cooling structure.

[0014] Furthermore, the characteristic geometric parameters in step 1 include porous foam rib porosity, pore density, rib height and rib spacing, impact holes and air film holes.

[0015] Furthermore, in step 3, the maximum surface average comprehensive cooling efficiency The calculation formula is as follows:

[0016]

[0017] Minimum pressure loss coefficient C p The calculation formula is as follows:

[0018]

[0019] Where φ is the comprehensive cooling efficiency, T w,ex is the temperature of the outer surface of the air film plate, T g and T c are the temperatures of gas and air conditioning respectively; P imp,t and P film,t are the total pressures at the impact hole inlet and the film hole outlet, respectively.

[0020] Furthermore, the specific method for obtaining the multi-objective optimization parameter values at different sample points in step 4 is:

[0021] Step 4.1, geometric modeling of the porous foam rib area and double-wall structure;

[0022] Step 4.2, meshing the fluid and solid domains of the porous foam rib double-wall structure and performing local densification near the wall and at the fluid-solid interface;

[0023] Step 4.3: Use a Reynolds-averaged method coupled with a turbulence model to solve the three-dimensional compressible fluid mass, momentum, and energy conservation equations and the three-dimensional heat conduction equation in the solid domain, thereby obtaining the flow and temperature field characteristics of the porous foam rib plate cooling structure under different characteristic geometric parameters;

[0024] Step 4.4: Post-process the obtained numerical calculation results to obtain the multi-objective optimization parameter values of the porous foam ribbed plate structure at different sample points.

[0025] Furthermore, in step 4.1, the porous skeleton parameters describing the porous foam ribs are obtained by iteratively solving the set porosity and pore density values.

[0026] The beneficial effects of the present invention are: the present invention adopts a multi-objective optimization method of a porous foam rib layer structure based on an agent model, which can relatively quickly obtain the optimal design parameters of a cooling structure with high-efficiency cooling performance and low flow resistance characteristics within the design range, reduce the calculation cost required in the design, maximize the use of porous medium turbulent elements to enhance convective heat transfer and thermal conductivity characteristics, effectively regulate the cooling characteristics and temperature distribution uniformity and flow resistance characteristics of the layer cooling structure, realize efficient design of the layer cooling structure, and can be applied to aircraft engine blades to achieve multiple advantages such as lower temperature and thermal stress levels and higher strength and durability.

[0027] This method replaces complex physical models with proxy models, enabling the evaluation of numerous design solutions in a relatively short period of time. This significantly improves the efficiency of the optimization process and reduces computational time and cost. The proxy model can maintain high prediction accuracy while reducing the high computational overhead associated with directly using high-precision simulation models, making the optimization results more reliable. This method is applicable to a variety of porous media structures, and optimization objectives (such as cooling effect and flow resistance) can be adjusted according to specific needs to achieve optimal overall performance. It can simultaneously consider multiple mutually constrained objectives (such as maximizing cooling efficiency and minimizing flow resistance) to find the optimal solution or Pareto front, providing decision makers with more options.

[0028] The NSGA-II algorithm used in this invention is an improved version of the non-dominated sorting genetic algorithm, a very popular and effective algorithm in the field of multi-objective optimization. It exhibits many advantages in solving multi-objective optimization problems and can be used in conjunction with surrogate models to further reduce computational costs and improve optimization efficiency. These advantages make it an ideal choice for solving such multi-objective optimization problems. Optimization problems for porous foam ribbed plate structures often have multiple local optimal solutions. The global search capability of the NSGA-II algorithm can effectively explore the solution space, avoid being trapped in local optima, and thus find the global optimal solution.

Brief Description of the Drawings

[0029] Figure 1 This is a flow chart of a method for designing a porous foam rib plate cooling structure for turbine blades according to the present invention;

[0030] Figure 2 Schematic diagram of the porous foam rib plate cooling structure in the embodiment.

[0031] Among them, 1. impact hole, 2. impact orifice plate, 4. spoiler column, 5. air film hole, 6. air film orifice plate, 7. air film hole channel.

[0032] The present invention will be described in detail below with reference to the accompanying drawings and specific embodiments.

