Machine learning algorithms for three-dimensional mean-curvature computation in the level-set method

Larios-Cárdenas, Luis Ángel; Gibou, Frédéric

doi:10.1016/j.jcp.2023.111995

Journal of Computational Physics

2023

DOI: 10.1016/j.jcp.2023.111995

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Machine learning algorithms for three-dimensional mean-curvature computation in the level-set method

Luis Ángel Larios-Cárdenas

Frédéric Gibou

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2024

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Reconstruction of implicit surfaces from fluid particles using convolutional neural networks

Zhao,

Shinar,

Schroeder

2024

Computer Graphics Forum

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In this paper, we present a novel network‐based approach for reconstructing signed distance functions from fluid particles. The method uses a weighting kernel to transfer particles to a regular grid, which forms the input to a convolutional neural network. We propose a regression‐based regularization to reduce surface noise without penalizing high‐curvature features. The reconstruction exhibits improved spatial surface smoothness and temporal coherence compared with existing state of the art surface reconstruction methods. The method is insensitive to particle sampling density and robustly handles thin features, isolated particles, and sharp edges.

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Reconstruction of implicit surfaces from fluid particles using convolutional neural networks

Zhao,

Shinar,

Schroeder

2024

Computer Graphics Forum

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Machine learning algorithms for three-dimensional mean-curvature computation in the level-set method

Cited by 1 publication

References 70 publications

Reconstruction of implicit surfaces from fluid particles using convolutional neural networks

Reconstruction of implicit surfaces from fluid particles using convolutional neural networks

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