Grid rudder optimization design method based on sub-grid flow parameters

Abstract

A grid rudder optimization design method based on sub-grid flow parameters is applied to grid rudder pneumatic control surface pneumatic design of scenes such as a carrier rocket one-sub-stage reuse reentry process and cruise flight, rapid design of a high-performance and high-control-efficiency grid rudder is achieved in the pneumatic layout design process of overall design, and the design efficiency of the grid rudder is improved. Comprising the following steps: selecting a plurality of grid rudder grids as grid objects; taking the grid object as a research object, selecting different pneumatic optimization and multidisciplinary optimization methods according to design requirements and optimization objectives, and carrying out grid object optimization by taking design parameters with optimal characteristics under a preset requirement framework as objectives to obtain optimized appearance parameters; according to the balancing and control requirements of the overall design of the rocket body, on the basis of the optimized appearance parameters, the number of needed grids is calculated according to the total normal force coefficient requirement needed by grid rudder control, and a grid rudder design scheme is formed.

Description

Technical Field

[0001] This invention relates to a grid fin optimization design method based on sub-grid flow parameters, which is applied to the aerodynamic design of grid fin aerodynamic control surfaces in the reusable reentry process of a launch vehicle first stage, enabling rapid design of high-performance, high-maneuverability grid fins in the overall aerodynamic layout design process. Background Technology

[0002] Research on reusable launch vehicle technology is currently one of the hottest development topics in the field of space transportation. Using aerodynamic control surfaces for attitude and trajectory control during reentry to achieve controlled atmospheric return and precise recovery of the launch vehicle's sub-stage is the most critical step in reusability. Grid fins, a complex aerodynamic control mechanism with multiple lifting surfaces composed of several continuously arranged grids, are foldable during ascent to reduce their impact. Their superior stall characteristics and lower hinge moment compared to traditional airfoils make them the preferred and key technology for the development of reusable launch vehicles.

[0003] However, the aerodynamic design of grid rudders is more challenging than that of conventional flat rudders because their aerodynamic characteristics arise from the collection of flow effects within almost identical individual grids. This results in a greater number of design parameters. Besides sharing the same outer contour dimensions as ordinary flat rudders, there are additional parameters such as grid chord length, grid width, grid thickness, sweep angle, and mounting angle, all of which significantly impact the aerodynamic performance of grid rudders. Furthermore, the internal flow within each grid is complex, exhibiting significant variations in flow characteristics across three adjacent Mach numbers. Especially in transonic conditions, shock waves cause airflow congestion. These significant flow differences lead to variations in the shape and optimal characteristics of grid rudders across different velocity ranges, making aerodynamic design quite difficult. Therefore, aerodynamic design involves two separate processes: outer contour dimension design and grid dimension design. The former addresses overall requirements, while the latter addresses flow efficiency.

[0004] Furthermore, the numerous grids of the fins, with minimum dimensions on the order of millimeters, represent a 3-4 order of magnitude difference in size compared to the overall rocket dimensions. This presents significant challenges for both calculation and experimentation. Conventional optimization methods employ a holistic approach, considering the rocket body and fins as a single object. This results in massive computational demands, making engineering implementation difficult and hindering rapid iterative design capabilities, preventing the inclusion of reusable overall optimization design processes. Consequently, the designed fins exhibit low aerodynamic efficiency and poor maneuverability. Achieving an optimized shape is challenging in engineering design, and the fin structure is structurally heavy. To pursue advanced technology, there is an urgent need to develop advanced and rapid aerodynamic layout design methods for fins. Summary of the Invention

[0005] The technical problem solved by this invention is to overcome the shortcomings of the prior art and provide a grid rudder optimization design method based on sub-grid flow parameters, which solves the problems of numerous grid rudder aerodynamic design parameters, complex aerodynamic characteristics, and long time consumption for full-rocket calculation.

[0006] The technical solution of this invention is: a grid rudder optimization design method based on sub-grid flow parameters, comprising:

[0007] Select several grid rudder cells as grid objects;

[0008] Based on the design requirements, different aerodynamic optimization or multidisciplinary optimization methods are selected to obtain the optimal design parameters under the preset requirement framework. The grid objects are then optimized to obtain the optimized grid rudder grid shape parameters.

[0009] Based on the overall design of the rocket body and the requirements for balancing and maneuvering, and using the optimized grid fin shape parameters as a basis, the required number of grid fin grids is calculated according to the total normal force coefficient required for grid fin maneuvering, thus forming a grid fin design scheme.

[0010] Furthermore, the grid cells in the grid object satisfy either central symmetry or planar symmetry.

[0011] Furthermore, the grid object optimization includes: taking the maximum normal force coefficient per unit area as the optimization objective, determining the impact of grid parameter changes on grid flow, obtaining the characteristic shape parameters of the grid flow with the best efficiency, and then determining the grid design parameters.

[0012] Furthermore, the design parameters include grid width, aspect ratio, and local sweep angle.

[0013] Furthermore, the grid object optimization includes: taking the minimum resistance per unit area as the optimization objective, determining the impact of grid parameter changes on grid flow, obtaining the characteristic shape parameters of the grid flow with the best efficiency, and then determining the grid design parameters.

