Field-Level Uncertainty Quantification for AI-Based Ship Hull Surface Pressure Prediction

This study investigates uncertainty quantification for field-level ship hull surface pressure predictions using a U-Net-based data-driven model. A speed-conditioned U-Net is trained on a large CFD dataset covering multiple ship types and velocity conditions to predict pressure distributions on hull...

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Autors principals:	Jeongbeom Seo, Inwon Lee
Format:	Artigo
Idioma:	Inglês
Publicat:	MDPI AG 2026-03-01
Col·lecció:	Journal of Marine Science and Engineering
Matèries:	Artificial Intelligence (AI) machine learning ship hydrodynamics surface pressure prediction speed-conditioned U-Net deep-ensemble
Accés en línia:	https://www.mdpi.com/2077-1312/14/5/504
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