Design method and system for anti-deposition bionic structure of inner cavity of micro-channel cooling turbine blade

Abstract

The invention discloses a micro-channel cooling turbine blade inner cavity anti-deposition bionic structure design method and system, and relates to the field of turbine blade cooling of aero-engines. The problems of optimizing the wall cooling effect, flow resistance and calculation efficiency of the micro-channel structure are solved. The method comprises the steps that parameterization design is conducted on a bionic turbulent flow structure, and characteristic geometric parameters are obtained; establishing a micro-channel three-dimensional model of the bionic fish scale structure; screening the characteristic geometric parameters as design variables, and designing upper and lower intervals of the variables; taking heat exchange, pressure drop and particle deposition of the micro-channel as optimization targets, adjusting a design variable interval, and constructing a test sample space; performing numerical calculation by using the channel model to obtain a multi-objective optimization parameter value; establishing an agent model between the optimization parameter values and the geometric characteristic parameters; and optimizing by utilizing an agent model and a multi-objective optimization algorithm to obtain the optimal geometric parameters of the bionic fish scale turbulent flow structure, so that the efficient design of the micro-channel structure and the efficient utilization of the cold air consumption are realized.

Description

Technical Field

[0001] The present invention relates to the technical field of cooling turbine blades of aircraft engines, and in particular to a method for designing an anti-deposition bionic structure for an inner cavity of a turbine blade cooled by a micro-channel. Background Art

[0002] The power and efficiency of aircraft engines / gas turbines increase with increasing turbine inlet gas temperature. The turbine inlet temperature of advanced gas turbine engines continues to rise, with current turbine inlet temperatures exceeding 1850K, far exceeding the temperature limit (1150K) of the high-temperature alloys used to manufacture the blades. Therefore, efficient cooling measures are essential to ensure safe and reliable operation of turbine blades under high thermal loads.

[0003] The micro-channel heat exchange method can effectively thin the fluid boundary layer, thereby enhancing heat transfer. The heat transfer capacity in the turbulent area is particularly obvious. Under the same Reynolds number, as the equivalent diameter of the channel decreases, the channel surface heat transfer coefficient will be significantly improved compared to conventional large-scale channels. In order to address the problem that traditional large-scale cooling structures are difficult to meet the cooling needs of "blind spots" and "dead spots", relevant researchers have begun to apply micro-channels to the design of turbine blades for aircraft engines / gas turbines. Arranging a large number of tiny cooling channels on the inner wall of the blade close to the gas side can increase the surface heat transfer coefficient and heat transfer area, making the blade cooling more uniform, thereby significantly improving the thermal stress problem caused by uneven heat exchange in large-scale cooling methods, and improving the reliability and service life of turbine blades.

[0004] In traditional blade designs, flow-disrupting structures such as straight, oblique, and V-shaped ribs on the walls of internal cooling channels can effectively enhance the channel's convective heat transfer capacity, but they also increase the channel's flow resistance, potentially adversely affecting micro-channel applications. Dust and salt spray carried in the gas can also cause internal channel blockage, further exacerbating the adverse effects on channel flow resistance. Mechanistically, the extended surface formed by the ribs on the wall can be considered a "heat sink," absorbing heat flux from the high-temperature gas through solid heat conduction and convection with the fluid, thereby enhancing the channel's heat transfer efficiency. In nature, the skin and scales of numerous aquatic organisms, such as sharks and whales, have evolved to exhibit excellent self-cleaning and drag-reducing properties. With advances in processing technologies such as 3D printing, the use of biomimetic structures for drag reduction has great potential. Applying biomimetic structural design to the micro-channel design of aircraft engine / gas turbine blades can reduce channel flow resistance and enhance heat transfer, extending the blade's service life in extreme operating environments.

[0005] Ma Fuliang et al. introduced the drag reduction mechanism of shark shield scale structure in the “Research Status and Progress of Bionic Surface Drag Reduction” published in 2016: the surface of shark skin is arranged with scales and non-smooth shield scale structures similar to round valleys and forms a groove structure. When the fluid flows along the groove direction, the radial vortex can only have a small area of contact with the groove apex. At this time, the part below the groove apex will be blocked by viscosity during the flow process, the thickness of the viscous bottom layer becomes larger, and the flow is relatively more stable. Therefore, the existence of the groove structure significantly reduces the shear pressure on the inner wall of the groove. In addition, the existence of the shield scale structure can also block the lateral vortex and reduce the surface friction resistance. In the “Nature-inspired Inverted FishScale microscale passages for enhanced heat transfe” published in 2016, it was recorded that when the fish scale structure arranged in the microchannel has a blocking ratio (h / D h ) and the ratio of the flow length to the height (p / h) are different, the flow and heat transfer characteristics of the channel. Under the same Reynolds number, if p / h remains unchanged, the higher the blockage ratio of the fish scale structure, the greater the channel flow resistance and the greater the average Nusselt number of the wall; and when h / D h When the p / h value of the fish scale structure increases, the channel flow resistance becomes smaller and the average Nusselt number of the wall becomes smaller.

