CN103678763A - Method for aeroelastic tailoring of composite wing and genetic/sensitivity-based hybrid optimization method of composite wing - Google Patents
Method for aeroelastic tailoring of composite wing and genetic/sensitivity-based hybrid optimization method of composite wing Download PDFInfo
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Abstract
The invention provides a method for aeroelastic tailoring of a composite wing. The method for aeroelastic tailoring of the composite wing comprises the steps that aeroelastic tailoring of the composite wing is achieved by means of aeroelasticity optimization, and solution of aeroelasticity optimization is conducted according to a genetic/sensitivity-based hybrid optimization method. The genetic/sensitivity-based hybrid optimization method comprises the steps that (A) a group of individuals are generated randomly according to a genetic algorithm; (B) performance evaluation is conducted on the individuals in the group one by one; (C) according to a user definition, whether sensitivity-based optimization is applied or not is judged; (D) whether the end condition is met or not is judged; (E) if the end condition is not met, a new generation of excellent individuals are generated; if the end condition is met, operation is ended. By the adoption of the method for aeroelastic tailoring of the composite wing and the genetic/sensitivity-based hybrid optimization method, under the condition that multiple requirements for flutter, diffusion, inherent frequency, deformation, aileron efficiency, strength, the flight load, weight and the like are met, tailoring design of the structure is achieved and optimized.
Description
Technical field
The present invention relates to a kind of heredity/sensitivity method for mixing and optimizing, and the aeroelastic tailoring method of the civil aircraft composite wing based on the method, belong to operational method and the structural design field of aviation aircraft.
Background technology
Along with the development of aeroplane structure design technology, big-and-middle-sized aeroplane structure design adopts advanced composite structure to become inevitable main flow trend.Compound substance has the series of advantages such as high specific strength, high ratio modulus, good fatigue resistence, corrosion resistivity, strong designability.The high aspect ratio wing that big-and-middle-sized airplane in transportation category adopts mostly, its structural flexibility is larger, and in order to meet rigidity Design requirement, the aeroelasticity design with the composite wing of obvious weight advantage has become the hot issue of large aircraft wing structure design.On the big-and-middle-sized civilian airplane in transportation category of a new generation, the consumption of compound substance grows with each passing day, the main load-carrying construction such as empennage, wing central wing box, fuselage, and consumption has reached 50%, has obtained obvious weight loss effect, has extended organism life-span.As Boeing 777 used for advanced composite material amount 9.9t, account for 10% left and right of gross weight.The used for advanced composite material amount of Air Passenger A300 series aircraft also reaches 15% left and right.High aspect ratio wing structural design adopts compound substance in a large number, not only can increase substantially the structure efficiency of aircraft wing, and is cut out design and can be maximally utilised aeroelasticity usefulness to improve the overall performance of aircraft by suitable.
Meanwhile, the Torsion Coupling characteristic that high aspect ratio band swept back wing is outstanding, increases the flexion torsion distortion of wing wing tip under high-subsonic flight condition, and aeroelasticity effect is remarkable, then causes effectiveness of aileron to decline obviously, and Flutter Problem is serious.Therefore, conventionally need in design process, use aeroelasticity optimization method to carry out repeatedly design proposal comprehensive and compromise, to can, for singularity and the complicacy on high aspect ratio wing class aircraft aeroelastic characteristic, improve design efficiency and/or make design meet the performance requirement of aeroelasticity.
Summary of the invention
Therefore, the inventor proposes a kind of aeroelastic tailoring designing technique of aircarrier aircraft composite wing, under the multiple requirements such as it can be meeting flutter, disperse, natural frequency, distortion, effectiveness of aileron, intensity, flight load and weight, realize and optimize structure cut out design.
Heredity/sensitivity method for mixing and optimizing according to the present invention has multidisciplinary optimizational function, can be used for the structure optimization of wing, empennage or complete machine.This software meeting flutter, disperse, under the multiple requirement such as natural frequency, distortion, effectiveness of aileron, intensity, flight load and weight, carry out Optimal Structure Designing; At structural shape, unchangeably under prerequisite, also can carry out suitable profile optimization design.Optimum Design Results can be used as the reference of aircaft configuration topological design and detailed design.The NASTRAN of version can support following analysis subject at present: statics, orthogonal modes, flexing, direct method frequency response, model frequency response, mode transient response, pneumostatic dynamic elasticity, aeroelastic flutter, direct method complex eigenvalue and mode complex eigenvalue, these all can be used as the constraint of this software.The Aeroelastic Problems that is applicable to composite airplane.Compound substance has advantages of unique, but structural model element is many, and node is many, and model modeling or correction are comparatively loaded down with trivial details.The method is applicable to a large amount of design variables (element) situation, and calculating and fast convergence rate, is applicable to the aeroelasticity optimal design of compound substance.
