Real‐time smoke simulation with improved turbulence by spatial adaptive vorticity confinement

Abstract

Turbulence modeling has recently drawn many attentions in fluid animation to generate small-scale rolling features. Being one of the widely adopted approaches, vorticity confinement method re-injects lost energy dissipation back to the flow. However, previous works suffer from deficiency when large vorticity coefficient e is used, due to the fact that constant e is applied all over the simulated domain. In this paper, we propose a novel approach to enhance the visual effect by employing an adaptive vorticity confinement which varies the strength with respect to the helicity instead of a user-defined constant. To further improve fine details in turbulent flows, we are not only applying our proposed vorticity confinement to lowresolution grid, but also on a finer grid to generate sub-grid level turbulence. Since the incompressible Navier-Stokes equations are solved only in low-resolution grid, this saves a significant amount of computation. Several experiments demonstrate that our method can produce realistic smoke animation with enhanced turbulence effects in real-time.

Research on Vortex-Based Fluid Animation

“…If value of  is too large, simulation result won't be real, as illustrated in reference [4]. So He [5] improved traditional vortex restriction method and put forward self-adaptive vortex restriction method, which is about the changing of vortex restriction intensity according to spiral degree instead of being set by a human being.…”

Reducing numerical dissipation in smoke simulation

“…The problem lies in the fact that the coefficient is constant over the entire simulation domain. To solve the problem, He et al [8] presented an adaptive vorticity confinement coefficient according to helicity other than user-defined constant value. Fig.…”

“…13. Simulations using the vorticity confinement methods with constant (right) [8] and variable coefficients (left) [7]. dissipation.…”

“…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.…”

Visual fluid animation via lifting wavelet transform

“…He et al . proposed a novel approach to enhancing the visual effect based on adaptive vorticity confinement, which varies the strength with respect to the helicity instead of relying on a user‐defined constant. He and Lau further extended this method to synthesize controllable turbulence using second vorticity confinement.…”