Fast animation of turbulence using energy transport and procedural synthesis

Narain, Rahul; Sewall, Jason; Carlson, Mark

doi:10.1145/1457515.1409119

Cited by 58 publications

(70 citation statements)

References 26 publications

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“…Recently curl operation [46] is applied on Perlin [9,47] and wavelet vector noises [48] to generate turbulent components at various frequencies and scales. Energy cascade is modeled to include spatial distribution and turbulence dynamics using local assembled wavelets [48], linear k-e equation [47], oneequation [9], and complete tow-equation of k-e [49,10]. Instead of directly layering turbulence components on the basic flow, Zhao et al [41] modeled fluctuations as controllable turbulence force to agitate the basic flow.…”

Section: Subscale Turbulence Modelmentioning

confidence: 99%

“…Adaptive mesh [3], irregular mesh [4,5], and dynamical mesh [6] are proposed to reduce the numerical dissipation without significantly increasing computation. Rather than directly reducing the numerical dissipation, several methods generate artificial details to compensate for visual loss using vorticity confinement [7,8] and subscale turbulence models [9,10]. Grid-based methods require resampling flow field, which is equivalent to the low-pass filter to smear out high-frequency components.…”

Section: Introductionmentioning

confidence: 99%

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Reducing numerical dissipation in smoke simulation

Huang¹,

Kavan²,

Li³

et al. 2015

Graphical Models

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Section: Subscale Turbulence Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Reducing numerical dissipation in smoke simulation

Huang¹,

Kavan²,

Li³

et al. 2015

Graphical Models

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“…In contrast to this, our work targets the interaction of objects with the fluid, namely turbulence created by flows around obstacles. While previously used methods either require a manual seeding of turbulence [Selle et al 2005] or rely on the simulation to resolve the interaction with the object accurately enough [Kim et al 2008b;Narain et al 2008], we precompute the turbulence generated around an object using techniques from the wall flow theory of traditional computational fluid dynamics (CFD). Such theory models the behavior of near-wall regions of flow around objects, which is important since these boundary layers strongly influence forces on the object as well as shed turbulent structures.…”

Section: Introductionmentioning

confidence: 99%

“…Our method also elegantly handles turbulent free surface flows, a topic that has been barely studied in previous work other than the work of Selle et al [2005] and Narain et al [2008]. In addition, our method can accurately compute turbulent wakes around objects that are too fine to be resolved on the simulation grid.…”

Section: Introductionmentioning

confidence: 99%

“…They explicitly address computing flows around objects efficiently by modulating the potential field, however, their method does not model the complex turbulent effects near the wall. Most recently, researchers have considered transporting quantities with a lower resolution simulation which is used to generate detail [Kim et al 2008b;Schechter and Bridson 2008;Narain et al 2008]. However, the treatment of obstacles is not the focus of these techniques.…”

Section: Introductionmentioning

confidence: 99%

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Synthetic turbulence using artificial boundary layers

et al. 2009

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Figure 1: Our algorithm allows us to precompute detailed boundary layer data and efficiently reuse it for new simulations. We are able to generates turbulent vortices taking into account the relative velocity of an obstacle in the flow. Here, we apply our algorithm to a very thin object that is barely represented on the simulation grid. AbstractTurbulent vortices in fluid flows are crucial for a visually interesting appearance. Although there has been a significant amount of work on turbulence in graphics recently, these algorithms rely on the underlying simulation to resolve the flow around objects. We build upon work from classical fluid mechanics to design an algorithm that allows us to accurately precompute the turbulence being generated around an object immersed in a flow. This is made possible by modeling turbulence formation based on an averaged flow field, and relying on universal laws describing the flow near a wall. We precompute the confined vorticity in the boundary layer around an object, and simulate the boundary layer separation during a fluid simulation. Then, a turbulence model is used to identify areas where this separated layer will transition into actual turbulence. We sample these regions with vortex particles, and simulate the further dynamics of the vortices based on these particles. We will show how our method complements previous work on synthetic turbulence, and yields physically plausible results. In addition, we demonstrate that our method can efficiently compute turbulent flows around a variety of objects including cars, whisks, as well as boulders in a river flow. We can even apply our model to precomputed static flow fields, yielding turbulent dynamics without a costly simulation.

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Simulating colliding flows in smoothed particle hydrodynamics with fractional derivatives

Ozgen

Sumengen

Kallmann

et al. 2013

Computer Animation & Virtual

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We propose a new method based on the use of fractional differentiation for improving the efficiency and realism of simulations based on smoothed particle hydrodynamics (SPH). SPH represents a popular particle‐based approach for fluid simulation and a high number of particles is typically needed for achieving high quality results. However, as the number of simulated particles increase, the speed of computation degrades accordingly. The proposed method employs fractional differentiation to improve the results obtained with SPH in a given resolution. The approach is based on the observation that effects requiring a high number of particles are most often produced from colliding flows, and therefore, when the modeling of this behavior is improved, higher quality results can be achieved without changing the number of particles being simulated. Our method can be employed to reduce the resolution without significant loss of quality, or to improve the quality of the simulation in the current chosen resolution. The advantages of our method are demonstrated with several quantitative evaluations. Copyright © 2013 John Wiley & Sons, Ltd.

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Fast animation of turbulence using energy transport and procedural synthesis

Cited by 58 publications

References 26 publications

Reducing numerical dissipation in smoke simulation

Reducing numerical dissipation in smoke simulation

Synthetic turbulence using artificial boundary layers

Simulating colliding flows in smoothed particle hydrodynamics with fractional derivatives

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