A stream function solver for liquid simulations

Ando, Ryoichi; Thuerey, Nils; Wojtan, Chris

doi:10.1145/2766935

Cited by 46 publications

(50 citation statements)

References 44 publications

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“…The FLIP method has also been used for fluid control [PHT * 13] and two-phase flow [BB12,ATW15]. Note that our narrow band approach is actually used by Ando et al [ATW15].…”

Section: Related Workmentioning

confidence: 99%

Narrow Band FLIP for Liquid Simulations

Ferstl

Ando

Wojtan

et al. 2016

Computer Graphics Forum

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Figure 1: Two simulations with a (background-)grid resolution of 200 3 : Our method (left) is nearly indistinguishable from regular FLIP (right), but uses only one million particles instead of 24 million. Computations outside of the pressure solver are sped up by a factor of more than 6, the total computation time for 250 frames is reduced from 4.4h to 2h, and the average memory footprint is reduced by a factor of 2. AbstractThe Fluid Implicit Particle method (FLIP) for liquid simulations uses particles to reduce numerical dissipation and provide important visual cues for events like complex splashes and small-scale features near the liquid surface. Unfortunately, FLIP simulations can be computationally expensive, because they require a dense sampling of particles to fill the entire liquid volume. Furthermore, the vast majority of these FLIP particles contribute nothing to the fluid's visual appearance, especially for larger volumes of liquid. We present a method that only uses FLIP particles within a narrow band of the liquid surface, while efficiently representing the remaining inner volume on a regular grid. We show that a naïve realization of this idea introduces unstable and uncontrollable energy fluctuations, and we propose a novel coupling scheme between FLIP particles and regular grid which overcomes this problem. Our method drastically reduces the particle count and simulation times while yielding results that are nearly indistinguishable from regular FLIP simulations. Our approach is easy to integrate into any existing FLIP implementation.

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“…The FLIP method has also been used for fluid control [PHT * 13] and two-phase flow [BB12,ATW15]. Note that our narrow band approach is actually used by Ando et al [ATW15].…”

Section: Related Workmentioning

confidence: 99%

Narrow Band FLIP for Liquid Simulations

Ferstl

Ando

Wojtan

et al. 2016

Computer Graphics Forum

Self Cite

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“…Narrow band and adaptive particle sampling techniques as well as adaptive/unstructured Eulerian grids dramatically increase efficiency [Ando et al 2012[Ando et al , 2013Ando and Tsuruno 2011;Ferstl et al 2016;Hong et al 2008. Ando et al [2015] use a stream function to enforce incompressibility, rather than the more commonly used MAC projection. Mercier et al [2015] increase apparent resolution of FLIP with secondary surface wave simulation.…”

Section: Previous Workmentioning

confidence: 99%

A polynomial particle-in-cell method

et al. 2017

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Fig. 1. Ink drop. We compare from left to right FLIP, APIC, and PolyPIC for an inkjet in an ambient incompressible fluid. PolyPIC more effectively resolves the vorticial details.Recently the Affine Particle-In-Cell (APIC) Method was proposed by 2017b] to improve the accuracy of the transfers in Particle-In-Cell (PIC) [Harlow 1964] techniques by augmenting each particle with a locally affine, rather than locally constant description of the velocity. This reduced the dissipation of the original PIC without suffering from the noise present in the historic alternative, Fluid-Implicit-Particle (FLIP) [Brackbill and Ruppel 1986]. We present a generalization of APIC by augmenting each particle with a more general local function. By viewing the grid-to-particle transfer as a linear and angular momentum conserving projection of the particle-wise local grid velocities onto a reduced basis, we greatly improve the energy and vorticity conservation over the original APIC. Furthermore, we show that the cost of the generalized projection is negligible over APIC when using a particular class of local polynomial functions. Lastly, we note that our method retains the filtering property of APIC and PIC and thus has similar robustness to noise.

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“…Boyd and Bridson [BB12] extended it to multiFLIP to simulate two‐phase fluids with glugging effects. Ando et al [ATW15] used FLIP with stream functions to enforce incompressibility of fluids, and later they improved the computational efficiency of FLIP by use of narrow band calculations [FAW*16]. Cornelis et al [CIPT14] proposed the IISPHFLIP method for simulating incompressible fluids, in which IISPH and FLIP are combined to conserve mass and reduce the computational load.…”

Section: Previous Workmentioning

confidence: 99%

MPM simulation of interacting fluids and solids

Yan

Chen

et al. 2018

Computer Graphics Forum

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The material point method (MPM) has attracted increasing attention from the graphics community, as it combines the strengths of both particle‐ and grid‐based solvers. Like the smoothed particle hydrodynamics (SPH) scheme, MPM uses particles to discretize the simulation domain and represent the fundamental unknowns. This makes it insensitive to geometric and topological changes, and readily parallelizable on a GPU. Like grid‐based solvers, MPM uses a background mesh for calculating spatial derivatives, providing more accurate and more stable results than a purely particle‐based scheme. MPM has been very successful in simulating both fluid flow and solid deformation, but less so in dealing with multiple fluids and solids, where the dynamic fluid‐solid interaction poses a major challenge. To address this shortcoming of MPM, we propose a new set of mathematical and computational schemes which enable efficient and robust fluid‐solid interaction within the MPM framework. These versatile schemes support simulation of both multiphase flow and fully‐coupled solid‐fluid systems. A series of examples is presented to demonstrate their capabilities and performance in the presence of various interacting fluids and solids, including multiphase flow, fluid‐solid interaction, and dissolution.

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A stream function solver for liquid simulations

Cited by 46 publications

References 44 publications

Narrow Band FLIP for Liquid Simulations

Narrow Band FLIP for Liquid Simulations

A polynomial particle-in-cell method

MPM simulation of interacting fluids and solids

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