[0006] The authors of the aforementioned paper focused on the influence of two geometric parameters of the biomimetic structure on the flow and heat transfer characteristics of the channel. However, determining the optimal geometric parameters requires extensive operating condition calculations. Furthermore, in the design of biomimetic flow-inspired channels, the layout and density of the fish-scale structures are also important design parameters. Different parameters affect flow and heat transfer in different ways, making exhaustive design methods inefficient and difficult to apply to engineering design. Summary of the Invention

[0007] The present invention addresses the problems of insufficient and uneven wall cooling and large flow resistance in existing micro-channel structures, as well as the low efficiency caused by the large number of working condition calculation results required to determine the optimal geometric parameters. A method for designing an anti-deposition biomimetic structure for the inner cavity of a micro-channel-cooled turbine blade is proposed. The method comprises:

[0008] S1: Obtain basic geometric parameters, perform parametric design on the bionic spoiler structure, and obtain characteristic geometric parameters;

[0009] S2: Based on the set geometric parameters and the dimensions of the microchannels arranged on the turbine blades under real working conditions, a three-dimensional model of the microchannels of the bionic fish scale structure is established;

[0010] S3: Select characteristic geometric parameters as optimized design variables and preset the upper and lower ranges of the optimized design variables;

[0011] S4: Taking the heat transfer, pressure drop and particle deposition characteristics of the microchannel as the optimization objectives, adjust the variation range of the selected optimized design variables and construct the experimental sample space;

[0012] S5: A channel model is established based on the geometric parameters of each test point in the test sample space, and numerical calculations are performed to obtain the multi-objective optimization parameter values under different sample points. Based on the test sample space, a proxy model between the multi-objective optimization parameter values and the geometric feature parameters is established;

[0013] S6: When the channel flow resistance and wall deposition rate are less than or equal to the limit values, and the maximum surface average Nusselt number is the highest optimization goal, the surrogate model and multi-objective optimization algorithm are used to find the optimal geometric parameter design values of the micro-channel bionic spoiler structure that meet the optimization goals, thereby obtaining the optimal geometric parameters of the bionic fish scale spoiler structure.

[0014] Furthermore, a preferred embodiment is proposed, wherein the basic geometric parameters include the height, flow length, and span length of the bionic structure; and the characteristic geometric parameters include the blockage ratio, the ratio of flow length to height, and the arrangement density.

[0015] Furthermore, a preferred embodiment is proposed, wherein the size of the microchannel is 100 μm-1 mm.

[0016] Furthermore, a preferred method is proposed, wherein the heat exchange, pressure drop, and particle deposition characteristics of the microchannel are used as optimization targets, including:

[0017]

[0018] Where Nu is the average Nusselt number on the wall, h is the convective heat transfer coefficient, and D h is the equivalent diameter of the channel, λ is the thermal conductivity, f is the friction factor, ΔP is the channel pressure drop, ρ is the fluid density, U is the channel inlet velocity, L is the channel length, η is the particle deposition rate, m dep is the mass of particles deposited on the wall, m in is the mass of particles put into the inlet.

[0019] Furthermore, a preferred method is proposed, wherein the channel model is established based on the geometric parameters of each test point in the test sample space, and numerical calculation is performed, including:

[0020]

[0021] Where ui is the velocity component of the fluid in the i direction, t is the fluid flow time, xi is the component of the fluid displacement along the i direction, p is the pressure, μ is the dynamic viscosity, u kis the velocity component of the fluid in the k direction, x k is the component of fluid displacement along the k direction, is the operator symbol of partial derivative, x j is the component of fluid displacement along the j direction, f i is the component of the volume force per unit mass of fluid in the i direction, and e is the energy per unit mass of fluid.

[0022] Furthermore, a preferred method is proposed, wherein obtaining multi-objective optimization parameter values at different sample points includes:

[0023] Conduct geometric modeling of bionic fish scale spoiler structures and microchannels;

[0024] The fluid domain of the microchannel of the bionic fish scale structure is meshed and local densification is performed near the wall and in the area where the bionic structure is arranged;

[0025] The mass, momentum, and energy conservation equations of a three-dimensional compressible fluid are solved by using a Reynolds-averaged method coupled with a turbulence model. The flow and temperature field characteristics of a microchannel with a biomimetic perturbation structure under different characteristic geometric parameters are obtained.

[0026] The numerical calculation results are post-processed to obtain the multi-objective optimization parameter values of the bionic spoiler structure at different sample points.

[0027] Furthermore, a preferred method is proposed, in which step S5 also includes: adding test sample points, performing numerical simulation and comparing the results with those predicted by the proxy model to verify the numerical accuracy of the proxy model; if the calculation results of the proxy model do not reach the set accuracy, increasing the number of sample points and re-establishing the proxy model until the accuracy of the proxy model meets the design requirements.

