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Buckling resistance of hot‐finished CHS beam‐columns using FE modelling and machine learning

Buckling resistance of hot‐finished CHS beam‐columns using FE modelling and machine learning The use of circular hollow sections (CHS) has increased in recent years owing to its excellent mechanical behaviour including axial compression and torsional resistance as well as its aesthetic appearance. They are popular in a wide range of structural members, including beams, columns, trusses and arches. The behaviour of hot‐finished CHS beam‐columns made from normal‐ and high‐strength steels is the main focus of this article. A particular attention is given to predict the ultimate buckling resistance of CHS beam‐columns using the recent advancement of the artificial neural network (ANN). Finite element (FE) models were established and validated to generate an extensive parametric study. The ANN model is trained and validated using a total of 3439 data points collected from the generated FE models and experimental tests available in the literature. A comprehensive comparative analysis with the design rules in Eurocode 3 is conducted to evaluate the performance of the developed ANN model. It is shown that the proposed ANN‐based design formula provides a reliable means for predicting the buckling resistance of the CHS beam‐columns. This formula can be easily implemented in any programming software, providing an excellent basis for engineers and designers to predict the buckling resistance of the CHS beam–columns with a straightforward procedure in an efficient and sustainable manner with least computational time. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Steel Construction: Design and Research Wiley

Buckling resistance of hot‐finished CHS beam‐columns using FE modelling and machine learning

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References (45)

Publisher
Wiley
Copyright
© 2023 Ernst & Sohn GmbH
ISSN
1867-0520
eISSN
1867-0539
DOI
10.1002/stco.202200036
Publisher site
See Article on Publisher Site

Abstract

The use of circular hollow sections (CHS) has increased in recent years owing to its excellent mechanical behaviour including axial compression and torsional resistance as well as its aesthetic appearance. They are popular in a wide range of structural members, including beams, columns, trusses and arches. The behaviour of hot‐finished CHS beam‐columns made from normal‐ and high‐strength steels is the main focus of this article. A particular attention is given to predict the ultimate buckling resistance of CHS beam‐columns using the recent advancement of the artificial neural network (ANN). Finite element (FE) models were established and validated to generate an extensive parametric study. The ANN model is trained and validated using a total of 3439 data points collected from the generated FE models and experimental tests available in the literature. A comprehensive comparative analysis with the design rules in Eurocode 3 is conducted to evaluate the performance of the developed ANN model. It is shown that the proposed ANN‐based design formula provides a reliable means for predicting the buckling resistance of the CHS beam‐columns. This formula can be easily implemented in any programming software, providing an excellent basis for engineers and designers to predict the buckling resistance of the CHS beam–columns with a straightforward procedure in an efficient and sustainable manner with least computational time.

Journal

Steel Construction: Design and ResearchWiley

Published: Jul 24, 2023

Keywords: artificial neural networks (ANN); Eurocode 3; FE modelling; hot-finished CHS beam-columns; normal- and high-strength steels

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