Ante Qu

Contacts and collisions are ubiquitous in physics simulations and computer animations. In this dissertation, we discuss two ways to more effectively simulate and process collisions. In particular, we model ground impact sounds and verify the topology of loopy structures. Firstly, rigid-body sound-synthesis methods often omit the ground sound in object–ground impacts, and we propose and discuss a physics-based analytical expression to model the transient ground-sound emission. This model can be used either in a Rayleigh integral to directly sum the total ground sound or as an "acoustic shader" for a finite-difference time-domain wave simulation. We find that when the object's modal sound is inaudible due to its shape and size, the ground sound is more audible than the transient object sound in scenarios where a dense object impacts a soft ground and scenarios where the impact point has a low elevation angle to the listening point. Secondly, it is increasingly common to model, simulate, and process complex materials based on loopy structures, such as in yarn-level cloth garments, which possess meaningful topological constraints between inter-looping curves. We explore a family of methods for efficiently computing and verifying linking numbers between closed curves, and apply them 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. We evaluate these methods on a suite of test problems, including yarn-level cloth and chainmail examples, that involve significant processing: physics-based relaxation and animation, user-modeled deformations, and curve compression and reparameterization. We also verify the topology of a stitch pattern of open curves, arranged as a braid. We show that topology errors can be efficiently identified to enable more robust processing of loopy structures.

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.

3D weaving is an emerging technology for manufacturing multilayer woven textiles. In this work, we present Weavecraft: an interactive, simulation-based design tool for 3D weaving. Unlike existing textile software that uses 2D representations for design patterns, we propose a novel weave block representation that helps the user to understand 3D woven structures and to create complex multi-layered patterns. With Weavecraft, users can create 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.

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 high-frequency 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 semi-implicit 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 relevant sim-to-real manipulation tasks.

A. M. Castro, A. Qu, N. Kuppuswamy, A. Alspach and M. Sherman, "A Transition-Aware Method for the Simulation of Compliant Contact With Regularized Friction," in IEEE Robotics and Automation Letters, vol. 5, no. 2, pp. 1859–1866, April 2020.

Rigid-body impact sound synthesis methods often omit the ground sound. In this paper we analyze an idealized ground-sound model based on an elastodynamic halfspace, and use it to identify scenarios wherein ground sound is perceptually relevant versus when it is masked by the impacting object’s modal sound or transient acceleration noise. Our analytical model gives a smooth, closed-form expression for ground surface acceleration, which we can then use in the Rayleigh integral or in an “acoustic shader” for a finite-difference time-domain wave simulation. We find that when modal sound is inaudible, ground sound is audible in scenarios where a dense object impacts a soft ground and scenarios where the impact point has a low elevation angle to the listening point.

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.

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.

Many objects of interest in imaging, such as biological cells or turbulent air, are phase-only objects that are transparent and thus produce little to no contrast in wide-field microscopes. The phase accumulated by this light carries important information about the refractive index and the thickness of the object. We propose a method for retrieving the phase by using a spatial light modulator (SLM) to conjugate the phase of the object, flattening the wavefront of light passing through the SLM and the object. After we flatten the wavefront, the resulting configuration on the SLM is the conjugate of the phase image, which we can easily invert to recover the original phase image. This method retrieves the phase without using any prior knowledge about the object.

    Our algorithm performs a decomposition of the image into basis functions and searches for the coefficients that yield the flattest output intensity pattern. This algorithm takes advantage of the fact that a relatively small number of basis elements can store the majority of the information in the image. Popular phase retrieval methods such as the Gerchberg–Saxton algorithm can only converge to the phase image under light that is sufficiently coherent. From our simulations, we find that our method consistently produces correlations of over 99% with the original phase image, using either incoherent or coherent light and only 10% as many basis elements as the number of pixels in the image. We believe this result is a strong indication that this method will be able to reliably retrieve a direct phase image in the laboratory.

The guiding center code ORBIT was originally developed 30 years ago to study the drift-orbit effects of charged particles in the strong guiding magnetic fields of tokamaks. Today, ORBIT remains a very active tool in magnetic-confinement fusion research and continues to adapt to the latest toroidal devices, such as the NSTX-Upgrade, for which it plays a very important role in the study of energetic particle effects. Although the capabilities of ORBIT have improved throughout the years, the code still remains a serial application, which has now become an impediment to the lengthy simulations required for the NSTX-U project. In this work, multi-threaded parallelism is introduced in the core of the code with the goal of achieving the largest performance improvement while minimizing changes made to the source code. To that end, we introduce compiler directives in the most compute-intensive parts of the code, which constitutes the stable core that seldom changes. Standard OpenMP directives are used for shared-memory CPU multi-threading while newly developed OpenACC directives and CUDA Fortran code are used for Graphics Processing Unit (GPU) multi-threading. Our data shows that the fully-optimized CUDA Fortran version is 53.6 times faster than the original code.