Wing wingtip winglet design method and platform
By employing parametric modeling, mesh generation, numerical simulation, and optimization design steps, combined with gradient and global optimization algorithms, the automated design of winglets was achieved. This solved the problems of long design cycles and suboptimal aerodynamic performance in existing technologies, and improved design efficiency and result reliability.
Patent Information
- Application Number
- CN202511098505.0
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-08-06
- Publication Date
- 2025-11-18
AI Technical Summary
Existing technologies make it difficult to simultaneously consider multiple design parameters in winglet design, resulting in long design cycles and difficulty in achieving optimal aerodynamic performance.
By employing parametric modeling, mesh generation, numerical simulation, and optimization design steps, combined with gradient algorithms and global optimization algorithms, the winglet can be automatically modeled and numerically calculated. The optimal solution is obtained by continuously optimizing the aerodynamic shape control parameters.
It significantly reduces the design cycle and the workload of engineers, improves aerodynamic efficiency, and ensures the reliability and repeatability of design results.
Smart Images
Figure CN120974634A_ABST
Abstract
Description
TECHNICAL FIELD
[0001] The present application relates to the technical field of wing tip winglet design, and particularly relates to a wing tip winglet design method and platform. BACKGROUND
[0002] The wing tip winglet is an advanced lift-drag technology, and the drag reduction effect of the wing tip winglet is very significant. The maximum effect of the wing tip winglet is to reduce induced drag and increase part of the wing lift to improve the climbing ability of the aircraft. The wing tip winglet includes multiple important design parameters, and the influence of each design parameter on the aerodynamic performance is in a nonlinear relationship. Different parameter combinations will affect the aerodynamic characteristics of the wing tip winglet. In the design process, engineers need to repeatedly iterate and combine and analyze various parameters, and the design cycle is long, and it is also difficult to simultaneously consider multiple design parameters in the design process. Therefore, only a wing tip winglet with feasible performance can be designed, and the aerodynamic performance cannot be optimized. SUMMARY
[0003] In view of the problems in the prior art, the present application provides a wing tip winglet design method and platform for calculating the aerodynamic shape control parameters of the wing tip winglet with optimal aerodynamic performance, realizing the automation of wing tip winglet modeling and numerical calculation, and reducing the workload and design cycle of engineers.
[0004] To achieve the above object, the present application provides the following technical scheme.
[0005] A wing tip winglet design method, comprising
[0006] A parameterized modeling step: obtaining wing tip winglet aerodynamic shape control parameters and performing parameterized modeling to obtain a wing tip winglet three-dimensional model;
[0007] A mesh division step: performing mesh division on the wing tip winglet three-dimensional model to obtain a mesh file;
[0008] A numerical simulation calculation step: performing numerical simulation calculation on the mesh file to obtain a lift-drag characteristic result file;
[0009] An optimization design step: inputting the lift-drag characteristic result file into an optimization design module to output optimization parameters, taking the optimization parameters as new aerodynamic shape control parameters, and repeatedly performing the parameterized modeling step, the mesh division step, the numerical simulation calculation step and the optimization design step until target parameters are obtained.
[0010] Further, in the parameterized modeling step, the aerodynamic shape control parameters include a winglet height h, an outboard angle φ, a sweepback angle Λ, a tip ratio λ and an installation angle ψ.
[0011] Further, in the parameterized modeling step, a parameterized program is written by using a vb language to realize parameterized modeling.
[0012] Furthermore, a mesh generation program is configured in the mesh generation step. The mesh generation program reads the winglet 3D model and converts it into a finite element model, and obtains the mesh file according to a preset mesh generation strategy.
[0013] Furthermore, a numerical simulation calculation module is configured in the numerical simulation calculation step. The numerical simulation calculation module reads the mesh file, calculates the surface aerodynamic distribution of the mesh file according to the engineering aerodynamic calculation method, uses the surface aerodynamic distribution as the boundary condition for solution calculation, and obtains the lift-drag characteristic result file.
[0014] Furthermore, in the optimization design step, the optimization design module is configured with optimization algorithms, including gradient algorithms and global optimization algorithms.
