Multidisciplinary design optimization of a 3D composite hydrofoil via variable accuracy architecture

An accurate multidisciplinary analysis (MDA) and design optimization (MDO) process coupling hydro-and structural dynamics is required to assess and design flexible marine structures. When performing MDO, the large computational cost associated to high-fidelity simulations within MDA can be mitigated by reducing the number of design variables and using surrogate models. An architecture for performing efficient MDO is here presented. Sequential and variable accuracy surrogate-based optimization is performed driven by a multi-criterion adaptive sampling method. The latter is guided by the objective function value and the uncertainty associated to both multidisciplinary coupling (in the MDA) and surrogate model prediction. Multidisciplinary consistency and accurate surrogate-model training are achieved at the end of the MDO process. The Karhunen-Loève expansion is used to assess the design space and reduce its dimensionality preserving the original geometric variability. The method is suitable for derivative-free optimization allowing for the use of expensive black box simulation tools. Outer shape and inner fiber layout of a flexible 3D hydrofoil in carbon fiber-reinforced plastic are optimized aiming at minimizing the drag.