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

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dc.contributor.author Singh, Navin
dc.date.accessioned 2025-03-21T04:19:10Z
dc.date.available 2025-03-21T04:19:10Z
dc.date.issued 2023-09
dc.identifier.uri https://iopscience.iop.org/article/10.1088/1402-4896/acf692/meta
dc.identifier.uri http://dspace.bits-pilani.ac.in:8080/jspui/handle/123456789/18451
dc.description.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). en_US
dc.language.iso en en_US
dc.publisher IOP en_US
dc.subject Physics en_US
dc.subject Fibre bundle models (FBMs) en_US
dc.subject Global load sharing (GLS) en_US
dc.subject Neural network regression (NNR) en_US
dc.title A neural network regression model for estimating the lifespan of a Fibre Bundle en_US
dc.type Article en_US


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