A wing parachute airfoil design method based on ISIGHT

Abstract

The application discloses a wing parachute airfoil design method based on ISIGHT, belongs to the technical field of aircrafts, and can further optimize the aerodynamic shape after the cutout parameters of the cutout airfoil of the wing parachute are determined, so that more improvement is brought to the aerodynamic performance of the wing parachute by changing the selection optimization in the traditional design optimization method into the optimal solution seeking. The application provides a kind of full-automatic optimization design method for the cutout airfoil of the wing parachute. The optimization method is integrated with airfoil generation, mesh division, flow field calculation and algorithm optimization four modules on the ISIGHT platform, so as to realize the full-automatic optimization of the cutout airfoil. After the optimization based on ISIGHT, the aerodynamic shape of the optimized cutout airfoil has increased camber, the maximum thickness position is moved forward, the aerodynamic performance is improved, the lift-drag ratio of the two-dimensional cutout airfoil before optimization is improved by 11.2%, and the lift coefficient is improved by 17%.

Description

Technical Field

[0001] This invention belongs to the field of aircraft technology, specifically relating to a wing airfoil design method based on ISIGHT. Background Technology

[0002] Ram-air parachutes are a modern type of parachute that primarily rely on an open leading-edge cutout for air intake. Within the air chamber, the low permeability of the canopy material creates stagnant pressure, maintaining the canopy's shape. Once fully inflated, a ram-air parachute can generate sufficient lift. Furthermore, because ram-air parachutes are mostly made of lightweight fabrics, they do not possess excessive mass, thus exhibiting highly efficient gliding performance. As a typical low-altitude, unpowered, flexible gliding aircraft, ram-air parachutes are widely used in parachuting, airdrops, spacecraft recovery, and air shows due to their excellent aerodynamic and maneuverability. High glide ratio performance is particularly important for research on precision parachute airdrop systems. To further improve the maneuverability and gliding performance of ram-air parachutes and enhance their overall performance, it is necessary to conduct structural design and aerodynamic performance research on high glide ratio parachutes.

[0003] The airfoil is one of the key factors affecting the aerodynamic performance of ramjet parachutes. Current research on improving the aerodynamic performance of ramjet parachutes largely focuses on the angle and height of the leading-edge notch of the basic airfoil. That is, to obtain the base airfoil with optimal aerodynamic performance by selecting a suitable notch angle and height while ensuring the parafoil's inflation performance, and then designing the parafoil based on this notched airfoil. However, comparing the notch height and angle to select appropriate notch parameters can only be considered a selection of the best, not the optimal one. Currently, there is no optimization specifically for notched airfoils designed for ramjet parachutes. Summary of the Invention

[0004] This invention provides a paraglider airfoil design method based on ISIGHT. Addressing the shortcomings of existing research that optimizes ramjet paraglider cut-out airfoils by merely selecting the best rather than finding the optimal solution, this invention proposes a fully automated optimization method for paraglider-specific cut-out airfoils. By integrating four modules—airfoil generation, mesh generation, flow field calculation, and algorithm optimization—on the ISIGHT platform and performing an optimization loop, fully automated optimization of cut-out airfoils is achieved. This method can be used to improve the aerodynamic performance of ramjet paragliders and can be extended to the optimization of the aerodynamic characteristics of other specialized airfoils.

[0005] To achieve the above objectives, the present invention adopts the following technical solution:

[0006] A wing airfoil design method based on ISIGHT includes the following steps:

[0007] Step S1: Airfoil Generation: The notched airfoil is parameterized. The shape of the airfoil is represented by the linear superposition of analytical functions. The coordinates of each point on the airfoil surface can be represented as a linear combination of the original coordinates and the disturbance.

[0008]

[0009]

[0010] With y loω These are the ordinates of the upper and lower surfaces after the airfoil modification and optimization, y and y', respectively. ou With y ol Here, represents the ordinates of the upper and lower surfaces before airfoil optimization, respectively; k (k = 1, 2, 3, ..., N) is the number of key variables controlling the main parameters of the airfoil shape, such as camber and thickness; c k The coefficients of the key point variables (type function coefficients), f k (x) represents the selected Hicks-Henne type function. The Hicks-Henne type function can ensure that the key variable points on the optimized airfoil are evenly distributed, thereby making the shape of the optimized airfoil smooth and even, and improving the optimization speed and efficiency.

