Multidisciplinary Optimization of Transonic Wing Design Based on Evolutionary Algorithms Coupled with Cfd Solver

Evolutionary Algorithms (EAs) were applied to multidisciplinary transonic wing design optimizations. Aerodynamic performances of the design candidates were evaluated by using the three-dimensional compressive Navier-Stokes equations to guarantee an accurate model of the flow field. The wing structure is modeled on a box-beam to estimate the wing thickness and wing weight. To overcome enormous computational time necessary for the optimization, the computation was parallelized on Numerical Wind Tunnel at NAL in Japan and NEC SX-4 computers at Computer Center of Tohoku University in Japan. First, a singleobjective wing design optimization was demonstrated by maximizing L/D with a structural constraint using a real-coded Adaptive Range Genetic Algorithm (ARGA). Because the structural constraint imposed a tradeoff between minimizations of the induced drag and the wave drag, the present ARGA found a compromised but reasonable design. Then, a multiobjective wing design optimization is performed by minimizing both drag and weight with a constraint on CL using a Multiobjective Evolutionary Algorithm (MOEA). Due to the tradeoff between minimization of aerodynamic drag and minimization of weight of wing structure, the solution to this problem is not a single point but a set of compromised designs. The present MOEA successfully captured these solutions that revealed the tradeoff information. These results showed that EAs were promising approach to multidisciplinary optimization problems.