Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

A multi-objective optimization method for aircraft based on adaptive surrogate model

A multi-objective optimization and self-adaptive agent technology, applied in the field of aircraft design optimization, can solve problems such as large calculation time, achieve strong versatility, facilitate program development, and improve approximate accuracy

Active Publication Date: 2017-06-30
BEIJING INSTITUTE OF TECHNOLOGYGY
View PDF3 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0044] The present invention constructs a comprehensive preference function through the physical programming method, realizes the transformation of the multi-objective optimization problem into a single-objective optimization problem reflecting the design preference, and then constructs an adaptive proxy model for the comprehensive preference function and constraint conditions, replacing the high-precision analysis model, and solves the problem of In order to solve the problem of time-consuming calculation of optimal design, the augmented Lagrange multiplier method was used to transform the constrained problem into an unconstrained problem, and the genetic algorithm (GA) was used to solve the problem

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • A multi-objective optimization method for aircraft based on adaptive surrogate model
  • A multi-objective optimization method for aircraft based on adaptive surrogate model
  • A multi-objective optimization method for aircraft based on adaptive surrogate model

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0099] Embodiment 1: wing airfoil design optimization.

[0100]The optimization of the aerodynamic and stealth design of the wing airfoil is of great significance to improve the overall aerodynamic and stealth performance of the aircraft. With the development of computer technology, Computational Fluid Dynamics (CFD) technology and Computational Electromagnetics (CME) technology are widely used in airfoil design optimization. Taking NACA64A816 as the reference airfoil, the CST method is used to describe the coordinate points of the upper and lower surfaces of the airfoil. The design goal is to modify the shape of the airfoil curve to maximize the lift-to-drag ratio and radar cross section (RCS) under the premise of satisfying the constraint conditions. ) minimum. The constraints used include: the maximum thickness of the airfoil t * max Not less than the maximum thickness t of the initial airfoil max0 , to ensure the structural strength; the lift coefficient Cl is not less...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

No PUM Login to View More

Abstract

The invention discloses an aircraft multi-objective optimization method based on a self-adaptive agent model, relates to a multi-objective optimization method for treating complex aircraft design, and belongs to the field of aircraft design optimization. According to the aircraft multi-objective optimization method, an integrated preference function is constructed by use of a physical planning method to realize the conversion of the multi-objective optimization problem into a single-objective optimization problem reflecting design preference; next, the self-adaptive agent model is constructed from the integrated preference function and constraint conditions to take the place of a high-accuracy analysis model, and therefore, the problem of great time taken in calculation of optimization design is solved; finally, the constraint problem is converted into a non-constraint problem by use of an augmentation Lagrange multiplier method, and the non-constraint problem is solved by use of a genetic algorithm. The aircraft multi-objective optimization method has the advantages that the solving process of the aircraft multi-objective optimization method taking much time in calculation is simple and efficient, and therefore, a Pareto noninferior solution meeting the requirements of a user can be obtained quickly to shorten the design period of the aircraft, and the design cost is reduced. Besides, the aircraft multi-objective optimization method is high in universality and convenient for program development.

Description

technical field [0001] The invention relates to a multi-objective optimization method for processing complex product design, in particular to a multi-objective optimization method for processing complex aircraft design, belonging to the field of aircraft design optimization. Background technique [0002] In aircraft engineering design, it is often necessary to comprehensively consider various performance indicators of the aircraft system, and to deal with multi-objective optimization problems. In addition, it will consume a lot of time to call high-precision subject analysis models for performance calculations. Therefore, in the multi-objective optimization design of aircraft The existing weights are difficult to choose and time-consuming, and a set of practical optimization design methods is needed for design guidance. [0003] In dealing with multi-objective optimization problems, the commonly used methods are Pareto (Pareto) evolutionary algorithm, weighted coefficient me...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
no application Login to View More
Patent Type & Authority Patents(China)
IPC IPC(8): G06F17/50
Inventor 龙腾李学亮刘莉蒋孟龙
Owner BEIJING INSTITUTE OF TECHNOLOGYGY
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products