research-article

Feedback control of cumuliform cloud formation based on computational fluid dynamics

Authors:

Yoshinori Dobashi,

Katsutoshi Kusumoto,

Tomoyuki Nishita,

Tsuyoshi YamamotoAuthors Info & Claims

ACM Transactions on Graphics (TOG), Volume 27, Issue 3

Pages 1 - 8

https://doi.org/10.1145/1360612.1360693

Published: 01 August 2008 Publication History

Abstract

Clouds play an important role for creating realistic images of outdoor scenes. In order to generate realistic clouds, many methods have been developed for modeling and animating clouds. One of the most effective approaches for synthesizing realistic clouds is to simulate cloud formation processes based on the atmospheric fluid dynamics. Although this approach can create realistic clouds, the resulting shapes and motion depend on many simulation parameters and the initial status. Therefore, it is very difficult to adjust those parameters so that the clouds form the desired shapes. This paper addresses this problem and presents a method for controlling the simulation of cloud formation. In this paper, we focus on controlling cumuliform cloud formation. The user specifies the overall shape of the clouds. Then, our method automatically adjusts parameters during the simulation in order to generate clouds forming the specified shape. Our method can generate realistic clouds while their shapes closely match to the desired shape.

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Cited By

Satilmis PBashford-Rogers T(2025)A multi-timescale image space model for dynamic cloud illuminationComputers & Graphics10.1016/j.cag.2024.104124126(104124)Online publication date: Mar-2025
https://doi.org/10.1016/j.cag.2024.104124
Xie HArihara KSato SMiyata K(2024)DualSmoke: Sketch-based smoke illustration design with two-stage generative modelComputational Visual Media10.1007/s41095-022-0318-010:5(965-979)Online publication date: 8-Feb-2024
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Zamri MSunar M(2022)Atmospheric cloud modeling methods in computer graphics: A review, trends, taxonomy, and future directionsJournal of King Saud University - Computer and Information Sciences10.1016/j.jksuci.2020.11.03034:6(3468-3488)Online publication date: Jun-2022
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Index Terms

Feedback control of cumuliform cloud formation based on computational fluid dynamics
1. Computing methodologies
  1. Computer graphics
    1. Animation

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Published In

cover image ACM Transactions on Graphics

ACM Transactions on Graphics Volume 27, Issue 3

August 2008

844 pages

ISSN:0730-0301

EISSN:1557-7368

DOI:10.1145/1360612

Issue’s Table of Contents

Copyright © 2008 ACM.

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 01 August 2008

Published in TOG Volume 27, Issue 3

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Cited By

Satilmis PBashford-Rogers T(2025)A multi-timescale image space model for dynamic cloud illuminationComputers & Graphics10.1016/j.cag.2024.104124126(104124)Online publication date: Mar-2025
https://doi.org/10.1016/j.cag.2024.104124
Xie HArihara KSato SMiyata K(2024)DualSmoke: Sketch-based smoke illustration design with two-stage generative modelComputational Visual Media10.1007/s41095-022-0318-010:5(965-979)Online publication date: 8-Feb-2024
https://doi.org/10.1007/s41095-022-0318-0
Zamri MSunar M(2022)Atmospheric cloud modeling methods in computer graphics: A review, trends, taxonomy, and future directionsJournal of King Saud University - Computer and Information Sciences10.1016/j.jksuci.2020.11.03034:6(3468-3488)Online publication date: Jun-2022
https://doi.org/10.1016/j.jksuci.2020.11.030
Zhang ZCen YZhang FLiang X(2021)Cumulus cloud modeling from images based on VAE-GANVirtual Reality & Intelligent Hardware10.1016/j.vrih.2020.12.0043:2(171-181)Online publication date: Apr-2021
https://doi.org/10.1016/j.vrih.2020.12.004
Goswami P(2021)A survey of modeling, rendering and animation of clouds in computer graphicsThe Visual Computer: International Journal of Computer Graphics10.1007/s00371-020-01953-y37:7(1931-1948)Online publication date: 1-Jul-2021
https://dl.acm.org/doi/10.1007/s00371-020-01953-y
Wang YMcGraw T(2021)Art-Directable Cloud AnimationAdvances in Visual Computing10.1007/978-3-030-90439-5_31(392-399)Online publication date: 4-Oct-2021
https://dl.acm.org/doi/10.1007/978-3-030-90439-5_31
Zhang ZMa YLi YLi FShum HYang BGuo JLiang X(2020)Cumuliform cloud formation control using parameter-predicting convolutional neural networkGraphical Models10.1016/j.gmod.2020.101083111(101083)Online publication date: Sep-2020
https://doi.org/10.1016/j.gmod.2020.101083
Zhang ZLi YYang BLi FLiang X(2020)Target‐driven cloud evolution using position‐based fluidsComputer Animation and Virtual Worlds10.1002/cav.193731:6Online publication date: 6-Sep-2020
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Chen JCen YLiang X(2018)Sketch-based Cloud Model Retrieval for Cumulus Cloud Scene ConstructionProceedings of the 2nd International Conference on Digital Signal Processing10.1145/3193025.3193043(166-170)Online publication date: 25-Feb-2018
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