Extending structural optimization capabilities of FEA softs according to machine learning principles

The purpose of this paper is to extend structural optimization capabilities of some FEA softs (NASTRAN/PATRAN, MARC-MENTAT) by coupling them with MATLAB codes in order to develop light weight design based on machine learning principles. We apply these ideas to some composite material with gyroid str...

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Bibliographic Details
Published in:	INCAS bulletin Vol. 16; no. 2; pp. 99 - 111
Main Authors:	Bocioaga, Mircea, Moisei, Cristian, Nistor, Octavian, Bacria, Ciprian, Nitescu, Denise, Baran, Daniela
Format:	Journal Article
Language:	English
Published:	Bucharest INCAS - National Institute for Aerospace Research "Elie Carafoli" 01-06-2024 National Institute for Aerospace Research “Elie Carafoli” - INCAS
Subjects:	Algorithms Artificial intelligence Composite materials composite materials with gyroid structure Design optimization finite element simulations Machine learning Mathematical programming Nastran Optimization Principles Stress analysis structural optimization Variables
Online Access:	Get full text
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Summary:	The purpose of this paper is to extend structural optimization capabilities of some FEA softs (NASTRAN/PATRAN, MARC-MENTAT) by coupling them with MATLAB codes in order to develop light weight design based on machine learning principles. We apply these ideas to some composite material with gyroid structure. The obtained results are interesting from both a theoretical and a practical point of view, shortening the design cycle for this type of materials.
ISSN:	2066-8201 2247-4528
DOI:	10.13111/2066-8201.2024.16.2.3