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ACM Transactions on Graphics (SIGGRAPH)

Capturing the visually compelling features of large-scale water phenomena,such as the spray clouds of crashing waves, stormy seas, or waterfalls, involves simulating not only the water but also the motion of the air interacting with it. However, current solutions in the visual effects industry still largely rely on single-phase solvers and non-physical “white-water” heuristics. To address these limitations, we present Phase-Field-FLIP (PF-FLIP), a hybrid Eulerian/Lagrangian method for the fully physics-based simulation of very large-scale, highly turbulent multiphase flows at high Reynolds numbers and high fluid density contrasts. PF-FLIP transports mass and momentum in a consistent, non-dissipative manner and, unlike most existing multiphase approaches, does not require a surface reconstruction step. Furthermore, we employ spatial adaptivity across all critical components of the simulation algorithm, including the pressure Poisson solver. We augment PF-FLIP with a dual multiresolution scheme that couples an efficient treeless adaptive grid with adaptive particles, along with a fast adaptive Poisson solver tailored for high-density-contrast multiphase flows. Our method enables the simulation of two-phase flow scenarios with a level of physical realism and detail previously unattainable in graphics, supporting billions of particles and adaptive 3D resolutions with thousands of grid cells per dimension on a single workstation.

Proceedings of the ACM on Computer Graphics and Interactive Techniques (SCA)

Demand for high-quality virtual 3D characters continues to grow in both entertainment and communication, and with it, the desire for interactive avatars. This presents unique challenges for high-fidelity interactive solutions that must be quick to set up, efficient to run in real-time on consumer hardware, and work well, not only on human characters, but also on fantastical and heavily stylized ones.  We present Interactive Facial Animation (IFA), a novel approach to augment facial animation rigs with shell simulation and contact without requiring anatomical priors or artist intervention. Our method uses an efficient shell model that tracks the output of a face rig in real-time and incorporates realistic contact. By designing our shell model to be differentiable, we can use inverse simulation to reconstruct realistic non-uniform stiffness that captures both stiff (ears, nose) and soft (cheeks, lips) areas, based on the rig’s deformation space. The reconstruction process imposes hard limits on acceptable errors, which ensures that IFA preserves the resolution and expressiveness of the source material, a common shortcoming in many face simulation pipelines. With performance in mind, we demonstrate IFA using a variant of the Fast Mass-Springs method. However, the presented concept can be realized with any differentiable physics solver that provides reliable convergence.  We showcase our method in four different character rigs, achieving simulation update runtimes between 0.39 and 1.27 milliseconds (787-2564 FPS) on a single CPU thread. Unlike existing methods that require lengthy preparation times, our pipeline can be ready to use within minutes, also on the CPU.

Computer Graphics Forum

Physics simulation is a cornerstone of many computer graphics applications, ranging from video games and virtual reality to visual effects and computational design. The number of techniques for physically-based modeling and animation has thus skyrocketed over the past few decades, facilitating the simulation of a wide variety of materials and physical phenomena. This report captures the state-of-the-art of multiphysics simulation for computer graphics applications. Although a lot of work has focused on simulating individual phenomena, here we put an emphasis on methods developed by the computer graphics community for simulating various physical phenomena and materials, as well as the interactions between them. These include combinations of discretization schemes, mathematical modeling frameworks, and coupling techniques. For the most commonly used methods we provide an overview of the state-of-the-art and deliver valuable insights into the various approaches. A selection of software frameworks that offer out-of-the-box multiphysics modeling capabilities is also presented. Finally, we touch on emerging trends in physics-based animation that affect multiphysics simulation, including machine learning-based methods which have become increasingly popular in recent years.