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DC Field | Value | Language |
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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 |
Appears in Collections: | Department of Physics |
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