CN111177855A

CN111177855A - Pneumatic structure solving method and system in global aeroelasticity optimization

Info

Publication number: CN111177855A
Application number: CN201911412666.7A
Authority: CN
Inventors: 刘艳
Original assignee: Shenyang Aircraft Design and Research Institute Aviation Industry of China AVIC
Current assignee: Shenyang Aircraft Design and Research Institute Aviation Industry of China AVIC
Priority date: 2019-12-31
Filing date: 2019-12-31
Publication date: 2020-05-19
Anticipated expiration: 2039-12-31
Also published as: CN111177855B

Abstract

The application provides a method for solving a pneumatic structure in global aeroelasticity optimization, which comprises the following steps: constructing a proxy model for full-order pneumatic/structural coupling solution, wherein the proxy model has design variables and target variables, and the target variables can be obtained through mutual iteration of pneumatic solution and structural solution until the result is converged, wherein: according to the wing bending deformation and the torsion deformation of the design variables and solving by an intrinsic orthogonal decomposition method, the pressure coefficient distribution of the wing surface is obtained; transmitting the pressure coefficient of the surface of the wing to be distributed in a structural finite element model, and solving the structural finite element model to obtain structural elastic deformation, wherein the structural elastic deformation comprises wing bending deformation and torsion deformation; interpolating the elastic deformation of the structure to a pneumatic surface grid, updating the pneumatic grid, and solving by an intrinsic orthogonal decomposition method again to obtain the pressure coefficient distribution of the surface of the wing; and repeating the process until the elastic deformation of the aerodynamic flow field and the structure is converged.

Description

Pneumatic structure solving method and system in global aeroelasticity optimization

Technical Field

The application belongs to the technical field of aircraft aerodynamic/structural design, and particularly relates to a method and a system for solving an aerodynamic structure in global aeroelasticity optimization.

Background

In a global aeroelasticity optimization system of a high-aspect-ratio wing aircraft, the low efficiency of an optimization algorithm results in the need of carrying out pneumatic/structural coupling solution on a large number of different design parameter configurations in the optimization process of the system so as to obtain the pneumatic characteristic closer to the actual flight state. However, the aerodynamic/structural coupling solution, especially the RANS (reynolds average equation) -based high-precision aeroelastic solution, needs to occupy large computational resources, and brings challenges to the global three-dimensional wing aeroelastic optimization. In order to increase the practicability of the global aeroelastic optimization design, a proxy Model (simulation Model) is usually adopted in the optimization system for fast prediction, instead of a full-order pneumatic/structural coupling solution. After the agent model is introduced, the efficiency of the global aeroelasticity optimization system is greatly improved, and the practicability is obviously enhanced.

However, the proxy model-based aeroelasticity optimization process still has two links requiring a certain number of pneumatic/structural coupling solutions: the first link is a sampling link which is necessary for constructing a proxy model; the second link is a sample updating link which is carried out in order to ensure that the model precision can adapt to the development of the optimization process in the optimization process. In order to ensure the prediction accuracy of the agent model, the number of samples for constructing the agent model is often in an exponential relation with the dimension of the design variable, and the larger the dimension of the design variable is, the more the number of samples required for updating the agent model in the optimization process is. Therefore, hundreds or even thousands of pneumatic/structural coupling solutions are needed in the process of performing three-dimensional wing aeroelasticity optimization, and even if a proxy model is adopted, a large amount of computing resources are consumed, so that the practicability of the optimization system is adversely affected. Therefore, on the basis of the proxy model, there is still a need to further shorten the time required for the pneumatic/structural coupling solution in the global aeroelastic optimization system.

Disclosure of Invention

The present application is directed to a method and system for solving a pneumatic structure in global aeroelastic optimization, which solves or reduces at least one of the problems of the related art.

In one aspect, the technical solution provided by the present application is: a method of solving a pneumatic structure in global aeroelastic optimization, the method comprising:

constructing a proxy model for full-order pneumatic/structural coupling solution, wherein the proxy model has design variables and target variables, and the target variables can be obtained through mutual iteration of pneumatic solution and structural solution until the result is converged, wherein:

according to the wing bending deformation and the torsion deformation of the design variables and solving by an intrinsic orthogonal decomposition method, the pressure coefficient distribution of the wing surface is obtained;

transmitting the pressure coefficient of the surface of the wing to be distributed in a structural finite element model, and solving the structural finite element model to obtain structural elastic deformation, wherein the structural elastic deformation comprises wing bending deformation and torsion deformation;

interpolating the elastic deformation of the structure to a pneumatic surface grid, updating the pneumatic grid, and solving by an intrinsic orthogonal decomposition method again to obtain the pressure coefficient distribution of the surface of the wing;

and repeating the process until the elastic deformation of the aerodynamic flow field and the structure is converged.

