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Please note – latest publications can be found here! Abstract: We present a novel deep learning algorithm to synthesize high resolution flow simulations with reusable repositories of space-time flow data. In our work, we employ a descriptor learning approach to encode the similarity between what is the most computationally efficient way to make ripples? regions with differences in resolution and numerical viscosity. We use convolutional neural networks to generate the descriptors from fluid data such as smoke density and flow velocity.

Abstract: This paper proposes a novel framework to evaluate fluid simulation methods based on crowd-sourced user studies in order to robustly gather large numbers of opinions. The key idea for a robust and reliable evaluation is to use a reference video from a carefully selected real-world setup in the user study. By conducting a series of controlled user studies and comparing their evaluation results, we observe various factors that affect the perceptual evaluation. Abstract: In this paper we present a novel approach to simulate cutting of deformable solids in virtual environments. A particular strength of our method is that there is no requirement to modify either topology or geometry of the underlying discretization mesh. Abstract: We propose a novel method to extract hierarchies of vortex filaments from given three-dimensional flow velocity fields. They extract multi-scale information from the input velocity field, which is not possible with any previous filament extraction approach.

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Once computed, these HVSs provide a powerful mechanism for data compression and a very natural way for modifying flows. Abstract: Liquids exhibit complex non-linear behavior under changing simulation conditions such as user interactions. We propose a method to map this complex behavior over a parameter range onto reduced representation based on space-time deformations. In order to represent the complexity of the full space of inputs, we leverage the power of generative neural networks to learn a reduced representation. Abstract: This paper proposes a new data-driven approach for modeling detailed splashes for liquid simulations with neural networks. Our model learns to generate small-scale splash detail for fluid-implicit-particle methods using training data acquired from physically accurate, high-resolution simulations.

We use neural networks to model the regression of splash formation using a classifier together with a velocity modification term. Abstract: We apply a novel optimization scheme from the image processing and machine learning areas, a fast Primal-Dual method, to achieve controllable and realistic fluid simulations. While our method is generally applicable to many problems in fluid simulations, we focus on the two topics of fluid guiding and separating solid-wall boundary conditions. Each problem is posed as an optimization problem and solved using our method, which contains acceleration schemes tailored to each problem. Abstract: Collision sequences are commonly used in games and entertainment to add drama and excitement. Authoring even two body collisions in real world can be difficult, as one has to get timing and the object trajectories to be correctly synchronized. Abstract: We propose a method to simulate the rich, scale-dependent dynamics of water waves.

Our method preserves the dispersion properties of real waves, yet it supports interactions with obstacles and is computationally efficient. Fundamentally, it computes wave accelerations by way of applying a dispersion kernel as a spatially variant filter, which we are able to compute efficiently using two core technical contributions. Abstract: We present a novel method to interpolate smoke and liquid simulations in order to perform data-driven fluid simulations. Our approach calculates a dense space-time deformation using grid-based signed-distance functions of the inputs. A key advantage of this implicit Eulerian representation is that it allows us to use powerful techniques from the optical flow area.

We employ a five-dimensional optical flow solve. Abstract: Physics-based animation is often used to animate scenes containing destruction of near-rigid, man-made materials. For these applications, the most important visual features are plastic deformation and fracture. Methods based on continuum mechanics model these materials as elastoplastic, and must perform expensive elasticity computations even though elastic deformations are imperceptibly small for rigid materials. Unfortunately, FLIP simulations can be computationally expensive, because they require a dense sampling of particles to fill the entire liquid volume.

Abstract: We present a method to increase the apparent resolution of particlebased liquid simulations. Our method first outputs a dense, temporally coherent, regularized point set from a coarse particle-based liquid simulation. We then apply a surface-only Lagrangian wave simulation to this high-resolution point set. We develop novel methods for seeding and simulating waves over surface points, and use them to generate high-resolution details. Abstract: This paper presents a liquid simulation technique that enforces the incompressibility condition using a stream function solve instead of a pressure projection. Previous methods have used stream function techniques for the simulation of detailed single-phase flows, but a formulation for liquid simulation has proved elusive in part due to the free surface boundary conditions. Abstract: This work presents a method for efficiently simplifying the pressure projection step in a liquid simulation.

