Increasing design flexibility by manually adapting the solution space for crashworthiness

Author:

Ascia PaoloORCID,Lange Volker A.ORCID,Duddeck FabianORCID

Abstract

AbstractThe solution space methodology, as presented in 2013, was meant to guide developers at the very beginning of the development process of a new mechanically crashworthy car. Several attempts were already made to use this methodology at later development stages. However, they all encountered problems related to its very strict and demanding corridors, thus constricting the design parameters. To allow more flexibility, two different approaches were proposed to relax the initial strict conditions. The first introduced temporal dependencies to widen the corridors. The second locally changed the corridors to adapt to the needs of the development, introducing dependencies between components. We, on the contrary, propose a new method to increase flexibility without introducing any kind of dependencies. We manage this by computing the intervals of solution space under user-defined conditions, hence selecting a custom set of independent corridors that fits the data gathered during development; i.e.: force-deformation curves that can be measured during a drop-tower test simulation. This new methodology of the adaptive solution space allows designers to edit the corridors, in order to have more flexibility for fulfilling high-level requirements when independently designing new components.

Funder

H2020 Marie Skłodowska-Curie Actions

Technische Universität München

Publisher

Springer Science and Business Media LLC

Subject

Applied Mathematics

Reference18 articles.

1. Burmberger L. Efficient Global Optimization of Structural Components for Solution Spaces in Vehicle Crash Design. M.Sc. Thesis, Technical University of Munich, Germany; 2020.

2. Daub M. Optimizing Flexibility for Component Design in Systems Engineering under Epistemic Uncertainty. PhD thesis. Technical University of Munich, Germany; 2020.

3. Daub M, Duddeck F, Zimmermann M. Optimizing component solution spaces for systems design. Struct Multidiscip Optim. 2020;61:2097–109. https://doi.org/10.1007/s00158-019-02456-8.

4. Daub M, Wöhr F, Zimmermann M. Optimizing distributed design processes for flexibility and cost. In: Proceedings of the 22nd international DSM conference (DSM 2020). 2020. p. 1–10.

5. Erschen S. Optimal decomposition of high-dimensional solution spaces for chassis design. PhD thesis. Technical University of Munich, Germany; 2018.

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