In the method of the application, the distribution of the wing surface pressure coefficient is predicted by adopting a mode of superposing POD basis vectors and basis coefficients.

In the method of the present application, the POD basis coefficient after the structure elastic deformation is obtained from the design variable and the structure elastic deformation amount in the proxy model.

In the method of the present application, the interpolation is RBF interpolation.

On the other hand, the technical scheme provided by the application is as follows: a method for a system of solution of aerodynamic structures in global aeroelastic optimization, the system comprising:

the model construction module is used for constructing a proxy model for full-order pneumatic/structural coupling solution, the proxy model is provided with design variables and target variables, and the target variables can be obtained through mutual iteration of pneumatic solution and structural solution until the result is converged, wherein:

the first solving unit is used for solving according to the wing bending deformation and the torsion deformation of the design variables and by an intrinsic orthogonal decomposition method to obtain the distribution of the pressure coefficient of the surface of the wing;

the second solving unit is used for transmitting the pressure coefficient of the surface of the wing to be distributed in a structural finite element model, and solving the structural finite element model to obtain structural elastic deformation, wherein the structural elastic deformation comprises wing bending deformation and torsion deformation;

the third solving unit is used for interpolating the elastic deformation of the structure into the aerodynamic surface grid, updating the aerodynamic grid and solving by an intrinsic orthogonal decomposition method again to obtain the pressure coefficient distribution of the surface of the wing;

and the circulating processing unit is used for repeating the process until the elastic deformation of the pneumatic flow field and the structure is converged.

In the system of the present application, the distribution of the wing surface pressure coefficients is predicted by superimposing POD basis vectors and basis coefficients.

In the system of the present application, the POD basis coefficient after the structure elastic deformation is obtained from the design variable and the structure elastic deformation amount in the proxy model.

In the system of the present application, the interpolation is RBF interpolation.

In a third aspect, the technical solution provided by the present application is: a computing processing device, the computing processing device comprising: at least one processor; at least one memory; and a computer program stored on the memory and executable by the processor, for implementing the method as claimed in any one of the above when the computer program is executed by the processor.

In a final aspect, the present application provides the following technical solutions: a readable storage medium, storing a computer program which, when executed by a processor, is adapted to carry out the method of any of the above.

Drawings

In order to more clearly illustrate the technical solutions provided by the present application, the following briefly introduces the accompanying drawings. It is to be expressly understood that the drawings described below are only illustrative of some embodiments of the invention.

Fig. 1 is a schematic diagram of the process of the present application.

Fig. 2 is a frame diagram of the POD-Surrogate-based pneumatic/structural coupling solution method of the present application.

Fig. 3 is a pressure coefficient cloud chart of two optimized configurations of uCRM + VCCTEF in the present application.

Fig. 4 is a comparison of the distribution of the stress coefficients of the spanwise cross section of two optimized uCRM + VCCTEF configurations in the examples of the present application.

Fig. 5 is a schematic diagram of the system components of the present application.

Detailed Description

In order to make the implementation objects, technical solutions and advantages of the present application clearer, the technical solutions in the embodiments of the present application will be described in more detail below with reference to the drawings in the embodiments of the present application.

The method starts from a basic principle, and the pneumatic/structure coupling solving process is a process from continuous mutual iteration of pneumatic solving and structure solving to convergence, and in the process, compared with the pneumatic flow field solving, the time required by the structure elastic deformation solving can be ignored. Therefore, shortening the aeroelastic optimization process is the most effective method for shortening the solution time of the pneumatic/structural coupling, and generally only three aspects can be tried: the method has the advantages of reducing the number of pneumatic/structural coupling iterations, replacing pneumatic solving with an approximation method, and shortening the solving time of a single pneumatic flow field. Since the iterative solution times are not artificially controlled depending on whether convergence occurs, if the second aspect or the third aspect can be broken through, the pneumatic/structural coupling solution time in the aeroelastic optimization process can be further shortened on the basis of the proxy model. The existing pneumatic/structural coupling solution is carried out by adopting a mode of mutually and continuously iterating and solving a flow field and a structure, namely: firstly, CFD solution is carried out to obtain wing surface load; then transferring the elastic deformation to a structure finite element model to solve the elastic deformation of the structure; interpolating the elastic deformation of the structure onto the pneumatic surface grid and updating the pneumatic grid; and (5) performing CFD solving again, and repeating the process until the aerodynamic flow field and the elastic deformation are converged. If the surface load of the model at the moment can be rapidly predicted through the elastic deformation of the structure, the long-time CFD calculation is replaced, and the aeroelasticity solving time is greatly shortened.

