CN115659504A - Multidisciplinary fusion automatic optimization design method for high paraglider - Google Patents

Multidisciplinary fusion automatic optimization design method for high paraglider Download PDF

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CN115659504A
CN115659504A CN202211315638.5A CN202211315638A CN115659504A CN 115659504 A CN115659504 A CN 115659504A CN 202211315638 A CN202211315638 A CN 202211315638A CN 115659504 A CN115659504 A CN 115659504A
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parafoil
airfoil
lift
canopy
wing
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李岩军
陈子悦
彭栎洁
仇博文
余莉
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Nanjing University of Aeronautics and Astronautics
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Nanjing University of Aeronautics and Astronautics
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Abstract

The multidisciplinary fusion automatic optimization design method for the high paraglider parachute is characterized in that functions of geometrical modeling, grid modeling, calculation of aerodynamic characteristics of the paraglider parachute, optimization of the airfoil shape and the like of the paraglider parachute are achieved automatically and modularly respectively, and a multidisciplinary optimization design framework is established by integrating modules through an Isight platform. The method decouples the pneumatic performance improvement problem of the three-dimensional parafoil, automatically optimizes the parafoil airfoil profile based on parameters such as canopy structure, materials and the like, automatically reads a preorder result file and operates in a circulating mode without manual intervention, automatically outputs the optimized airfoil profile with the maximum parafoil lift-drag ratio, is high in efficiency, adopts a functional airfoil profile design, is high in precision and is convenient for automatic processing and production. The method is of great significance to the optimal design of the high paraglider parachute.

Description

Multidisciplinary fusion automatic optimization design method for high paraglider
Technical Field
The invention belongs to the field of air-drop and pneumatic deceleration equipment, and particularly relates to an automatic optimization design of a parafoil.
Background
Under certain airflow state, the wing shape of the parafoil directly influences the flow field and the pneumatic performance of the ram-type parafoil, and the gliding capability of the parafoil is determined.
Unlike the basic wing profile of a conventional wing, the wing umbrella wing profile has a cut at the leading edge to facilitate canopy inflation. The cut breaks the streamline of the front edge of the wing profile, so that the aerodynamic performance of the wing profile of the parafoil is greatly different from that of the basic wing profile. Most of the traditional parafoil design obtains the aerodynamic performance of a basic airfoil profile through wind tunnel tests or numerical calculation, and the airfoil profile is manually corrected on the basis to obtain the aerodynamically optimal basic airfoil profile. Finally, the basic wing profile is subjected to notch modification to obtain the wing umbrella wing profile, and then the canopy design is carried out. However, this design process requires a large number of iterative modifications to the basic airfoil profile, requires repeated tests or modeling calculations based on the experience of professionals, and has poor repeatability and design efficiency.
In recent years, some scholars begin to perform geometric optimization on the wing profile of the parafoil by using an Isight platform, so that the aerodynamic performance of the notch wing profile is improved. However, due to the influence of the structural features of the parafoil, such as the small aspect ratio and the under canopy reflection, on the glide performance of the parafoil, the maximum glide ratio of the parafoil and the lift-drag ratio of the wing profile are not simple correspondences, and therefore, the optimal parafoil profile satisfying the high-glide parafoil cannot be obtained only by optimizing the notch profile.
Disclosure of Invention
The invention aims to solve the problem of complex numerical analysis of the aerodynamic performance of the three-dimensional parafoil and nonlinear optimization coupling of airfoil profiles through efficient flow field numerical calculation and a theoretical model, establish a multidisciplinary fused parafoil airfoil profile automatic optimization design framework, and automatically obtain the high-glide parafoil airfoil profile meeting the requirements of parafoil structures, materials and the like.
