@article {pub3632,
	title = {Kriging-Assisted Topology Optimization of Crash Structures},
	author = {Elena Raponi AND Mariusz Bujny AND Markus Olhofer AND Nikola Aulig AND Simonetta Boria AND Fabian Duddeck},
	year = {2019},
	abstract = {Over the recent decades, Topology Optimization (TO) has become an important tool in the design and analysis of mechanical structures. Although structural TO is already used in many industrial applications, it needs much more investigation in the context of vehicle crashworthiness. Indeed, crashworthiness optimization problems present strong nonlinearities and discontinuities, and gradient-based methods cannot be applied. The aim of this work is to present an in-depth analysis of the novel Kriging-Guided Level Set Method (KG-LSM) for TO, which is based on an adaptive optimization strategy with Kriging model and a modified Constrained Expected Improvement (CEI) as the update criterion. The adopted representation using Moving Morphable Components (MMCs) allows for a significant reduction of the dimensionality of the problem and an efficient use of surrogate-based optimization techniques. A cantilever beam test case of different dimensionalities is used to validate the presented strategy, as well as identify its potential and limits. The method is then applied to a 2D crash test case, involving a cylindrical pole impact on a rectangular beam fixed at both ends. Compared to the state-of-the-art Covariance Matrix Adaptation Evolution Strategy (CMA-ES), this optimization algorithm demonstrates to be efficient in terms of convergence speed and performance of the optimized designs.},
	publisher = {Elsevier },
	journal = {Computer Methods in Applied Mechanics and Engineering}
}