[0028] Based on the same inventive concept, the present invention also proposes a biomimetic structure design system for anti-deposition in the inner cavity of a micro-channel-cooled turbine blade, the system comprising:

[0029] The characteristic geometric parameter acquisition unit is used to obtain basic geometric parameters: perform parametric design on the bionic spoiler structure and obtain characteristic geometric parameters;

[0030] A micro-channel 3D model building unit is used to build a micro-channel 3D model of a bionic fish scale structure based on the set geometric parameters and the dimensions of the micro-channels arranged on the turbine blades under actual working conditions;

[0031] The interval preset unit is used to select characteristic geometric parameters as optimized design variables and preset the upper and lower intervals of the optimized design variables;

[0032] The optimization unit is used to adjust the variation range of the selected optimized design variables and construct the test sample space by taking the heat transfer, pressure drop and particle deposition characteristics of the microchannel as the optimization targets;

[0033] The proxy model construction unit is used to establish a channel model based on the geometric parameters of each test point in the test sample space, perform numerical calculations, obtain multi-objective optimization parameter values under different sample points, and establish a proxy model between the multi-objective optimization parameter values and the geometric feature parameters based on the test sample space;

[0034] The geometric parameter acquisition unit of the bionic fish scale spoiler structure is used to use the proxy model and multi-objective optimization algorithm to search for the optimal value when the channel flow resistance and wall deposition rate are less than or equal to the limit value and the maximum surface average Nusselt number is the highest optimization goal, so as to obtain the geometric parameter design values of the micro-channel bionic spoiler structure that meet the optimization goals, thereby obtaining the optimal geometric parameters of the bionic fish scale spoiler structure.

[0035] Based on the same inventive concept, the present invention also proposes a computer device, including a memory and a processor, wherein a computer program is stored in the memory. When the processor runs the computer program stored in the memory, the processor executes a method for designing an anti-deposition bionic structure for the inner cavity of a micro-channel cooled turbine blade according to any one of the above items.

[0036] Based on the same inventive concept, the present invention also proposes a computer-readable storage medium, characterized in that a computer program is stored on the computer-readable storage medium, and when the computer program is run by a processor, the steps of the method for designing an anti-deposition bionic structure for the inner cavity of a micro-channel cooled turbine blade are executed as described in any one of the above.

[0037] The present invention is beneficial in that:

[0038] The present invention provides a new approach for designing a micro-channel cooling structure for turbine blades that enhances heat transfer based on a bionic fish-scale structure. Compared to the general multi-parameter exhaustive method, the bionic fish-scale structure multi-objective optimization method based on a proxy model can more quickly obtain the optimal geometric design parameters of a fish-scale structure with high cooling performance, low flow resistance, and low particle deposition within the design range, reducing the computational cost required for parameter design. It maximizes the use of the bionic fish-scale structure to enhance convective heat transfer and thermal conductivity, effectively regulating the cooling characteristics, temperature distribution uniformity, and flow resistance characteristics of the micro-channel cooling structure. At the same time, it avoids problems such as excessive drag loss and lack of cold air flow caused by unreasonable settings of the geometric parameters and number of bionic spoiler structures, thereby achieving efficient design of the micro-channel cooling structure. Application to aircraft engine blades can achieve multiple advantages, including lower temperatures and thermal stress levels, higher strength, and durability. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] Figure 1 A schematic diagram and a simplified model diagram of the arrangement of the micro-channel portion of a turbine blade with a bionic fish-scale structure according to the eleventh embodiment;

[0040] Figure 2 This is a schematic diagram of the micro-channel cooling principle of the bionic fish scale structure according to the eleventh embodiment;

[0041] Figure 3 Schematic diagram of the main geometric parameters of the bionic fish scale spoiler structure according to the eleventh embodiment, wherein H f is the side width, S f is the side length, W f is the front width, V f is the flow length;

[0042] Figure 4 This is a flowchart of the multi-objective optimization design of a microchannel according to the eleventh embodiment;

[0043] Figure 5 Schematic diagram of the modeling process of the bionic fish scale spoiler structure construction described in the eleventh embodiment. DETAILED DESCRIPTION

[0044] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in combination with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments.

[0045] Embodiment 1: This embodiment provides a method for designing an anti-deposition biomimetic structure for a micro-channel cooling turbine blade inner cavity, the method comprising:

[0046] S1: Obtain basic geometric parameters, perform parametric design on the bionic spoiler structure, and obtain characteristic geometric parameters;

[0047] S2: Based on the set geometric parameters and the dimensions of the microchannels arranged on the turbine blades under real working conditions, a three-dimensional model of the microchannels of the bionic fish scale structure is established;

[0048] S3: Select characteristic geometric parameters as optimized design variables and preset the upper and lower ranges of the optimized design variables;

[0049] S4: Taking the heat transfer, pressure drop and particle deposition characteristics of the microchannel as the optimization objectives, adjust the variation range of the selected optimized design variables and construct the experimental sample space;

[0050] S5: A channel model is established based on the geometric parameters of each test point in the test sample space, and numerical calculations are performed to obtain the multi-objective optimization parameter values under different sample points. Based on the test sample space, a proxy model between the multi-objective optimization parameter values and the geometric feature parameters is established;

[0051] S6: When the channel flow resistance and wall deposition rate are less than or equal to the limit values, and the maximum surface average Nusselt number is the highest optimization goal, the surrogate model and multi-objective optimization algorithm are used to find the optimal geometric parameter design values of the micro-channel bionic spoiler structure that meet the optimization goals, thereby obtaining the optimal geometric parameters of the bionic fish scale spoiler structure.