[0033] The present invention provides a method for designing a porous foam rib laminate cooling structure for turbine blades, which achieves the optimization goal by optimizing the pores, rib geometry parameters, and layout parameters of impact holes / film holes of uniformly open porous foam ribs arranged around the film holes in the laminate structure. Figure 1 As shown, specifically including the following:

[0034] Step 1: Extract the minimum unit cooling structure of a double-walled turbine guide vane under real operating conditions; parameterize the porous foam rib plate cooling structure to obtain its characteristic geometric parameters. The microscopic topological cellular structure of the porous foam rib can be a hollow hexahedron with regular pores, a Kelvin tetradecahedron, or a spherical segment model.

[0035] Step 2: Select an optimizable characteristic geometric parameter from the characteristic geometric parameters as an optimized design variable, and set an upper and lower range of the design variable;

[0036] Step 3: Determine the optimization target of the porous foam ribbed plate composite cooling structure, change the design value within the upper and lower ranges of the design variables, and construct a test point sample space;

[0037] Among them, the maximum average comprehensive cooling efficiency and the minimum pressure loss coefficient C p As a multi-objective optimization function;

[0038] Step 4: Perform numerical calculations on the test points to obtain the multi-objective optimization parameter values at different sample points, and establish a proxy model between the multi-objective optimization parameter values and the geometric feature parameters based on the sample space;

[0039] By increasing the number of test sample points, performing numerical simulations and comparing the results with those predicted by the proxy model, the numerical accuracy of the proxy model is verified:

[0040] If the accuracy of the proxy model is less than the set value, the number of sample points is increased and the proxy model is rebuilt until the accuracy of the proxy model meets the design requirements;

[0041] Step 5: At the minimum pressure loss coefficient C p Less than or equal to the limit value and the maximum surface average comprehensive cooling efficiency Under the highest optimization goal, the agent model is used to search for the optimal solution using the NSGA-II non-dominated genetic multi-objective optimization algorithm to obtain the geometric parameter design values of the porous foam rib plate structure that meets the optimization goal, thereby obtaining the optimal porous foam rib plate cooling structure.

[0042] In some embodiments, the characteristic geometric parameters in step 1 include the porous foam rib porosity, pore density, rib height and rib spacing, impact holes and air film holes. In practice, the corresponding characteristic geometric parameters will be determined based on the selected microscopic topological cellular structure.

[0043] In some embodiments, in step 3, the maximum surface average integrated cooling efficiency The calculation formula is as follows:

[0044]

[0045] The calculation formula for the minimum pressure loss coefficient Cp is as follows:

[0046]

[0047] Where φ is the comprehensive cooling efficiency, T w,ex is the temperature of the outer surface of the air film plate, T g and T c are the temperatures of gas and air conditioning respectively; P imp,t and P film,t are the total pressures at the impact hole inlet and the film hole outlet, respectively.

[0048] In some embodiments, the specific method for obtaining the multi-objective optimization parameter values at different sample points in step 4 is:

[0049] Step 4.1, geometric modeling of the porous foam rib area and double-wall structure;

[0050] Step 4.2: Mesh the fluid domain (i.e., the impact cavity channel and the gas channel) and the solid domain (i.e., the porous ribs, the impact plate, and the air film plate) of the porous foam rib double-wall structure and perform local meshing near the wall and at the fluid-solid interface.

[0051] Step 4.3: Use a Reynolds-averaged method coupled with a turbulence model to solve the three-dimensional compressible fluid mass, momentum, and energy conservation equations and the three-dimensional heat conduction equation in the solid domain, thereby obtaining the flow and temperature field characteristics of the porous foam rib plate cooling structure under different characteristic geometric parameters (i.e., sample points);

[0052] For the porous foam rib region, porosity and pore density are the two most important parameters, significantly impacting flow and heat transfer. Generally speaking, at the same flow rate and porosity, as pore density increases (i.e., the thickness and distribution density of the porous skeleton increase), the turbulence effect of the porous rib region continues to increase, the intensity of convective heat transfer continues to increase, and cooling efficiency gradually improves, while also gradually increasing pressure loss.

[0053] Step 4.4: Post-process the obtained numerical calculation results to obtain the multi-objective optimization parameter values (such as the surface average comprehensive cooling efficiency and pressure loss coefficient value) of the porous foam rib plate structure at different sample points.

