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Physically based modeling and rendering of avalanches

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Abstract

Avalanche is a natural disaster in the snow-covered mountainous area in winter, which may cause great disasters to human life and property. It is also a danger for skiers and climbers. This paper presents a new physically based algorithm to simulate the dynamic avalanches under position-based dynamics framework. To realistically simulate avalanches’ dynamic characteristics, we introduce the Bingham plastic model from geodynamics to model snow flow motion in avalanches. The interaction between snow flow in the avalanche and the surrounding objects is simulated by a level set-based two-way fluid–solid coupling model. We also propose static and kinetic friction mixed model to determine the accumulated transition of the avalanche. To create an avalanche scene with more realistic details, we employ an aerodynamics-based snow drag force model to generate snow fog effect. Finally, by choosing different criterion shear rate and friction parameters, different kinds of wet and dry avalanche scenes are realistically rendered. Compared with the real photographs of avalanches, our simulated results are quite satisfactory.

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Funding

Funding was provided by 863 Program of China (No. 2015AA016404), National Key R&D Program of China (No. 2017YFB1002703) and Natural Science Foundation of China (No. U1736109).

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Authors and Affiliations

  1. State Key Laboratory of CAD & CG, Zhejiang University, Hangzhou, 310058, People’s Republic of China

    Xincheng Liu, Haitong Zhang, Zhangye Wang & Qunsheng Peng

  2. Communication University of Zhejiang, Hangzhou, 310018, People’s Republic of China

    Yi Chen

  3. School of Design, Shanghai Jiao Tong University, Shanghai, 20040, People’s Republic of China

    Yuhong Zou

Authors
  1. Xincheng Liu
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  2. Yi Chen
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  3. Haitong Zhang
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  4. Yuhong Zou
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  5. Zhangye Wang
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  6. Qunsheng Peng
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Correspondence to Zhangye Wang.

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Liu, X., Chen, Y., Zhang, H. et al. Physically based modeling and rendering of avalanches. Vis Comput 37, 2619–2629 (2021). https://doi.org/10.1007/s00371-021-02215-1

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