Modelling piezoresistive behaviour in finitely deformed elastomeric composites

Ahmadi, Masoud (2024) Modelling piezoresistive behaviour in finitely deformed elastomeric composites. PhD thesis, University of Glasgow.

Abstract

This thesis contributes to studying the relationship between the electrical conductivity of elastomeric composites and their finite deformations. Elastomeric composites exhibit significant shifts in the orientation of their reinforcements under large deformations, altering their electrical conductivity. This piezoresistive property is exploited in applications such as wearable technology, human-machine interfaces, energy harvesting, and soft robotics. This research employs two methodologies: a computational framework for analysing mechanical behaviour under finite deformations and an analytical model to predict electrical conductivity.
A computational framework employing finite element methods is used to analyse mechanical behaviour under finite deformations, employing single-field and three-field mixed formulations. Simulations of extreme deformation numerical examples validate the developed finite element codes. A novel procedure for incorporating the plane stress condition for general hyperelastic models is introduced. The plane stress model is used for analysing elastomeric composites, where admissible boundary conditions are implemented using pixel meshing techniques, assessing fibre orientation impact. The analytical model, based on Eshelby’s equivalent inclusion method, predicts electrical conductivity considering electron tunnelling and conductive network formation. This model accounts for fibre orientation and distribution, with rigorous validation against experimental data. By integrating computational and analytical approaches, this thesis offers a robust foundation for analysing piezoresistivity in elastomeric composites.

• Item Type: Thesis (PhD)
• Qualification Level: Doctoral
• Keywords: Finite element method; soft materials; composites; hyperelasticity; piezoresistivity.
• Subjects: T Technology > TJ Mechanical engineering and machinery
• Colleges/Schools: College of Science and Engineering > School of Engineering
• Supervisor's Name: Saxena, Dr. Prashant, McBride, Professor Andrew and Kumar, Professor Shanmugam
• Date of Award: 2024
• Depositing User: Theses Team
• Unique ID: glathesis:2024-84772
• Copyright: Copyright of this thesis is held by the author.
• Date Deposited: 20 Dec 2024 12:22
• Last Modified: 20 Dec 2024 14:07
• Thesis DOI: 10.5525/gla.thesis.84772
• URI: https://theses.gla.ac.uk/id/eprint/84772

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