In order to achieve the purpose, the invention adopts the following technical scheme:
a multidisciplinary fusion high-glide parafoil automatic optimization design method integrates multidisciplinary modules, automatically runs, optimizes and outputs parafoil airfoil profiles meeting high-glide performance requirements, and comprises the following steps:
step 1, establishing an automatic geometric modeling module, reading an airfoil profile parameter file, and automatically establishing a parafoil airfoil geometric model;
step 2, establishing an automatic grid modeling module, automatically establishing a wing-shaped flow field of the parafoil and dividing grids;
step 3, establishing a parafoil aerodynamic characteristic automatic calculation module, inputting parafoil canopy structure parameters, automatically calculating a wing flow field, and outputting a canopy maximum lift-drag ratio, wherein the method specifically comprises the following steps: step 3.1, reading the grid model, carrying out computational fluid mechanics analysis, completing flow field boundary conditions and calculation setting, calculating a stable flow field of the parafoil airfoil profile in a certain flight attack angle range, and outputting a change rule C of aerodynamic coefficient of the parafoil airfoil profile along with the attack angle L,2D (α),C D,2D (α). 3.2, according to the three-dimensional parafoil canopy pneumatic characteristic calculation model, obtaining the three-dimensional canopy pneumatic characteristics under different attack angles alpha, and accordingly determining the maximum lift-drag ratio of the parafoil; step 3.3, saving the flow field calculation setting file as a batch processing file, packaging the batch processing file with a three-dimensional canopy aerodynamic characteristic calculation program, and automatically calculating the maximum lift-drag ratio of the parafoil canopy;
step 4, judging whether the parachute canopy lift-drag ratio is stable and converged after the wing profile optimization, if so, stopping running, and outputting a wing profile parameterized function and a maximum fly-drag ratio; otherwise, establishing an airfoil profile optimization module by using an Isight multi-island genetic algorithm, automatically optimizing the airfoil profile based on the aerodynamic characteristic calculation result by taking the improvement of the canopy lift-drag ratio of the parafoil as a target to obtain a new parameterized airfoil profile function coefficient, and returning to the step 1 for geometric modeling again;
and 5, integrating a parafoil airfoil automatic geometric modeling module, an automatic grid modeling module, a parafoil aerodynamic characteristic automatic calculation module and an airfoil shape optimization module to establish a multidisciplinary optimization design framework, wherein each module automatically reads a preorder result file, operates in a circulating mode and automatically outputs the optimal airfoil shape corresponding to the maximum lift-drag ratio canopy.
Preferably, step 1 specifically comprises: step 1.1, selecting an initial parafoil type, establishing the coordinates of the parafoil type based on a body axis coordinate system, wherein the cut point of the upper airfoil surface is O, the chord line is OX axis, the cut point of the lower airfoil surface is B, and the trailing edge point of the airfoil type is C (1, 0); step 1.2, adopting a method of analytic function linear superposition, and respectively establishing parameterized functions y of the upper airfoil surface and the lower airfoil surface through programming coordinate fitting u (x)、y d (x) (ii) a Step 1.3, fixing coordinate positions of wing section feature points O, B and C, using various type function coefficients of upper and lower wing section parameterization functions as control variables, jointly representing an initial wing section shape, and outputting shape control parameters as a data file; and step 1.4, reading the optimized wing section geometric parameter data file, and automatically establishing a wing section geometric model of the parafoil according to the positions of the characteristic points and the coefficients of the type functions.
Preferably, in step 1.2, the upper and lower surfaces of the airfoil are functionally represented by the following formula:
Figure BDA0003909122670000031
wherein, N and c k Respectively representing the number and coefficients of the type functions, f k (x) For the chosen type function:
Figure BDA0003909122670000032
in the formula
Figure BDA0003909122670000033
The lower surface of the airfoil can also adopt a straight airfoil surface to improve the flight stability, and the function is y d (x)＝c d1 x+c d2 。
Preferably, step 2 specifically comprises: step 2.1, reading an airfoil geometric model, and establishing a C-shaped flow field area according to the airfoil chord length; step 2.2, block division is carried out on the flow field area, and a C-shaped block is established based on the airfoil shape; determining the size of a grid according to the chord length of the wing profile and the working condition of the incoming flow, automatically generating a structured grid and outputting a grid model file; and 2.3, saving the meshing process as a batch file so as to realize automatic modeling of the flow field domain and the mesh of the airfoil profile.
