Isoline Tracking in Particle-Based Fluids Using Level-Set Learning Representation

Isoline Tracking in Particle-Based Fluids Using Level-Set Learning Representation

In this paper, we propose a learning model for tracking the isolines of fluid based on the physical properties of particles in particle-based fluid simulations. Our method involves analyzing which weights, closely related to surface tracking among the various physical properties of fluid particles,...

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Bibliographic Details
Main Authors: Jun Yeong Kim, Chang Geun Song, Jung Lee, Jong-Hyun Kim, Jong Wan Lee, Sun-Jeong Kim
Format: Article
Language:English
Published: MDPI AG 2024-03-01
Series:Applied Sciences
Subjects:
isoline tracking
fluid simulation
fluid surfaces
level set
artificial neural network
particle-based fluids
Online Access:https://www.mdpi.com/2076-3417/14/6/2644

Internet

https://www.mdpi.com/2076-3417/14/6/2644

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