Multi-stage high order semi-Lagrangian schemes for incompressible flows in Cartesian geometries

Efficient transport algorithms are essential to the numerical resolution of incompressible fluid flow problems. Semi-Lagrangian methods are widely used in grid based methods to achieve this aim. The accuracy of the interpolation strategy then determines the properties of the scheme. We introduce a simple multi-stage procedure which can easily be used to increase the order of accuracy of a code based on multi-linear interpolations. This approach is an extension of a corrective algorithm introduced by Dupont \& Liu (2003, 2007). This multi-stage procedure can be easily implemented in existing parallel codes using a domain decomposition strategy, as the communications pattern is identical to that of the multi-linear scheme. We show how a combination of a forward and backward error correction can provide a third-order accurate scheme, thus significantly reducing diffusive effects while retaining a non-dispersive leading error term.Comment: 14 pages, 10 figure

Liquid simulation with mesh-based surface tracking

Animating detailed liquid surfaces has always been a challenge for computer graphics researchers and visual effects artists. Over the past few years, researchers in this field have focused on mesh-based surface tracking to synthesize extremely detailed liquid surfaces as efficiently as possible. This course provides a solid understanding of the steps required to create a fluid simulator with a mesh-based liquid surface. The course begins with an overview of several existing liquid-surface-tracking techniques and the pros and cons of each method. Then it explains how to embed a triangle mesh into a finite-difference-based fluid simulator and describes several methods for allowing the liquid surface to merge together or break apart. The final section showcases the benefits and further applications of a mesh-based liquid surface, highlighting state-of-the-art methods for tracking colors and textures, maintaining liquid volume, preserving small surface features, and simulating realistic surface-tension waves

ITR/PE+SY digital clay for shape input and display

Issued as final reportNational Science Foundatio

The back and forth error compensation and correction method for linear hyperbolic systems and a conservative BFECC limiter

In this thesis, we studied the Back and Forth Error Compensation and Correction (BFECC) method for linear hyperbolic PDE systems and nonlinear scalar conservation laws. We extend the BFECC method from scalar hyperbolic PDEs to linear hyperbolic PDE systems, and showed similar stability and accuracy improvement are still valid under modest assumptions on the systems. Motivated by this theoretical result, we propose BFECC schemes for the Maxwell’s equations. On uniform orthogonal grids, the BFECC schemes are guaranteed to be second order accurate and have larger CFL numbers than that of the classical Yee scheme. On non-orthogonal and unstructured grids, we propose to use a simple least square local linear approximation scheme as the underlying scheme for the BFECC method. Numerical results showed the proposed schemes are stable and are second order accurate on non-orthogonal grids and for systems with variable coefficients. We also studied a conservative BFECC limiter that reduces spurious oscillations for numerical solutions of nonlinear scalar conservation laws. Numerical examples with the Burgers’ equation and KdV equations are studied to demonstrate effectiveness of this limiter.Ph.D

IST Austria Thesis

Computer graphics is an extremely exciting field for two reasons. On the one hand, there is a healthy injection of pragmatism coming from the visual effects industry that want robust algorithms that work so they can produce results at an increasingly frantic pace. On the other hand, they must always try to push the envelope and achieve the impossible to wow their audiences in the next blockbuster, which means that the industry has not succumb to conservatism, and there is plenty of room to try out new and crazy ideas if there is a chance that it will pan into something useful. Water simulation has been in visual effects for decades, however it still remains extremely challenging because of its high computational cost and difficult artdirectability. The work in this thesis tries to address some of these difficulties. Specifically, we make the following three novel contributions to the state-of-the-art in water simulation for visual effects. First, we develop the first algorithm that can convert any sequence of closed surfaces in time into a moving triangle mesh. State-of-the-art methods at the time could only handle surfaces with fixed connectivity, but we are the first to be able to handle surfaces that merge and split apart. This is important for water simulation practitioners, because it allows them to convert splashy water surfaces extracted from particles or simulated using grid-based level sets into triangle meshes that can be either textured and enhanced with extra surface dynamics as a post-process. We also apply our algorithm to other phenomena that merge and split apart, such as morphs and noisy reconstructions of human performances. Second, we formulate a surface-based energy that measures the deviation of a water surface froma physically valid state. Such discrepancies arise when there is a mismatch in the degrees of freedom between the water surface and the underlying physics solver. This commonly happens when practitioners use a moving triangle mesh with a grid-based physics solver, or when high-resolution grid-based surfaces are combined with low-resolution physics. Following the direction of steepest descent on our surface-based energy, we can either smooth these artifacts or turn them into high-resolution waves by interpreting the energy as a physical potential. Third, we extend state-of-the-art techniques in non-reflecting boundaries to handle spatially and time-varying background flows. This allows a novel new workflow where practitioners can re-simulate part of an existing simulation, such as removing a solid obstacle, adding a new splash or locally changing the resolution. Such changes can easily lead to new waves in the re-simulated region that would reflect off of the new simulation boundary, effectively ruining the illusion of a seamless simulation boundary between the existing and new simulations. Our non-reflecting boundaries makes sure that such waves are absorbed

