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dc.contributor.authorLyu, Luanen_US
dc.contributor.authorRen, Xiaohuaen_US
dc.contributor.authorCao, Weien_US
dc.contributor.authorZhu, Jianen_US
dc.contributor.authorWu, Enhuaen_US
dc.contributor.authorYang, Zhi-Xinen_US
dc.contributor.editorBermano, Amit H.en_US
dc.contributor.editorKalogerakis, Evangelosen_US
dc.date.accessioned2024-04-16T14:40:17Z
dc.date.available2024-04-16T14:40:17Z
dc.date.issued2024
dc.identifier.issn1467-8659
dc.identifier.urihttps://doi.org/10.1111/cgf.15023
dc.identifier.urihttps://diglib.eg.org:443/handle/10.1111/cgf15023
dc.description.abstractWe introduce an efficient technique for recovering the vector potential in wavelet space to simulate pointwise incompressible fluids. This technique ensures that fluid velocities remain divergence-free at any point within the fluid domain and preserves local volume during the simulation. Divergence-free wavelets are utilized to calculate the wavelet coefficients of the vector potential, resulting in a smooth vector potential with enhanced accuracy, even when the input velocities exhibit some degree of divergence. This enhanced accuracy eliminates the need for additional computational time to achieve a specific accuracy threshold, as fewer iterations are required for the pressure Poisson solver. Additionally, in 3D, since the wavelet transform is taken in-place, only the memory for storing the vector potential is required. These two features make the method remarkably efficient for recovering vector potential for fluid simulation. Furthermore, the method can handle various boundary conditions during the wavelet transform, making it adaptable for simulating fluids with Neumann and Dirichlet boundary conditions. Our approach is highly parallelizable and features a time complexity of O(n), allowing for seamless deployment on GPUs and yielding remarkable computational efficiency. Experiments demonstrate that, taking into account the time consumed by the pressure Poisson solver, the method achieves an approximate 2x speedup on GPUs compared to state-of-the-art vector potential recovery techniques while maintaining a precision level of 10-6 when single float precision is employed. The source code of ’'Wavelet Potentials' can be found in https://github.com/yours321dog/WaveletPotentials.en_US
dc.publisherThe Eurographics Association and John Wiley & Sons Ltd.en_US
dc.subjectCCS Concepts: Computing methodologies -> Physical simulation
dc.subjectComputing methodologies
dc.subjectPhysical simulation
dc.titleWavelet Potentials: An Efficient Potential Recovery Technique for Pointwise Incompressible Fluidsen_US
dc.description.seriesinformationComputer Graphics Forum
dc.description.sectionheadersFluid Simulation
dc.description.volume43
dc.description.number2
dc.identifier.doi10.1111/cgf.15023
dc.identifier.pages18 pages


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