Single-objective and Multi-objective Robust Optimization of Airfoils using Adjoint Solutions

Abstract

The approach shown here is based on the use of the Adjoint solver to drive the shape modification of airfoils: the adjoint sensitivities are used to guide intelligent design modifications and improve the product perfomance. This work demonstrates that the adjoint sensitivities can be manipulated to perform not only single-objective optimization but also multi-objective optimization. Additionally when uncertainties are not neglected adjoint sensitivities will be demonstrated to be able to drive robust optimization procedures.

Aerodynamic shape optimization of airfoils at ultra-low Reynolds numbers

“…In the design process, as the airfoil geometry is changed a new grid is generated by a mesh morphing scheme which ensures smooth repositioning of the grid points [21]. Convergence is said to have occurred when there is no further improvement in the values of the objective function with design iterations.…”