Compound substance based on heredity/sensitivity method for mixing and optimizing is cut out the advantage that designing technique can make full use of genetic algorithm and sensitivity algorithms, meeting flutter, disperse, under the multiple requirement such as natural frequency, distortion, effectiveness of aileron, intensity, flight load and weight, implementation structure cut out design.
Accompanying drawing explanation
Fig. 1 is heredity/sensitivity method for mixing and optimizing process flow diagram
Fig. 2 is that heredity/sensitivity method for mixing and optimizing calls NASTRAN part process flow diagram
Fig. 3 is composite wing finite element model
Fig. 4 is covering thickness distribution schematic diagram on the composite wing after optimizing
Fig. 5 is covering thickness distribution schematic diagram under the composite wing after optimizing
Embodiment
A key of the aeroelastic tailoring of composite wing is to select rationally effectively aeroelasticity optimization method.
According to an aspect of the present invention, provide a kind of heredity/sensitivity method for mixing and optimizing, and the aeroelastic tailoring method of the composite wing based on this optimization method is provided.
In the aeroelastic tailoring method of composite wing according to an embodiment of the invention, the mode of optimizing by aeroelasticity realizes the aeroelastic tailoring of wing, and aeroelasticity optimization belongs to a kind of of optimization problem, by heredity/sensitivity method for mixing and optimizing, solve.In the present invention, this optimization problem can be expressed as search in ndv dimension space and make the minimized one group of design variable of objective function F (v), that is:
Min. F(v) (1)
S.T. g
j(v)≤0 j=1,2,...,n
c (2)
v
il≤v
i≤v
iu i=1,2,...,n
d (3)
Wherein, v is design variable vector, n
cfor constraint number, n
dfor design variable number, formula (1) is objective function, and formula (2) is for defining inequality constrain, and formula (3) is used to specify the up-and-down boundary of each design variable.According in the aeroelastic tailoring optimization method of composite wing of the present invention, the design variable of heredity/sensitivity method for mixing and optimizing is got the laying number of each covering subregion, beam thickness of flange etc., constraint comprise wing flutter speed, disperse, natural frequency, distortion, effectiveness of aileron, intensity, flight load etc., objective function is construction weight.
According to this patent embodiment, genetic algorithms use basic genetic algorithmic, sensitivity algorithms adopts in NASTRAN the optimization methods such as amended feasible direction method.
As shown in Figure 1, be the process flow diagram of a kind of heredity/sensitivity method for mixing and optimizing according to an embodiment of the invention.As shown in Figure 1, first determine optimisation strategy, mainly comprise definition population size, selected system of selection, cross method, variation method, determine crossover probability, variation probability, selects the contents (step 101) such as convergence criteria.Afterwards, genetic algorithm produces a group individuality (step 102) at random, and the individuality of this group is carried out to Performance Evaluation (step 103) one by one; According to a specific embodiment, aeroelastic analysis module in this Performance Evaluation invocation of procedure NASTRAN and sensitivity method are optimized module as analysis and solution device and sensitivity method Optimization Solution device, by the corresponding interface, repeatedly call the fusion of these two modules realizations and genetic algorithm, as shown in Figure 2.
Afterwards, according to user's definition, select whether to adopt sensitivity optimization (step 104).As select sensitivity optimization, excellent individual is carried out to sensitivity optimization reappraise (step 105); As do not selected sensitivity optimization, enter end condition determining step (step 106); If do not meet end condition, by use fitness change of scale, microhabitat operation and/or three kinds of main operations (copy, intersect and/or make a variation) to produce excellent individual of new generation to colony; Three kinds of genetic manipulations can be selected arbitrarily one of them or a plurality of combination in any (step 107) as required herein.Then, Yong Xin colony replaces old colony (step 108), Dui Xin colony assesses and judges whether to meet end condition (comprising constraint conditions such as whether meeting stress, strain, flutter speed), if do not meet end condition, continue colony to carry out aforesaid operations and Performance Evaluation, until meet end condition (step 109).