Preferably, in step 3.2, the lift coefficient of the flat wing is determined according to the lift line theory
Figure BDA0003909122670000041
Is calculated, wherein
Figure BDA0003909122670000042
Denotes the slope of the lift line, Δ α = α - α 0 Expressing the difference value with a zero lift force attack angle, wherein lambda is an aspect ratio, and m is a constant; as the aerodynamic performance of the parafoil is greatly influenced by the structural characteristics of dihedral angle and small aspect ratio, the lift coefficient of the parafoil can be expressed as C L,3D ＝C Lβ +C Lλ In the formula C Lβ Denotes the influence of the anhedral angle on the lift coefficient, C Lλ The influence of the small aspect ratio of the canopy on the aerodynamic performance is shown; the parafoil drag coefficient can be expressed as C D,3D ＝C D,2D +C D,S In which C is D,2D And C D,S Respectively representing the pressure difference resistance generated by the cut wing profile and other resistances generated by the canopy; finally obtaining the lift-drag ratio
Figure BDA0003909122670000043
Preferably, the parafoil lift coefficient formula is C Lβ In particular to C Lβ ＝kΔαcos 2 Beta, where k is the slope of the parafoil lifting line, expressed as
Figure BDA0003909122670000044
Calculating beta is the lower dihedral angle of the parafoil; c Lλ The method specifically comprises the following steps: c Lλ And (1.67-0.67 lambda) sin delta alpha sin2 delta alpha, which represents the influence of the small aspect ratio of the umbrella on the aerodynamic performance.
Preferably, the canopy resistance can be decomposed into C according to the working principle of the parafoil D,S ＝C D,Q +C D,M +C D,Y In which C is D,Q 、C D,M And C D,Y Respectively representing the flow resistance of a front edge cut, the friction resistance generated by the irregularity of the airfoil surface and the roughness of the fabric and the induced resistance generated by two ends of the parafoil; the calculation formula of the incision flow resistance is C D,Q = qh/c, where q is constant and h/c is that the incision is relatively highDegree; the induced resistance can be calculated according to the aspect ratio, and the specific formula is
Figure BDA0003909122670000051
Preferably, step 4 outputs the maximum canopy lift-drag ratio corresponding to the airfoil shape in each iteration process, and if the fluctuation of the result of five iterations is not more than 5%, the iteration is considered to be converged.
Preferably, in the genetic algorithm optimization module in the step 4, the optimization variables are wing-shaped functional coefficients { c } of parafoil k Is multiplied by the lift-drag ratio of the three-dimensional canopy 3D,max ＝max{λ 3D (α) reaches a maximum of an objective function with a constraint of λ 3D,max ≥λ 3D,max,0 Wherein λ is 3D,max,0 The lift-drag ratio of the parachute canopy corresponding to the maximum parachute is the initial wing profile.
The multidisciplinary fusion automatic optimization design method for the high paraglider parachute has the following beneficial effects:
1. according to the method, the complicated three-dimensional parafoil pneumatic lifting problem is decoupled into the geometrical optimization problem of the airfoil shape through the parafoil pneumatic characteristic model. A plurality of modules of geometrical modeling, flow field grid modeling, flow field computational analysis, appearance optimization and the like of the wing-shaped of the parafoil are integrated through a multidisciplinary optimization design framework, so that the influence of structural characteristics of the parafoil such as a notch, a lower inverse, an aspect ratio and the like on aerodynamic performance is considered, frequent manual data updating in each module and among modules is avoided, the whole optimization design process automatically and circularly operates, and the optimization design efficiency is greatly improved.
2. The shape optimization module is established based on an intelligent optimization algorithm, the automatic parameterized optimization design of the wing profile of the parafoil is realized, on one hand, the design experience of technicians is not relied, the design efficiency is improved, and the manual error is reduced; on the other hand, the function model of the airfoil profile is directly obtained, so that the intelligent machining and manufacturing are facilitated, and the machining error is small.
