Animating fluid sediment mixture in particle-laden flows

Gao, Ming; Pradhana, Andre; Han, Xuchen; Guo, Qi; Kot, Grant; Sifakis, Eftychios; Jiang, Chenfanfu

doi:10.1145/3197517.3201309

Cited by 82 publications

(48 citation statements)

References 50 publications

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“…Particle-deficient pockets are created when fluid regions merge. This is a well-known problem with MPM, and some approaches have been proposed to address it [33,34].…”

Section: Limitationsmentioning

confidence: 99%

Affine particle in cell method for MAC grids and fluid simulation

Ding

Shinar

Schroeder

2020

Journal of Computational Physics

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We present a new technique for transferring momentum and velocity between particles and MAC grids based on the Affine-Particle-In-Cell (APIC) framework [1, 2] previously developed for co-located grids. APIC represents particle velocities as locally affine, rather than locally constant as in traditional PIC. These previous APIC schemes were designed primarily as an improvement on Particle-in-Cell (PIC) transfers, which tend to be heavily dissipative, and as an alternative to Fluid Implicit Particle (FLIP) transfers, which tend to be noisy. The original APIC paper [1] proposed APIC-style transfers for MAC grids, based on a limit for multilinear interpolation. We extend these to the case of smooth basis functions and show that the proposed transfers satisfy all of the original APIC properties. In particular, we achieve conservation of angular momentum across our transfers, something which eluded [1]. Early indications in [1] suggested that APIC might be suitable for simulating high Reynolds fluids due to favorable retention of vortices, but these properties were not studied further and the question was left unresolved. One significant drawback of APIC relative to FLIP is that energy is dissipated even when ∆t = 0. We use two dimensional Fourier analysis to investigate dissipation in this important limit. We investigate dissipation and vortex retention numerically in the general case to quantify the effectiveness of APIC compared with PIC, FLIP, and XPIC.

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“…Particle-deficient pockets are created when fluid regions merge. This is a well-known problem with MPM, and some approaches have been proposed to address it [33,34].…”

Section: Limitationsmentioning

confidence: 99%

Affine particle in cell method for MAC grids and fluid simulation

Ding

Shinar

Schroeder

2020

Journal of Computational Physics

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“…studied the application of laser-heating technology to browning dough. Graphics applications have used mixture theory and multi-species simulations to model porous water, sand and air mixtures [Gao et al 2018a;Liu et al 2008;Tampubolon et al 2017]. Many other graphics applications have made compelling use of multi-species simulations for water, sprays and foams [Losasso et al 2008;Nielsen and Osterby 2013;Takahashi et al 2003;Yang et al 2014], liquids with bubbles [Mihalef et al 2009;Thürey et al 2007] as well as for mixing of fluids [Bao et al 2010;He et al 2015;Kang et al 2010;Ren et al 2014;Yang et al 2015].…”

Section: Previous Workmentioning

confidence: 99%

“…Lastly, we note that we include the effects of thermal expansion which neither Stomakhin et al nor Gao et al address. Our approach, as with many other MPM approaches, use the notion of effective stress [Atkin and Craine 1976] with multi-species mixtures. These approaches naturally admit MPM discretizations where particles track each species, however stiff drag interaction terms can require small time steps [Bandara and Soga 2015;Gao et al 2018a;Tampubolon et al 2017]. Alternatively, we track the motion of species relative to one set of particles.…”

Section: Previous Workmentioning

confidence: 99%

“…Our approach is designed to track the solid phase (everything but the water and CO 2 ) since it is most apparent for visual rendering. Various MPM approaches have treated porous mixtures of water, gas and solid species [Abe et al 2014;Bandara et al 2016;Bandara and Soga 2015;Gao et al 2018a;Jassim et al 2013;Tampubolon et al 2017;Yerro et al 2015;Zhang et al 2009]. Tampubolon et al [2018a; use two sets of material points to track distinct water and sand phases.…”

Section: Introductionmentioning

confidence: 99%

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A thermomechanical material point method for baking and cooking

et al. 2019

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We present a Material Point Method for visual simulation of baking breads, cookies, pancakes and similar materials that consist of dough or batter (mixtures of water, flour, eggs, fat, sugar and leavening agents). We develop a novel thermomechanical model using mixture theory to resolve interactions between individual water, gas and dough species. Heat transfer with thermal expansion is used to model thermal variations in material properties. Water-based mass transfer is resolved through the porous mixture, gas represents carbon dioxide produced by leavening agents in the baking process and dough is modeled as a viscoelastoplastic solid to represent its varied and complex rheological properties. Water content in the mixture reduces during the baking process according to Fick's Law which contributes to drying and cracking of crust at the material boundary. Carbon dioxide gas produced by leavening agents during baking creates internal pressure that causes rising. The viscoelastoplastic model for the dough is temperature dependent and is used to model melting and solidification. We discretize the governing equations using a novel Material Point Method designed to track the solid phase of the mixture.

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“…In computer graphics, Gao et al [GTJS17] achieved low‐level performance gain using a vectorized interpolation weight computation scheme for GIMP. Explicit MPM can also be combined with semi‐implicit fluid solvers to couple particles with imcompressible fluids [GTH*18]. In this work, we describe an efficient scheme to store asynchronous MPM states and a new multi‐threading parallelization approach for optimized particle‐grid transfers that works for both traditional synchronous MPM (SyncMPM) and proposed asynchronous MPM (AsyncMPM).…”

Section: Related Workmentioning

confidence: 99%

A Temporally Adaptive Material Point Method with Regional Time Stepping

Fang

et al. 2018

Computer Graphics Forum

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Spatially and temporally adaptive algorithms can substantially improve the computational efficiency of many numerical schemes in computational mechanics and physics‐based animation. Recently, a crucial need for temporal adaptivity in the Material Point Method (MPM) is emerging due to the potentially substantial variation of material stiffness and velocities in multi‐material scenes. In this work, we propose a novel temporally adaptive symplectic Euler scheme for MPM with regional time stepping (RTS), where different time steps are used in different regions. We design a time stepping scheduler operating at the granularity of small blocks to maintain a natural consistency with the hybrid particle/grid nature of MPM. Our method utilizes the Sparse Paged Grid (SPGrid) data structure and simultaneously offers high efficiency and notable ease of implementation with a practical multi‐threaded particle‐grid transfer strategy. We demonstrate the efficacy of our asynchronous MPM method on various examples including elastic objects, granular media, and fluids.

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Animating fluid sediment mixture in particle-laden flows

Cited by 82 publications

References 50 publications

Affine particle in cell method for MAC grids and fluid simulation

Affine particle in cell method for MAC grids and fluid simulation

A thermomechanical material point method for baking and cooking

A Temporally Adaptive Material Point Method with Regional Time Stepping

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