[0015] The beneficial effects of this invention are:
[0016] 1. This invention automates winglet modeling and numerical calculation through secondary development technology, making it easier to establish multiple sets of winglet 3D models with different parameter combinations and obtain their lift-drag characteristic result files. At the same time, it can realize data flow transfer between modeling and numerical simulation, reducing the design cycle and the workload of engineers.
[0017] 2. By combining the optimization algorithm with the aforementioned secondary development modeling and numerical calculation modules, the target parameters can be obtained through continuous optimization of the aerodynamic shape control parameters, thereby achieving the optimal combination of aerodynamic shape parameters and improving the aerodynamic efficiency of the winglet. Attached Figure Description
[0018] Figure 1 This is a schematic diagram of the design method flow in this invention;
[0019] Figure 2 These are the aerodynamic shape control parameters in this invention;
[0020] Figure 3 This is the wing model designed in this invention;
[0021] Figure 4 This is a schematic diagram of the structure of the winglet optimization design platform in this invention.
[0022] Reference numerals: 1. Wing section; 2. Winglet section; 3. Winglet tip section. Detailed Implementation
[0023] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.
[0024] It should be noted that when a component is described as "fixed to" another component, it can be directly on the other component or may have a component in between. When a component is considered "connected to" another component, it can be directly connected to the other component or may have a component in between. When a component is considered "set on" another component, it can be directly set on the other component or may have a component in between. The terms "vertical," "horizontal," "left," "right," and similar expressions used in this document are for illustrative purposes only.
[0025] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains. The terminology used herein in the description of the invention is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. The term "and / or" as used herein includes any and all combinations of one or more of the associated listed items.
[0026] Please see Figure 1 This embodiment of a wingtip winglet design method includes:
[0027] Parametric modeling steps: Obtain the aerodynamic shape control parameters of the winglet and perform parametric modeling to obtain the 3D model of the winglet;
[0028] Meshing steps: Mesh the 3D model of the winglet to obtain a mesh file;
[0029] Numerical simulation calculation steps: Perform numerical simulation calculations on the mesh file to obtain the lift-drag characteristic result file;
[0030] Optimization design steps: Input the lift-drag characteristic result file into the optimization design module to output optimization parameters. Use the optimization parameters as new aerodynamic shape control parameters. Repeat the parametric modeling step, mesh generation step, numerical simulation calculation step, and optimization design step until the target parameters are obtained.
[0031] In the parametric modeling step, a parametric modeling module is configured. This module is used to generate a three-dimensional model of the winglet based on the input aerodynamic shape control parameters. For example... Figure 2As shown, the aerodynamic shape control parameters of the winglet designed parametrically using three-dimensional software include, but are not limited to, five basic parameters: winglet height h, outward cant angle φ, sweep angle Λ, tip ratio λ, and installation angle ψ. The influence of each parameter on the aerodynamic efficiency of the wing exhibits nonlinear characteristics.
[0032] like Figure 3 The aerodynamic shape of the designed winglet mainly consists of three parts: wing section 1, winglet section 2, and winglet tip section 3. The winglet height h, outward cant angle φ, sweep angle Λ, tip ratio λ, and installation angle ψ are automatically modeled under different parameters by a parametric program written in VB language. It has the advantages of fast modeling speed and strong versatility.
[0033] To achieve automated modeling and parameter-driven control, the parametric modeling module employs secondary development of 3D modeling software based on the VB language. Specifically, it can be implemented in the following two ways:
[0034] Fully programmed method: By writing program code to call SolidWorks API interface functions, the entire process of sketching, feature extrusion, boundary definition and part saving is completed, so that the entire modeling process is fully linked with external input parameters, and the model generation is driven by all parameters.
[0035] The modeling and programming approach involves first creating a set of standard initial models in SolidWorks and setting the main feature parameters as controllable variables, such as dimensions and angles. Then, the parameter values are dynamically called and modified through a VB program to complete the model reconstruction and output.
[0036] The parametric modeling module can quickly complete the combined modeling process of the winglet segment, wingtip segment, and tip segment after receiving a set of control parameters, and generate a standardized 3D model file for subsequent mesh generation and numerical simulation calculations. This parametric modeling module significantly improves model generation speed, supports batch parameter group modeling, and possesses good versatility and scalability, providing an efficient input interface for subsequent optimization algorithm iterations.