Drawings
FIG. 1 is a flow chart of an optimization of one embodiment of the present invention;
FIG. 2 is a schematic diagram of an airfoil coordinate and parameterized function model according to an embodiment of the present invention
FIG. 3 is a schematic diagram of an airfoil flow field and grid model and grid details according to an embodiment of the present invention;
FIG. 4 is a graph of the results of an iteration of lift-to-drag ratios according to one embodiment of the present invention;
FIG. 5 is a comparison of an optimized leading and trailing airfoil geometry according to one embodiment of the present invention;
FIG. 6 is a comparison graph of airfoil pressure distributions before and after optimization in accordance with one embodiment of the present invention;
FIG. 7 is a comparison of velocity vector distributions before and after optimization, in accordance with an embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the available embodiment libraries of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The invention discloses a multidisciplinary fusion automatic wing profile optimization design method, which comprises the steps of performing geometric modeling through self-programming to obtain a parameterized function model of a wing umbrella wing profile as shown in figure 1; automatically performing flow field mesh modeling on the airfoil geometric model to obtain a flow field calculation model of the airfoil; performing computational fluid dynamics analysis on the airfoil profile by using flow field analysis software to obtain aerodynamic characteristic data of the airfoil profile; according to the three-dimensional parafoil canopy pneumatic characteristic calculation model, determining the maximum lift-drag ratio of the three-dimensional parafoil canopy; selecting an intelligent optimization algorithm, and performing parameter optimization on the geometrical shape of the wing type of the parafoil according to the aerodynamic characteristics of the three-dimensional parafoil; and establishing a multidisciplinary optimization design integration framework, realizing automatic cycle operation of the whole optimization process, iteratively screening until the optimal aerodynamic performance condition is reached, and outputting an airfoil profile and flow field result under the optimal aerodynamic performance condition. The method integrates airfoil modeling, flow field calculation analysis and genetic algorithm optimization software through multidisciplinary optimization design framework software, realizes accurate analysis in various disciplinary fields and automatic operation of the whole optimization cycle process, solves the problems of flow field analysis calculation and multidisciplinary multi-target coupling optimization of a complex three-dimensional parafoil, can be used in the optimization design problem of various aircrafts, and improves the design efficiency.
With reference to fig. 2 to 7, taking the optimization of the profile of the Clark-Y parafoil as an example, the parafoil has an extended length b of 8m, a chord length c of 4m, and an aspect ratio λ of 2, specifically illustrating the implementation steps of the present invention:
step 1, establishing an automatic geometric modeling module, reading an airfoil profile parameter file, and automatically establishing a parameterized geometric model of the airfoil of the parafoil. The method specifically comprises the following steps:
step 1.1, selecting a Clark-Y cut wing profile as an initial wing profile, establishing coordinate description of the wing profile based on a body axis coordinate system, wherein an upper wing surface cut point is O (0, 0), a lower wing surface cut point B (0.046, -0.045), an wing profile trailing edge point is C (1, 0), and specific coordinates are as shown in Table 1:
TABLE 1 Clark-Y notch airfoil coordinate description
Figure BDA0003909122670000071
Figure BDA0003909122670000081
Step 1.2, establishing a parameterized function y of the upper airfoil surface by adopting a method of analytic function linear superposition u (x) The formula is as follows:
y u (x)＝c 1 f 1 (x)+c 2 f 2 (x)+c 3 f 3 (x)+c 4 f 4 (x)+c 5 f 5 (x)+c 6 f 6 (x)+c 7 f 7 (x)；
wherein f is k (x) Is an airfoil function of the formula
Figure BDA0003909122670000082
In the formula
Figure BDA0003909122670000083
{c k Is the type function coefficient of the upper airfoil function
Determining the initial value of the coefficients of the shape function by fitting Matlab programmed coordinates:
c 1 ＝0.0032,c 2 ＝0.0425,c 3 ＝0.0209,c 4 ＝0.0346,c 5 ＝0.0171,c 6 ＝0.0249,c 7 ＝0.0147
in order to ensure the flight stability of the parafoil, the lower airfoil surface adopts a flat airfoil surface, and a lower airfoil surface function y is obtained through programming fitting d (x)＝0.0472x-0.0472。
The original airfoil coordinates and the parameterized model represent the airfoil profile as shown in fig. 2, and the original airfoil coordinates and the parameterized model are basically identical to each other, so that the accuracy of the parameterized model is illustrated.
