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

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 loadi...

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Bibliographic Details
Published in:Physica scripta 2023-10, Vol.98 (10), p.105946
Main Authors: V, Gokul, Singh, Navin
Format: Article
Language:English
Subjects:
estimating
lifespans
networks
neural
regressions
Citations: Items that this one cites
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Summary: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).
ISSN:0031-8949
1402-4896
DOI:10.1088/1402-4896/acf692