[0037] Furthermore, a mesh generation program is configured in the mesh generation step. This program reads the 3D model of the winglet and converts it into a finite element model, obtaining the mesh file according to a preset mesh generation strategy. The mesh generation program can use existing programs, such as using Distmesh to divide the area to be segmented into a series of small regions, generating a mesh node in each small region, and then using an algorithm to connect the nodes to form a mesh. The shape, number, and density distribution of the mesh are preset.
[0038] In the mesh generation step of this invention, a mesh generation module is configured to convert the three-dimensional model output by the parametric modeling module into a finite element mesh structure that can be used for numerical simulation. The mesh generation process includes multiple sub-steps such as geometric model preprocessing, mesh structure generation, local refinement control, boundary condition setting, and mesh independence verification.
[0039] First, the mesh generation module reads the generated 3D model and performs geometric model repair operations, including feature cleaning, topology repair and boundary closure, to ensure the integrity of subsequent mesh generation.
[0040] Next, an unstructured mesh is generated on the geometry, using a combination of hybrid tetrahedral and pyramidal elements to balance flow simulation accuracy and computational efficiency. Local mesh refinement regions are configured near key areas such as the wingtip, boundary layer, and flow separation region, with their size controlled between 0.01 mm and 0.2 mm to capture detailed aerodynamic behavior.
[0041] The mesh module further defines the boundary regions of the external and internal flow fields, specifying appropriate boundary shapes and flow calculation ranges. The external flow field is set as the far-field boundary condition region, and the internal flow field is set as the boundary layer region near the solid surface. The mesh size can be configured in the range of 0.01 mm to 50 mm, and is automatically adapted according to the Reynolds number distribution and geometric scale.
[0042] To ensure simulation accuracy, the module also performs a mesh number independence verification, which involves gradually increasing the mesh number under fixed geometric parameters and observing the changes in lift and drag outputs. When the change is stable within 1%, the mesh accuracy is considered to meet the calculation requirements.
[0043] The final generated mesh file is output in a standard format, such as .msh or .cfd, and includes a mesh quality report and boundary identification information for use in the numerical simulation module.
[0044] Furthermore, the numerical simulation calculation step includes a numerical simulation calculation module. This module reads the mesh file, calculates the surface aerodynamic distribution of the mesh file according to an engineering aerodynamic calculation method, uses the surface aerodynamic distribution as boundary conditions for solution calculation, and obtains the lift-drag characteristic result file. The engineering aerodynamic calculation method employs a conventional calculation approach.
[0045] In the optimization design steps of this invention, an optimization design module is configured. This module is used to automatically adjust and iteratively optimize the aerodynamic shape control parameters of the winglet based on the aforementioned numerical simulation calculation results, so as to obtain the optimal solution for aerodynamic performance. The optimization design module mainly includes a variable definition and constraint setting submodule, an objective function construction submodule, an optimization search and iteration submodule, a constraint judgment and penalty function processing submodule, a convergence judgment module, and an optimal solution output submodule.
[0046] Specifically, the variable definition and constraint setting submodule first receives the winglet aerodynamic shape control parameters output from the parametric modeling stage, which constitute the design variable vector:
[0047] x = {h, φ, Λ, λ, ψ}
[0048] Where h represents the winglet height, φ represents the cant angle, Λ represents the sweep angle, λ represents the tip-to-tip ratio, and ψ represents the installation angle.
[0049] Users can set the allowed range of variation for each variable [x] min ,x max At the same time, optimization constraints are set, such as maximum lift limit, structural load constraint, and aerodynamic balance constraint.
[0050] The objective function construction submodule is used to calculate the lift coefficient C obtained in the aforementioned numerical simulation steps. L (x) and drag coefficient C D (x), construct the optimization objective function with maximizing the lift-to-drag ratio as the main objective:
[0051]
[0052] If multiple objectives are required, weighted summation or Pareto front objectives can be further constructed.