Step 1.3, fixing the coordinate positions of the wing profile characteristic points O, B and C, wherein the coefficients of various types of functions of the wing profile parameterized function are { C k And (5) control variables which jointly represent the initial airfoil shape and output the profile control parameters as a data file.
And 1.4, reading an optimized airfoil profile geometric parameter data file by using a batch file, and automatically establishing a notch airfoil profile geometric model in the ICEM according to the positions of the characteristic points and the coefficients of the characteristic functions, wherein the geometric shape of the initial parafoil airfoil profile is shown as a central blank area in the figure 2.
And 2, establishing an automatic grid modeling module, automatically establishing an airfoil flow field and dividing grids. The method specifically comprises the following steps:
step 2.1, establishing a C-shaped flow field area by taking the upper airfoil surface cut point of the cut airfoil as a geometric center according to the airfoil chord length C, wherein the diameter of a semicircle is 10C, and the rectangular part is 10C multiplied by 12C;
and 2.2, block division is carried out on the flow field area, and a C-shaped block is established based on the airfoil shape. Determining the size of the grids according to the chord length of the airfoil profile, the inflow working condition and the like, wherein the number of the grids is about 7.8 thousands, generating C-type structured grids, calculating the flow field and the grids by the initial airfoil profile as shown in figure 3, and simultaneously outputting grid files.
And 2.3, storing the grid division process into an ICEM script file, and realizing automatic modeling of the flow field and the grid of the airfoil profile.
And 3, establishing a parafoil aerodynamic characteristic automatic calculation module, automatically calculating the airfoil flow field, and outputting the maximum lift-drag ratio of the canopy. The method specifically comprises the following steps:
and 3.1, reading a grid file output by the ICEM, establishing a notch airfoil flow field calculation model by using commercial software Fluent, and carrying out computational fluid mechanics analysis. The incoming flow velocity v =12m/s at the infinite distance of the wing profile, and the outlet is a free outlet; the turbulence model adopts a Sparart-Allmoras single-pass model, the equations are dispersed by using a second-order windward format, and the airfoil surface adopts a non-slip wall surface condition. Calculating the steady-state flow field of the parafoil airfoil profile in the flight attack angle range of-4 to 12 degrees and automatically outputting the aerodynamic characteristic C of the two-dimensional parafoil airfoil profile changing along with the attack angle alpha L,2D (α),C D,2D (α)。
And 3.2, calculating the lift resistance according to the three-dimensional parafoil canopy aerodynamic characteristic calculation model.
The lift coefficient is C L ＝C Lβ +C Lλ ，
Wherein C is Lβ ＝kΔαcos 2 β，Δα＝α-α 0 The difference value between the angle of attack and the zero lift is shown, beta is the down-dihedral angle of the parafoil, composed of
Figure BDA0003909122670000101
Calculation, the equivalent length L of the umbrella rope is taken in the embodiment sh =4.8m, calculated β =23.8 °.
The gradient k of the wing-shaped parachute lifting line is determined according to the gradient of the two-dimensional wing-shaped lifting line and the canopy aspect ratio,
Figure BDA0003909122670000102
wherein m is a non-elliptical correction coefficient, and the small aspect ratio is 0.046.
C Lλ And (1.67-0.67 lambda) sin delta alpha sin2 delta alpha, which represents the influence of the small aspect ratio of the canopy on the aerodynamic performance.
The resistance coefficient is calculated by the formula C D,3D ＝C D,2D +C D,S ，
Wherein C D,2D And C D,S Respectively representing the pressure-drag produced by notched wing profile and by canopyOther resistance forces;
according to the working principle of the parafoil, the resistance of the canopy can be decomposed into three parts, namely C D,S ＝C D,Q +C D,M +C D,Y In which C is D,Q 、C D,M And C D,Y Respectively representing the flow resistance of the front edge cut, the friction generated by the irregularity of the wing surface and the roughness of the fabric and the induced resistance generated by the two ends of the parafoil.
