We propose a physics-based combustion simulation method for computer graphics that extends the mathematical models of previous efforts to automatically capture more realistic flames as well as temperature and soot distributions. Our method includes mathematical models for the thermodynamic properties of real-world fuels which enables, for example, the prediction of adiabatic flame temperatures. We couple this with a model of heat transfer that includes convection, conduction as well as both radiative cooling and heating. This facilitates among other things ignition at a distance without heating up the intermediate air. We model the combustion as infinitely fast chemistry and couple this with the thin flame model, spatially varying laminar burning velocities based on local species and empirical measurements, physically validated soot formation and oxidation as well as water vapor production and condensation. We implement this on adaptive octree-like grids with collocated state variables, a new SBDF2-derived semi-Lagrangian time integrator for velocity, and a multigrid scheme used for multiple solver components. In combination, these models enable us to simulate deflagration phenomena ranging from small scale premixed and diffusion flames to fireballs and subsonic explosions which we demonstrate by several examples. In addition, we validate several of the results based on reference footage and measurements and discuss the relation of prevalent heuristic techniques arising in visual effects production to some of the physics-based models we propose.

Physics based simulation of the dynamics of water spray - water droplets dispersed in air - is a means to increase the visual plausibility of computer graphics modeled phenomena such as waterfalls, water jets and stormy seas. Spray phenomena are frequently encountered by the visual effects industry and often challenge state of the art methods. Current spray simulation pipelines typically employ a combination of Lagrangian (particle) and Eulerian (volumetric) methods - the Eulerian methods being used for parts of the spray where individual droplets are not apparent. However, existing Eulerian methods in computer graphics are based on gas solvers that will for example exhibit hydrostatic equilibrium in certain scenarios where the air is expected to rise and the water droplets fall. To overcome this problem, we propose to simulate spray in the Eulerian domain as a two-way coupled two-continua of air and water phases co-existing at each point in space. The fundamental equations originate in applied physics and we present a number of contributions that make Eulerian two-continua spray simulation feasible for computer graphics applications. The contributions include a Poisson equation that fits into the operator splitting methodology as well as (semi-)implicit discretizations of droplet diffusion and the drag force with improved stability properties. As shown by several examples, our approach allows us to more faithfully capture the dynamics of spray than previous Eulerian methods.

Computer animated ocean waves for feature films are typically carefully choreographed to match the vision of the director and to support the telling of the story. The rough shape of these waves is established in the previsualization (previs) stage, where artists use a variety of modeling tools with fast feedback to obtain the desired look. This poses a challenge to the effects artists who must subsequently match the locked-down look of the previs waves with high-quality simulated or synthesized waves, adding the detail necessary for the final shot. We propose a set of automated techniques for synthesizing Fourier-based ocean waves that match a previs input, allowing artists to quickly enhance the input wave animation with additional higher-frequency detail that moves consistently with the coarse waves, tweak the wave shapes to flatten troughs and sharpen peaks if desired (as is characteristic of deep water waves), and compute a physically reasonable velocity field of the water analytically. These properties are demonstrated with several examples, including a previs scene from a visual effects production environment.

Art direction of high resolution naturalistic liquid simulations is notoriously hard, due to both the chaotic nature of the physics and the computational resources required. Resimulating a scene at higher resolution often produces very different results, and is too expensive to allow many design cycles. We present a method of constraining or guiding a high resolution liquid simulation to stay close to a finalized low resolution version (either simulated or directly animated), restricting the solve to a thin outer shell of liquid around a guide shape . Our method is generally faster than an unconstrained simulation and can be integrated with a standard fluid simulator. We demonstrate several applications, with both simulated and hand-animated inputs.

Abstract 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.

This article presents a generic framework for the representation and deformation of level set surfaces at extreme resolutions. The framework is composed of two modules that each utilize optimized and application specific algorithms: 1) A fastout-of-coredata management scheme that allows for resolutions of the deforming geometry limited only by the available disk space as opposed to memory, and 2) compact and fastcompressionstrategies that reduce both offline storage requirements and online memory footprints during simulation. Out-of-core and compression techniques have been applied to a wide range of computer graphics problems in recent years, but this article is the first to apply it in the context of level set and fluidsimulations. Our framework is generic and flexible in the sense that the two modules can transparently be integrated, separately or in any combination, into existing level set and fluid simulation software based on recently proposed narrow band data structures like the DT-Grid of Nielsen and Museth [2006] and the H-RLE of Houston et al [2006]. The framework can be applied to narrow band signed distances, fluid velocities, scalar fields, particle properties as well as standard graphics attributes like colors, texture coordinates, normals, displacements etc. In fact, our framework is applicable to a large body of computer graphics problems that involve sequential or random access to very large co-dimension one (level set) and zero (e.g. fluid) data sets. We demonstrate this with several applications, including fluid simulations interacting with large boundaries (≈ 15003), surface deformations (≈ 20483), the solution of partial differential equations on large surfaces (≈ 40963) and mesh-to-level set scan conversions of resolutions up to ≈ 350003(7 billion voxels in the narrow band). Our out-of-core framework is shown to be several times faster than current state-of-the-art level set data structures relying on OS paging. In particular we show sustained throughput (grid points/sec) for gigabyte sized level sets as high as 65% of state-of-the-art throughput for in-core simulations. We also demonstrate that our compression techniques out-perform state-of-the-art compression algorithms for narrow bands.

This article introduces the Hierarchical Run-Length Encoded (H-RLE) Level Set data structure. This novel data structure combines the best features of the DT-Grid (of Nielsen and Museth [2004]) and the RLE Sparse Level Set (of Houston et al. [2004]) to provide both optimal efficiency and extreme versatility. In brief, the H-RLE level set employs an RLE in a dimensionally recursive fashion. The RLE scheme allows the compact storage of sequential nonnarrowband regions while the dimensionally recursive encoding along each axis efficiently compacts nonnarrowband planes and volumes. Consequently, this new structure can store and process level sets with effective voxel resolutions exceeding 5000 × 3000 × 3000 (45 billion voxels) on commodity PCs with only 1 GB of memory. This article, besides introducing the H-RLE level set data structure and its efficient core algorithms, also describes numerous applications that have benefited from our use of this structure: our unified implicit object representation, efficient and robust mesh to level set conversion, rapid ray tracing, level set metamorphosis, collision detection, and fully sparse fluid simulation (including RLE vector and matrix representations.) Our comparisons of the popular octree level set and Peng level set structures to the H-RLE level set indicate that the latter is superior in both narrowband sequential access speed and overall memory usage.