Neural Network-Based Projective Grid Model for Learning Representation of Surface and Wave Foams
In this paper, we propose a projective grid model that enables learning representation of foam effects using artificial neural networks. In 3D fluid simulations, foam is one of the most representative secondary effects in water. Consequently, the processes of foam generation, advection, and dissolut...
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Main Author: | Jong-Hyun Kim |
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Format: | Article |
Language: | English |
Published: |
IEEE
2025-01-01
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Series: | IEEE Access |
Subjects: | |
Online Access: | https://ieeexplore.ieee.org/document/11097292/ |
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