Calculation formula of incision flow resistance according to C D,Q Calculating by using the formula of = qh/C, wherein q is a constant, taking 0.3 according to engineering experience, and obtaining C by taking the relative height of a cut as h/C =0.067 D,Q ＝0.02。
The common fabric material of the parafoil is nylon silk, and the friction resistance coefficient can be C D,M =0.004. Coefficient of induced drag of airfoil profile based on
Figure BDA0003909122670000103
And (4) calculating.
Establishing a three-dimensional parafoil canopy aerodynamic characteristic model by utilizing Matlab programming according to the formula, and automatically calculating aerodynamic coefficients C under different aerodynamic attack angles L,3D (α),C D,3D (alpha) and output of the drag ratio of the parafoil
Figure BDA0003909122670000111
And 3.3, storing the flow field calculation setting file as a Fluent log file, packaging the Fluent log file with a three-dimensional canopy aerodynamic characteristic calculation program, and automatically calculating the aerodynamic characteristics of the two-dimensional wing profile and the three-dimensional canopy by using the grid file obtained in the second step to automatically output the maximum lift-drag ratio of the parafoil.
Step 4, judging whether the parachute canopy lift-drag ratio is stable and converged after the wing profile optimization, if so, stopping running, and outputting a wing profile parameterized function and a maximum fly-drag ratio; otherwise, establishing an airfoil shape optimization module by using an Isight multi-island genetic algorithm, wherein parameters of the genetic algorithm are selected as follows: the sub-population scale is 5, the sub-population number of individuals is 6, the iteration step number is 200, the hybridization probability is 0.9, the variation probability is 0.01, the mobility is 0.3, and the migration interval is 4. Based on the result of calculation of aerodynamic characteristics, at a lift-to-drag ratio lambda 3D (alpha) up to a maximum of the order ofAnd marking and setting constraint conditions: after optimization, the lift coefficient is increased and the drag coefficient is reduced, i.e. C L,3D ＞C L,3D0 ,C D,3D ＜C D,3D0 Automatically obtaining new parameterized airfoil-shaped function coefficients { c } k }. And returning to step one to 1.4 to automatically re-geometrically model.
And 5, integrating a parafoil airfoil automatic geometric modeling module, an automatic grid modeling module, a parafoil aerodynamic characteristic automatic calculation module and an airfoil shape optimization module to establish a multidisciplinary optimization design framework, wherein each module automatically reads a preorder result file, operates in a circulating mode and automatically outputs the optimal airfoil shape corresponding to the maximum lift-drag ratio canopy.
In the optimization process, the aerodynamic characteristics of the optimized iterative airfoil profile can be output in real time, the variation of the drag ratio of the parafoil obtained in the optimization process after 200 steps of iteration is shown in figure 4, and the graph shows that the drag ratio of the parafoil is obviously improved along with the increase of the optimization times and finally reaches stability.
The wing profile geometric modeling module in the step 1 automatically outputs the optimized wing profile geometric shape, the optimized wing profile changes as shown in figure 5, the maximum thickness of the front edge of the optimized wing profile is slightly increased, the wing profile curvature is obviously improved, and the improvement of the lift force of the wing profile is facilitated.
The aerodynamic performance of the optimized airfoil profile is automatically output by the airfoil profile aerodynamic characteristic calculation module in the step 3, pressure and velocity vector distribution of the airfoil profile before and after optimization are respectively shown in fig. 6 and fig. 7, the pressure of the lower surface of the airfoil profile after optimization is basically unchanged and the pressure of the upper surface is reduced when seen from the pressure diagram before and after optimization, and the flow velocity of the upper surface of the airfoil profile after optimization is correspondingly seen from the velocity vector diagram, so that the lift force of the airfoil profile is increased, and the flow field result proves that: optimizing the airfoil enables an improvement in aerodynamic performance. The drag ratio of the parafoil obtained in the airfoil aerodynamic characteristic calculation module is optimized and then is increased to 4.18 from 3.94, the drag ratio is increased by 6.1 percent, and the glide distance of the parafoil air-drop system can be effectively increased.
It should be noted that the present invention integrates the above optimization design steps and modules, and the whole optimization process automatically operates, so that the automatic optimization design of the high paraglider parachute can be realized.