We first devise a straightforward dimension reduction technique that dramatically reduces the cost of solving the pressure projection. Next, we introduce a novel change of basis that satisfies free-surface boundary conditions exactly, regardless of the accuracy of the pressure solve. Abstract: We present a method for smoothly blending between existing liquid animations. We introduce a semi-automatic method for matching two existing liquid animations, which we use to create new fluid motion that plausibly interpolates the input. Abstract: We explore the connection between fluid capture, simulation and proximal methods, a class of algorithms commonly used for inverse problems in image processing and computer vision. Our key finding is that the proximal operator constraining fluid velocities to be divergence-free is directly equivalent to the pressure-projection methods commonly used in incompressible flow solvers. Abstract: We introduce a new method for efficiently simulating liquid with extreme amounts of spatial adaptivity.

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Our method combines several key components to drastically speed up the simulation of large-scale fluid phenomena: We leverage an alternative Eulerian tetrahedral mesh discretization to significantly reduce the complexity of the pressure solve while increasing the robustness with respect to element quality and removing the possibility of locking. Abstract: We propose a method of increasing the apparent spatial resolution of an existing liquid simulation. Previous approaches to this “up-resing” problem have focused on increasing the turbulence of the underlying velocity field. Motivated by measurements in the free surface turbulence literature, we observe that past certain frequencies, it is sufficient to perform a wave simulation directly on the liquid surface, and construct a reduced-dimensional surface-only simulation. Abstract: Buoyant turbulent smoke plumes with a sharp smoke-air interface, such as volcanic plumes, are notoriously hard to simulate. The surface clearly shows small-scale turbulent structures which are costly to resolve.

In addition, the turbulence onset is directly visible at the interface, and is not captured by commonly used turbulence models. We present a novel approach that employs a triangle mesh as a high-resolution surface representation combined with a coarse Eulerian solver. Abstract: We present an approach for artist-directed animation of liquids using multiple levels of control over the simulation, ranging from the overall tracking of desired shapes to highly detailed secondary effects such as dripping streams, separating sheets of fluid, surface waves and ripples. The first portion of our technique is a volume preserving morph that allows the animator to produce a plausible fluid-like motion from a sparse set of control meshes. In our method, we preserve fluid sheets by filling the breaking sheets with particle splitting in the thin regions, and by collapsing them in the deep water. Abstract: We present a novel, scalable turbulence method for fluid simulations that simulates small-scale detail based on a particle representation, which does not require neighborhood information.

We compute transport of turbulent energy using a full two-equation k-e model with extensions for stability and for realistically capturing anisotropic turbulence effects. Abstract: We present an approach to simulate flows driven by surface tension based on triangle meshes. Our method consists of two simulation layers: the first layer is an Eulerian method for simulating surface tension forces that is free from typical strict time step constraints. The second simulation layer is a Lagrangian finite element method that simulates sub-grid scale wave details on the fluid surface. Abstract: We propose a mesh-based surface tracking method for fluid animation that both preserves fine surface details and robustly adjusts the topology of the surface in the presence of arbitrarily thin features like sheets and strands. We replace traditional re-sampling methods with a convex hull method for connecting surface features during topological changes. Abstract: Turbulent vortices in fluid flows are crucial for a visually interesting appearance.

Although there has been a significant amount of work on turbulence in graphics recently, these algorithms rely on the underlying simulation to resolve the flow around objects. We build upon work from classical fluid mechanics to design an algorithm that allows us to accurately precompute the turbulence being generated around an object immersed in a flow. Abstract: We present a method for accurately tracking the moving surface of deformable materials in a manner that gracefully handles topological changes. We employ a Lagrangian surface tracking method, and we utilize a triangle mesh for our surface representation so that fine features can be retained. Abstract: We present a real-time camera control system that uses a global planning algorithm to compute large, occlusion free camera paths through complex environments. The algorithm incorporates the visibility of a focus point into the search strategy, so that a path is chosen along which the focus target will be in view. Abstract: We propose a new fluid control technique that uses scale-dependent force control to preserve small-scale fluid detail.

