SBIR-STTR Award

This proposal develops a two-dimensional, FUN3D-based, flow-structure-coupled adjoint optimization framework capable of handling chaotic dynamics, and validate this framework on an elastic tandem airfoil configuration in chaotic flow. To overcome the challenge of sensitivity analysis in chaotic flows, we will develop in this proposal the adjoint NI-LSS algorithm. This algorithm is the discrete adjoint of the tangent NI-LSS method that we developed previously. We have shown that the tangent NI-LSS method is superior to finite difference methods in sensitivity analysis of statistics in chaotic flows. The adjoint NI-LSS algorithm proposed here is consistent to the tangent NI-LSS algorithm to machine precision, allowing easy verification; it can have significantly lower computation cost than the tangent NI-LSS method in optimization with many design variables. The resulting sensitivities to shape and sizing design variables will be validated against very-long-time finite difference calculations. We plan to extend this two-dimensional, FUN3D-based, flow-structure-coupled adjoint optimization framework to three-dimensions in Phase II.

The overall technical objective of the Phase II effort is to develop a FUN3D-based adjoint framework using the Non-Intrusive Least Squares Shadowing (NI-LSS) for sensitivity analysis of complex configurations when exposed to buffet loads produced by chaotic flows. The FUN3D-based adjoint framework will be capable of generating buffet loads sensitivities with respect to both shape and sizing design variables. The applicability of the FUN3D-based adjoint framework to complex configurations will be demonstrated on F-15 C/D. Specifically, the component loads sensitivity on the vertical tail of F-15 C/D in chaotic flow will be validated with the trend of the primal solution statistics with respect to the shape of the leading edge extension and wing leading edge sweep angle as well as the structure properties of the F-15 C/D vertical tail.