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A U-net based reconstruction of high-fidelity simulation results for flow around a ship hull based on low-fidelity inviscid flow simulation

In this study, neural networks are trained to transform inviscid simulation data for flow around a ship hull into data representative of viscous flow simulations. The objective is to provide high-fidelity viscous flow simulation data using machine learning in conjunction with inviscid flow simulatio...

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Principais autores: Dayeon Kim, Jeongbeom Seo, Inwon Lee
Format: Artigo
Jezik:Inglês
Izdano: Elsevier 2025-01-01
Serija:International Journal of Naval Architecture and Ocean Engineering
Teme:
Online dostop:http://www.sciencedirect.com/science/article/pii/S2092678225000342
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