Observations regarding the use of advanced computational fluid dynamics (CFD) analysis, sensitivity analysis (SA), and design codes in gradient-based multidisciplinary design optimization (MDO) reflect wr perception of the interactions required of CFD and our experience in recent aerodynamic design optimization studies using CFD. Sample results from these latter studies are summarized for conve...

This paper examines the viability of using the combination of the vortex lattice method for aerodynamic performance prediction with a genetic algorithm for the optimization of the aerodynamic performance of horizontal axis wind turbine blades. The work described in this paper includes the adaptation of a vortex lattice code designed to predict propeller performance to wind turbine performance p...

* Assistant Professor † Assistant Professor with a joint appointment in the Department of Industrial & Manufacturing Engineering. Corresponding Author. Phone/fax: (814) 863-7136/4745. Email: [email protected]. Member AIAA. ‡ Post-doctoral Research Fellow § Associate Professor and AIAA Member Abstract Multidisciplinary design instances arise when the performance of large-scale, complex systems can be...

Evolutionary Algorithm (EA) is applied to a practical three-dimensional shape optimization for aerodynamic design of an aircraft wing. Aerodynamic performances of the design candidates are evaluated by using the three-dimensional compressive Navier-Stokes equations. A structural constraint is introduced to avoid an apparent solution of zero thickness wing for low drag in high speeds. To overcom...

Aerodynamic shape optimization based on high-fidelity models is a computational intensive endeavor. The majority of the computational time is spent in the flow solver, and in the gradient calculation. In this paper, we present two approaches for reducing the overall computational cost of the optimization. The techniques are tested using the Common Research Model wing benchmark defined by the Ae...