[0053] The optimization search and iteration submodule can call strategies including, but not limited to, gradient optimization algorithms (such as the conjugate gradient method) and global optimization algorithms (such as genetic algorithms, simulated annealing, and particle swarm optimization). In each iteration, the current variable combination x is... k The input is fed into the parametric modeling module and the mesh generation module. The numerical simulation calculation module obtains the current lift-to-drag ratio as feedback, which is then passed to the optimization module as the objective function value.
[0054] When the current output value does not meet the constraints or is far from the target value, the constraint judgment and penalty function processing submodule will penalize the target function using a penalty function of the following form:
[0055]
[0056] Among them, g i(x) represents the i-th constraint condition, α i This is the corresponding penalty factor. This mechanism can forcibly eliminate combinations of variables that violate design constraints, preventing convergence to invalid solutions.
[0057] The convergence judgment module in the optimization process sets the following two convergence criteria: First, the increase in the objective function over multiple consecutive iterations is lower than the first threshold value ε, i.e.:
[0058] |f(x k+1 )-f(x k )|<ε,
[0059] Second, the step size of the design variable is lower than the second threshold value δ, that is:
[0060] ||x k+1 -x k ||<δ,
[0061] When any criterion is met, the optimization process terminates, and the optimal solution output submodule outputs the current optimal design parameters as the optimization result of this round, which can be used by the parametric modeling module for modeling again or as the final output.
[0062] The introduction of this optimized design step significantly improves the automation level and reliability of the winglet design process, reduces manual parameter adjustment time, ensures the convergence and repeatability of the design results in terms of aerodynamic performance indicators, and has strong engineering adaptability.
[0063] In the numerical simulation calculation step of the present invention, a numerical simulation calculation module is configured to receive the mesh file output by the mesh generation module, and apply corresponding boundary conditions to solve the flow field and obtain aerodynamic performance indicators such as the lift coefficient and drag coefficient of the winglet.
[0064] The module employs an engineering aerodynamics simulation method, mainly including the following sub-steps:
[0065] Boundary condition loading: Set the free flow parameters such as airflow velocity, density, and pressure as inlet boundary conditions, and set the far-field boundary as a pressure outlet condition. The far-field boundary can be set as a spherical boundary or a cubic boundary. Apply no-slip wall boundary conditions to the winglet surface to simulate body-fit flow under viscous laminar or turbulent conditions.
[0066] Solution model selection: Select appropriate flow control equations based on the magnitude of Reynolds number and Mach number. Incompressible Reynolds-averaged Navier-Stokes equations are often used, or compressible Navier-Stokes equations are used at high speeds. Combine with the k-ωSST turbulence model to improve the shear layer prediction capability.
[0067] Discrete scheme and iterative method: The finite volume method is used to discretize the governing equations, and a second-order upwind scheme is used to improve numerical stability. The solver uses the SIMPLE or PISO method for pressure-velocity coupled iteration.
[0068] Convergence criterion: Define the residual convergence threshold as 10. -4 Up to 10 -6 The stability of aerodynamic output is used as an auxiliary criterion. When the change in lift / drag is less than a preset value in several consecutive iterations, the solution is considered to have converged.
[0069] Output format: The numerical simulation module outputs the aerodynamic distribution, pressure field and velocity field of the winglet surface obtained by the solution in the form of structured data. At the same time, it calculates the lift coefficient, drag coefficient and lift-to-drag ratio, and generates a standard result file for the optimization module to call.
[0070] The simulation module supports command-line batch processing, which can be seamlessly integrated with the optimization iteration process. It features high stability and fast computational efficiency, and is suitable for multi-round automatic iterative optimization processes.
[0071] Furthermore, in the optimization design step, the optimization design module is configured with optimization algorithms, including gradient algorithms and global optimization algorithms. The optimization design module mainly configures the range of control variables, constraints, and optimization objectives (maximum / minimum / approaching a certain value). By continuously controlling the values of optimization variables, penalty functions are added to eliminate values that do not meet the constraints, and finally the optimal solution is obtained.
[0072] In the optimization design steps of this invention, an optimization design module is configured. This module is used to automatically adjust and iteratively optimize the aerodynamic shape control parameters of the winglet based on the aforementioned numerical simulation calculation results, so as to obtain the optimal solution for aerodynamic performance. The optimization design module mainly includes a variable definition and constraint setting submodule, an objective function construction submodule, an optimization search and iteration submodule, a constraint judgment and penalty function processing submodule, a convergence judgment module, and an optimal solution output submodule.
