Physics-based fluid control has long been a challenging problem in balancing efficiency and accuracy. We introduce a novel physicsbased fluid control pipeline using Laplacian Eigenfluids. Utilizing the adjoint method with our provided analytical gradient expressions, the derivative computation of the control problem is efficient and easy to formulate. We demonstrate that our method is fast enough to support real-time fluid simulation, editing, control, and optimal animation generation. Our pipeline naturally supports multi-resolution and frequency control of fluid simulations. The effectiveness and efficiency of our fluid control pipeline are validated through a variety of 2D examples and comparisons.
@inproceedings{chen2024fluid,
title={Fluid Control with Laplacian Eigenfunctions},
author={Chen, Yixin and Levin, David and Langlois, Timothy},
booktitle={ACM SIGGRAPH 2024 Conference Papers},
pages={1--11},
year={2024}
}
We express our gratitude to all reviewers for their valuable feedback and suggestions on this work. We thank Qiaodong Cui, Jingwei Tang, and Zherong Pan for sharing their codes and offering help for comparisons. We would also like to thank John Hancock and Xuan Dam for their essential administrative support. Special thanks to Masha Shugrina for drawing the beautiful teaser keyframes. We appreciate the support from Yiting Li and Zhecheng Wang, who assisted with video editing and proofreading. This work is supported by funding from the NSERC Discovery Grant, the Ontario Early Researchers Award, the Canada Research Chairs Program, and gifts from Adobe Research and Autodesk.