article published yes Stefan Jeschke author 44D6411A-F248-11E8-B48F-1D18A9856A87 Tomas Skrivan author 486A5A46-F248-11E8-B48F-1D18A9856A87 Matthias Mueller Fischer author Nuttapong Chentanez author Miles Macklin author Christopher J Wojtan author 3C61F1D2-F248-11E8-B48F-1D18A9856A870000-0001-6646-5546 ChWo department Big Splash: Efficient Simulation of Natural Phenomena at Extremely Large Scales project International IST Doctoral Program project The current state of the art in real-time two-dimensional water wave simulation requires developers to choose between efficient Fourier-based methods, which lack interactions with moving obstacles, and finite-difference or finite element methods, which handle environmental interactions but are significantly more expensive. This paper attempts to bridge this long-standing gap between complexity and performance, by proposing a new wave simulation method that can faithfully simulate wave interactions with moving obstacles in real time while simultaneously preserving minute details and accommodating very large simulation domains. Previous methods for simulating 2D water waves directly compute the change in height of the water surface, a strategy which imposes limitations based on the CFL condition (fast moving waves require small time steps) and Nyquist's limit (small wave details require closely-spaced simulation variables). This paper proposes a novel wavelet transformation that discretizes the liquid motion in terms of amplitude-like functions that vary over space, frequency, and direction, effectively generalizing Fourier-based methods to handle local interactions. Because these new variables change much more slowly over space than the original water height function, our change of variables drastically reduces the limitations of the CFL condition and Nyquist limit, allowing us to simulate highly detailed water waves at very large visual resolutions. Our discretization is amenable to fast summation and easy to parallelize. We also present basic extensions like pre-computed wave paths and two-way solid fluid coupling. Finally, we argue that our discretization provides a convenient set of variables for artistic manipulation, which we illustrate with a novel wave-painting interface. https://research-explorer.ista.ac.at/download/134/5744/2018_ACM_Jeschke.pdf application/pdfno https://creativecommons.org/licenses/by-nc-sa/4.0/ ACM2018 eng 00044818500005510.1145/3197517.3201336 374 https://ist.ac.at/en/news/new-water-simulation-captures-small-details-even-in-large-scenes/ Jeschke, Stefan, Tomas Skrivan, Matthias Mueller Fischer, Nuttapong Chentanez, Miles Macklin, and Chris Wojtan. “Water Surface Wavelets.” <i>ACM Transactions on Graphics</i>. ACM, 2018. <a href="https://doi.org/10.1145/3197517.3201336">https://doi.org/10.1145/3197517.3201336</a>. S. Jeschke, T. Skrivan, M. Mueller Fischer, N. Chentanez, M. Macklin, and C. Wojtan, “Water surface wavelets,” <i>ACM Transactions on Graphics</i>, vol. 37, no. 4. ACM, 2018. Jeschke S, Skrivan T, Mueller Fischer M, Chentanez N, Macklin M, Wojtan C. Water surface wavelets. <i>ACM Transactions on Graphics</i>. 2018;37(4). doi:<a href="https://doi.org/10.1145/3197517.3201336">10.1145/3197517.3201336</a> Jeschke S, Skrivan T, Mueller Fischer M, Chentanez N, Macklin M, Wojtan C. 2018. Water surface wavelets. ACM Transactions on Graphics. 37(4), 94. Jeschke, S., Skrivan, T., Mueller Fischer, M., Chentanez, N., Macklin, M., &#38; Wojtan, C. (2018). Water surface wavelets. <i>ACM Transactions on Graphics</i>. ACM. <a href="https://doi.org/10.1145/3197517.3201336">https://doi.org/10.1145/3197517.3201336</a> S. Jeschke, T. Skrivan, M. Mueller Fischer, N. Chentanez, M. Macklin, C. Wojtan, ACM Transactions on Graphics 37 (2018). Jeschke, Stefan, et al. “Water Surface Wavelets.” <i>ACM Transactions on Graphics</i>, vol. 37, no. 4, 94, ACM, 2018, doi:<a href="https://doi.org/10.1145/3197517.3201336">10.1145/3197517.3201336</a>. 1342018-12-11T11:44:48Z2024-10-22T09:58:20Z