Droplets, splashes and sprays: highly detailed liquids in visual effects production.

An often misunderstood or under-appreciated feature of the visual effects pipeline is the sheer quantity of components and layers that go into a single shot, or even, single effect. Liquids, often combining waves, splashes, droplets and sprays, are a particular example of this. Whilst there has been a huge amount of research on liquid simulation in the last decade or so, little has been successful in reducing the number of layers or elements required to create a plausible final liquid effect. Furthermore, the finer-scale phenomena of droplets and sprays, often introduced in this layered approach and crucial for plausibility, are some of the least well catered-for in the existing toolkit. In lieu of adequate tooling, creation of these elements relies heavily on non-physical methods, bespoke setups and artistic ingenuity. This project explores physically-based methods for creating these phenomena, demonstrat- ing improved levels of detail and plausibility over existing non-physical approaches. These provide an alternative to existing workflows that are heavily reliant on artistic input, allowing artists to focus efforts on creative direction rather than trying to recreate physical plausibility. We explore various approaches to increasing the level of detail captured in physically-based liquid simulations, developing a collection of tools that improve existing workflows. First, we investigate the potential of a re-simulation approach to increasing artist iteration on fluid simulations using previous simulation data. Following this, a novel droplet interaction model for ballistic particle simulations is developed to introduce higher levels of detail in simulations of liquid droplets and sprays. This allows physically-plausible interactions between droplet particles to be modelled efficiently and helps to create realistic droplet and spray behaviours. Then, to maximise the quality of the results of these and other particle-based simulations, we develop a high quality particle surfacing algorithm to handle the varied nature of inputs common in production. Finally, we discuss the development of an expression language to manipulate point and volume data commonly used in creating these simulations, as well as elsewhere throughout visual effects. This research was driven directly by production requirements in partnership with a world- leading visual effects studio, DNEG. Projects have been developed to immediately integrate into production, using efficient, industry-standard, open technologies such as OpenVDB. It is shown that the toolkit for splashing liquids, even at fine-scales, can be improved by incorporating greater physical motivation further demonstrating the importance of physical simulation in visual effects and suggesting effects similarly reliant on artistic input (e.g. character/skin deformation) may benefit from increased physical correctness

Narrow band FLIP for liquid simulations

The Fluid Implicit Particle method (FLIP) for liquid simulations uses particles to reduce numerical dissipation and provide important visual cues for events like complex splashes and small-scale features near the liquid surface. Unfortunately, FLIP simulations can be computationally expensive, because they require a dense sampling of particles to fill the entire liquid volume. Furthermore, the vast majority of these FLIP particles contribute nothing to the fluid's visual appearance, especially for larger volumes of liquid. We present a method that only uses FLIP particles within a narrow band of the liquid surface, while efficiently representing the remaining inner volume on a regular grid. We show that a naïve realization of this idea introduces unstable and uncontrollable energy fluctuations, and we propose a novel coupling scheme between FLIP particles and regular grid which overcomes this problem. Our method drastically reduces the particle count and simulation times while yielding results that are nearly indistinguishable from regular FLIP simulations. Our approach is easy to integrate into any existing FLIP implementation

Interactive freeform editing techniques for large-scale, multiresolution level set models

Level set methods provide a volumetric implicit surface representation with automatic smooth blending properties and no self-intersections. They can handle arbitrary topology changes easily, and the volumetric implicit representation does not require the surface to be re-adjusted after extreme deformations. Even though they have found some use in movie productions and some medical applications, level set models are not highly utilized in either special effects industry or medical science. Lack of interactive modeling tools makes working with level set models difficult for people in these application areas.This dissertation describes techniques and algorithms for interactive freeform editing of large-scale, multiresolution level set models. Algorithms are developed to map intuitive user interactions into level set speed functions producing specific, desired surface movements. Data structures for efficient representation of very high resolution volume datasets and associated algorithms for rapid access and processing of the information within the data structures are explained. A hierarchical, multiresolution representation of level set models that allows for rapid decomposition and reconstruction of the complete full-resolution model is created for an editing framework that allows level-of-detail editing. We have developed a framework that identifies surface details prior to editing and introduces them back afterwards. Combining these two features provides a detail-preserving level set editing capability that may be used for multi-resolution modeling and texture transfer. Given the complex data structures that are required to represent large-scale, multiresolution level set models and the compute-intensive numerical methods to evaluate them, optimization techniques and algorithms have been developed to evaluate and display the dynamic isosurface embedded in the volumetric data.Ph.D., Computer Science -- Drexel University, 201