Physics-Based Animation

We propose a novel method of controlling a multi-phase fluid so that it flows into a target shape in a natural way. To preserve the sharp detail of the target shape, we represent it as an implicit function and construct the level-set of that function. Previous approaches add the target-driven control force as an external term, which then becomes attenuated during the velocity projection step, making the convergence process unstable and causing sharp detail to be lost from the target shape. But we calculate the force on the fluid from the pressure discontinuity at the interface between phases, and integrate the control force into the projection step so as to preserve its effect. The control force is calculated using an enhanced version of the ghost fluid method (GFM), which guarantees that the fluid flows from the source shape and converges into the target shape, while achieving a more natural animation than other approaches. Our control force is merged during the projection step avoiding the need for a post-optimization process to eliminate divergence at the liquid interface. This makes our method easy to implement using existing fluid engines and it incurs little computational overhead. Experimental results show the accuracy and robustness of this technique.

Target-driven liquid animation with interfacial discontinuities

This paper describes a motion blur technique which can be applied to rendering fluid simulations that are carried out in the Eulerian framework. Existing motion blur techniques can be applied to rigid bodies, deformable solids, clothes, and several other kinds of objects, and produce satisfactory results. As there is no specific reason to discriminate fluids from the above objects, one may consider applying an existing motion blur technique to render fluids. However, here we show that existing motion blur techniques are intended for simulations carried out in the Lagrangian framework, and are not suited to Eulerian simulations. Then, we propose a new motion blur technique that is suitable for rendering Eulerian simulations.

Eulerian Motion Blur

GPU Gems 3 is out, and it contains a chapter on real-time 3D simulation & rendering of fluids (smoke and liquids) on the GPU, and is available as a free sample chapter online. You may have seen some of these results before on Keenan Crane’s website.

GPU Gems 3

We present a fast method for physically-based animation of fluids on adaptive, unstructured meshes. Our algorithm is capable of correctly handling large-scale fluid forces, as well as their interaction with elastic objects. Our adaptive mesh representation can resolve boundary conditions accurately while maintaining a high level of
efficiency.

Fast Fluid Simulation using Residual Distribution Schemes

We propose a new framework for solving General Shallow Wave Equations (GSWE) in order to efficiently simulate
water flows on solid surfaces under shallow wave assumptions. Within this framework, we develop implicit
schemes for solving the external forces applied to water, including gravity and surface tension. We also present a
two-way coupling method to model interactions between fluid and floating rigid objects. Water flows in this system
can be simulated not only on planar surfaces by using regular grids, but also on curved surfaces directly without
surface parametrization. The experiments show that our system is fast, stable, physically sound, and straightforward
to implement on both CPUs and GPUs. It is capable of simulating a variety of water effects including:
shallow waves, water drops, rivulets, capillary events and fluid/floating rigid body coupling. Because the system
is fast, we can also achieve real-time water drop control and shape design.

Solving General Shallow Wave Equations on Surfaces

Turing first theorized that many biological patterns arise through the processes of reaction and diffusion. Subsequently, reaction-diffusion systems have been studied in many fields, including computer graphics. We first show that for visual simulation purposes, reaction-diffusion equations can be made unconditionally stable using a variety of straightforward methods. Second, we propose an anisotropy embedding that significantly expands the space of possible patterns that can be generated. Third, we show that by adding an advection term, the simulation can be coupled to a fluid simulation to produce visually appealing flows. Fourth, we couple fast marching methods to our anisotropy embedding to create a painting interface to the simulation. Unconditional stability to maintained throughout, and our system runs at interactive rates. Finally, we show that on the Cell processor, it is possible to implement reaction-diffusion on top of an existing fluid solver with no significant performance impact.

Stable Advection-Reaction-Diffusion Systems