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Acta Mechanica

Erschienen in:

10.04.2020 | Original Paper

An open-source computational framework for optimization of laminated composite plates

verfasst von: A. Kaveh, A. Dadras Eslamlou, N. Geran Malek, R. Ansari

Erschienen in: Acta Mechanica | Ausgabe 6/2020

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Abstract

In the present paper, a flexible framework is developed for the optimization of composite laminate plates. In this framework, an optimization algorithm is employed to find the optimal stacking sequence design of the FE models by interfacing the Abaqus solver with MATLAB through a Python script. The Python script submits dimension, orientation, and diameter of the cutout combinations to Abaqus/CAE. The performance of the codes is validated by applying them to several problems of previous research. Three distinct types of boundary conditions, namely CCCC, SCSC, and SSSS, with different geometries comprising a square and rectangular plates with and without cutouts, are considered as optimal design problems. Besides that, analyses are performed on new symmetrical composites with 16 and 80 plies. The framework is equipped with the GA for optimizing the fiber orientations and maximizing the buckling capacities. The results are comprehensively discussed, showing a reasonable agreement with the literature. This code can easily be used by scientists and industry professionals as an automated tool for optimizing different finite element models and using any arbitrary optimization algorithm.

Vorheriger Artikel Impact of point source and mass loading sensitivity on the propagation of an SH wave in an imperfectly bonded FGPPM layered structure

Nächster Artikel Nonlinear resonant behavior of thick multilayered nanoplates via nonlocal strain gradient elasticity theory

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Titel: An open-source computational framework for optimization of laminated composite plates
verfasst von: A. Kaveh
A. Dadras Eslamlou
N. Geran Malek
R. Ansari
Publikationsdatum: 10.04.2020
Verlag: Springer Vienna
Erschienen in: Acta Mechanica / Ausgabe 6/2020
Print ISSN: 0001-5970
Elektronische ISSN: 1619-6937
DOI: https://doi.org/10.1007/s00707-020-02648-0

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