[0014] Furthermore, the grid object optimization includes: taking the optimal combination of normal force coefficient and drag per unit area as the optimization objective, and using the weighted combination of the two based on needs and experience as the optimization objective, determining the impact of grid parameter changes on grid flow, obtaining the characteristic shape parameters of grid flow with the best efficiency, and then determining the grid design parameters.

[0015] Furthermore, the grid object optimization includes: conducting joint optimization based on aerodynamic and structural strength characteristics with the goal of minimizing structural mass. Two characteristic points are selected according to the characteristics of the flight trajectory mission, corresponding design points are selected for each. Based on the joint optimization results, the impact of grid parameter variations on grid flow and structural characteristics is determined, obtaining the characteristic shape parameters of the grid flow with optimal efficiency, and determining the grid design parameters. The aerodynamic characteristics include minimizing drag per unit area or maximizing lift coefficient, and the structural strength characteristics include minimizing mass under structural strength constraints.

[0016] Furthermore, the grid object optimization sets corresponding optimization objectives according to different design requirements and goals, and adopts corresponding optimization methods; the multidisciplinary optimization includes a joint optimization method of aerodynamic optimization and structural optimization.

[0017] A computer-readable storage medium storing a computer program, which, when executed by a processor, implements the steps of the grid rudder optimization design method based on subgrid flow parameters.

[0018] A grid rudder optimization design device based on subgrid flow parameters includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the steps of the grid rudder optimization design method based on subgrid flow parameters.

[0019] The advantages of this invention compared to the prior art are:

[0020] This invention is applied to the aerodynamic design and optimization of the first stage reentry flight of a launch vehicle using grid fins (or other aircraft using grid fins / wings). It enables the introduction of grid fin aerodynamic design into existing optimization methods, avoiding the problems of computational complexity, huge computational resource consumption, and excessively long optimization time that make conventional whole-rocket object optimization methods difficult to apply in engineering. It can significantly reduce the layout optimization design time and realize the engineering application of high-efficiency and rapid design of high-performance grid fin aerodynamic layout. Detailed Implementation

[0021] To better understand the above technical solutions, the technical solutions of the present invention will be described in detail below through specific embodiments. It should be understood that the embodiments of the present invention and the specific features in the embodiments are detailed descriptions of the technical solutions of the present invention, rather than limitations on the technical solutions of the present invention. In the absence of conflict, the embodiments of the present invention and the technical features in the embodiments can be combined with each other.

[0022] The following provides a more detailed description of a grid rudder optimization design method based on sub-grid flow parameters provided by an embodiment of the present invention. Specific implementation methods may include:

[0023] Select several grid rudder cells as grid objects;

[0024] Based on the design requirements, different aerodynamic optimization or multidisciplinary optimization methods are selected to obtain the optimal design parameters under the preset requirement framework. The grid objects are then optimized to obtain the optimized grid rudder grid shape parameters.

[0025] Based on the overall design of the rocket body and the requirements for balancing and maneuvering, and using the optimized grid fin shape parameters as a basis, the required number of grid fin grids is calculated according to the total normal force coefficient required for grid fin maneuvering, thus forming a grid fin design scheme.

[0026] The solution provided in the embodiments of the present invention specifically includes the following steps:

[0027] (1) Select a low number of rasters as the research object (hereinafter referred to as: raster object) and establish a basic characteristic database.

[0028] Grid rudders consist of a variable number of grids, all with essentially the same shape, making grid flow a suitable design and research object. To minimize computational load, 1, 4, or 9 grids can be selected as the research object, with 1 or 4 grids recommended. The characteristic parameters of the grid object need to encompass the parameters and ranges required for object optimization and design. Replacing the combination of grid rudders and the aircraft body with grid objects reduces shape complexity, significantly decreases the number of grids, and substantially reduces computational load. Large-scale calculations of aerodynamic characteristics with varying parameters can be performed, establishing a database of characteristic parameter variations in a shorter time, and obtaining parameter and research parameter variation patterns under various flow conditions.

[0029] (2) Aerodynamic shape optimization based on grid objects.

[0030] Taking the grid object as the research object, aerodynamic optimization, multidisciplinary optimization, and other optimization methods can be carried out according to design requirements and optimization objectives to conduct grid parameter optimization design. The goal is to obtain the design parameters with optimal characteristics within the design framework. Generally, the function of the grid rudder is to provide the control capability of a specific channel through deflection. The control capability comes from the rotation of the grid rudder relative to the rocket body mounting axis, forming an angle of attack with the incoming flow, thereby generating a normal force on the rudder surface. This normal force generates a torque change relative to the rocket body's center of mass, thus affecting the attitude of the channel during the reentry process of the launch vehicle. Therefore, the maximum value of the normal force coefficient per unit area can be used as the optimization objective to understand the impact of grid parameter changes on grid flow, and to obtain the characteristic shape parameters of the grid flow with optimal efficiency. This allows the determination of the grid design parameters (grid width, chord ratio, sweep angle, etc.).

