One of the main difficulties of optimization is the computational cost associated with the evaluation of numerical models. In order to overcome this problem, many works have emerged in the last few years based on model reduction methods, surrogate model and multifidelity and their coupling. This special issue focuses on these growing tools.
Stress-constrained topology optimization using approximate reanalysis with on-the-fly reduced order modeling
Most of the methods used today for handling local stress constraints in topology optimization, fail to directly address the non-self-adjointness of the stress-constrained topology optimization problem. This in...