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Control particles define local force fields and can be generated automatically from either a physical simulation or a sequence of target shapes. We use a multi-scale decomposition of the velocity field and apply control forces only to the coarse-scale components of the flow. The results of this paper can also be seen in the “Magic Fluid Control” animation, which can be found below. Abstract: We present a novel wavelet method for the simulation of fluids at high spatial resolution.

The algorithm enables large- and small-scale detail to be edited separately, allowing high-resolution detail to be added as a post-processing step. Instead of solving the Navier-Stokes equations over a highly refined mesh, we use the wavelet decomposition of a low-resolution simulation to determine the location and energy characteristics of missing high-frequency components. Abstract: The goal of this paper is to enable the interactive simulation of phenomena such as animated fluid characters. While full 3D fluid solvers achieve this with control algorithms, these 3D simulations are usually too costly for real-time environments. In order to achieve our goal, we reduce the problem from a three- to a two-dimensional one, and make use of the shallow water equations to simulate surface waves that can be solved very efficiently. This reduces the required computational time by more than a factor of three for simulations with large volumes of fluid.

To achieve this, the simulation of large fluid regions is performed with coarser grid resolutions. ETH Zurich provides an internationally renowned degree in computer science with a specialization track in computer graphics. A new project-based game development course serves as a capstone to the program by reinforcing core computer science concepts and specialized topics in Visual Computing. Performance results for different test cases and architectures will be given. The algorithm for parallelization yields a high performance, and can be combined with the adaptive LBM simulations. Moreover, the effects of the adaptive simulation on the parallel performance will be evaluated.

Abstract: The paper presents a way to simulate the behavior of particle agglomerates in a fluid flow by coupling the Lattice Boltzmann Method to a rigid body physics engine. Abstract: We present a new method for enhancing shallow water simulations by the effect of overturning waves. While full 3D fluid simulations can capture the process of wave breaking, this is beyond the capabilities of a pure height field model. 3D simulations, however, are still too expensive for real-time applications, especially when large bodies of water need to be simulated. Abstract: Bubbles and foam are important fluid phenomena on scales that we encounter in our lives every day. While different techniques to handle these effects were developed in the past years, they require a full 3D fluid solver with free surfaces and surface tension. We present a shallow water based particle model that is coupled with a smoothed particle hydrodynamics simulation to demonstrate that real-time simulations of bubble and foam effects are possible with high frame rates.

The results of this paper can also be seen in the “Magic Fluid Control” animation, which can be found here. Abstract: The goal of this paper is to perform simulations that capture fluid effects from small drops up to the propagation of large waves. To achieve this, we present a hybrid simulation method, that couples a two-dimensional shallow water simulation with a full three-dimensional free surface fluid simulation. We explain the approximations imposed by the shallow water model, and how to parametrize it according to the parameters of a 3D simulation.

To achieve this we extend methods available for flows without a free surface to enables simulations of moving objects with varying surface roughness, two-way coupled interaction and improved mass conservation. We furthermore show how to efficiently initialize boundary conditions for the moving objects from an arbitrary triangle mesh. Abstract: Computing motion blur is a complex task for modern raytracers, usually temporal supersampling is used to compute motion blur. However, this leads to increased rendering time and high computational complexity.

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In the following we present an image based technique which is based on the optical flow method to achieve an approximated motion field in an image sequence. Both methods have been compared in terms of accuracy and computational effort. It is shown that they give comparable results if all numerical parameters are controlled carefully. LBM requires a much higher computational effort, however, in contrast to ASD it is able to simulate partially sintered agglomerates as well. Ease of implementation, extensibility, and computational efficiency are the major reasons for LBM’s growing field of application and increasing popularity.

