Physics-Based Animation

Smoke animations are hard to art-direct because simple changes in parameters such as simulation resolution often lead to unpredictable changes in the final result. Previous work has addressed this problem with a guiding approach which couples low-resolution simulations – that exhibit the desired flow and behaviour – to the final, high-resolution simulation. This is done in such a way that the desired low frequency features are to some extent preserved in the high-resolution simulation. However, the steady (i.e. constant) guiding used often leads to a lack of sufficiently high detail, and employing time-dependent guiding is expensive because the matrix of the resulting set of equations needs to be recomputed at every iteration. We propose an improved mathematical model for Eulerian-based simulations which is better suited for dynamic, time-dependent guiding of smoke animations through a novel variational coupling of the low- and high-resolution simulations. Our model results in a matrix that does not require re-computation when the guiding changes over time, and hence we can employ time-dependent guiding more efficiently both in terms of storage and computational requirements. We demonstrate that time-dependent guiding allows for more high frequency detail to develop without losing correspondence to the low resolution simulation. Furthermore, we explore various artistic effects made possible by time-dependent guiding.

Improved Variational Guiding of Smoke Animations

This paper presents a physically based method for simulating the heat transfers between the different environmental elements to synthesize realistic winter sceneries. We simulate the snow fall over the ground, as well as the conductive, convective and radiative thermal transfers using a finite volume method according to the variations of air and dew point temperatures, the amount of snow, cloud cover and day-night cycles. Our approach takes into account phase changes such as snow melting into water or water freezing into ice.

Heat Transfer Simulation for Modeling Realistic Winter Sceneries

Ke-Sen’s list of Eurographics 2010 papers is filling out, and the full list is here.

The physics-related subset:

• A Hybrid Approach to Multiple Fluid Simulation Using Volume Fractions
• Improved Variational Guiding of Smoke Animations
• Heat Transfer Simulation for Modeling Realistic Winter Scenes
• Hybrid Simulation of Miscible Mixing with Viscous Fingering
• Tetrahedral Embedded Boundary Methods for Accurate and Flexible Adaptive Fluids

And a couple short papers as well:

• A Spatially Adaptive Morphological Filter For Dual-Resolution Interface Tracking Of Fluids
• Animating Sand as a Surface Flow

This paper presents a hybrid approach to multiple fluid simulation that can handle miscible and immiscible fluids, simultaneously. We combine distance functions and volume fractions to capture not only the discontinuous interface between immiscible fluids but also the smooth transition between miscible fluids. Our approach consists of four steps: velocity field computation, volume fraction advection, miscible fluid diffusion, and visualization. By providing a combining scheme between volume fractions and level set functions, we are able to take advantages of both representation schemes of fluids. From the system point of view, our work is the first approach to Eulerian grid-based multiple fluid simulation including both miscible and immiscible fluids. From the technical point of view, our approach addresses the issues arising from variable density and viscosity together with material diffusion. We show that the effectiveness of our approach to handle multiple miscible and immiscible fluids through experiments.

A Hybrid Approach to Multiple Fluid Simulation Using Volume Fractions

We describe an interactive system featuring fluid-driven animation that responds to moving objects. Our system includes a GPU-accelerated Eulerian fluid solver that is suited for real-time use because it is unconditionally stable, takes constant calculation time per frame, and provides good visual fidelity. We dynamically translate the fluid simulation domain to track a user-controlled object. The fluid motion is visualized via its effects on particles which respond to the calculated fluid velocity field, but which are not constrained to stay within the bounds of the simulation domain. As particles leave the simulation domain, they seamlessly transition to purely particle-based motion, obscuring the point at which the fluid simulation ends. We additionally describe a hardware-accelerated volume rendering system that treats the particles as participating media and can render effects such as smoke, dust, or mist. Taken together, these components can be used to add fluid-driven effects to an interactive system without enforcing constraints on user motion, and without visual artifacts resulting from the finite extents of Eulerian fluid simulation methods.

Interactive Fluid-Particle Simulation using Translating Eulerian Grids

Our goal is to design robust algorithms that can be used for building real-time systems, but rather than starting with overly simplistic particle-based methods, we aim to modify higher-end visual effects algorithms. A major stumbling block in utilizing these visual effects algorithms for real-time simulation is their computational intensity. Physics engines struggle to fully exploit available resources to handle high scene complexity due to their need to divide those resources among many smaller time steps, and thus to obtain the maximum spatial complexity we design our algorithms to take only one time step per frame. This requires addressing both accuracy and stability issues for collisions, contact, and evolution in a manner significantly different from a typical simulation in which one can rely on shrinking the time step to ameliorate accuracy and stability issues. In this paper we present a novel algorithm for conserving both energy and momentum when advancing rigid body orientations, as well as a novel technique for clamping energy gain during contact and collisions. We also introduce a technique for fast and realistic fracture of rigid bodies using a novel collision-centered prescoring algorithm.

Energy Stability and Fracture for Frame Rate Rigid Body Simulations

Huamin Wang’s PhD thesis on liquid animation is available here:

Practical Water Animation Using Physics and Image Based Methods

Finite element simulations of nonlinear deformable models are computationally costly, routinely taking hours or days to compute the motion of detailed meshes. Dimensional model reduction can make simulations orders of magnitude faster, but is unsuitable for general deformable body simulations because it requires expensive precomputations, and it can suppress motion that lies outside the span of a pre-specified low-rank basis. We present an online model reduction method that does not have these limitations. In lieu of precomputation, we analyze the motion of the full model as the simulation progresses, incrementally building a reduced-order nonlinear model, and detecting when our reduced model is capable of performing the next timestep. For these subspace steps, full-model computation is “skipped” and replaced with a very fast (on the order of milliseconds) reduced order step. We present algorithms for both dynamic and quasistatic simulations, and a “throttle” parameter that allows a user to trade off between faster, approximate previews and slower, more conservative results. For detailed meshes undergoing low-rank motion, we have observed speedups of over an order of magnitude with our method.

Skipping Steps in Deformable Simulation with Online Model Reduction

Turbulent 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.

Synthetic Turbulence using Artificial Boundary Layers

A variety of animation effects such as herds and fluids contain detailed motion fields characterized by repetitive structures. Such detailed motion fields are often visually important, but tedious to specify manually or expensive to simulate computationally. Due to the repetitive nature, some of these motion fields (e.g. turbulence in fluids) could be synthesized by procedural texturing, but procedural texturing is known for its limited generality.

We apply example-based texture synthesis for motion fields. Our technique is general and can take on a variety of user inputs, including captured data, manual art, and physical/procedural simulation. This data-driven approach enables artistic effects that are difficult to achieve via previous methods, such as heart shaped swirls in fluid animation. Due to the use of texture synthesis, our method is able to populate a large output field from a small input exemplar, imposing minimum user workload. Our algorithm also allows the synthesis of output motion fields not only with the same dimension as the input (e.g. 2D to 2D) but also of higher dimension, such as 3D volumetric outputs from 2D planar inputs. This cross-dimension capability supports a convenient usage scenario, i.e. the user could simply supply 2D images and our method produces a 3D motion field with similar characteristics. The motion fields produced by our method are generic, and could be combined with a variety of large-scale low-resolution motions that are easy to specify either manually or computationally but lack the repetitive structures to be characterized as textures. We apply our technique to a variety of animation phenomena, including smoke, liquid, and group motion.

Motion Field Texture Synthesis