Fig. 2 is the idiographic flow that calls NASTRAN part in heredity/sensitivity method for mixing and optimizing.The input file that NASTRAN is optimized design comprises master file, design variable and Parameter File, other son file for optimization, and these files define in genetic algorithm, are directly inputted in NASTRAN software (step 201).According to whether carrying out sensitivity optimization (step 104 in Fig. 1), calculate respectively (step 202) afterwards.As adopt sensitivity optimization, and call sensitivity optimization module and use feasible direction method to carry out basis of sensitivity analysis to the excellent individual in genetic algorithm, according to result of calculation, read objective function and constraint satisfaction degree (step 203), carry out fitness calculating (step 205); If do not adopted sensitivity optimization, call aeroelastic analysis module, individuality is calculated, and judge convergence situation according to Output rusults, as convergence, read objective function Renewal Design variable (step 204), finally carry out fitness calculating (step 205).
In this mixed method, genetic algorithm is used for global search to avoid being absorbed in locally optimal solution; The excellent individual that every generation obtains through genetic algorithm optimization, will further be used amended feasible direction method to optimize to obtain locally optimal solution to it.Like this by repeatedly just searching for progressively convergence globally optimal solution.The design parameter of sensitivity optimization method is according to the requirements definition of the method, and the definition of genetic algorithm parameter is separate.
Take a civil aircraft composite machine wing model now as example (as shown in Figure 3), carry out aeroelastic tailoring optimization process under multi-constraint condition.Wherein, optimization problem can be described as:
Objective function: wing quality
Design variable: each laying thickness of the upper and lower covering of wing
Constraint condition: wing tip torsional angle, wing tip distortion, stress constraint, effectiveness of aileron, flutter speed, the constraint of losing efficacy, strain constraint; Concrete binding occurrence is as shown in table 1.
Table 1 constraint condition parameter value
| Performance index | Binding occurrence |
| Long purlin stress constraint (Mpa) | [-326,326] |
| Beam bead stress constraint (Mpa) | [-326,326] |
| Wing tip torsional angle (°) | ≤4.5 |
| Wing tip displacement (mm) | ≤1900 |
| Effectiveness of aileron (%) | ≥60% |
| Flutter speed (m/s) | ≥320 |
| Covering lost efficacy and retrained (Cai-Hu tensor criteria) | [-1,1] |
| The longitudinal tension and compression design of covering permissible constraint μ ε | [-3200,3200] |
| The vertical lateral shear design of covering permissible constraint μ ε | [-5000,5000] |
Optimization method: heredity/sensitivity method for mixing and optimizing
Adopt heredity/sensitivity method for mixing and optimizing, when considering structural strength constraint, take into full account the aeroelastic characteristic to model, in optimizing process, considered the factors such as malformation, driving efficiency and flutter speed, carried out the aeroelastic tailoring Synthetical Optimization under multi-constraint condition.After optimizing, covering laying variation in thickness schematic diagram is as Fig. 4, shown in Fig. 5.In Figure 4 and 5, unit wires is more intensive, represents that covering laying thickness is thicker.From the results of view, unit wires is intensive gradually from wingtip to turning point, sparse gradually from turning point to wing root, illustrates that covering thickness is maximum at turning point place, and successively decreases to wingtip wing root both sides; In Fig. 5, lines global density, than large in Fig. 4, illustrates down that covering laying thickness is greater than covering laying thickness.Wing performance parameter after optimization is as shown in table 2.
Table 2 wing performance parameter
| Project | Scheme before optimizing | Scheme after optimizing |
| Wing tip displacement (mm) | 1543 | 1518 |
| Wing tip torsional angle (°) | 4.05 | 3.56 |
| Effectiveness of aileron | 91.22% | 90.98% |
| Flutter speed (m/s) | 379 | 322 |
| Construction weight (Kg) | 3246 | 3004 |
This result shows, through the composite wing of aeroelasticity optimization, meeting under the prerequisite of the indicators of overall performance constraints such as stress, strain, distortion, effectiveness of aileron, flutter speed comprehensively, can not increase the construction weight of reference composite material wing.Therefore by heredity/sensitivity hybrid optimization means, can realize the design of cutting out to composite wing, make structural arrangement and Stiffness Distribution more efficient and rational simultaneously, weight is lighter.
Advantage of the present invention comprises:
1) for the design of civil aircraft composite wing laying provides a relatively rationally effective aeroelastic tailoring technology.
