Multidisciplinary design optimization of a generic b-pillar under package and design constraints

This article introduces a novel constraining approach for structural optimization,
which aims to support the conceptual engineer during the early embodiment phase for structural lightweight design. It reduces the time spent on structural engineering studies by enabling optimization algorithms to detect geometric intersections by analyzing the mesh information. This article reviews  approaches from the literature focusing on CAD-environments, sampling methods, data analytics and optimization techniques for design and sizing optimization with FE-models. The evaluated approaches are integrated into a Python-based optimization environment. Accordingly, the introduced methodology enables the environment to handle geometric infeasible designs. The presentation of the first results focuses on the feasibility of structural assemblies and the results  demonstrate the viability of the NSGA-II for optimization tasks. The example considers the design of a generic b-pillar structure under crash-safety requirements. Using this approach, the NSGA-II algorithm avoids geometric
infeasible areas and comparably increases structural performance.