[0054] In some embodiments, the specific method of step 4.1 is to iteratively solve the porous skeleton parameters describing the porous foam ribs using set porosity and pore density values. For the spherical segment unit cell model, the parameters of the cell size and the diameter of the internal spheres of the porous foam rib unit cell model are determined for different porosity and pore density values. The pores are connected by cylindrical open channels, and the porosity is adjusted by varying the radius of the cylinder and the radius and center distance of adjacent spheres. The porous foam rib microstructure is generated using the foam dynamics software Surface Evolver. The porous foam ribs are obtained through structural arraying and scaling.

[0055] Example

[0056] This embodiment adopts a porous foam rib plate cooling structure design method for turbine blades, and its optimization objectives are as follows: Figure 2The porous foam rib plate cooling structure shown. The porous foam rib plate cooling structure includes multiple cooling units, and a cooling unit specifically includes an impact orifice plate 2 and an air film orifice plate 6 arranged in parallel and at intervals, both of which are quadrilateral plate structures, and impact channels are formed at the intervals. An impact hole 1 is a cylindrical hole, which is arranged at the center of the impact plate 2. The four air film hole channels 7 are all 1 / 4 cylindrical holes, which are arranged at the four vertices of the air film orifice plate 6. The air film hole 5 appears as four 1 / 4 cylindrical holes in a cooling unit. When a plurality of cooling units are combined, the four 1 / 4 cylindrical holes are combined to form a complete air film hole 5. Four spoiler columns 4 are connected and arranged between the impact orifice plate 2 and the air film orifice plate 6, and are evenly arranged around the impact hole 1. The impact orifice plate 2 serves as an air inlet plate, and the cold flow enters from the impact hole 1. The air film orifice plate 6 serves as an air outlet plate, and exhausts from the air film hole 5 to complete the cold air coverage.

[0057] The porous foam rib plate cooling structure is arranged in the mid-chord area of the blade.

[0058] The design method is as follows:

[0059] Step 1. Select the impact hole diameter d i , air film pore diameter d f , the diameter d of the porous spoiler column and the porosity of the porous spoiler column are taken as the structural parameters to be optimized.

[0060] Step 2: The maximum comprehensive cooling efficiency and minimum pressure loss of the porous foam rib plate cooling structure are taken as optimization goals.

[0061] Step 3: Generate 27 design points using the optimal Latin hypercube sampling method (OLHS) and calculate the objective function values of these points through RANS analysis.

[0062] variable Reference value / mm Maximum value / mm Minimum value / mm Impact hole diameter 5 10 1 Air film hole diameter 5 10 1 Diameter of porous spoiler column 5 10 1 Porosity of porous spoiler column 0.8 0.65 0.95

[0063] Step 4: The optimization process is carried out by the optimization platform (based on ISIGHT optimization software) using the NSGA-Ⅱ multi-objective optimization algorithm based on the Kriging method to obtain the Pareto optimal solution frontier.

[0064] Step 5: Analyze the Pareto front solution set for multi-objective optimization to assess the trade-offs between different design options. Based on the Pareto front solution set, assign weights to the optimization objectives of comprehensive cooling efficiency and pressure loss according to project requirements and priorities, and select the most appropriate solution for implementation based on actual needs.

[0065] The present invention adopts a multi-objective optimization method for porous foam rib layer structure based on an agent model, which can relatively quickly obtain the optimal design parameters of the cooling structure with high-efficiency cooling performance and low flow resistance characteristics within the design range, reduce the calculation cost required in the design, maximize the use of porous medium turbulent elements to enhance convective heat transfer and thermal conductivity characteristics, effectively regulate the cooling characteristics, temperature distribution uniformity and flow resistance characteristics of the layer cooling structure, and realize efficient design of the layer cooling structure. When applied to aircraft engine blades, it can achieve multiple advantages such as lower temperature and thermal stress levels and higher strength and durability.

[0066] This method replaces complex physical models with proxy models, enabling the evaluation of numerous design solutions in a relatively short period of time. This significantly improves the efficiency of the optimization process and reduces computational time and cost. The proxy model can maintain high prediction accuracy while reducing the high computational overhead associated with directly using high-precision simulation models, making the optimization results more reliable. This method is applicable to a variety of porous media structures, and optimization objectives (such as cooling effect and flow resistance) can be adjusted according to specific needs to achieve optimal overall performance. It can simultaneously consider multiple mutually constrained objectives (such as maximizing cooling efficiency and minimizing flow resistance) to find the optimal solution or Pareto front, providing decision makers with more options.

