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dc.contributor.authorSingh, Navin-
dc.date.accessioned2025-03-21T04:19:10Z-
dc.date.available2025-03-21T04:19:10Z-
dc.date.issued2023-09-
dc.identifier.urihttps://iopscience.iop.org/article/10.1088/1402-4896/acf692/meta-
dc.identifier.urihttp://dspace.bits-pilani.ac.in:8080/jspui/handle/123456789/18451-
dc.description.abstractFibre 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.isoenen_US
dc.publisherIOPen_US
dc.subjectPhysicsen_US
dc.subjectFibre bundle models (FBMs)en_US
dc.subjectGlobal load sharing (GLS)en_US
dc.subjectNeural network regression (NNR)en_US
dc.titleA neural network regression model for estimating the lifespan of a Fibre Bundleen_US
dc.typeArticleen_US
Appears in Collections:Department of Physics

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