[0011]

[0012] in: x represents the lateral coordinate of the key point within the airfoil (assuming the chord length of the airfoil is 1). When k = 2, 3, 4, 5, 6, 7, x k The σ values ​​are 0.15, 0.30, 0.45, 0.60, 0.75, and 0.90 respectively. The σ function f has the form when x = 0 and 1. k (x) = 0, which ensures that the leading and trailing edge points of the airfoil remain fixed during the optimization process. In order to preserve the integrity of the leading edge notch, the two leading edges of the lower airfoil are not included in the optimization, that is, the coefficients of variables c8 and c9 are not evaluated. There are 7 key optimization points on the upper airfoil and 5 on the lower airfoil. The value ranges of these 12 variables are as follows:

[0013] c1=[-0.008, 0.006], c2=[-0.007, 0.007], c3=[-0.010, 0.004], c4=[-0.006, 0.008],

[0014] c5=[-0.006, 0.008], c6=[-0.005, 0.002], c7=[-0.008, 0.006], c 10 = [-0.004, 0.010],

[0015] c 11= [-0.004, 0.010], c 12 = [-0.005, 0.009], c 13 = [-0.008, 0.006], c 14 = [-0.009, 0.005].

[0016] Type function coefficients c k As an optimization variable, new airfoil data will be generated through MATLAB software programming;

[0017] Step S2: Mesh Generation: During the mesh generation of the airfoil, the mature script recording function in ICEM is used to automate the repeated mesh generation of individual airfoils in each generation during the optimization process. ICEM's comprehensive script recording file system generates a script file (*.rpl) each time the ICEM process runs. This script file contains various commands needed to form the airfoil entity from the generated airfoil key point data and perform mesh generation. ISIGHT drives ICEM to run by driving the ICEM batch file. ICEM uses its log file to form the airfoil geometry from the airfoil key points output in the previous module and performs mesh generation to output an msh file.

[0018] Step S3: Flow Field Calculation: The CFD software Fluent is used to perform aerodynamic calculations on the airfoil. Like ICEM, Fluent also supports script functionality, i.e., journal scripts. The log file of Fluent software records the settings of the turbulence model, boundary conditions, initial conditions, material properties, reference values, flow velocity, residuals, and number of iterations in the numerical model. ISIGHT drives Fluent to run by driving the Fluent batch file. Fluent imports the msh output from the previous module according to its log file, runs according to the solution settings of the mesh in the log file, and obtains an output file containing lift coefficients and drag coefficients. Then, this result is used as the input file for the genetic optimization algorithm module.

[0019] Step S4: Algorithm Optimization: Set up the NSGA-II genetic algorithm in ISIGHT. This algorithm will generate offspring based on its own mechanism. The optimization targets are lift coefficient and lift-to-drag ratio. The genetic algorithm uses the input parameters calculated from the flow field to determine the next generation of individuals (airfoils) based on the fitness of each airfoil. The NSGA-II algorithm is used to generate the new generation of individuals, resulting in new shape function coefficients c. k This forms an optimization loop, which eventually converges to obtain the optimal solution.

[0020] Beneficial effects: This invention provides an ISIGHT-based airfoil design method, which can further optimize the aerodynamic shape after the cut parameters of the airfoil are determined. It transforms the selection of the best option in traditional design optimization methods into finding the optimal solution, bringing more improvements to the aerodynamic performance of the airfoil. This optimization method can also be applied to the aerodynamic optimization of other special airfoils. After ISIGHT-based optimization, the aerodynamic shape of the two-dimensional cut airfoil has increased camber and the maximum thickness position is moved forward compared with the unoptimized airfoil, resulting in improved aerodynamic performance. The lift-to-drag ratio is increased by 11.2% and the lift coefficient is increased by 17% compared with the unoptimized two-dimensional cut airfoil. Attached Figure Description

[0021] Figure 1 This is a flowchart illustrating the sight optimization process for the notched airfoil in this embodiment of the invention.

