An adaptive SVD–Krylov reduced order model for surrogate based structural shape optimization through isogeometric boundary element method

This work presents an adaptive Singular Value Decomposition (SVD)–Krylov reduced order model to solve structural optimization problems. By utilizing the SVD, it is shown that the solution space of a structural optimization problem can be decomposed into a geometry subspace and a design subspace. Any structural response of a specific configuration in the optimization problem is then obtained through a linear combination of the geometry and design...