Finally, it should be noted that: although the present invention has been described in detail with reference to the foregoing embodiments, it will be apparent to those skilled in the art that modifications may be made to the embodiments described above, or equivalents may be substituted for elements thereof. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims (9)

1. A multidisciplinary fusion high-glide parafoil automatic optimization design method integrates multidisciplinary modules, automatically runs, optimizes and outputs parafoil airfoil profiles meeting high-glide performance requirements, and is characterized by comprising the following steps of:
step 1, establishing an automatic geometric modeling module, reading an airfoil profile parameter file, and automatically establishing a parafoil airfoil geometric model;
step 2, establishing an automatic grid modeling module, automatically establishing a wing-shaped flow field of the parafoil and dividing grids;
step 3, establishing a parafoil aerodynamic characteristic automatic calculation module, inputting parafoil canopy structure parameters, automatically calculating a wing flow field, and outputting a canopy maximum lift-drag ratio, wherein the method specifically comprises the following steps:
step 3.1, reading the grid model, carrying out computational fluid mechanics analysis, completing flow field boundary conditions and calculation setting, calculating a stable flow field of the parafoil airfoil profile in a certain flight attack angle range, and outputting a change rule C of aerodynamic coefficient of the parafoil airfoil profile along with the attack angle L,2D (α),C D,2D (α)；
3.2, according to the three-dimensional parafoil canopy pneumatic characteristic calculation model, obtaining the three-dimensional canopy pneumatic characteristics under different attack angles alpha, and accordingly determining the maximum lift-drag ratio of the parafoil;
3.3, saving the flow field calculation setting file as a batch processing file, packaging the batch processing file with a three-dimensional canopy aerodynamic characteristic calculation program, and automatically calculating the maximum lift-drag ratio of the parafoil canopy;
step 4, judging whether the parachute canopy lift-drag ratio is stable and converged after the wing profile optimization, if so, stopping running, and outputting a wing profile parameterized function and the maximum lift-drag ratio of the parafoil; otherwise, establishing an airfoil profile optimization module by using an Isight multi-island genetic algorithm, automatically optimizing the airfoil profile based on the aerodynamic characteristic calculation result by taking the improvement of the canopy lift-drag ratio of the parafoil as a target to obtain a new parameterized airfoil profile function coefficient, and returning to the step 1 for geometric modeling again;
and 5, integrating a parafoil airfoil automatic geometric modeling module, an automatic grid modeling module, a parafoil aerodynamic characteristic automatic calculation module and an airfoil shape optimization module to establish a multidisciplinary optimization design framework, wherein each module automatically reads a preorder result file, operates circularly and automatically outputs the maximum lift-drag ratio canopy corresponding to the optimized airfoil shape.
2. The multidisciplinary fusion automatic optimization design method for the high paraglider parachute according to claim 1, wherein the step 1 specifically comprises the following steps:
step 1.1, selecting an initial parafoil airfoil, establishing a parafoil airfoil coordinate based on a body axis coordinate system, wherein an upper airfoil surface cut point is O, a chord line is OX axis, a lower airfoil surface cut point is B, and an airfoil trailing edge point is C (1, 0);
step 1.2, adopting a method of linear superposition of analytic functions, and respectively establishing parameterized functions y of the upper airfoil surface and the lower airfoil surface through programming coordinate fitting u (x)、y d (x)；
Step 1.3, fixing coordinate positions of wing section feature points O, B and C, using various type function coefficients of upper and lower wing section parameterization functions as control variables, jointly representing an initial wing section shape, and outputting shape control parameters as a data file;
and step 1.4, reading the optimized wing section geometric parameter data file, and automatically establishing a wing section geometric model of the parafoil according to the positions of the characteristic points and the coefficients of the type functions.
