Accelerated Smoke Simulation by Super-Resolution With Deep Learning on Downscaled and Binarized Space

Accelerated Smoke Simulation by Super-Resolution With Deep Learning on Downscaled and Binarized Space

In this paper, we propose a highly efficient method for synthesizing high-resolution(HR) smoke simulations based on deep learning. A major issue for physics-based HR fluid simulations is that they require large amounts of physical memory and long execution times. In recent years, this issue has been...

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Bibliographic Details
Main Authors: Byeong-Sun Hong, Qimeng Zhang, Chang-Hun Kim, Jung Lee, Jong-Hyun Kim
Format: Article
Language:English
Published: IEEE 2021-01-01
Series:IEEE Access
Subjects:
Fluid simulations
deep learning
super-resolution
adaptive synthesizing
octree
physics-based simulations
Online Access:https://ieeexplore.ieee.org/document/9478850/

Internet

https://ieeexplore.ieee.org/document/9478850/

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