[0052] The method proposed in this embodiment optimizes the flow characteristics of microchannels through the design of a bionic fish-scale structure. This effectively disturbs the fluid flow, improves the efficiency of heat transfer from the wall, and thus enhances the cooling efficiency of turbine blades. Compared with traditional cooling methods, the bionic fish-scale structure can more evenly distribute the cooling fluid and avoid local overheating. By optimizing the geometric parameters of the bionic turbulent structure, the pressure drop (flow resistance) during the flow can be effectively reduced, improving the overall performance of the flow within the channel. This is particularly important for cooling the inner cavity of turbine blades, as reducing flow resistance can increase the flow velocity of the cooling fluid, thereby enhancing heat exchange efficiency. The bionic fish-scale structure design can improve the turbulent characteristics of the flow, increase the contact opportunities between the fluid and the wall, slow the particle deposition process, and reduce the impact of deposits on the cooling effect. Reduced deposition also helps to extend the service life of the turbine blades. This method uses a multi-objective optimization algorithm to comprehensively consider multiple optimization objectives, including flow heat transfer efficiency, pressure drop, and particle deposition. This optimized design not only achieves optimal thermal performance but also meets the engineering constraints such as pressure drop and deposition rate, thus avoiding the compromises of traditional design methods. By combining surrogate models (such as those based on the experimental sample space) with multi-objective optimization algorithms, the computational overhead associated with a large number of operating condition calculations can be effectively reduced, improving the efficiency of the design process. This approach avoids the inefficiency of requiring a large number of operating condition calculations in traditional design, resulting in more efficient and accurate designs.

[0053] Implementation method 2. This implementation method further limits the design method of anti-deposition bionic structure for the inner cavity of a micro-channel cooled turbine blade described in implementation method 1. The basic geometric parameters include the height, flow length, and span length of the bionic structure; the characteristic geometric parameters include the blockage ratio, the ratio of flow length to height, and the arrangement density.

[0054] The biomimetic structure in this embodiment effectively controls the deposition of fluid within the turbine blade cavity. By optimizing the biomimetic structure's geometric parameters (such as the blockage ratio, the flow length-to-height ratio, and the arrangement density), it effectively inhibits the formation of deposits, reducing the blockage and efficiency loss of cooling channels caused by deposit accumulation. In particular, by adjusting the fluid flow pattern, the retention of deposits in the cooling channels is reduced, further improving the operational reliability of the blade.

[0055] Embodiment 3: This embodiment further limits the method for designing an anti-deposition bionic structure for the inner cavity of a micro-channel-cooled turbine blade described in embodiment 1, wherein the size of the micro-channel is 100 μm-1 mm.

[0056] Embodiment 4: This embodiment further defines the method for designing an anti-deposition biomimetic structure for a microchannel-cooled turbine blade inner cavity described in Embodiment 1. The optimization targets are heat transfer, pressure drop, and particle deposition characteristics of the microchannel, including:

[0057]

[0058] Where Nu is the average Nusselt number on the wall, h is the convective heat transfer coefficient, and D h is the equivalent diameter of the channel, λ is the thermal conductivity, f is the friction factor, ΔP is the channel pressure drop, ρ is the fluid density, U is the channel inlet velocity, L is the channel length, η is the particle deposition rate, m dep is the mass of particles deposited on the wall, m in is the mass of particles put into the inlet.

[0059] Embodiment 5. This embodiment further defines the method for designing a biomimetic structure for anti-deposition in the inner cavity of a micro-channel-cooled turbine blade described in Embodiment 4. The channel model is established based on the geometric parameters of each test point in the test sample space, and numerical calculations are performed, including:

[0060]

[0061] Where ui is the velocity component of the fluid in the i direction, t is the fluid flow time, xi is the component of the fluid displacement along the i direction, p is the pressure, μ is the dynamic viscosity, u k is the velocity component of the fluid in the k direction, x k is the component of fluid displacement along the k direction, is the operator symbol of partial derivative, x j is the component of fluid displacement along the j direction, f i is the component of the volume force per unit mass of fluid in the i direction, and e is the energy per unit mass of fluid.

[0062] Embodiment 6: This embodiment further limits the method for designing an anti-deposition bionic structure for the inner cavity of a micro-channel-cooled turbine blade described in Embodiment 1. The method of obtaining multi-objective optimization parameter values at different sample points includes:

[0063] Conduct geometric modeling of bionic fish scale spoiler structures and microchannels;

[0064] The fluid domain of the microchannel of the bionic fish scale structure is meshed and local densification is performed near the wall and in the area where the bionic structure is arranged;

[0065] The mass, momentum, and energy conservation equations of a three-dimensional compressible fluid are solved by using a Reynolds-averaged method coupled with a turbulence model. The flow and temperature field characteristics of a microchannel with a biomimetic perturbation structure under different characteristic geometric parameters are obtained.

