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Identification of optimal topologies for crashworthiness with the evolutionary level set method
Structural topology optimisation (TO) methods are well established in many engineering disciplines. However, for highly non-linear problems, including crashworthiness, methods are less developed and still subject to active research. In particular, due to the simplifications made in the state-of-the-...
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Published in: | International journal of crashworthiness 2018-07, Vol.23 (4), p.395-416 |
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container_title | International journal of crashworthiness |
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creator | Bujny, Mariusz Aulig, Nikola Olhofer, Markus Duddeck, Fabian |
description | Structural topology optimisation (TO) methods are well established in many engineering disciplines. However, for highly non-linear problems, including crashworthiness, methods are less developed and still subject to active research. In particular, due to the simplifications made in the state-of-the-art methods as well as heuristic character of most of them, the optimality of the obtained structures is arguable. In this paper, a TO approach based on the level set method and evolutionary algorithms is presented. The method is free from the heuristic assumptions and therefore, allows for a direct optimisation of the underlying crash problem. As a result, a reliable information about the optima of crash problems can be obtained. In order to assure the consistency of the results, a comprehensive study of optimisation settings is performed and discussed. Optimisation results for 2D crash test cases are presented and general conclusions concerning the behaviour of the optimal crash structures are derived. |
doi_str_mv | 10.1080/13588265.2017.1331493 |
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source | Taylor and Francis Science and Technology Collection |
subjects | Crashworthiness Evolutionary algorithms Heuristic methods Impact strength level set method Methods optimal structures Topology topology optimisation Topology optimization |
title | Identification of optimal topologies for crashworthiness with the evolutionary level set method |
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