Innovative optimization and design techniques for modern aircraft (manned or UAV/UCAV) and engine systems aiming at maximum performance in a multidisciplinary context (aerodynamic efficiency, safety, drag, losses, weight, strength, heat fluxes, emission, noise), are now rapidly moving from research labs to industrial real and virtual platforms. To reach concurrently this level of excellence, emergent optimization methodologies require more and more robust and efficient associated software for a daily use in industrial collaborative design environments.

This course intends to provide the basic concepts and tools behind this technology, both in single discipline (single point or multi point design) and multidisciplinary (fluid-structure interaction, fluid-acoustics, conjugate heat transfer) context. Subjects which will be treated in detail include: gradient based and steepest descent methods, adjoint methods, one shot or goal oriented methods, evolutionary/differential evolution algorithms on parallel environments, game strategies like Pareto Fronts and Nash Equilibrium, parameterization, surrogate and reduced-order modeling (Radial Basis functions, Artificial Neural Networks, Kriging), multifidelity modeling approaches, robust design.
The content of this Course is oriented towards junior and experienced engineers and researchers involved in the field of multi disciplinary design and looking for innovative numerical solutions - or set of solutions- for complex multi criteria optimization problems.