Conceptual Aircraft Design – A Genetic Search and Optimization Approach

With recent advancements of computers and the advent of a search and optimization tool such as the genetic algorithm (GA), the ability to manipulate numerous aircraft design parameters in reasonable amount of time becomes feasible. It is from this standpoint that when one examines the aircraft design process, that is, the lengthy time and effort spent creating and integrating aerodynamics codes, sizing routines and performance modules, that the GA becomes beneficial. Consequently, a GA was created and employed as a tool to explore possible aircraft geometries that are more efficient and less costly than an existing design. The adaptive penalty method is employed in the GA to handle all constraints imposed on the design. In addition, the effects of the adjustments for varying degree of selection and crossover intensities and types on the aircraft evolutionary process are studied. A design study is also conducted to compare the GA optimized aircraft shape and configuration with that of the existing aircraft. Results indicated that the GA is a powerful multi-disciplinary optimization and search tool, that is capable of managing and reforming numerous aircraft design parameters, to arrive at aircraft conceptual designs that are both efficient and cost effective. *Research Assistant, School of Aerospace Engineering **Assistant Professor, School of Aerospace Engineering, and member of AIAA NOMENCLATURE 0 W = gross weight (lbs.) r C = wing root chord (ft) t C = wing tip chord (ft) b = wing span (ft) S = gross wing area ( 2 ft ) ht S = horizontal tail area ( 2 ft ) fus l = length of the fuselage (ft) t S = gross tail area ( 2 ft ) h V = horizontal tail volume coefficient v V = vertical tail volume coefficient F = stick force (lb.) α m C = change of pitching moment coefficient with angle of attack mo C = coefficient of moment at zero angle of