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2024 | OriginalPaper | Buchkapitel

Application of Artificial Neural Network in Impact and Crashworthiness: A Review

verfasst von : Dipjyoti Nath, Ankit, Debanga Raj Neog, Sachin Singh Gautam

Erschienen in: Recent Advances in Aerospace Engineering

Verlag: Springer Nature Singapore

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Abstract

The paper presents an extensive review of the application of machine learning (ML) techniques, especially artificial neural networks (ANNs), in the realm of crashworthiness, hypervelocity impacts, and inverse analysis across various structural and aerospace domains. It delves into the prediction of stiffness matrices, contact stiffness, impact forces, and failure conditions, showcasing the potential of ML to streamline complex structural analysis processes. While the review highlights the predictive accuracies and computational efficiencies achieved by these methods, it also underscores the need for a more critical evaluation of model robustness, uncertainties, and real-world applicability. The review offers valuable insights into how ML can transform inverse analysis yet emphasizes the importance of addressing challenges and limitations to ensure the reliability and practicality of these innovative approaches.

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Titel: Application of Artificial Neural Network in Impact and Crashworthiness: A Review
verfasst von: Dipjyoti Nath
Ankit
Debanga Raj Neog
Sachin Singh Gautam
Verlag: Springer Nature Singapore
Buch: Recent Advances in Aerospace Engineering
Print ISBN: 978-981-9713-05-9

Electronic ISBN: 978-981-9713-06-6

Copyright-Jahr: 2024
DOI: https://doi.org/10.1007/978-981-97-1306-6_32

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