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ANN-Based Random First-Ply Failure Analyses of Laminated Composite Plates

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Recent Advances in Computational Mechanics and Simulations

Part of the book series: Lecture Notes in Civil Engineering ((LNCE,volume 103))

Abstract

This paper presents the random first-ply failure analyses of laminated composite plates by using an artificial neural network (ANN)-based surrogate model. In general, materials and geometric uncertainties are unavoidable in such structures due to their inherent anisotropy and randomness in system configuration. To map such variabilities, stochastic analysis corroborates the fact of inevitable edge towards the quantification of uncertainties. In the present study, the finite element formulation is derived based on the consideration of eight-noded elements wherein each node consists of five degrees of freedom (DOF). The five failure criteria namely, maximum stress theory, maximum strain theory, Tsai-Hill (energy-based criterion) theory, Tsai-Wu (interaction tensor polynomial) theory and Tsai-Hill’s Hoffman failure criteria are considered in the present study. The input parameters include the ply orientation angle, assembly of ply, number of layers, ply thickness and degree of orthotropy, while the first-ply failure loads for five criteria representing output quantity of interest. The deterministic results are validated with past experimental results. The results obtained from the ANN-based surrogate model are observed to attain fitment with the results obtained by Monte Carlo Simulation (MCS). The statistical results are presented for both deterministic, as well as stochastic domain.

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Acknowledgments

The authors would like to acknowledge the Aeronautics Research and Development Board (AR&DB), Government of India (Project Sanction no.: ARDB/01/105885/M/I), for the financial support for the present research work.

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Authors and Affiliations

  1. National Institute of Technology, Silchar, India

    Subrata Kushari, S. R. Maity & S. Dey

  2. Indian Institute of Technology, Guwahati, India

    A. Chakraborty

  3. University of Oxford, Oxford, UK

    T. Mukhopadhyay

Authors
  1. Subrata Kushari
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  2. A. Chakraborty
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  3. T. Mukhopadhyay
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  4. S. R. Maity
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  5. S. Dey
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Corresponding author

Correspondence to Subrata Kushari .

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Editors and Affiliations

  1. School of Engineering, Indian Institute of Technology Mandi, Mandi, Himachal Pradesh, India

    Sandip Kumar Saha

  2. School of Engineering, Indian Institute of Technology Mandi, Mandi, Himachal Pradesh, India

    Mousumi Mukherjee

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Kushari, S., Chakraborty, A., Mukhopadhyay, T., Maity, S.R., Dey, S. (2021). ANN-Based Random First-Ply Failure Analyses of Laminated Composite Plates. In: Saha, S.K., Mukherjee, M. (eds) Recent Advances in Computational Mechanics and Simulations. Lecture Notes in Civil Engineering, vol 103. Springer, Singapore. https://doi.org/10.1007/978-981-15-8138-0_11

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  • DOI: https://doi.org/10.1007/978-981-15-8138-0_11

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-15-8137-3

  • Online ISBN: 978-981-15-8138-0

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