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Water surface wavelets

Published:30 July 2018Publication History
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Abstract

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.

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  1. Water surface wavelets

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    • Published in

      cover image ACM Transactions on Graphics
      ACM Transactions on Graphics  Volume 37, Issue 4
      August 2018
      1670 pages
      ISSN:0730-0301
      EISSN:1557-7368
      DOI:10.1145/3197517
      Issue’s Table of Contents

      Copyright © 2018 Owner/Author

      This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike International 4.0 License.

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      Association for Computing Machinery

      New York, NY, United States

      Publication History

      • Published: 30 July 2018
      Published in tog Volume 37, Issue 4

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