[0022] Figure 2 These are different morphologies of cut-out airfoils in embodiments of the present invention, where θ is the cut-out angle, h is the cut-out height, and t is the maximum thickness of the airfoil;

[0023] Figure 3 This is a schematic diagram of grid division in an embodiment of the present invention;

[0024] Figure 4 This is a schematic diagram of the optimized integration module in ISIGHT in an embodiment of the present invention;

[0025] Figure 5 This is a schematic diagram comparing the optimized airfoil before and after implementation in an embodiment of the present invention. Detailed Implementation

[0026] The present invention will now be described in detail with reference to the accompanying drawings and specific embodiments:

[0027] like Figure 1 As shown, the ISIGHT-based wing parachute airfoil design method includes the following steps:

[0028] This embodiment uses the ARAD-20% airfoil. Appropriate notch parameters are selected through numerical simulation, and the notched airfoil is optimized based on ISS.

[0029] An excessively large leading edge notch will increase the drag coefficient, while an excessively small notch will affect the parachute opening performance. Therefore, this embodiment selects... Figure 2The aerodynamic performance of nine modified airfoils with different cutout morphologies was studied to determine the optimal cutout parameters for the airfoil. Mesh was generated for the nine different cutout morphologies, and the incoming flow was simulated in Fluent (in this embodiment, the incoming flow velocity was simulated to be 7 m / s). The changes in the cutout angle and height of the two-dimensional profile of the modified airfoil were calculated and compared. Based on the numerical simulation results of the aerodynamic performance of the airfoil according to the cutout parameters, smaller cutout heights and angles can reduce the loss of aerodynamic performance caused by the cutout. Finally, an airfoil cutout height h / t of 0.3 and a cutout angle of 40° were selected as the cutout parameters for the baseline airfoil to determine the cutout airfoil to be optimized.

[0030] Save the coordinates of the notched airfoil as a text file in .dat format. Then, generate the airfoil data using a MATLAB program. The MATLAB airfoil generation program is as follows:

[0031]

[0032]

[0033]

[0034] The airfoil data can be accessed by the preprocessing software ICEM and divided into airfoil mesh files. In the subsequent iterative optimization process, the airfoil geometry model generates a new airfoil .dat output file based on the design variables provided by the genetic algorithm module, which serves as the new input file for the ICEM mesh generation module.

[0035] During the meshing process for the notched airfoil, the mature script recording function in ICEM is utilized to obtain .rpl log files containing various commands for meshing the notched airfoil. In ISIGHT, this allows for automated meshing of individual airfoils within each generation of the population during the optimization process. The notched airfoil mesh can be generated using various methods. Due to the relatively simple geometry of the airfoil, an O-type structured mesh is used in this embodiment. The entire computational domain mesh is as follows: Figure 3 As shown, the computational domain is 15 times the chord length in the width direction and 15 times the chord length in the length direction;

[0036] The airfoil was aerodynamically calculated using the CFD software Fluent. Like ICEM, Fluent also supports script functionality, specifically journal scripts. Fluent's log files record the settings for the turbulence model, boundary conditions, initial conditions, material properties, reference values, flow velocity, residuals, and iteration count in the numerical model. Fluent's log files can be automatically created during model setup via File->Write->Start Journal. Fluent output files can be created via File->Write->Start Journal. The transcript outputs the Fluent post-processing results to a specified file. Based on this Fluent function, log files, input / output files, and batch files for automatically starting Fluent are created for the integration process. The files required to integrate this module are a JOU script file and a Windows batch file that automatically opens Fluent. Through the airfoil aerodynamic flow field calculation of this module, data files recording aerodynamic coefficients, lift coefficients, and drag coefficients can be obtained. The calculation conditions in this embodiment are as follows: the inlet boundary condition is a flow velocity of 7 m / s at infinity, the outlet boundary condition is free outflow, the inlet angle of attack is 5°, the turbulence model is the (SST)kw two-equation turbulence model, and the calculation is performed using a second-order upwind scheme and the SIMPLE algorithm. The turbulence model is set in the Fluent solver. After all settings are completed, the solver automatically iterates for 500 steps, and other settings are kept at default.

[0037] The optimization objective is to maximize the lift-to-drag ratio and lift coefficient of the target under computational conditions. The lift-to-drag ratio is obtained by dividing the lift coefficient by the drag coefficient. Each generation has 12 individuals, for a total of 20 generations. The genetic algorithm used is NSGA-II, one of the most popular genetic algorithms currently available. It is an improvement on the first-generation non-dominated genetic algorithm. Compared to the first generation, it reduces computational complexity, improves the accuracy of optimization results, and retains all the best individuals. All other parameters use default values. Based on the aerodynamic coefficient file calculated from the flow field, the NSGA-II algorithm is used to generate a new generation of individuals, resulting in new shape function coefficients.