Modeling of Complex Large-Scale Flow Phenomena

Flows at large scales are capable of unmatched complexity. At large spatial scales, they can exhibit phenomena like waves, tornadoes, and a screaming concert audience; at high densities, they can create shockwaves, and can cause stampedes. Though strides have been made in simulating flows like fluids and crowds, extending these algorithms with scale poses challenges in ensuring accuracy while maintaining computational efficiency. In this dissertation, I present novel techniques to simulate large-scale flows using coupled Eulerian-Lagrangian models that employ a combination of discretized grids and dynamic particle-based representations. I demonstrate how such models can efficiently simulate flows at large-scales, while maintaining fine-scale features. In fluid simulation, a long-standing problem has been the simulation of large-scale scenes without compromising fine-scale features. Though approximate multi-scale models exist, accurate simulation of large-scale fluid flow has remained constrained by memory and computational limits of current generation PCs. I propose a hybrid domain-decomposition model that, by coupling Lagrangian vortex-based methods with Eulerian velocity-based methods, reduces memory requirements and improves performance on parallel architectures. The resulting technique can efficiently simulate scenes significantly larger than those possible with either model alone. The motion of crowds is another class of flows that exhibits novel complexities with increasing scale. Navigation of crowds in virtual worlds is traditionally guided by a static global planner, combined with dynamic local collision avoidance. However, such models cannot capture long-range crowd interactions commonly observed in pedestrians. This discrepancy can cause sharp changes in agent trajectories, and sub-optimal navigation. I present a technique to add long-range vision to virtual crowds by performing collision avoidance at multiple spatial and temporal scales for both Eulerian and Lagrangian crowd navigation models, and a novel technique to blend both approaches in order to obtain collision-free velocities efficiently. The resulting simulated crowds show better correspondence with real-world pedestrians in both qualitative and quantitative metrics, while adding a minimal computational overhead. Another aspect of real-world crowds missing from virtual agents is their behavior at high densities. Crowds at such scales can often exhibit chaotic behavior commonly known as emph{crowd turbulence}; this phenomenon has the potential to cause mishaps leading to loss of life. I propose modeling inter-personal stress in dense crowds using an Eulerian model, coupled with a physically-based Lagrangian agent-based model to simulate crowd turbulence. I demonstrate how such a hybrid model can create virtual crowds whose trajectories show visual and quantifiable similarities to turbulent crowds in the real world. The techniques proposed in this thesis demonstrate that hybrid Eulerian-Lagrangian modeling presents a versatile approach for modeling large-scale flows, such as fluids and crowds, efficiently on current generation PCs.Doctor of Philosoph

Advections with Significantly Reduced Dissipation and Diffusion

Back and Forth Error Compensation and Correction (BFECC) can be applied to reduce dissipation and diffusion in advection steps, such as velocity, smoke density, and image advections. It can be implemented trivially as a small modification of the first-order upwind or semi-Lagrangian integration of advection equations. It provides second-order accuracy in both space and time and reduces volume loss significantly. We demonstrate its benefits on the simulation of smoke, bubbles, and interaction between water, a solid, and air

Visual modeling and simulation of multiscale phenomena

Many large-scale systems seen in real life, such as human crowds, fluids, and granular materials, exhibit complicated motion at many different scales, from a characteristic global behavior to important small-scale detail. Such multiscale systems are computationally expensive for traditional simulation techniques to capture over the full range of scales. In this dissertation, I present novel techniques for scalable and efficient simulation of these large, complex phenomena for visual computing applications. These techniques are based on a new approach of representing a complex system by coupling together separate models for its large-scale and fine-scale dynamics. In fluid simulation, it remains a challenge to efficiently simulate fine local detail such as foam, ripples, and turbulence without compromising the accuracy of the large-scale flow. I present two techniques for this problem that combine physically-based numerical simulation for the global flow with efficient local models for detail. For surface features, I propose the use of texture synthesis, guided by the physical characteristics of the macroscopic flow. For turbulence in the fluid motion itself, I present a technique that tracks the transfer of energy from the mean flow to the turbulent fluctuations and synthesizes these fluctuations procedurally, allowing extremely efficient visual simulation of turbulent fluids. Another large class of problems which are not easily handled by traditional approaches is the simulation of very large aggregates of discrete entities, such as dense pedestrian crowds and granular materials. I present a technique for crowd simulation that couples a discrete per-agent model of individual navigation with a novel continuum formulation for the collective motion of pedestrians. This approach allows simulation of dense crowds of a hundred thousand agents at near-real-time rates on desktop computers. I also present a technique for simulating granular materials, which generalizes this model and introduces a novel computational scheme for friction. This method efficiently reproduces a wide range of granular behavior and allows two-way interaction with simulated solid bodies. In all of these cases, the proposed techniques are typically an order of magnitude faster than comparable existing methods. Through these applications to a diverse set of challenging simulation problems, I demonstrate the benefits of the proposed approach, showing that it is a powerful and versatile technique for the simulation of a broad range of large and complex systems