[0066] The numerical calculation results are post-processed to obtain the multi-objective optimization parameter values of the bionic spoiler structure at different sample points.

[0067] In this embodiment, geometric modeling and meshing of the microchannel fluid domain, particularly near the walls and in areas where biomimetic structures are deployed, ensure computational accuracy, particularly in areas of fluid-wall interaction. This allows for more accurate capture of fluid flow and temperature field variations, providing a reliable numerical basis for design optimization. The Reynolds-averaged turbulence model employed for calculations effectively handles complex turbulent flow conditions, particularly for high-speed flows or flows with high Reynolds numbers. A coupled turbulence model provides more accurate predictions for blade cooling design, accounting for the effects of turbulence on heat conduction and flow. This multi-objective optimization approach simultaneously considers multiple design objectives, such as the flow field and temperature characteristics of the fluid, as well as the cooling effect of the turbine blade. This allows the design to achieve a balance between multiple aspects, optimizing cooling efficiency while avoiding excessive pressure drop or inappropriate structural design. Post-processing of the numerical results allows for in-depth analysis of the flow and temperature field variations at different sample points, further analyzing the impact of the biomimetic structure on flow and heat transfer, and obtaining more precise optimization parameter values.

[0068] Implementation method seven. This implementation method further limits the anti-deposition bionic structure design method for the inner cavity of a micro-channel cooled turbine blade described in implementation method one. Step S5 also includes: adding test sample points, performing numerical simulation and comparing with the results predicted by the proxy model to verify the numerical accuracy of the proxy model; if the calculation results of the proxy model do not reach the set accuracy, increasing the number of sample points and re-establishing the proxy model until the accuracy of the proxy model meets the design requirements.

[0069] In this embodiment, by adding test sample points and comparing numerical simulation results with the predicted results of the proxy model, the numerical accuracy of the proxy model can be verified in a timely manner. This verification process ensures that the calculated results of the proxy model are more accurate, thereby avoiding the risk of designing or analyzing based on an inaccurate model. If the proxy model's accuracy does not meet the set requirements, the proxy model can be continuously optimized by adding sample points and rebuilding the model, so that it can provide more reliable prediction results during the design process. This iterative optimization mechanism can reduce design errors and improve design efficiency. Traditional numerical simulation methods generally require high computing resources and time, especially for complex engineering problems. By using a proxy model, the number and amount of computation required for direct complex numerical simulations can be significantly reduced, thereby reducing computational costs. Furthermore, by continuously optimizing the proxy model, the amount of computation can be reduced without sacrificing accuracy. The design of the inner cavity of a microchannel-cooled turbine blade involves very complex flow and heat conduction phenomena, and the use of a proxy model can effectively simulate these complex physical processes. Moreover, with the continuous optimization of the proxy model's accuracy, it can better adapt to complex design requirements and ensure higher performance in the final design.

[0070] Furthermore, in this embodiment, by gradually adding test sample points and comparing them with simulation results, not only can the existing design be optimized, but the model can also be continuously expanded and updated according to new experimental data, thereby enhancing the flexibility and scalability of the method.

[0071] Embodiment 8: A system for designing a biomimetic structure for anti-deposition in the inner cavity of a micro-channel-cooled turbine blade according to this embodiment includes:

[0072] The characteristic geometric parameter acquisition unit is used to obtain basic geometric parameters: perform parametric design on the bionic spoiler structure and obtain characteristic geometric parameters;

[0073] A micro-channel 3D model building unit is used to build a micro-channel 3D model of a bionic fish scale structure based on the set geometric parameters and the dimensions of the micro-channels arranged on the turbine blades under actual working conditions;

[0074] The interval preset unit is used to select characteristic geometric parameters as optimized design variables and preset the upper and lower intervals of the optimized design variables;

[0075] The optimization unit is used to adjust the variation range of the selected optimized design variables and construct the test sample space by taking the heat transfer, pressure drop and particle deposition characteristics of the microchannel as the optimization targets;

[0076] The proxy model construction unit is used to establish a channel model based on the geometric parameters of each test point in the test sample space, perform numerical calculations, obtain multi-objective optimization parameter values under different sample points, and establish a proxy model between the multi-objective optimization parameter values and the geometric feature parameters based on the test sample space;

[0077] The geometric parameter acquisition unit of the bionic fish scale spoiler structure is used to use the proxy model and multi-objective optimization algorithm to search for the optimal value when the channel flow resistance and wall deposition rate are less than or equal to the limit value and the maximum surface average Nusselt number is the highest optimization goal, so as to obtain the geometric parameter design values of the micro-channel bionic spoiler structure that meet the optimization goals, thereby obtaining the optimal geometric parameters of the bionic fish scale spoiler structure.

[0078] Embodiment 9. A computer device described in this embodiment includes a memory and a processor, wherein a computer program is stored in the memory. When the processor runs the computer program stored in the memory, the processor executes a method for designing an anti-deposition bionic structure for the inner cavity of a micro-channel cooled turbine blade according to any one of embodiments 1 to 7.