[0073] Specifically, the variable definition and constraint setting submodule first receives the winglet aerodynamic shape control parameters output from the parametric modeling stage, which constitute the design variable vector:
[0074] x = {h, φ, Λ, λ, ψ}
[0075] Where h represents the winglet height, φ represents the cant angle, Λ represents the sweep angle, λ represents the tip-to-tip ratio, and ψ represents the installation angle.
[0076] Users can set the allowed range of variation for each variable [x] min ,x maxAt the same time, optimization constraints are set, such as maximum lift limit, structural load constraint, and aerodynamic balance constraint.
[0077] The objective function construction submodule is used to calculate the lift coefficient C obtained in the aforementioned numerical simulation steps. L (x) and drag coefficient C D (x), construct the optimization objective function with maximizing the lift-to-drag ratio as the main objective:
[0078]
[0079] If multiple objectives are required, weighted summation or Pareto front objectives can be further constructed.
[0080] The optimization search and iteration submodule can call, but is not limited to, gradient optimization algorithms and global optimization algorithms. Gradient optimization algorithms include, for example, the conjugate gradient method, and global optimization algorithms include, for example, genetic algorithms, simulated annealing, and particle swarm optimization. In each iteration, the current variable combination x is... k The input is fed into the parametric modeling module and the mesh generation module. The numerical simulation calculation module obtains the current lift-to-drag ratio as feedback, which is then passed to the optimization module as the objective function value.
[0081] When the current output value does not meet the constraints or is far from the target value, the constraint judgment and penalty function processing submodule will penalize the target function using a penalty function of the following form:
[0082]
[0083] Among them, g i (x) represents the i-th constraint condition, α i Here, f(x) represents the corresponding penalty factor, f(x) is the objective function value, and x is the current design variable vector. This mechanism can forcibly eliminate variable combinations that violate design constraints, preventing convergence to invalid solutions.
[0084] The convergence judgment module in the optimization process sets the following two convergence criteria: First, the increase of the objective function in multiple consecutive iterations is lower than the first threshold ε, i.e.: |f(x k+1 )-f(x k )|<ε,
[0085] Second, the step size of the design variable is lower than the second threshold value δ, that is: δ‖x k+1 -x k ||<δ,
[0086] When any criterion is met, the optimization process terminates, and the optimal solution output submodule outputs the current optimal design parameters as the optimization result of this round, which can be used by the parametric modeling module for modeling again or as the final output.
[0087] The introduction of this optimized design step significantly improves the automation level and reliability of the winglet design process, reduces manual parameter adjustment time, ensures the convergence and repeatability of the design results in terms of aerodynamic performance indicators, and has strong engineering adaptability.
[0088] To automate the entire design process and achieve data closure, this invention provides a winglet optimization design platform, such as... Figure 4 As shown, the platform integrates parametric modeling, mesh generation, numerical simulation, and optimization design modules, and is configured with a unified parameter interface and result sharing mechanism.
[0089] The connections between the modules are as follows:
[0090] Users input initial control parameters or parameter ranges through the interface as aerodynamic shape control parameters. These parameters are first passed to the parametric modeling module to generate a three-dimensional geometric model.
[0091] The geometric model is imported into the mesh generation module to generate an unstructured mesh and output a standard mesh file with boundary attributes.
[0092] The mesh file is fed into the numerical simulation module, where lift and drag calculations are performed under the set aerodynamic boundary conditions to obtain the aerodynamic result file.
[0093] The obtained aerodynamic results file is read by the optimization design module, which calculates the lift-to-drag ratio of the current parameter combination and performs a convergence judgment.
[0094] If convergence is not achieved, the optimization design module outputs new design parameters, and the platform automatically returns to the modeling step, forming a closed-loop iterative process.
[0095] If the optimization termination criteria are met, the platform outputs the final optimal design parameters and their corresponding aerodynamic performance results for engineering use.
