Surrogate-assisted optimization for augmentation of finite element techniques

Abstract The application of finite element techniques for the analysis and optimization of complex thermo-mechanical structures typically involves highly nonlinear models for material characterization, tribological contact, large deformation, damage, etc. These nonlinearities usually call for a higher order spatio-temporal discretization, including a large number of elements and time-steps in order to provide good convergence and sufficiently accurate simulation results. Unfortunately, this inevitably leads to many expensive simulations in terms of cost and time if an optimization or adaption of design parameters has to be done. In this work, a surrogate-assisted optimization algorithm is utilized to find the setting of design parameters, which would lead to maximum damage in a simple tensile testing scenario involving a notched specimen with as few FEM simulations as possible.