We explore an integrated approach to sound generation that supports a wide variety of physics-based simulation models and computer-animated phenomena. Targeting high-quality offline sound synthesis, we seek to resolve animation-driven sound radiation with near-field scattering and diffraction effects. The core of our approach is a sharp-interface finite-difference time-domain (FDTD) wavesolver, with a series of supporting algorithms to handle rapidly deforming and vibrating embedded interfaces arising in physics-based animation sound. Once the solver rasterizes these interfaces, it must evaluate acceleration boundary conditions (BCs) that involve model-and phenomena-specific computations. We introduce acoustic shaders as a mechanism to abstract away these complexities, and describe a variety of implementations for computer animation: near-rigid objects with ringing and acceleration noise, deformable (finite element) models such as thin shells, bubble-based water, and virtual characters. Since time-domain wave synthesis is expensive, we only simulate pressure waves in a small region about each sound source, then estimate a far-field pressure signal. To further improve scalability beyond multi-threading, we propose a fully time-parallel sound synthesis method that is demonstrated on commodity cloud computing resources. In addition to presenting results for multiple animation phenomena (water, rigid, shells, kinematic deformers, etc.) we also propose 3D automatic dialogue replacement (3DADR) for virtual characters so that pre-recorded dialogue can include character movement, and near-field shadowing and scattering sound effects.
Multibody simulation with frictional contact has been a challenging subject of research for the past thirty years. Rigid-body assumptions are commonly used to approximate the physics of contact, and together with Coulomb friction, lead to challenging-to-solve nonlinear complementarity problems (NCP). On the other hand, robot grippers often introduce significant compliance. Compliant contact, combined with regularized friction, can be modeled entirely with ODEs, avoiding NCP solves. Unfortunately, regularized friction introduces highfrequency stiff dynamics and even implicit methods struggle with these systems, especially during slip-stick transitions.To improve the performance of implicit integration for these systems we introduce a Transition-Aware Line Search (TALS), which greatly improves the convergence of the Newton-Raphson iterations performed by implicit integrators. We find that TALS works best with semi-implicit integration, but that the explicit treatment of normal compliance can be problematic. To address this, we develop a Transition-Aware Modified Semi-Implicit (TAMSI) integrator that has similar computational cost to semiimplicit methods but implicitly couples compliant contact forces, leading to a more robust method. We evaluate the robustness, accuracy and performance of TAMSI and demonstrate our approach alongside a sim-to-real manipulation task.
It is increasingly common to model, simulate, and process complex materials based on loopy structures, such as in yarn-level cloth garments, which possess topological constraints between inter-looping curves. While the input model may satisfy specific topological linkages between pairs of closed loops, subsequent processing may violate those topological conditions. In this paper, we explore a family of methods for efficiently computing and verifying linking numbers between closed curves, and apply these to applications in geometry processing, animation, and simulation, so as to verify that topological invariants are preserved during and after processing of the input models. Our method has three stages: (1) we identify potentially interacting loop-loop pairs, then (2) carefully discretize each loop's spline curves into line segments so as to enable (3) efficient linking number evaluation using accelerated kernels based on either counting projected segment-segment crossings, or by evaluating the Gauss linking integral using direct or fast summation methods (Barnes-Hut or fast multipole methods). We evaluate CPU and GPU implementations of these methods on a suite of test problems, including yarn-level cloth and chainmail, that involve significant processing: physics-based relaxation and animation, user-modeled deformations, curve compression and reparameterization. We show that topology errors can be efficiently identified to enable more robust processing of loopy structures.
blocks either from scratch or by loading traditional weaves, compose the blocks into large structures, and edit the pattern at various scales. Furthermore, users can verify the design with a physically based simulator, which predicts and visualizes the geometric structure of the woven material and reveals potential defects at an interactive rate. We demonstrate a range of results created with our tool, from simple two-layer cloth and well known 3D structures to a more sophisticated design of a 3D woven shoe, and we evaluate the effectiveness of our system via a formative user study.CCS Concepts: • Computing methodologies → Shape modeling.
Thin shells -solids that are thin in one dimension compared to the other two -often emit rich nonlinear sounds when struck. Strong excitations can even cause chaotic thin-shell vibrations, producing sounds whose energy spectrum diffuses from low to high frequencies over time -a phenomenon known as wave turbulence. It is all these nonlinearities that grant shells such as cymbals and gongs their characteristic "glinting" sound. Yet, simulation models that efficiently capture these sound effects remain elusive.We propose a physically based, multi-scale reduced simulation method to synthesize nonlinear thin-shell sounds. We first split nonlinear vibrations into two scales, with a small low-frequency part simulated in a fully nonlinear way, and a high-frequency part containing many more modes approximated through time-varying linearization. This allows us to capture interesting nonlinearities in the shells' deformation, tens of times faster than previous approaches. Furthermore, we propose a method that enriches simulated sounds with wave turbulent sound details through a phenomenological diffusion model in the frequency domain, and thereby sidestep the expensive simulation of chaotic high-frequency dynamics. We show several examples of our simulations, illustrating the efficiency and realism of our model.
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