We propose a framework for simulating the complex dynamics of strands interacting with compressible, shear-dependent liquids, such as oil paint, mud, cream, melted chocolate, and pasta sauce. Our framework contains three main components: the strands modeled as discrete rods, the bulk liquid represented as a continuum (material point method), and a reduced-dimensional flow of liquid on the surface of the strands with detailed elastoviscoplastic behavior. These three components are tightly coupled together. To enable discrete strands interacting with continuum-based liquid, we develop models that account for the volume change of the liquid as it passes through strands and the momentum exchange between the strands and the liquid. We also develop an extended constraint-based collision handling method that supports cohesion between strands. Furthermore, we present a principled method to preserve the total momentum of a strand and its surface flow, as well as an analytic plastic flow approach for Herschel-Bulkley fluid that enables stable semi-implicit integration at larger time steps. We explore a series of challenging scenarios, involving splashing, shaking, and agitating the liquid which causes the strands to stick together and become entangled.


ACKNOWLEDGMENTS

This work was supported in part by the National Science Foundation under Grant Nos.: 1717178, 1319483, CAREER-1453101, the Natural Sciences and Engineering Research Council of Canada under Grant No. RGPIN-04360-2014, SoftBank Group, Pixar, Adobe, and SideFX. We also thank Florence Bertails-Descoubes, Theodore Kim, and Peter Yichen Chen for inspiring discussions, Henrique Maia for his contribution to the voiceover, Ryan Goldade for his assistence on surface reconstruction, Xiaowei Tan for his advice on the rendering, Adela Cheng for her help on the real footage (refer to our supplemental video), Robert Lane for his help on the computational devices, and Cristin Barghiel for his continued generous contribution of Houdini licenses. We would also like to thank Gilles Daviet, Jean-Marie Aubry, Yonghao Yue, Breannan Smith, Danny Kaufman, Xinxin Zhang, Mark Leone, Miklos Bergou and Susan Howard for the sharing of their code. In addition, we would like to thank the anonymous reviewers for their insightful comments.


© Yun (Raymond) Fei, Christopher Batty, Eitan Grinspun and Changxi Zheng, 2019. All images and videos are licensed under CC-BY-SA 4.0.