AIRCRAFT CONCEPTUAL DESIGN USING GENETIC ALGORITHMS

Nomenclature Aircraft design is a complex multidisciplinary process to determine aircraft configuration variables that satisfy a set of mission requirements. It is very hard for aircraft designers to foresee the consequences of changing certain variables. Furthermore, conventional optimization processes are limited by the type and number of parameters used, resulting in sub-optimal designs. The objective of this research is to test the functionality and implementation of a multidisciplinary aircraft conceptual design optimization method using an adaptive genetic algorithm (GA), as a feasible alternative to the existing sizing and optimization methods. To illustrate the approach the algorithm is used to optimize a medium range commercial aircraft, with takeoff weight as an optimization goal, subjected to constraints in performance and geometric parameters. Adaptive and traditional formulations for the handling of constraints by the GA are tested and compared. Results show the ability of the adaptive GA to unbiased search through the design space of aircraft conceptual designs, leading to more viable aircraft configurations than the traditional GA approach at reduced timeframes, with a lower cost than current aircraft design optimization procedures.

[1]  Daniel P. Raymer,et al.  Aircraft Design: A Conceptual Approach , 1989 .

[2]  D. Fogel,et al.  A comparison of methods for self-adaptation in evolutionary algorithms. , 1995, Bio Systems.

[3]  Yechiel Crispin.  Aircraft conceptual optimization using simulated evolution , 1994 .

[4]  Augustine R. Dovi,et al.  Aircraft design for mission performance using nonlinear multiobjective optimization methods , 1989 .

[5]  Brett Malone,et al.  Aircraft concept optimization using the global sensitivity approach and parametric multiobjective figures of merit , 1992 .

[6]  E. Torenbeek,et al.  Synthesis of Subsonic Airplane Design , 1979 .

[7]  John E. Angus,et al.  Optimal mutation probability for genetic algorithms , 1995 .

[8]  David E. Goldberg,et al.  Genetic Algorithms in Search Optimization and Machine Learning , 1988 .

[9]  William A. Crossley,et al.  Conceptual design of helicopters via genetic algorithm , 1996 .

[10]  Alice E. Smith,et al.  Penalty guided genetic search for reliability design optimization , 1996 .

[11]  John H. Holland,et al.  Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control, and Artificial Intelligence , 1992 .

[12]  Steven A. Brandt,et al.  Introduction to Aeronautics: A Design Perspective , 1997 .

[13]  William A. Crossley,et al.  COMMERCIAL TRANSPORT AIRCRAFT CONCEPTUAL DESIGN USING A GENETIC ALGORITHM BASED APPROACH , 1998 .

[14]  Brett Malone,et al.  Multidisciplinary optimization in aircraft design using analytic technology models , 1991 .

[15]  G. L. Giles,et al.  Aerospace engineering design by systematic decomposition and multilevel optimization , 1984 .

[16]  John H. Holland,et al.  Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control, and Artificial Intelligence , 1992 .

[17]  Dolf Bos.  Multidisciplinary Design Optimization of a supersonic transport aircraft using a hybrid genetic/gradient-based algorithm , 1996 .