AEROSPACE SIMULATIONS LABORATORY

Robust Aerospace Design

Under this research topic, our main objective is to integrate the advanced computationally efficient uncertainty quantification methods based on stochastic expansions to the design of aerospace vehicles. The integration of uncertainty quantification to design and optimization enables robust optimized aerospace systems or vehicle configurations with performances that are insensitive to the variations in the input parameters (e.g., operating conditions, geometry, etc.) and uncertainties in physical models (e.g., turbulence models, transport quantities, etc.). Another objective of this research is to extend the robust optimization techniques developed to the MDO of aerospace vehicles, which includes the simultaneous consideration of sub-systems (e.g., aero, propulsion, structures, thermal response) in a constraint optimization process. In addition to uncertainty quantification, our recent efforts have been focused on the development of physics-based multi-fidelity design approaches for MDO to achieve desired accuracy in the final design with computational efficiency.

Selected publications on the research topic:

1. Y. Zhang, S. Hosder, L. Leifsson, and S. Koziel, "Robust Airfoil Optimization Under Inherent and Model-Form Uncertainties Using Stochastic Expansions," 50th AIAA Aerospace Sciences Meeting and Exhibit, Paper No. AIAA-2012-0056, Nashville, TN, Jan. 2012.

2. S. Hosder, "Stochastic Response Surfaces Based On Non-Intrusive Polynomial Chaos for Uncertainty Quantification," International Journal of Mathematical Modeling and Numerical Optimization, Vol. 3., No. 1/2, pages 117-139, 2012.

3. T. Winter, B. Bettis, and S. Hosder, "Development of an Efficient Uncertainty Quantification Framework Applied to an Integrated Spacecraft System," AIAA Space 2011 Conference and Exposition, Paper No. AIAA-2011-7155, Long Beach CA, 27-29 September 2011.