[0096] The platform employs a distributed task control mechanism, enabling parallel computing in multi-core or multi-machine environments, significantly shortening the optimization cycle. It also reserves API interfaces to support integration with other aircraft design and simulation platforms.
[0097] The above are merely preferred embodiments of the present invention. The scope of protection of the present invention is not limited to the above embodiments. All technical solutions falling within the scope of the present invention's concept are within the scope of protection of the present invention. It should be noted that for those skilled in the art, any improvements and modifications made without departing from the principle of the present invention should also be considered within the scope of protection of the present invention.
Claims
1. A method for designing winglets at the wingtips, characterized in that: include Parametric modeling steps: Obtain the aerodynamic shape control parameters of the winglet and perform parametric modeling to obtain the 3D model of the winglet; Meshing steps: Mesh the 3D model of the winglet to obtain a mesh file; Numerical simulation calculation steps: Perform numerical simulation calculations on the mesh file to obtain the lift-drag characteristic result file; Optimization design steps: Input the lift-drag characteristic result file into the optimization design module to output optimization parameters. Use the optimization parameters as new aerodynamic shape control parameters. Repeat the parametric modeling step, mesh generation step, numerical simulation calculation step, and optimization design step until the target parameters are obtained.
2. The winglet design method according to claim 1, characterized in that: In the parametric modeling step, the aerodynamic shape control parameters include winglet height h, outward cant angle φ, sweep angle Λ, tip ratio λ, and mounting angle ψ.
3. The winglet design method according to claim 1, characterized in that: In the parametric modeling step, a parametric program is written using the VB language to achieve parametric modeling.
4. The winglet design method according to claim 1, characterized in that: The mesh generation step includes a mesh generation program, which includes a preset mesh generation strategy. The mesh generation strategy includes... The system reads the 3D model of the winglet and converts it into a finite element model. It then sequentially implements functions such as geometric model repair, surface mesh generation, volume mesh generation, local mesh refinement, boundary condition definition, and mesh output. Set the mesh sizes for the external and internal flow fields, both within the range of 0.01-50 mm. Next, the independence of the number of grids is verified. By continuously increasing the number of grids, the aerodynamic forces of the winglets are calculated. When the change in the number of grids causes a change in aerodynamic forces within the range of 0.01-5%, it is determined that the number of grids will not affect the calculation accuracy. The grid used is an unstructured grid, and local refinement is performed within the range of 0.01-0.2 mm in size.
5. The winglet design method according to claim 1, characterized in that: The numerical simulation calculation step includes a numerical simulation calculation module. The numerical simulation calculation module reads the mesh file, calculates the surface aerodynamic distribution of the mesh file according to the engineering aerodynamic calculation method, uses the surface aerodynamic distribution as the boundary condition for solution calculation, and obtains the lift-drag characteristic result file.
6. The winglet design method according to claim 1, characterized in that: In the optimization design step, the optimization design module is configured with optimization algorithms, including gradient algorithms and global optimization algorithms. The input of the optimization algorithm is the control parameters generated in the parametric modeling stage. The range of variables to be added in the optimization algorithm configuration stage is specified. The output is the calculated aerodynamic force. The program continuously modifies the input parameters and determines whether the output meets the requirements. Output values that deviate significantly from the target are eliminated through a penalty function.
7. A winglet design platform, applied to the winglet design method according to any one of claims 1-6, characterized in that: include The parametric modeling module allows users to input initial control parameters or parameter ranges as aerodynamic shape control parameters via the interface, which are then passed to the module to generate a 3D geometric model. The mesh generation module imports the three-dimensional geometric model into the mesh generation module to generate an unstructured mesh and outputs a standard mesh file with boundary attributes. The numerical simulation module receives the mesh file and performs lift and drag calculations under the set aerodynamic boundary conditions to obtain the aerodynamic result file. The optimization design module reads the aerodynamic results file, calculates the lift-to-drag ratio of the current parameter combination, and performs a convergence judgment. If convergence is not achieved, the optimization design module outputs new design parameters, and the platform automatically returns to the parametric modeling module, forming a closed-loop iterative process. If convergence is achieved, the platform outputs the final optimal design parameters and their corresponding aerodynamic performance results.