A neural network regression model for estimating the lifespan of a Fibre Bundle

No Thumbnail Available

Date

2023-09

Journal Title

Journal ISSN

Volume Title

Publisher

IOP

Abstract

Fibre Bundle Models (FBMs) use generalized distributions like the Weibull distribution to study the failure mechanics of disordered material under different load-sharing schemes. Here we attempt to use a simple neural network regression model to estimate the lifespan of Fibre Bundles for axial loading under the Global Load Sharing (GLS) scheme. We find that using neural networks can give a reliable estimate (within ∼2%) of the lifespan for different initial conditions. We also develop a semi-analytical expression for the lifespan of a bundle of fibres. The aim is to establish an empirical relationship using a neural network regression (NNR) method that helps us estimate the ultimate tensile strength. The expressions and methods developed here can be a precursor to future investigation under those cited in the following section(s).

Description

Keywords

Physics, Fibre bundle models (FBMs), Global load sharing (GLS), Neural network regression (NNR)

Citation

Endorsement

Review

Supplemented By

Referenced By