Aircraft aerodynamic configuration optimum design method based on improved parallel DE algorithm

Abstract

The invention discloses an aircraft aerodynamic configuration optimum design method based on the improved parallel DE algorithm. The method is used for achieving aircraft aerodynamic configuration optimum design. According to the method, different DE algorithm patterns are integrated in a pattern pool, and therefore the DE pattern selection range is expanded; besides, a dynamic parameter pattern is newly adopted, and more effective research on a large area of unknown solution spaces can be achieved through the pattern. In the iteration process, test vectors are generated through mutation operation and interlace operation; individual codes in a species group are reduced to corresponding aircraft configurations, the CFD computational analysis process is introduced to an individual fitness evaluation stage and serves as a basis for selection on a new generation of individuals, therefore, the design result analysis process and the parameter modification process can be effectively combined, and the design cycle is shortened; offspring groups are generated through selection operation. In view of the characteristic that the computing amount in the aircraft aerodynamic configuration design process is large, the parallel computing mechanism is introduced into the method, and therefore the method greatly shortens algorithm running time and improves design efficiency.

Description

technical field [0001] The invention relates to the technical field of aircraft aerodynamic shape optimization design, and the technical field of computer simulation and optimization, in particular to a method for optimizing the design of aircraft aerodynamic shape based on an improved parallel DE (Differential Evolution, differential evolution) algorithm. Background technique [0002] The importance of designing an aerodynamic shape with excellent performance is self-evident for the entire aircraft design. [0003] Traditional aircraft aerodynamic shape design methods are based on wind tunnel tests or CFD analysis results, mostly relying on experience-based "Cut and Try" method. Today's required aircraft performance indicators are getting higher and higher, and there are more and more indicators, which pose a severe challenge to these traditional aerodynamic design methods and means. First of all, the traditional design method is mainly based on experience or a large numbe...

AI Technical Summary

Problems solved by technology

For simple mutation operations and one-to-one competitive survival strategies, the differential evolution algorithm is implemented with real-number encoding, which greatly reduces the complexity of genetic operations

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