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Crashworthiness behavior assessment and multi-objective optimization of horsetail-inspired sandwich tubes based on artificial neural network.
- Source :
-
Mechanics of Advanced Materials & Structures . Sep2023, p1-18. 18p. 19 Illustrations, 1 Chart. - Publication Year :
- 2023
-
Abstract
- Abstract The crashworthiness behavior of horsetail-inspired sandwich tubes was analyzed in this study. Multilayer perceptron (MLP) algorithms with the Levenberg-Marquardt training algorithm (LMA) were used to predict force-displacement curve and optimize the geometrical parameters according to minimum peak crushing force and specific energy absorption. Based on the non-dominated sorting genetic algorithm II (NSGA-II) optimization results, the specimen with four core tubes and a thickness of 1 mm, and a height of 92 mm has the optimal crashworthiness performance. Finally, the optimal specimen is fabricated and the results of the numerical and MLP methods are validated versus experimental approach. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 15376494
- Database :
- Academic Search Index
- Journal :
- Mechanics of Advanced Materials & Structures
- Publication Type :
- Academic Journal
- Accession number :
- 172795570
- Full Text :
- https://doi.org/10.1080/15376494.2023.2257689