[0031] Furthermore, it should be noted that optimization can be carried out by setting corresponding optimization objectives and adopting different optimization methods according to different design requirements and goals (such as minimum drag, aerodynamic and structural coupling design, etc.) in order to obtain results that meet the design requirements.

[0032] (3) Design of grid rudder based on grid object optimization results.

[0033] Based on the overall design of the rocket body and the requirements for balancing and maneuvering, and using the optimized shape parameters of the grid object formed in the previous step as a basis, the required number of grids is calculated with the total normal force coefficient requirement of the grid rudder as the target, thus forming the grid rudder design scheme.

[0034] Another situation exists in the design: the rocket's return scheme has been designed with grid fins that meet the overall requirements, but it has not been optimized, resulting in low efficiency. This method can be used to carry out optimization design. Based on the lift coefficient per unit area of ​​the optimal feature shape of the grid object formed in the previous step, and comparing it with the existing grid fin aerodynamic schemes, while maintaining the same total normal force, the number of grid cells in the new scheme's grid fin is calculated based on the grid object database established in step one. This allows for the production of a new grid fin scheme to replace the original one.

[0035] (4) Verification of the design scheme.

[0036] The new grid fins obtained using this method can be installed on the entire rocket to obtain a numerical model of the integrated scheme. Numerical simulations or wind tunnel tests are then conducted to verify the correctness of the integrated scheme. If there are discrepancies with expectations, fine-tuning between the individual cells can usually meet the design requirements.

[0037] The present invention provides a computer-readable storage medium storing computer instructions that, when executed on a computer, cause the computer to perform the method described thereon.

[0038] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage and optical storage) containing computer-usable program code.

[0039] Obviously, those skilled in the art can make various modifications and variations to this invention without departing from its spirit and scope. Therefore, if these modifications and variations fall within the scope of the claims of this invention and their equivalents, this invention also intends to include these modifications and variations.

[0040] The contents not described in detail in this specification are common knowledge to those skilled in the art.

Claims

1. A grid rudder optimization design method based on sub-grid flow parameters, characterized in that, include: Select several grid rudder cells as grid objects; Based on the design requirements, different aerodynamic optimization or multidisciplinary optimization methods are selected to obtain the optimal design parameters under the preset requirement framework. The grid objects are then optimized to obtain the optimized grid rudder grid shape parameters. Based on the overall design of the rocket body and the requirements for balancing and maneuvering, and using the optimized grid fin shape parameters as a basis, the required number of grid fin grids is calculated according to the total normal force coefficient required for grid fin maneuvering, thus forming a grid fin design scheme.

2. The grid rudder optimization design method based on sub-grid flow parameters according to claim 1, characterized in that, The grid rudder cells in the grid object satisfy either central symmetry or planar symmetry.

3. The grid rudder optimization design method based on sub-grid flow parameters according to claim 1, characterized in that, The grid object optimization includes: taking the maximum normal force coefficient per unit area as the optimization objective, determining the impact of grid parameter changes on grid flow, obtaining the characteristic shape parameters of the grid flow with the best efficiency, and then determining the grid design parameters.

4. The grid rudder optimization design method based on sub-grid flow parameters according to claim 3, characterized in that, The design parameters include grid width, aspect ratio, and local sweep angle.

5. The grid rudder optimization design method based on sub-grid flow parameters according to claim 1, characterized in that, The grid object optimization includes: taking the minimum resistance per unit area as the optimization objective, determining the impact of grid parameter changes on grid flow, obtaining the characteristic shape parameters of the grid flow with the best efficiency, and then determining the grid design parameters.

6. The grid rudder optimization design method based on sub-grid flow parameters according to claim 1, characterized in that, The grid object optimization includes: taking the optimal combination of normal force coefficient and drag per unit area as the optimization objective, and using the weighted combination of the two as the optimization objective based on needs and experience, determining the impact of grid parameter changes on grid flow, obtaining the characteristic shape parameters of grid flow with the best efficiency, and then determining the grid design parameters.

7. The grid rudder optimization design method based on sub-grid flow parameters according to claim 1, characterized in that, The optimization of the grid object includes: conducting joint optimization based on aerodynamic and structural strength characteristics with the goal of minimizing structural mass. Two characteristic points are selected according to the characteristics of the flight trajectory mission, corresponding design points are selected for each. Based on the joint optimization results, the impact of grid parameter changes on grid flow and structural characteristics is determined, obtaining the characteristic shape parameters of the grid flow with optimal efficiency, and determining the grid design parameters. The aerodynamic characteristics include minimizing drag per unit area or maximizing lift coefficient, and the structural strength characteristics include minimizing mass under structural strength constraints.

8. The grid rudder optimization design method based on sub-grid flow parameters according to claim 1, characterized in that, The grid object optimization sets corresponding optimization objectives based on different design requirements and goals, and adopts corresponding optimization methods; the multidisciplinary optimization includes a joint optimization method of aerodynamic optimization and structural optimization.

9. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by a processor, it implements the steps of the method as described in any one of claims 1 to 8.

10. A grid rudder optimization design device based on sub-grid flow parameters, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, it implements the steps of the method as described in any one of claims 1 to 8.