[0079] Embodiment 10. A computer-readable storage medium described in this embodiment stores a computer program, which, when executed by a processor, executes the steps of a method for designing an anti-deposition bionic structure for the inner cavity of a micro-channel cooled turbine blade as described in any one of embodiments 1 to 7.

[0080] Implementation method 11, see Figure 1 、 Figure 2 、 Figure 3 、 Figure 4 and Figure 5 This embodiment provides a specific example of the anti-deposition bionic structure design method for the micro-channel cooling turbine blade cavity described in embodiment 1, and is also used to explain embodiments 2 to 7. Specifically:

[0081] A method for designing a bionic structure for anti-deposition in the inner cavity of a micro-channel cooling turbine blade is proposed. The method comprises the following steps: a bionic fish scale structure is arranged on both sides of the micro-channel structure. The bionic fish scale spoiler structure is parameterized to obtain its characteristic geometric parameters (reference Figure 3 , blocking ratio (h / D h ), flow length to height ratio (p / h) and arrangement density and other geometric parameters); within the allowable range of geometric parameters, change the geometric parameter design value to construct the test point sample space. By modifying the fish scale structure blocking ratio (h / D h), the ratio of flow length to height (p / h), and the arrangement density are used to obtain different geometric parameters of the perturbation structure in the microchannel. Geometric modeling and meshing are then performed to solve the three-dimensional compressible flow and heat transfer characteristic equations of the microchannel structure. The surface average Nusselt number, pressure loss coefficient, and particle deposition rate of the microchannel structure at different sample points are obtained. A proxy model is established between the surface heat transfer coefficient, pressure loss characteristics, wall deposition characteristics, and geometric parameters of the microchannel structure. Numerical simulations are continued to be performed with more test sample points, and the results are verified with the predicted results of the proxy model. If the accuracy of the proxy model is less than the set index, the number of sample points is increased in the sample space and the proxy model is re-established until the accuracy of the proxy model meets the design requirements. Furthermore: with the flow resistance loss being less than or equal to the limit value, the wall particle deposition rate being the lowest, and the channel wall average Nusselt number being the highest as the final optimization goal, a multi-objective optimization algorithm is used to search for the optimal solution and obtain the geometric parameter design values of the bionic fish scale perturbation structure that meet the optimization goals. This method can maximize the use of bionic fish-scale spoiler structures to enhance convective heat transfer and thermal conductivity, effectively regulate the cooling, deposition, and flow resistance characteristics of microchannels, and achieve efficient design of microchannel structures and efficient utilization of cooling air. The specific steps are as follows:

[0082] Step 1: Obtain basic geometric parameters (i.e., height h, streamwise length p, and spanwise length L of the bionic structure): perform parameterized design on the bionic spoiler structure (obtain characteristic geometric parameters (= blocking ratio (h / D h ), flow length to height ratio (p / h) and arrangement density), modeled using professional 3D CAD design software NX12.0);

[0083] Step 2: Based on the geometric parameters set in step 1 and the dimensions of the microchannels arranged on the turbine blade under actual operating conditions (100 μm-1 mm), a three-dimensional model of the microchannels arranged with the bionic fish scale structure is established;

[0084] Step 3: From the characteristic geometric parameters in step 1, select the characteristic geometric parameters that can be optimized as the optimized design variables (the characteristic geometric parameters in step 1, namely: blocking ratio (h / D h ), flow length to height ratio (p / h) and arrangement density), giving the upper and lower ranges of the design variables.

[0085] Step 4: Determine the heat transfer, pressure drop, and particle deposition characteristics of the microchannel as the optimization target, change the variation range of the characteristic geometric parameters selected for optimization in step 3, and construct the experimental sample space.

[0086] Among them, the average Nusselt number, friction factor and particle deposition rate of the wall surface of the bionic structure are used as multi-objective optimization functions.

[0087]

[0088] Where h is the convective heat transfer coefficient, D h is the equivalent diameter of the channel, λ is the thermal conductivity; m dep and m in are the mass of particles deposited on the wall and the mass of particles input at the inlet, respectively. ΔP is the channel pressure drop, ρ is the fluid density, U is the channel inlet velocity, and L is the channel length.

[0089] Step 5: Perform numerical calculations on the channel model established based on the geometric parameters of each test point. The gas phase results are obtained based on CFD calculations, including:

[0090] Continuity equation:

[0091]

[0092] Momentum equation:

[0093]

[0094] Energy equation:

[0095]

[0096] The particle phase uses Newton's law of motion to calculate the motion trajectory) and obtains multi-objective optimization parameter values at different sample points, including:

[0097] Step 5.1: Geometric modeling of the bionic fish scale spoiler structure and microchannel.

[0098] According to the design geometric parameters of the fish scale structure, the bionic fish scale structure (such as Figure 5 As shown), the structure array is then arranged on the wall of the microchannel (as shown Figure 2 shown).

[0099] Step 5.2: Mesh the fluid domain where the microchannel of the bionic fish scale structure is arranged and perform local encryption processing near the wall and the area where the bionic structure is arranged.

