Efficient algorithms for the realistic simulation of fluids

Nowadays there is great demand for realistic simulations in the computer graphics field. Physically-based animations are commonly used, and one of the more complex problems in this field is fluid simulation, more so if real-time applications are the goal. Videogames, in particular, resort to different techniques that, in order to represent fluids, just simulate the consequence and not the cause, using procedural or parametric methods and often discriminating the physical solution. This need motivates the present thesis, the interactive simulation of free-surface flows, usually liquids, which are the feature of interest in most common applications. Due to the complexity of fluid simulation, in order to achieve real-time framerates, we have resorted to use the high parallelism provided by actual consumer-level GPUs. The simulation algorithm, the Lattice Boltzmann Method, has been chosen accordingly due to its efficiency and the direct mapping to the hardware architecture because of its local operations. We have created two free-surface simulations in the GPU: one fully in 3D and another restricted only to the upper surface of a big bulk of fluid, limiting the simulation domain to 2D. We have extended the latter to track dry regions and is also coupled with obstacles in a geometry-independent fashion. As it is restricted to 2D, the simulation loses some features due to the impossibility of simulating vertical separation of the fluid. To account for this we have coupled the surface simulation to a generic particle system with breaking wave conditions; the simulations are totally independent and only the coupling binds the LBM with the chosen particle system. Furthermore, the visualization of both systems is also done in a realistic way within the interactive framerates; raycasting techniques are used to provide the expected light-related effects as refractions, reflections and caustics. Other techniques that improve the overall detail are also applied as low-level detail ripples and surface foam

Interactive simulation and rendering of fluids on graphics hardware

Computational uid dynamics can be used to reproduce the complex motion of fluids for use in computer graphics, but the simulation and rendering are both highly computationally intensive. In the past performing these tasks on the CPU could take many minutes per frame, especially for large scale scenes at high levels of detail, which limited their usage to offline applications such as in film and media. However, using the massive parallelism of GPUs, it is nowadays possible to produce uid visual effects in real time for interactive applications such as games. We present such an interactive simulation using the CUDA GPU computing environment and OpenGL graphics API. Smoothed Particle Hydrodynamics (SPH) is a popular particle-based fluid simulation technique that has been shown to be well suited to acceleration on the GPU. Our work extends an existing GPU-based SPH implementation by incorporating rigid body interaction and rendering. Solid objects are represented using particles to accumulate hydrodynamic forces from surrounding fluid, while motion and collision handling are handled by the Bullet Physics library on the CPU. Our system demonstrates two-way coupling with multiple objects floating, displacing fluid and colliding with each other. For rendering we compare the performance and memory consumption of two approaches, splatting and raycasting, we also describe the visual characteristics of each. In our evaluation we consider a target of between 24 and 30 fps to be sufficient for smooth interaction and aim to determine the performance impact of our new features. We begin by establishing a performance baseline and find that the original system runs smoothly up to 216,000 fluid particles but after introducing rendering this drops to 27,000 particles with the rendering taking up the majority of the frame time in both techniques. We find that the most significant limiting factor to splatting performance to be the onscreen area occupied by fluid while the raycasting performance is primarily determined by the resolution of the 3D texture used for sampling. Finally we find that performing solid interaction on the CPU is a viable approach that does not introduce significant overhead unless solid particles vastly outnumber fluid ones

On in-situ visualization for strongly coupled partitioned fluid-structure interaction

We present an integrated in-situ visualization approach for partitioned multi-physics simulation of fluid-structure interaction. The simulation itself is treated as a black box and only the information at the fluid-structure interface is considered, and communicated between the fluid and solid solvers with a separate coupling tool. The visualization of the interface data is performed in conjunction with the fluid solver. Furthermore, we present new visualization techniques for the analysis of the interrelation of the two solvers , with emphasis on the involved error due to discretization in space and time and the reconstruction. Our visualization approach also enables the investigation of these errors with respect of their mutual influence on the two simulation codes and their space-time discretization. For efficient interactive visualization, we employ the concept of explorable spatiotemporal images, which also enables finite-time temporal navigation in an in-situ context. We demonstrate our overall approach and its utility by means of a fluid-structure simulation using OpenFOAM that is coupled by the preCICE software layer

Stochastic Volume Rendering of Multi-Phase SPH Data

In this paper, we present a novel method for the direct volume rendering of large smoothed‐particle hydrodynamics (SPH) simulation data without transforming the unstructured data to an intermediate representation. By directly visualizing the unstructured particle data, we avoid long preprocessing times and large storage requirements. This enables the visualization of large, time‐dependent, and multivariate data both as a post‐process and in situ. To address the computational complexity, we introduce stochastic volume rendering that considers only a subset of particles at each step during ray marching. The sample probabilities for selecting this subset at each step are thereby determined both in a view‐dependent manner and based on the spatial complexity of the data. Our stochastic volume rendering enables us to scale continuously from a fast, interactive preview to a more accurate volume rendering at higher cost. Lastly, we discuss the visualization of free‐surface and multi‐phase flows by including a multi‐material model with volumetric and surface shading into the stochastic volume rendering

Design and development of a VR system for exploration of medical data using haptic rendering and high quality visualization

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Interactive GPU-based generation of solvent-excluded surfaces

The solvent-excluded surface (SES) is a popular molecular representation that gives the boundary of the molecular volume with respect to a specific solvent. SESs depict which areas of a molecule are accessible by a specific solvent, which is represented as a spherical probe. Despite the popularity of SESs, their generation is still a compute-intensive process, which is often performed in a preprocessing stage prior to the actual rendering (except for small models). For dynamic data or varying probe radii, however, such a preprocessing is not feasible as it prevents interactive visual analysis. Thus, we present a novel approach for the on-the-fly generation of SESs, a highly parallelizable, grid-based algorithm where the SES is rendered using ray-marching. By exploiting modern GPUs, we are able to rapidly generate SESs directly within the mapping stage of the visualization pipeline. Our algorithm can be applied to large time-varying molecules and is scalable, as it can progressively refine the SES if GPU capabilities are insufficient. In this paper, we show how our algorithm is realized and how smooth transitions are achieved during progressive refinement. We further show visual results obtained from real-world data and discuss the performance obtained, which improves upon previous techniques in both the size of the molecules that can be handled and the resulting frame rate.Peer ReviewedPostprint (author's final draft