“Stream-guided smoke simulations” by Sato, Dobashi and Kim

High-resolution fluid simulations are computationally expensive, so many post-processing methods have been proposed to add turbulent details to low-resolution flows. Guiding methods are one promising approach for adding naturalistic, detailed motions as a post-process, but can be inefficient. Thus, we propose a novel, efficient method that formulates fluid guidance as a minimization problem in stream function space. Input flows are first converted into stream functions, and a high resolution flow is then computed via optimization. The resulting problem sizes are much smaller than previous approaches, resulting in faster computation times. Additionally, our method does not require an expensive pressure projection, but still preserves mass. The method is both easy to implement and easy to control, as the user can control the degree of guiding with a single, intuitive parameter. We demonstrate the effectiveness of our method across various examples.

1. Ryoichi Ando, Nils Thuerey, and Chris Wojtan. 2015. A stream function solver for liquid simulations. ACM Transactions on Graphics 34, 4 (2015), Article 53.Google ScholarDigital Library
2. H. Bhatia, G. Norgard, V. Pascucci, and P. Bremer. 2013. The helmholtz-hodge decomposition – a survey. IEEE Transactions on Visualization and Computer Graphics 19, 8 (2013), 1386–1404.Google ScholarDigital Library
3. Robert Bridson. 2015. Fluid simulation for computer graphics. CRC Press.Google ScholarDigital Library
4. Robert Bridson, Jim Hourihan, and Marcus Nordenstam. 2007. Curl-noise for procedural fluid flow. ACM Transactions on Graphics 26, 3 (2007), Article 46.Google ScholarDigital Library
5. M. Chu and N. Thuerey. 2017. Data-Driven Synthesis of Smoke Flows with CNN-based Feature Descriptors. ACM Transactions on Graphics 36, 4 (2017), Article 14.Google ScholarDigital Library
6. R. Fattal and D. Lischinski. 2004. Target-driven smoke animation. ACM Transactions on Graphics 23, 3 (2004), 439–446.Google ScholarDigital Library
7. R. Fedkiw, J. Stam, and H. W. Jansen. 2001. Visual Simulation of Smoke. In Proceedings of ACM SIGGRAPH 2001. 15–22.Google Scholar
8. Zahra Forootaninia and Rahul Narain. 2020. Frequency-domain smoke guiding. ACM Trans. Graph. 39, 6, Article 172 (Dec. 2020).Google ScholarDigital Library
9. James Gregson, Ivo Ihrke, Nils Thuerey, and Wolfgang Heidrich. 2014. From Capture to Simulation: Connecting Forward and Inverse Problems in Fluids. ACM Trans. Graph. 33, 4, Article 139 (July 2014), 11 pages.Google ScholarDigital Library
10. T. Inglis, M.-L. Eckert, J. Gregson, and N. Thuerey. 2017. Primal-Dual Optimization for Fluids. Computer Graphics Forum 36, 8 (2017), 354–368.Google ScholarCross Ref
11. Doyub Kim. 2017. Fluid Engine Development. CRC Press.Google Scholar
12. Theodore Kim, Nils Thurey, Doug James, and Markus Gross. 2008. Wavelet turbulence for fluid simulation. ACM Transactions on Graphics 27, 3 (2008), Article 3.Google ScholarDigital Library
13. R. Narain, J. Sewall, M. Carlson, and M. C. Lin. 2008. Fast animation of turbulence using energy transport and procedural synthesis. ACM Transactions on Graphics 27, 5 (2008), Article 166.Google ScholarDigital Library
14. Michael B. Nielsen and Brian B. Christensen. 2010. Improved Variational Guiding of Smoke Animations. Computer Graphics Forum 29, 2 (2010), 705–712.Google ScholarCross Ref
15. Michael B. Nielsen, Brian B. Christensen, Nafees Bin Zafar, Doug Roble, and Ken Museth. 2009. Guiding of smoke animations through variational coupling of simulations at different resolutions. In Proceedings of the 2009 ACM SIGGRAPH/Eurographics Symposium on Computer Animation. 217–226.Google ScholarDigital Library
16. Syuhei Sato, Yoshinori Dobashi, Theodore Kim, and Tomoyuki Nishita. 2018. Example-based Turbulence Style Transfer. ACM Trans. Graph. 37, 4, Article 84 (2018).Google ScholarDigital Library
17. S. Sato, Y. Dobashi, Y. Yue, K. Iwasaki, and T. Nishita. 2015. Incompressibility-preserving deformation for fluid flows using vector potentials. The Visual Computer 31, 6 (2015), 959–965.Google ScholarDigital Library
18. H. Schechter and R. Bridson. 2008. Evolving sub-grid turbulence for smoke animation. In Proceedings of the 2008 ACM SIGGRAPH/Eurographics Symposium on Computer Animation. 1–7.Google ScholarDigital Library
19. Jos Stam. 1999. Stable Fluids. In Proceedings of ACM SIGGRAPH 1999, Annual Conference Series. 121–128.Google Scholar
20. N. Thürey, R. Keiser, M. Pauly, and U. Rüde. 2006. Detail-preserving fluid control. In Proceedings of the 2006 ACM SIGGRAPH/Eurographics symposium on Computer animation. 7–12.Google ScholarDigital Library
21. Y. Tong, S. Lombeyda, A. N. Hirani, and M. Desbrun. 2003. Discrete multiscale vector field decomposition. ACM Transactions on Graphics 22, 3 (2003), 445–452.Google ScholarDigital Library