The paper is entitled “Least Squares Approximation-based Polynomial Chaos Expansion for Uncertainty Quantification and Robust Optimization in Aeronautics”. The presentation is scheduled for the 17^th of June 2020 from 3:00 PM to 4:00 PM Eastern Time, USA, during the session MDO-16 Non-deterministic Design Methods and Applications.

In the framework of multi-physics problems and demanding high-fidelity simulations, the presentation will address the techniques for performing uncertainty quantification and propagation at reasonable costs, without requiring the development of dedicated solvers. Non-Intrusive Polynomial Chaos is a prime candidate, but not all of its variants are equally accurate and cost-effective. Efficiency and flexibility of Least Squares surrogates and gradient-enhanced Polynomial Chaos expansions for Uncertainty Quantification and Robust Optimization will be discussed employing an in-house framework. Advantages of the proposed methods over Collocation approaches will be demonstrated by comparing the results for a selection of algebraic test cases and for the shape optimization of the NACA 0012 airfoil under transonic conditions.

The full programme can be found on the conference website.