[0038] The entire optimization process is set up as follows Figure 4 As shown, the Isight loop works through four modules until the optimization converges. The coefficients of the converged function are used as the key variables of the perturbation. Then, the coordinates of the final optimized airfoil are generated by MATLAB.

[0039] The final optimization result of this embodiment is as follows: Figure 5As shown, compared with the original airfoil, the optimized airfoil has increased camber and moved the maximum thickness position forward. The shape change of the optimized airfoil also conforms to the conventional law. The aerodynamic characteristics before and after optimization are shown in Table 1. The optimized two-dimensional notched airfoil has an 11.2% higher lift-to-drag ratio and a 17% higher lift coefficient than the unoptimized two-dimensional notched airfoil.

[0040] Table 1 Comparison of aerodynamic characteristics before and after airfoil optimization.

[0041]

[0042] The above description is only a preferred embodiment of the present invention. It should be noted that those skilled in the art can make several improvements without departing from the principle of the present invention, and these improvements should also be considered within the scope of protection of the present invention.

Claims

1. A wing parachute airfoil design method based on ISIGHT, characterized in that, Comprising the following steps: Step S1: airfoil generation: parameterized representation of the cut airfoil, the shape of the airfoil is represented by analytical function linear superposition method, the coordinates of each point on the airfoil can be represented as a linear combination of the original coordinates and the disturbance: ， ， wherein, and are the upper and lower surface ordinates of the modified airfoil after optimization, respectively, and are the upper and lower surface ordinates of the modified airfoil before optimization, respectively, and k is the number of key point variables controlling the main parameters of the airfoil shape, is the coefficient of the key point variable, is the selected Hicks-Henne function, and the function coefficients are taken as optimization variables. In order to keep the leading edge notch intact during optimization, the first two points on the upper surface are not involved in the optimization. New airfoil data is generated through matlab software programming, and the optimization of the aerodynamic shape is carried out after the notch parameters of the parachute airfoil are determined. Step S2: meshing: in the process of meshing the airfoil, the mature script file recording function in ICEM is used, ISIGHT drives ICEM batch file to drive ICEM to run, ICEM forms the airfoil geometry according to its log file and outputs the msh file by meshing the key points of the airfoil output in the last module; Step S3: flow field calculation: aerodynamic calculation of the airfoil, ISIGHT drives Fluent batch file to drive Fluent to run, Fluent imports the msh file output in the last module according to its log file, runs according to the solution setting of the grid in the log file to get the output file containing the lift coefficient and drag coefficient, and then takes the result as the input file of the genetic optimization algorithm module; Step S4: algorithm optimization: set the genetic algorithm NSGA-II in ISIGHT, the optimization target is the lift coefficient and the lift-drag ratio, the genetic algorithm inputs the parameters according to the flow field calculation results, decides the individuals of the next generation population according to the fitness of each airfoil, generates new population individuals by using NSGA-II algorithm, gets new function coefficients, and forms an optimization cycle, finally converges to get the optimal solution, the optimized two-dimensional cut airfoil aerodynamic shape has increased camber and the maximum thickness position is moved forward compared with before optimization.

2. The ISIGHT-based wing-parachute airfoil design method of claim 1, wherein, is: ， where: e(k) = 1 - k / 2 , represents the transverse coordinate of the key point in the airfoil.

3. The ISIGHT-based wing-parachute airfoil design method of claim 1 or 2, wherein, and The coefficients of the two variables are not changed, and the optimization key points have 7 upper wings and 5 lower wings. The value range of the 12 variables is as follows: ， ， ， ， ， ， ， ， ， ， ， 。 4. The ISIGHT-based wing-parachute airfoil design method of claim 1, wherein, In step S2, the mature script file system in ICEM generates a script file every time ICEM process is run, which contains various commands required to generate key point data of the airfoil to form the airfoil entity and perform meshing.

5. The ISIGHT-based wing-parachute airfoil design method of claim 1, wherein, In step S3, the log file of Fluent software records the settings of turbulent flow model, boundary condition, initial condition, material property, reference value, flow velocity, residual error and iteration number in numerical simulation.

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