A machine learning-based surrogate model for optimization of truss structures with geometrically nonlinear behavior-Reference-Cited by-同舟云学术

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A machine learning-based surrogate model for optimization of truss structures with geometrically nonlinear behavior

Published:2021-11 Issue: Volume:196 Page:103572
ISSN:0168-874X
Container-title:Finite Elements in Analysis and Design
language:en
Short-container-title:Finite Elements in Analysis and Design

Author:

Mai Hau T.,Kang Joowon,Lee Jaehong

Funder

National Research Foundation of Korea

Ministry of Education, Science and Technology

Publisher

Elsevier BV

Subject

Applied Mathematics,Computer Graphics and Computer-Aided Design,General Engineering,Analysis

Reference73 articles.

1. Review of Nonlinear Analysis and Modeling of Steel and Composite Structures;Thai,2020

2. Geometrically nonlinear isogeometric analysis of functionally graded microplates with the modified couple stress theory;Nguyen;Comput. Struct.,2017

3. Design optimization of regular hexagonal thin-walled columns with crashworthiness criteria;Hou;Finite Elem. Anal. Des.,2007

4. Geometrical nonlinear analysis of thin-walled composite beams using finite element method based on first order shear deformation theory;Vo;Arch. Appl. Mech.,2011

5. Geometrically nonlinear theory of thin-walled composite box beams using shear-deformable beam theory;Vo;Int. J. Mech. Sci.,2010

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