The University of Southampton
University of Southampton Institutional Repository

Exploring buckling and post-buckling behavior of incompressible hyperelastic beams through innovative experimental and computational approaches

Exploring buckling and post-buckling behavior of incompressible hyperelastic beams through innovative experimental and computational approaches
Exploring buckling and post-buckling behavior of incompressible hyperelastic beams through innovative experimental and computational approaches
The objective of this paper is to conduct a comprehensive investigation into the buckling and post-buckling behavior of hyperelastic beams through both computational and experimental means. Natural rubber is used in the construction of a beam with a square cross-section. To determine the mechanical properties of natural rubber, a uniaxial tensile test is performed in accordance with ASTM D412. In finite element modeling (FEM), the nonlinear behavior of rubber is modeled using hyperelastic theory and the Yeoh strain energy function. The Static-Riks method is also implemented using Abaqus for the analysis of nonlinear buckling. To validate the present investigation results with FEM, an experimental test of digital image correlation (DIC) is conducted. The critical buckling force obtained via numerical methods exhibits an error of nearly 5% when compared to the corresponding results obtained from experimental testing. In order to ascertain the impact of various design parameters on the buckling behavior of the system, a comprehensive parametric analysis has been conducted. The parameters studied include the cross-sectional thickness, length of the structure, eccentric loads, as well as the mechanical properties of the materials used in the system. Consistent with the FEM outcomes, the critical buckling force exhibited by the hyperelastic beam demonstrates a positive correlation with increasing levels of hardness, cross-sectional thickness, and eccentric loads. The buckling behavior of the system is adversely affected by increasing its length. To ultimately validate the precision and reliability of the model, a supervised neural network (NN) learning method is employed.
DIC, Hyperelastic beam, neural network, post-buckling, static-riks, yeoh strain energy function
1539-7734
Azarnia, Omid
5827a977-b082-40f5-89f7-ba6592fcfd88
Forooghi, Ali
ddb95746-fba5-479e-98f9-ed198c8c5cf8
Vahidi Bidhendi, Mohammad
38dd859c-c2d2-4d14-a61a-f0b4f2bdfef7
Zangoei, AmirReza
2397ff0d-2028-4bc2-85d5-68f0d7c0ac48
Naskar, Susmita
5f787953-b062-4774-a28b-473bd19254b1
Azarnia, Omid
5827a977-b082-40f5-89f7-ba6592fcfd88
Forooghi, Ali
ddb95746-fba5-479e-98f9-ed198c8c5cf8
Vahidi Bidhendi, Mohammad
38dd859c-c2d2-4d14-a61a-f0b4f2bdfef7
Zangoei, AmirReza
2397ff0d-2028-4bc2-85d5-68f0d7c0ac48
Naskar, Susmita
5f787953-b062-4774-a28b-473bd19254b1

Azarnia, Omid, Forooghi, Ali, Vahidi Bidhendi, Mohammad, Zangoei, AmirReza and Naskar, Susmita (2023) Exploring buckling and post-buckling behavior of incompressible hyperelastic beams through innovative experimental and computational approaches. Mechanics Based Design of Structures and Machines. (doi:10.1080/15397734.2023.2242473).

Record type: Article

Abstract

The objective of this paper is to conduct a comprehensive investigation into the buckling and post-buckling behavior of hyperelastic beams through both computational and experimental means. Natural rubber is used in the construction of a beam with a square cross-section. To determine the mechanical properties of natural rubber, a uniaxial tensile test is performed in accordance with ASTM D412. In finite element modeling (FEM), the nonlinear behavior of rubber is modeled using hyperelastic theory and the Yeoh strain energy function. The Static-Riks method is also implemented using Abaqus for the analysis of nonlinear buckling. To validate the present investigation results with FEM, an experimental test of digital image correlation (DIC) is conducted. The critical buckling force obtained via numerical methods exhibits an error of nearly 5% when compared to the corresponding results obtained from experimental testing. In order to ascertain the impact of various design parameters on the buckling behavior of the system, a comprehensive parametric analysis has been conducted. The parameters studied include the cross-sectional thickness, length of the structure, eccentric loads, as well as the mechanical properties of the materials used in the system. Consistent with the FEM outcomes, the critical buckling force exhibited by the hyperelastic beam demonstrates a positive correlation with increasing levels of hardness, cross-sectional thickness, and eccentric loads. The buckling behavior of the system is adversely affected by increasing its length. To ultimately validate the precision and reliability of the model, a supervised neural network (NN) learning method is employed.

Text
Exploring buckling and post buckling behavior of incompressible hyperelastic beams through innovative experimental and computational approaches - Version of Record
Download (4MB)

More information

Accepted/In Press date: 22 July 2023
e-pub ahead of print date: 3 August 2023
Published date: 3 August 2023
Additional Information: Funding Information: SN acknowledges the initiation grant received from the University of Southampton. Publisher Copyright: © 2023 The Author(s). Published with license by Taylor & Francis Group, LLC.
Keywords: DIC, Hyperelastic beam, neural network, post-buckling, static-riks, yeoh strain energy function

Identifiers

Local EPrints ID: 480602
URI: http://eprints.soton.ac.uk/id/eprint/480602
ISSN: 1539-7734
PURE UUID: 4510fcc5-2436-4694-acea-6272fc720b3c
ORCID for Susmita Naskar: ORCID iD orcid.org/0000-0003-3294-8333

Catalogue record

Date deposited: 07 Aug 2023 16:44
Last modified: 17 Mar 2024 04:07

Export record

Altmetrics

Contributors

Author: Omid Azarnia
Author: Ali Forooghi
Author: Mohammad Vahidi Bidhendi
Author: AmirReza Zangoei
Author: Susmita Naskar ORCID iD

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×