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This is done by adaptively changing the parameterization of the simulation in a way that corresponds to a different size of the simulation time step. This means that the Mach number changes as well, and requires a rescaling of all distribution functions. Hence we only perform the rescaling when the velocities in the simulation become too large or small. Abstract: We present a 2D- and 3D-lattice Boltzmann model for the treatment of free surface flows including gas diffusion.

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Interface advection and related boundary conditions are based on the idea of the lattice Boltzmann equation. The fluid dynamic boundary conditions are approximated by using the mass and momentum fluxes across the interface, which do not require explicit calculation of gradients. A similar procedure is applied to fulfill the diffusion boundary condition. Abstract: We present two variants of free surface Lattice-Boltzmann fluid simulations for the animation of liquids in computer graphics. The Lattice-Boltzmann method is an attractive alternative to conventional fluid solvers, due to its simplicity and flexibility, especially for changing geometries and topologies. Abstract: The design of modern computer games is as much an art as painting, sculpting, music, or writing. Albeit relatively young and still evolving, game design is highly complex and requires a broad spectrum of artistic and technical skills.

The following contribution reviews the process of designing and developing modern computer games. Abstract: Physical simulations have become an important component of computer games. In next-generation games, players expect to see fully dynamic and destructible worlds, and this requires fast and stable simulation methods. In this class, lecturers who have made significant contributions in simulation methods present a wide spectrum of state-of-the-art methods for real-time simulation of rigid and deformable solids, and smoke and liquid simulation. Abstract: The movie consists of three clips to demonstrate the possibilities of controlled water simulations: 1.

A magician pulls out water from a basin which forms a teapot by moving his hand upwards from the basin. Water flows magically upwards a stair where it forms a human figure. This is achieved by using control particles from a reversed water simulation and from an invisible model. The magician moves a duck out of water from one basin to another and vice versa. Abstract: The numerical simulation of fluids has become an established tool in many engineering applications.

Free surface fluids represent a special case that is important for a variety of applications. For a free surface simulation, a two phase system, such as air and water, is described by a single fluid phase with a sharp interface and corresponding boundary conditions. This allows the efficient representation and simulation of complex problems. Iglberger, Nils Thuerey, Ulrich Ruede, H.

Abstract: The following work presents a way to simulate the nano-particle behavior in a flow by coupling the Lattice Boltzmann Method to a rigid body physics engine. By extending the basic fluid simulation for the treatment of curved particle surfaces and by a force interaction method, the fluid forces acting on the nano-particles can be calculated. Abstract: In this work we show, that the Lattice Boltzmann method is capable of calculating the drag force on spheres with a sufficient accuracy. The main interest lies on laminar flows around nano particle agglomerates.

To give an overview over the simulated force accuracy the results are compared with analytical solutions. Thereby the benefit from curved boundary treatments such as and is taken into account. The free surface tracking is similar to Volume-of-Fluid methods for conventional Navier-Stokes solvers. For the free surface three types of cells are distinguished – fluid cells that are treated with the normal LBM, empty cells, that do not require any computations, and interface cells. Abstract: In this paper we present our algorithm for animating fluids with a free surface.

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It is based on the Lattice-Boltzmann Method, instead of a direct discretization of the Navier-Stokes equations. This allows a relatively simple treatment of the free surface boundary conditions at high computational efficiency, without sacrificing the underlying physics. We give a detailed description of our algorithm, focussing on details that are required to achieve a good visual appearance. Abstract: The fluid solver presented here is capable of simulating a single fluid phase with a free surface, including surface tension, bubbles and coalescence. The chronology of the universe describes the history and future of the universe according to Big Bang cosmology.

The earliest stages of the universe’s existence are estimated as taking place 13. For the purposes of this summary, it is convenient to divide the chronology of the universe since it originated, into five parts. Time” column is based on extrapolation of observed metric expansion of space back in the past. For the earliest stages of chronology this extrapolation may be invalid. The radiation temperature refers to the cosmic background radiation and is given by 2. The Planck scale is the scale beyond which current physical theories do not have predictive value. The Planck epoch is the time during which physics is assumed to have been dominated by quantum effects of gravity.