Scalable fluid simulation using anisotropic turbulence particles
ACM SIGGRAPH Asia 2010 papers
Stochastic modeling of immersed rigid-body dynamics
SIGGRAPH Asia 2013 Technical Briefs
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Light-weight objects floating inside a flow play a significant role in the liveliness of our world (e.g., leaves, dust, snowflakes, bubbles). They follow the flow and show complex and chaotic motion. First, animators usually add simple random noise to the streaming path. However, this method yields low-quality floating behavior since the random noise does not take into account the spatial and temporal distribution of underlying flow turbulence. For example, obstacle-induced oscillation cannot be easily created as a major source of the unique motion. Second, floating objects can be passively advected by flow velocities from physically-based simulation. A critical challenge is that modeling the important jiggling motion requires turbulent flow field, which is hard to achieve by direct numerical simulation (DNS) due to limited computational resources and numerical dissipation. This situation deteriorates severely when realtime performance and interactivity are demanded in a 3D gaming environment. Moreover, the floating motion has intrinsic stochastic nature, i.e., the repeated executions result in nonidentical dynamics, which is not achievable with deterministic simulation. Third, adding noise to fluid solvers can introduce chaotic flow velocities (e.g. [Pfaff et al. 2010]). In an approach, special Langevin particles affect fluid solver with forces [Chen et al. 2011]. However, such methods rely on DNS and apply chaotic addition to the whole fluid domain, which is inefficient in handling a group of floating objects inside.