2) adopt hereditary sensitivity mixed method, sensitivity algorithms and genetic algorithm are learnt from other's strong points to offset one's weaknesses, become a kind of efficient global search method.
3) in this mixed method, genetic algorithm is explored for the overall situation of every generation, and sensitivity algorithms for carrying out Local Search near the excellent individual of every generation.The method can improve significantly the speed of convergence of genetic algorithm and overcome the defect that sensitivity algorithms optimum results depends critically upon the initial value of design variable.
Claims (9)
1. heredity/sensitivity the method for mixing and optimizing that is applicable to the aeroelastic tailoring method of composite wing, is characterized in that comprising:
A) utilize genetic algorithm, produce at random a group individuality (step 102);
B) and to the individuality of this group carry out Performance Evaluation (step 103) one by one;
C) according to user's definition, select whether to adopt sensitivity optimization (step 104);
D) judge whether to meet end condition (step 106);
E), when not meeting end condition, produce excellent individual of new generation (step 107); When meeting end condition, end operation (step 109).
2. according to the method for claim 1, it is characterized in that being further included in described steps A) before, first determine optimisation strategy (step 101), comprising:
Definition population size,
Selected system of selection, cross method, variation method,
Determine crossover probability, variation probability,
Select convergence criteria content.
3. according to the method for claim 1, it is characterized in that described step B) comprising:
Aeroelastic analysis module and the sensitivity method called in NASTRAN are optimized module as analysis and solution device and sensitivity method Optimization Solution device,
By the corresponding interface, repeatedly call described aeroelastic analysis module and/or sensitivity method optimization module, realize the fusion with genetic algorithm.
4. according to the method for claim 3, it is characterized in that:
The input file that NASTRAN is optimized design comprises master file, design variable and Parameter File, other son file for optimization, and these files define in genetic algorithm, and are directly inputted in NASTRAN software (step 201),
According to whether carrying out sensitivity optimization (step 104), calculate respectively (step 202) afterwards; As adopt sensitivity optimization, and call sensitivity optimization module and use feasible direction method to carry out basis of sensitivity analysis to the excellent individual in genetic algorithm, according to result of calculation, read objective function and constraint satisfaction degree (step 203), carry out fitness calculating (step 205); If do not adopted sensitivity optimization, call aeroelastic analysis module, individuality is calculated, and judge convergence situation according to Output rusults, as convergence, read objective function Renewal Design variable (step 204), finally carry out fitness calculating (step 205).
5. according to the method for claim 1, it is characterized in that described step C) further comprise:
When selecting sensitivity to optimize, excellent individual is carried out to sensitivity optimization reappraise (step 105);
When not selecting sensitivity to optimize, enter end condition determining step (step 106).
6. according to the method for claim 1, it is characterized in that described step e) in when not meeting end condition, produce excellent individual of new generation (step 107) operation comprise colony used:
Fitness change of scale,
Microhabitat operation and/or
Copy, intersection and/or mutation operation produce excellent individual of new generation (step 107).
7. according to the method for claim 1, it is characterized in that further comprising
Described step e) in after producing excellent individual of new generation (step 107),
Yong Xin colony replaces old colony (step 108),
Dui Xin colony assesses and judges whether to meet end condition, wherein
As meet end condition, terminating operation (step 109),
If do not meet end condition, described step B is returned in operation), Dui Xin colony carries out above-mentioned steps B)-E) and processing, until meet end condition.
8. an aeroelastic tailoring method for composite wing, is characterized in that comprising:
The mode of optimizing by aeroelasticity realizes the aeroelastic tailoring of wing, and described aeroelasticity optimization is by solving according to the heredity/sensitivity method for mixing and optimizing one of claim 1-7 Suo Shu.
9. method according to Claim 8, is characterized in that,
Described aeroelasticity optimization is expressed as search in ndv dimension space and makes the minimized one group of design variable of objective function F (v), that is:
Min. F(v) (1)
S.T. g
j(v)≤0 j=1,2,...,n
c (2)
v
il≤v
i≤v
iu i=1,2,...,n
d (3)
Wherein, the vector that v is design variable, n
cfor the number of constraint, n
dfor design variable number, formula (1) is objective function, and formula (2) is for defining inequality constrain, and formula (3) is used to specify the up-and-down boundary of each design variable,
In described heredity/sensitivity method for mixing and optimizing, described design variable comprises laying number, the beam thickness of flange of each covering subregion, described constraint comprise wing flutter speed, disperse, natural frequency, distortion, effectiveness of aileron, intensity, flight load, described objective function is construction weight.
