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Citation:
　Jacopo Bardiani,Luca Lomazzi,Claudio Sbarufatti,et al.A Machine Learning-based Tool to Correlate Coupled and Uncoupled Numerical Simulations for Submerged Plates Subjected to Underwater Explosions[J].Journal of Marine Science and Application,2026,(2):342-361.[doi:10.1007/s11804-025-00624-5]
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A Machine Learning-based Tool to Correlate Coupled and Uncoupled Numerical Simulations for Submerged Plates Subjected to Underwater Explosions

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Title:
A Machine Learning-based Tool to Correlate Coupled and Uncoupled Numerical Simulations for Submerged Plates Subjected to Underwater Explosions
Author(s):
Jacopo Bardiani;  Luca Lomazzi;  Claudio Sbarufatti;  Andrea Manes
Affilations:
Author(s):
Jacopo Bardiani;  Luca Lomazzi;  Claudio Sbarufatti;  Andrea Manes
Department of Mechanical Engineering, Politecnico di Milano, Via G. La Masa, 120156, Milano, Italy
Keywords:
Underwater explosion|Fluid-structure interaction|Numerical simulation|Deep neural network|Uncoupled approach
分类号:
-
DOI:
10.1007/s11804-025-00624-5
Abstract:
In naval engineering, understanding underwater explosions is crucial for structural integrity and safety, particularly for combat ships. Coupled numerical analyses, which account for fluid-structure interaction (FSI), are accurate but computationally expensive and impractical for real-time applications. In contrast, uncoupled methods are efficient but overlook FSI effects. This study introduces a data-driven approach using a feedforward Deep Neural Network (DNN) to estimate FSI-induced displacements from uncoupled simulations. Trained on numerical datasets of blast-loaded plates with varying characteristics, the DNN predicts the coupled displacement field based on structural parameters of uncoupled simulations. Results demonstrate that this framework provides a fast and reliable alternative to coupled simulations, offering a practical engineering tool for underwater blast scenarios. This work serves as proof of concept that deep-learning-enhanced uncoupled simulations can replace coupled ones, with validity beyond the specific structure in the case study.

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Memo

Memo:
Received date:2024-11-30;Accepted date:2025-1-31。<br>Corresponding author:Jacopo Bardiani,E-mail:jacopo.bardiani@polimi.it
Last Update: 2026-06-08