[0100] Step 5.3: Use the Reynolds average method and couple the turbulence model to solve the three-dimensional compressible fluid mass, momentum, and energy conservation equations to obtain the flow field and temperature field characteristics in the microchannel of the bionic perturbation structure under different characteristic geometric parameters (sample points).

[0101] For the bionic fish scale structure, its height ratio and length ratio are the two most important parameters, which have a great influence on flow and heat transfer. Generally speaking, under the same Reynolds number conditions, if p / h remains unchanged, the higher the blockage ratio of the fish scale structure, the greater the channel flow resistance and the greater the average Nusselt number of the wall surface; and when h / Dh When the p / h value of the fish scale structure increases, the channel flow resistance becomes smaller and the average Nusselt number of the wall becomes smaller.

[0102] Step 5.4: Post-process the numerical calculation results to obtain the multi-objective optimization parameter values of the bionic spoiler structure at different sample points (including the surface average Nusselt number, friction factor, and particle deposition rate);

[0103] According to the experimental sample space, a proxy model between multi-objective optimization parameter values and geometric feature parameters is established;

[0104] By increasing the number of test sample points, conducting numerical simulations and comparing the results with those predicted by the proxy model, the numerical accuracy of the proxy model is verified.

[0105] If the calculation results of the proxy model do not meet the set accuracy (the error accuracy depends on the design requirements, and the effect is better within 5%. When it is difficult to meet the requirements, the error within 10% is also acceptable), the number of sample points is increased and the proxy model is re-established until the accuracy of the proxy model meets the design requirements.

[0106] The specific method for obtaining the multi-objective optimization parameter values at different sample points is:

[0107] Step 6: When the channel flow resistance and wall deposition rate are less than or equal to the limit values, and the maximum surface average Nusselt number is the highest optimization goal, the agent model and multi-objective optimization algorithm (such as NSGA-II non-dominated genetic algorithm) are used to search for the optimal geometric parameter design values of the micro-channel bionic spoiler structure that meets the optimization goals, thereby obtaining the optimal geometric parameters of the bionic fish scale spoiler structure.

[0108] Although the preferred embodiments of the present disclosure have been described, those skilled in the art may make additional changes and modifications to these embodiments once they have learned the basic creative concepts. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present disclosure.

[0109] Obviously, those skilled in the art may make various changes and modifications to the present disclosure without departing from the spirit and scope of the present disclosure. Thus, if these modifications and variations of the present disclosure fall within the scope of the claims of the present disclosure and their equivalents, the present disclosure is intended to include these modifications and variations.

[0110] Those skilled in the art will appreciate that embodiments of the present disclosure may be provided as methods, systems, or computer program products. Thus, the present disclosure may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware. Furthermore, the present disclosure may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0111] The present disclosure is described with reference to flowcharts and / or block diagrams of methods, devices (systems) and computer program products according to embodiments of the present disclosure. It should be understood that each process and / or block in the flowchart and / or block diagram and the combination of processes and / or blocks in the flowchart and / or block diagram can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 a process or multiple processes and / or boxes Figure 1 These computer program instructions can also be stored in a computer-readable memory that can guide a computer or other programmable data processing device to work in a specific way, so that the instructions stored in the computer-readable memory produce a product including the instruction device, which implements the function specified in the process. Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0112] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0113] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present disclosure and are not intended to limit its scope of protection. Although the present disclosure has been described in detail with reference to the above embodiments, ordinary technicians in the relevant field should understand that after reading the present disclosure, those skilled in the art can still make various changes, modifications or equivalent substitutions to the specific implementation methods of the invention, but these changes, modifications or equivalent substitutions are all within the scope of protection of the disclosed claims.

Claims

1. A method for designing an anti-deposition bionic structure for the inner cavity of a micro-channel-cooled turbine blade, characterized in that: The method comprises: S1: Obtain basic geometric parameters, perform parametric design on the bionic spoiler structure, and obtain characteristic geometric parameters; S2: Based on the set geometric parameters and the dimensions of the microchannels arranged on the turbine blades under real working conditions, a three-dimensional model of the microchannels of the bionic fish scale structure is established; S3: Select characteristic geometric parameters as optimized design variables and preset the upper and lower ranges of the optimized design variables; S4: Taking the heat transfer, pressure drop and particle deposition characteristics of the microchannel as the optimization objectives, adjust the variation range of the selected optimized design variables and construct the experimental sample space; S5: A channel model is established based on the geometric parameters of each test point in the test sample space, and numerical calculations are performed to obtain the multi-objective optimization parameter values under different sample points. Based on the test sample space, a proxy model between the multi-objective optimization parameter values and the geometric feature parameters is established; S6: When the channel flow resistance and wall deposition rate are less than or equal to the limit values, and the maximum surface average Nusselt number is the highest optimization goal, the surrogate model and multi-objective optimization algorithm are used to find the optimal geometric parameter design values of the micro-channel bionic spoiler structure that meet the optimization goals, thereby obtaining the optimal geometric parameters of the bionic fish scale spoiler structure.

