CORE
🇺🇦
make metadata, not war
Services
Services overview
Explore all CORE services
Access to raw data
API
Dataset
FastSync
Content discovery
Recommender
Discovery
OAI identifiers
OAI Resolver
Managing content
Dashboard
Bespoke contracts
Consultancy services
Support us
Support us
Membership
Sponsorship
Community governance
Advisory Board
Board of supporters
Research network
About
About us
Our mission
Team
Blog
FAQs
Contact us
Continuum Foam: A Material Point Method for Shear-Dependent Flows
Authors
Christopher Batty
Eitan Grinspun
+3 more
Breannan Smith
Yonghao Yue
Changxi Zheng
Publication date
1 October 2015
Publisher
'Association for Computing Machinery (ACM)'
Doi
Cite
Abstract
© ACM, 2015. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published in Yue, Y., Smith, B., Batty, C., Zheng, C., & Grinspun, E. (2015). Continuum Foam: A Material Point Method for Shear-Dependent Flows. Acm Transactions on Graphics, 34(5), 160. https://doi.org/10.1145/2751541We consider the simulation of dense foams composed of microscopic bubbles, such as shaving cream and whipped cream. We represent foam not as a collection of discrete bubbles, but instead as a continuum. We employ the material point method (MPM) to discretize a hyperelastic constitutive relation augmented with the Herschel-Bulkleymodel of non-Newtonian viscoplastic flow, which is known to closely approximate foam behavior. Since large shearing flows in foam can produce poor distributions of material points, a typical MPM implementation can produce non-physical internal holes in the continuum. To address these artifacts, we introduce a particle resampling method for MPM. In addition, we introduce an explicit tearing model to prevent regions from shearing into artificially thin, honey-like threads. We evaluate our method's efficacy by simulating a number of dense foams, and we validate our method by comparing to real-world footage of foam.This work was supported in part by the JSPS Postdoctoral Fellowshipsfor Research Abroad, NSF (Grants IIS-13-19483, CMMI-11-29917, CAREER-1453101), NSERC (Grant RGPIN-04360-2014), Intel, The Walt Disney Company, Autodesk, Side Effects, NVIDIA,Adobe, and The Foundry
Similar works
Full text
Open in the Core reader
Download PDF
Available Versions
University of Waterloo's Institutional Repository
See this paper in CORE
Go to the repository landing page
Download from data provider
oai:uwspace.uwaterloo.ca:10012...
Last time updated on 01/01/2018
CiteSeerX
See this paper in CORE
Go to the repository landing page
Download from data provider
oai:CiteSeerX.psu:10.1.1.726.1...
Last time updated on 30/10/2017