Project : tropics
Section: New Results
Keywords : optimum design, optimal control, gradient, adjoint model.
Now that simulation is well mastered by research groups in industry, optimization is naturally the next frontier. Optimization problems in aerodynamics are still very difficult, because they require a enormous computing power. To meet these needs, our investigations in AD are focused on the reverse mode, which is an elegant way to obtain the adjoints that optimization uses.
The reverse mode, and the subsequent adjoint state, are the best way to get the gradients when the number of parameters is large. This corresponds to what happens in industry. For example, optimizing only a dozen shape parameters will not produce an optimal shape for an aircraft, because an accurate description of a shape requires hundreds of parameters. Some shape parameters can be functions defined on a surface or a volume. Therefore the number of scalar parameters depends on the discretization chosen, and is a priori large.
Therefore, practical application of AD to control problems requires that we consider the following issues:
efficient computation of a large scale adjoint system
efficient optimization algorithms for large scale systems
efficient preconditioners for this optimization.
New application on ship sail optimization have been also completed, published  and was the theme of a PhD thesis (Marco Michieli de Vitturi) in the partner laboratory in Pisa.