[0067] The NSGA-II algorithm used in this invention is an improved version of the non-dominated sorting genetic algorithm, a very popular and effective algorithm in the field of multi-objective optimization. It exhibits many advantages in solving multi-objective optimization problems and can be used in conjunction with surrogate models to further reduce computational costs and improve optimization efficiency. These advantages make it an ideal choice for solving such multi-objective optimization problems. Optimization problems for porous foam ribbed plate structures often have multiple local optimal solutions. The global search capability of the NSGA-II algorithm can effectively explore the solution space, avoid being trapped in local optima, and thus find the global optimal solution.

Claims

1. A method for designing a porous foam rib plate cooling structure for turbine blades, characterized in that: Includes the following: Step 1: Extract the minimum unit cooling structure of the double-wall configuration of the turbine guide blade under real working conditions, parameterize the porous foam rib plate cooling structure, and obtain its characteristic geometric parameters; The characteristic geometric parameters in step 1 include porous foam rib porosity, pore density, rib height and rib spacing, impact holes and air film holes; Step 2: Select an optimizable characteristic geometric parameter from the characteristic geometric parameters as an optimized design variable, and set an upper and lower range of the design variable; Step 3: Determine the optimization target of the porous foam ribbed plate composite cooling structure, change the design value within the upper and lower ranges of the design variables, and construct a test point sample space; Among them, the maximum average comprehensive cooling efficiency and the minimum pressure loss coefficient C p As a multi-objective optimization function; Step 4: Perform numerical calculations on the test points to obtain the multi-objective optimization parameter values at different sample points, and establish a proxy model between the multi-objective optimization parameter values and the geometric feature parameters based on the sample space; By increasing the number of test sample points, performing numerical simulations and comparing the results with those predicted by the proxy model, the numerical accuracy of the proxy model is verified: If the accuracy of the proxy model is less than the set value, the number of sample points is increased and the proxy model is rebuilt until the accuracy of the proxy model meets the design requirements; The specific method for obtaining the multi-objective optimization parameter values at different sample points in step 4 is: Step 4.1, geometric modeling of the porous foam rib area and double-wall structure; Step 4.2, meshing the fluid and solid domains of the porous foam rib double-wall structure and performing local densification near the wall and at the fluid-solid interface; Step 4.3: Use a Reynolds-averaged method coupled with a turbulence model to solve the three-dimensional compressible fluid mass, momentum, and energy conservation equations and the three-dimensional heat conduction equation in the solid domain, thereby obtaining the flow and temperature field characteristics of the porous foam rib plate cooling structure under different characteristic geometric parameters; Step 4.4, post-process the obtained numerical calculation results to obtain the multi-objective optimization parameter values of the porous foam ribbed plate structure at different sample points; Step 5: When the minimum pressure loss coefficient Cp is less than or equal to the limit value and the maximum surface average comprehensive cooling efficiency is achieved Under the highest optimization goal, the agent model and the NSGA-II non-dominated genetic multi-objective optimization algorithm are used to search for the optimal solution, and the geometric parameter design values of the porous foam rib plate structure that meet the optimization goal are obtained, thereby obtaining the optimal porous foam rib plate cooling structure.

2. The method for designing a porous foam rib plate cooling structure for a turbine blade according to claim 1, wherein: In step 3, the maximum surface average comprehensive cooling efficiency φ is calculated as follows: Minimum pressure loss coefficient C p The calculation formula is as follows: Where φ is the comprehensive cooling efficiency, T w,ex is the temperature of the outer surface of the air film plate, T g and T c are the temperatures of gas and air conditioning respectively; P imp,t and P film,t are the total pressures at the impact hole inlet and the film hole outlet, respectively.

3. The method for designing a porous foam rib plate cooling structure for a turbine blade according to claim 1, wherein: In step 4.1, the porous skeleton parameters describing the porous foam ribs are obtained by iteratively solving the set porosity and pore density values.

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