3. The multidisciplinary fusion automatic optimization design method for the high paraglider parachute according to claim 2, wherein in step 1.2, the upper and lower surfaces of the wing profile are functionally represented by the following formula:
Figure FDA0003909122660000021
wherein, N and c k Respectively representing the number and coefficients of the type functions, f k (x) For the chosen type function:
Figure FDA0003909122660000031
in the formula
Figure FDA0003909122660000032
Or the lower surface of the wing profile adopts a straight wing surface to improve the flight stability, and the function is y d (x)＝c d1 x+c d2 。
4. The multidisciplinary fusion automatic optimization design method for the high paraglider parachute according to claim 3, wherein the step 2 specifically comprises:
step 2.1, reading an airfoil geometric model, and establishing a C-shaped flow field area according to the airfoil chord length;
step 2.2, block division is carried out on the flow field area, and a C-shaped block is established based on the airfoil shape; determining the size of a grid according to the chord length of the wing profile and the working condition of the incoming flow, automatically generating a structured grid and outputting a grid model file;
and 2.3, storing the grid division process into batch processing files so as to realize automatic modeling of the flow field domain and the grid of the airfoil profile.
5. The method as claimed in any one of claims 1 to 4, wherein the lift coefficient of the straight wing is determined by the lift line theory in step 3.2
Figure FDA0003909122660000033
Is calculated, wherein
Figure FDA0003909122660000034
Denotes the slope of the lift line, Δ α = α - α 0 Expressing the difference value with a zero lift force attack angle, wherein lambda is an aspect ratio, and m is a constant;
as the aerodynamic performance of the parafoil is greatly influenced by the structural characteristics of a lower dihedral angle and a small aspect ratio, the lift coefficient of the parafoil can be expressed as C L,3D ＝C Lβ +C Lλ In the formula C Lβ Denotes the influence of the anhedral angle on the lift coefficient, C Lλ The influence of the small aspect ratio of the canopy on the aerodynamic performance is shown;
the drag coefficient of the parafoil can be expressed as C D,3D ＝C D,2D +C D,S In which C is D,2D And C D,S Respectively representing the pressure difference resistance generated by the cut wing profile and other resistance generated by the canopy;
finally obtaining the lift-drag ratio
Figure FDA0003909122660000041
6. The method as claimed in claim 5, wherein C is the coefficient of lift of the parafoil Lβ In particular to C Lβ ＝kΔαcos 2 Beta, where k is the slope of the parafoil lifting line, expressed as
Figure FDA0003909122660000042
Calculating beta is the lower dihedral angle of the parafoil;
C Lλ the method comprises the following specific steps: c Lλ And (1.67-0.67 lambda) sin delta alpha sin2 delta alpha, which represents the influence of the small aspect ratio of the canopy on the aerodynamic performance.
7. The method as claimed in claim 6, wherein the canopy resistance can be decomposed into C according to the working principle of the parafoil D,S ＝C D,Q +C D,M +C D,Y In which C is D,Q 、C D,M And C D,Y Respectively shows the flow resistance of the front edge cut, the friction generated by the irregularity of the airfoil surface and the roughness of the fabric and the attraction generated at the two ends of the parafoilThe guide resistance; the calculation formula of the incision flow resistance is C D,Q = qh/c, where q is a constant and h/c is the relative height of the incision; the induced resistance can be calculated according to the aspect ratio, and the specific formula is
Figure FDA0003909122660000043
8. The multidisciplinary fusion automatic optimization design method for the high paraglider parachute according to claim 7, wherein the step 4 outputs the maximum canopy lift-drag ratio corresponding to the airfoil profile in each iteration process, and the iteration is considered to be converged if the fluctuation of the result of five consecutive iterations is not more than 5%.
9. The multidisciplinary fusion automatic optimization design method for high paraglider parachute according to claim 8, wherein in the genetic algorithm optimization module in step 4, the optimization variables are the wing parachute airfoil type function coefficients { c } c k At a three-dimensional canopy lift-drag ratio λ 3D,max ＝max{λ 3D (α) reaches a maximum of an objective function with a constraint of λ 3D,max ≥λ 3D,max,0 Wherein λ is 3D,max,0 The lift-drag ratio of the parachute canopy corresponding to the maximum parachute is the initial wing profile.
CN202211315638.5A 2022-10-26 2022-10-26 Multidisciplinary fusion automatic optimization design method for high paraglider Pending CN115659504A (en)

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