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Please use this identifier to cite or link to this item: http://dspace.bits-pilani.ac.in:8080/jspui/handle/123456789/18451
Title: A neural network regression model for estimating the lifespan of a Fibre Bundle
Authors: Singh, Navin
Keywords: Physics
Fibre bundle models (FBMs)
Global load sharing (GLS)
Neural network regression (NNR)
Issue Date: Sep-2023
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).
URI: https://iopscience.iop.org/article/10.1088/1402-4896/acf692/meta
http://dspace.bits-pilani.ac.in:8080/jspui/handle/123456789/18451
Appears in Collections:Department of Physics

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