Based on the above content, the application provides a pneumatic structure coupling solving method, so as to solve the problem that the pneumatic structure coupling solving is time-consuming in the global aeroelasticity optimization of the aircraft in the prior art, the method can shorten the time required by the pneumatic/structural coupling solving in the aeroelasticity optimization design, can realize extremely quick and accurate initial flow field prediction, and further shorten the time required by the pneumatic/structural coupling solving in the global aeroelasticity optimization design system on the basis of a proxy model, so that the practicability of the aeroelasticity optimization system is enhanced, and the level of the aeroelasticity optimization design of the aircraft is improved.

As shown in fig. 1, the method for solving a pneumatic structure in global aeroelasticity optimization provided by the present application mainly includes the following processes:

s1, establishing a proxy model for the full-order pneumatic/structural coupling solution,

the method is based on an intrinsic Orthogonal Decomposition (POD) method to replace the CFD calculation in the static aeroelastic analysis, and specifically includes:

s2, rapidly identifying the distribution of the pressure coefficient Cp (x) of the wing surface according to the design variables or the bending deformation and the torsional deformation of the wing;

s3, calculating and transmitting aerodynamic load information to a structure finite element grid through Radial Basis Function (RBF);

s4, obtaining wing bending deformation and torsion deformation through structural statics analysis, and identifying the distribution of the wing surface pressure coefficient based on the POD technology;

s5, and iteration is carried out in sequence until convergence, so that the method can greatly save the time for analyzing the static bomb.

In the application, when the POD technology is used for identifying the wing surface pressure coefficient, in order to save calculation time, the distribution of the wing surface pressure coefficient is predicted in a mode of superposing POD basis vectors and basis coefficients, and the POD basis coefficients after elastic deformation are quickly obtained according to design variables and elastic deformation by adopting the proxy model technology. Finally, a static aeroelasticity reduced order model (SAEROM) coupling the POD and the proxy model is constructed, a frame diagram is shown in FIG. 2, and the combined use of the proxy model and the POD technology in the diagram replaces a grid deformation module and full-order CFD analysis, so that the pneumatic/structural coupling solving time is greatly saved.

In the application, the accuracy influence factors of a POD-Surrogate model for predicting the flow field after elastic deformation are researched by elastic deformation mathematical modeling

And completely performing pneumatic/structural coupling iteration, establishing a brand-new POD-Surrogate model different from the pneumatic/structural coupling initial flow field prediction model, quickly predicting the flow field after the structure is elastically deformed, and using the model after each structural elastic deformation. However, the POD-Surrogate model for predicting the flow field after elastic deformation is constructed in different ways, and before the model is constructed, the elastic deformation needs to be mathematically modeled, and the elastic deformation of the model is described as much as possible by using limited variables. A typical control surface method is selected in the application, the bending deformation and the torsional deformation of the control surface are respectively extracted, and the elastic deformation of the structure is described by using the limited control surface deformation. Through detailed research on the influence of parameters such as the number of control surfaces and the distribution of the control surfaces on the model precision, the POD-simulation model of the deformed flow field is established.

Actual effect of POD-Surrogate-based static aeroelasticity accelerated solving method and effect verification in aeroelasticity optimization

An air-force/structure coupling solving acceleration method is established on the basis of a CFD program, and meanwhile, the acceleration method is applied to an aeroelasticity optimization design system, so that the actual improvement effect of the reliability and the calculation efficiency of the aeroelasticity optimization design system is verified.

In an embodiment of the present application, the method of the present application is introduced into a CRM configuration (CRM configuration framework configuration) of a continuously Variable camber Trailing Edge control surface system (VCCTEF), for example, to optimally design a VCCTEF control surface deflection angle. In order to compare with the computing resources consumed by the traditional optimization design method, the optimization design only adopting the proxy model is also performed in the embodiment.

The calculation state in this embodiment: the Mach number Ma is designed to be 0.85, and the Reynolds number Re of the average pneumatic chord length is designed to be 5.0e⁶And the fixed lift coefficient Cl is 0.5, the structure model adopts a finite element model, and the constraint that the difference between deflection angles of adjacent control planes is not more than 3.0 degrees is considered. Selecting NSGA-And the II intelligent optimization algorithm optimizes the control surface deflection angle distribution of the VCCTEF system to achieve the purpose of minimum resistance, the population number of each generation is 200, and the optimized generation number is 30.

In order to compare with the computational resources consumed by the conventional optimization design method, in this embodiment, the same number of snapshots (298 snapshots) are selected to obtain POD basis vectors and basis coefficients corresponding to pressure distribution coefficients, proxy models Kriging1 and Kriging2 are respectively established, a saorom static aeroelastic analysis system is established, and sample points required by the optimization design are generated.

The table 1 shows the aerodynamic characteristic comparison of the uCRM + VCCTEF configuration before and after optimization, and the resistance coefficient of the optimized configuration based on the SAEROM is reduced by 0.8% compared with the original configuration, and the lift-drag ratio is increased; the resistance coefficient is increased by only 0.3counts relative to the optimized configuration obtained based on the Kriging agent model.