2. The method for designing an anti-deposition bionic structure for the inner cavity of a micro-channel-cooled turbine blade according to claim 1, characterized in that: The basic geometric parameters include the height, flow length, and span length of the bionic structure; the characteristic geometric parameters include the blockage ratio, the ratio of flow length to height, and the arrangement density.

3. The method for designing an anti-deposition bionic structure for the inner cavity of a micro-channel-cooled turbine blade according to claim 1, characterized in that: The size of the microchannel is 100 μm-1 mm.

4. The method for designing an anti-deposition bionic structure for the inner cavity of a micro-channel-cooled turbine blade according to claim 1, characterized in that: The optimization targets are heat transfer, pressure drop, and particle deposition characteristics of microchannels, including: Where Nu is the average Nusselt number on the wall, h is the convective heat transfer coefficient, and D h is the equivalent diameter of the channel, λ is the thermal conductivity, f is the friction factor, ΔP is the channel pressure drop, ρ is the fluid density, U is the channel inlet velocity, L is the channel length, η is the particle deposition rate, m dep is the mass of particles deposited on the wall, m in is the mass of particles put into the inlet.

5. The method for designing an anti-deposition bionic structure for the inner cavity of a micro-channel-cooled turbine blade according to claim 4, characterized in that: The channel model established based on the geometric parameters of each test point in the test sample space and the numerical calculation are performed, including: Among them, u i is the velocity component of the fluid in the i direction, t is the fluid flow time, x i is the component of fluid displacement along the i direction, p is pressure, μ is dynamic viscosity, u k is the velocity component of the fluid in the k direction, x k is the component of fluid displacement along the k direction, is the operator symbol of partial derivative, x j is the component of fluid displacement along the j direction, f i is the component of the volume force per unit mass of fluid in the i direction, and e is the energy per unit mass of fluid.

6. The method for designing an anti-deposition bionic structure for the inner cavity of a micro-channel-cooled turbine blade according to claim 1, characterized in that: The obtaining of multi-objective optimization parameter values at different sample points includes: Conduct geometric modeling of bionic fish scale spoiler structures and microchannels; The fluid domain of the microchannel of the bionic fish scale structure is meshed and local densification is performed near the wall and in the area where the bionic structure is arranged; The mass, momentum, and energy conservation equations of a three-dimensional compressible fluid are solved by using a Reynolds-averaged method coupled with a turbulence model. The flow and temperature field characteristics of a microchannel with a biomimetic perturbation structure under different characteristic geometric parameters are obtained. The numerical calculation results are post-processed to obtain the multi-objective optimization parameter values of the bionic spoiler structure at different sample points.

7. The method for designing an anti-deposition bionic structure for the inner cavity of a micro-channel-cooled turbine blade according to claim 1, characterized in that: Step S5 also includes: adding test sample points, performing numerical simulation and comparing the results with those predicted by the proxy model to verify the numerical accuracy of the proxy model; if the calculation results of the proxy model do not meet the set accuracy, increasing the number of sample points and re-establishing the proxy model until the accuracy of the proxy model meets the design requirements.

8. A micro-channel cooling turbine blade cavity anti-deposition bionic structure design system, characterized by: The system comprises: The characteristic geometric parameter acquisition unit is used to obtain basic geometric parameters: perform parametric design on the bionic spoiler structure and obtain characteristic geometric parameters; A micro-channel 3D model building unit is used to build a micro-channel 3D model of a bionic fish scale structure based on the set geometric parameters and the dimensions of the micro-channels arranged on the turbine blades under actual working conditions; The interval preset unit is used to select characteristic geometric parameters as optimized design variables and preset the upper and lower intervals of the optimized design variables; The optimization unit is used to adjust the variation range of the selected optimized design variables and construct the test sample space by taking the heat transfer, pressure drop and particle deposition characteristics of the microchannel as the optimization targets; The proxy model construction unit is used to establish a channel model based on the geometric parameters of each test point in the test sample space, perform numerical calculations, obtain multi-objective optimization parameter values under different sample points, and establish a proxy model between the multi-objective optimization parameter values and the geometric feature parameters based on the test sample space; The geometric parameter acquisition unit of the bionic fish scale spoiler structure is used to use the proxy model and multi-objective optimization algorithm to search for the optimal value when the channel flow resistance and wall deposition rate are less than or equal to the limit value and the maximum surface average Nusselt number is the highest optimization goal, so as to obtain the geometric parameter design values of the micro-channel bionic spoiler structure that meet the optimization goals, thereby obtaining the optimal geometric parameters of the bionic fish scale spoiler structure.

9. A computer device, characterized in that: The method comprises a memory and a processor, wherein a computer program is stored in the memory. When the processor runs the computer program stored in the memory, the processor executes a method for designing an anti-deposition bionic structure for the inner cavity of a micro-channel-cooled turbine blade according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that The computer-readable storage medium stores a computer program, which, when executed by a processor, executes the steps of a method for designing an anti-deposition bionic structure for an inner cavity of a micro-channel-cooled turbine blade according to any one of claims 1 to 7.

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