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Cited By (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104978449A (en) * | 2015-08-17 | 2015-10-14 | 北京航空航天大学 | Aerodynamic optimization method of leading edge slats position and trailing edge flap position of two-dimensional three-section airfoil profile |
| CN105716842A (en) * | 2014-12-05 | 2016-06-29 | 中国飞机强度研究所 | Double-beam type long straight wing load processing method |
| CN109521673A (en) * | 2018-10-25 | 2019-03-26 | 北京航空航天大学 | A kind of section sliding formwork suppressing method of two-dimensional wing Flutter Problem |
| CN112464372A (en) * | 2020-11-25 | 2021-03-09 | 西北工业大学 | Design sensitivity engineering numerical method for control surface efficiency of aileron of elastic wing |
| CN112555451A (en) * | 2020-10-29 | 2021-03-26 | 成都成高阀门有限公司 | Pressing process parameter determination method for all-welded ball valve seat sealing groove and semi-finished valve seat |
| CN112765731A (en) * | 2021-01-19 | 2021-05-07 | 北京航空航天大学 | Aeroelasticity optimization method of curved fiber composite structure considering local buckling |
| CN113886967A (en) * | 2020-10-09 | 2022-01-04 | 北京航空航天大学 | Multi-cruise-condition aeroelasticity optimization method for large aircraft wing |
Citations (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1673036A (en) * | 2004-03-25 | 2005-09-28 | 北京航空航天大学 | Network system in structure optimized through genetic algorithm |
-
2013
- 2013-10-14 CN CN201310479086.6A patent/CN103678763A/en active Pending
Patent Citations (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1673036A (en) * | 2004-03-25 | 2005-09-28 | 北京航空航天大学 | Network system in structure optimized through genetic algorithm |
Non-Patent Citations (4)
| Title |
|---|
| GAA THUWIS等: "Aeroelastic tailoring using lamination parameters", 《STRUCTURAL & MULTIDISCIPLINARY OPTIMIZATION》 * |
| 万志强等: "大展弦比复合材料机翼气动弹性优化", 《复合材料学报》 * |
| 万志强等: "混合遗传算法在气动弹性多学科优化中的应用", 《北京航空航天大学学报》 * |
| 王韬: "复合材料前掠翼气动弹性剪裁技术分析与研究", 《中国优秀硕士论文全文数据库-工程科技Ⅱ辑》 * |
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| CN105716842A (en) * | 2014-12-05 | 2016-06-29 | 中国飞机强度研究所 | Double-beam type long straight wing load processing method |
| CN104978449A (en) * | 2015-08-17 | 2015-10-14 | 北京航空航天大学 | Aerodynamic optimization method of leading edge slats position and trailing edge flap position of two-dimensional three-section airfoil profile |
| CN109521673A (en) * | 2018-10-25 | 2019-03-26 | 北京航空航天大学 | A kind of section sliding formwork suppressing method of two-dimensional wing Flutter Problem |
| CN113886967A (en) * | 2020-10-09 | 2022-01-04 | 北京航空航天大学 | Multi-cruise-condition aeroelasticity optimization method for large aircraft wing |
| CN113886967B (en) * | 2020-10-09 | 2023-07-07 | 北京航空航天大学 | Aerodynamic elasticity optimization method for large aircraft wing under multi-cruise working condition |
| CN112555451A (en) * | 2020-10-29 | 2021-03-26 | 成都成高阀门有限公司 | Pressing process parameter determination method for all-welded ball valve seat sealing groove and semi-finished valve seat |
| CN112555451B (en) * | 2020-10-29 | 2022-03-18 | 成都成高阀门有限公司 | Pressing process parameter determination method for all-welded ball valve seat sealing groove and semi-finished valve seat |
| CN112464372A (en) * | 2020-11-25 | 2021-03-09 | 西北工业大学 | Design sensitivity engineering numerical method for control surface efficiency of aileron of elastic wing |
| CN112464372B (en) * | 2020-11-25 | 2021-08-27 | 西北工业大学 | Design sensitivity engineering numerical method for control surface efficiency of aileron of elastic wing |
| CN112765731A (en) * | 2021-01-19 | 2021-05-07 | 北京航空航天大学 | Aeroelasticity optimization method of curved fiber composite structure considering local buckling |
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Application publication date: 20140326 |