TABLE 1 comparison of aerodynamic characteristics of uCRM + VCCTEF configuration before and after optimization

ID	Cd	Cl/Cd	AOA
				Original uCRM	0.02337	21.396	2.137
OPT_Kriging	0.02316	21.579	2.042
				OPT_SAEROM	0.02319	21.561	2.053

Fig. 3 shows a comparison of pressure coefficient cloud charts of two optimized uCRM + VCCTEF configurations, and it can be seen that the pressure coefficient distribution of the inner wing section of the optimized configuration is very close, and the pressure coefficient distribution of the trailing edge of the outer wing section is different.

Fig. 4 shows six spanwise profile pressure coefficient distributions of two optimized uCRM + VCCTEF configurations, and it can be seen that the spanwise profile pressure coefficient distributions of the two optimized configurations are similar in form and are closer in value, but the difference in detail is that the pressure coefficient values of sections of 10.911m in the spanwise direction y at wing kin are almost the same; the pressure coefficients of five sections of the outer wing section are different, and the initial position and the strength of the shock wave are slightly different.

Table 2 shows the calculation resources required for calculating the sample points in the optimization process of two optimization systems, and it can be seen that the VCCTEF system optimization process based on SAEROM saves about 60% of the calculation time compared with the optimization based on the Kriging agent model, the optimization cycle is obviously shortened, and the optimization efficiency is significantly improved.

TABLE 2 comparison of computational resource consumption for optimization processes of two optimization methods

Note: d is day, h is hour, m is minute.

As shown in fig. 5, the present application further provides a method for solving a pneumatic structure in global aeroelastic optimization, where the system includes:

a model construction module 10, configured to construct a proxy model for full-order pneumatic/structural coupling solution, where the proxy model has design variables and target variables, and the target variables can be obtained through mutual iteration between pneumatic solution and structural solution until a result converges, where:

the first solving unit 11 is used for solving according to the wing bending deformation and the torsion deformation of the design variables and by an intrinsic orthogonal decomposition method to obtain the distribution of the pressure coefficient of the wing surface;

the second solving unit 12 is used for transmitting the pressure coefficient distribution of the surface of the wing on the structural finite element model, and solving the structural finite element model to obtain structural elastic deformation, wherein the structural elastic deformation comprises wing bending deformation and torsion deformation;

the third solving unit 13 is used for interpolating the elastic deformation of the structure into the aerodynamic surface grid, updating the aerodynamic grid, and solving again through an intrinsic orthogonal decomposition method to obtain the pressure coefficient distribution of the surface of the wing;

and the circulation processing unit 14 is used for repeating the process until the pneumatic flow field and the elastic deformation of the structure are converged.

In addition, the present application also provides a computing processing device, including: at least one processor; at least one memory; and a computer program stored on the memory and executable by the processor, for implementing a method as in any one of the above when the computer program is executed by the processor.

Finally, the present application also provides a readable storage medium, in which a computer program is stored, which computer program, when being executed by a processor, is adapted to carry out the method of any of the above.

The above description is only for the specific embodiments of the present application, but the scope of the present application is not limited thereto, and any changes or substitutions that can be easily conceived by those skilled in the art within the technical scope of the present application should be covered within the scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.

Claims

1. A method for solving a pneumatic structure in global aeroelastic optimization, which is characterized by comprising the following steps:

2. The method for solving aerodynamic structures in global aeroelastic optimization according to claim 1, wherein the distribution of wing surface pressure coefficients is predicted by superimposing POD basis vectors and basis coefficients.

3. The method for solving an aerodynamic structure in global aeroelastic optimization according to claim 2, wherein POD basis coefficients after the elastic deformation of the structure are obtained from the design variables and the elastic deformation amount of the structure in the proxy model.

4. The method for solving an aero structure in global aeroelastic optimization according to claim 1, wherein the interpolation is RBF interpolation.

5. A system for solving a pneumatic structure in global aeroelastic optimization, the system comprising:

6. The system according to claim 5, wherein the distribution of the airfoil surface pressure coefficients is predicted by superimposing POD basis vectors and basis coefficients.

7. The system according to claim 6, wherein POD basis coefficients after the elastic deformation of the structure are obtained in the proxy model according to the design variables and the elastic deformation amount of the structure.

8. The method of solving an aerodynamic structure in global aeroelastic optimization according to claim 5, wherein said interpolation is RBF interpolation.

9. A computing processing device, characterized in that the computing processing device comprises

At least one processor;

at least one memory; and

a computer program stored on the memory and executable by the processor, for implementing the method of any one of claims 1 to 4 when the computer program is executed by the processor.

10. A readable storage medium, storing a computer program, wherein the computer program, when executed by a processor, is adapted to carry out the method of any one of claims 1 to 4.