Visual Simulation of Flow

We have adopted a numerical method from computational fluid dynamics, the Lattice Boltzmann Method (LBM), for real-time simulation and visualization of flow and amorphous phenomena, such as clouds, smoke, fire, haze, dust, radioactive plumes, and air-borne biological or chemical agents. Unlike other approaches, LBM discretizes the micro-physics of local interactions and can handle very complex boundary conditions, such as deep urban canyons, curved walls, indoors, and dynamic boundaries of moving objects. Due to its discrete nature, LBM lends itself to multi-resolution approaches, and its computational pattern, which is similar to cellular automata, is easily parallelizable. We have accelerated LBM on commodity graphics processing units (GPUs), achieving real-time or even accelerated real-time on a single GPU or on a GPU cluster. We have implemented a 3D urban navigation system and applied it in New York City with real-time live sensor data. In addition to a pivotal application in simulation of airborne contaminants in urban environments, this approach will enable the development of other superior prediction simulation capabilities, computer graphics and games, and a novel technology for computational science and engineering

Flow simulation with locally-refined LBM

We simulate 3D fluid flow by a locally-refined lattice Boltzmann method (LBM) on graphics hardware. A low resolution LBM simulation running on a coarse grid models global flow behavior of the entire domain with low consumption of computational resources. For regions of interest where small visual details are desired, LBM simulations are performed on fine grids, which are separate grids superposed on the coarse one. The flow properties on boundaries of the fine grids are determined by the global simulation on the coarse grid. Thus, the locally refined fine-grid simulations follow the global fluid behavior, and model the desired small-scale and turbulent flow motion with their denser numerical discretization. A fine grid can be initiated and terminated at any time while the global simulation is running. It can also move inside the domain with a moving object to capture small-scale vortices caused by the object. Besides the performance improvement due to the adaptive simulation, the locally-refined LBM is suitable for acceleration on contemporary graphics hardware (GPU), since it involves only local and linear computations. Therefore, our approach achieves fast and adaptive 3D flow simulation for computer games and other interactive applications

Lattice Boltzmann modeling for shallow water equations using high performance computing

The aim of this dissertation project is to extend the standard Lattice Boltzmann method (LBM) for shallow water flows in order to deal with three dimensional flow fields. The shallow water and mass transport equations have wide applications in ocean, coastal, and hydraulic engineering, which can benefit from the advantages of the LBM. The LBM has recently become an attractive numerical method to solve various fluid dynamics phenomena; however, it has not been extensively applied to modeling shallow water flow and mass transport. Only a few works can be found on improving the LBM for mass transport in shallow water flows and even fewer on extending it to model three dimensional shallow water flow fields. The application of the LBM to modeling the shallow water and mass transport equations has been limited because it is not clearly understood how the LBM solves the shallow water and mass transport equations. The project first focuses on studying the importance of choosing enhanced collision operators such as the multiple-relaxation-time (MRT) and two-relaxation-time (TRT) over the standard single-relaxation-time (SRT) in LBM. A (MRT) collision operator is chosen for the shallow water equations, while a (TRT) method is used for the advection-dispersion equation. Furthermore, two speed-of-sound techniques are introduced to account for heterogeneous and anisotropic dispersion coefficients. By selecting appropriate equilibrium distribution functions, the standard LBM is extended to solve three-dimensional wind-driven and density-driven circulation by introducing a multi-layer LB model. A MRT-LBM model is used to solve for each layer coupled by the vertical viscosity forcing term. To increase solution stability, an implicit step is suggested to obtain stratified flow velocities. Numerical examples are presented to verify the multi-layer LB model against analytical solutions. The model’s capability of calculating lateral and vertical distributions of the horizontal velocities is demonstrated for wind- and density- driven circulation over non-uniform bathymetry. The parallel performance of the LBM on central processing unit (CPU) based and graphics processing unit (GPU) based high performance computing (HPC) architectures is investigated showing attractive performance in relation to speedup and scalability

Modeling electrospinning process and a numerical scheme using Lattice Boltzmann method to simulate viscoelastic fluid flows

In the recent years, researchers have discovered a multitude of applications using nanofibers in fields like composites, biotechnology, environmental engineering, defense, optics and electronics. This increase in nanofiber applications needs a higher rate of nanofiber production. Electrospinning has proven to be the best nanofiber manufacturing process because of simplicity and material compatibility. Study of effects of various electrospinning parameters is important to improve the rate of nanofiber processing. In addition, several applications demand well-oriented nanofibers. Researchers have experimentally tried to control the nanofibers using secondary external electric field. In the first study, the electrospinning process is modeled and the bending instability of a viscoelastic jet is simulated. For this, the existing discrete bead model is modified and the results are compared, qualitatively, with previous works in literature. In this study, an attempt is also made to simulate the effect of secondary electric field on electrospinning process and whipping instability. It is observed that the external secondary field unwinds the jet spirals, reduces the whipping instability and increases the tension in the fiber. Lattice Boltzmann method (LBM) has gained popularity in the past decade as the method is easy implement and can also be parallelized. In the second part of this thesis, a hybrid numerical scheme which couples lattice Boltzmann method with finite difference method for a Oldroyd-B viscoelastic solution is proposed. In this scheme, the polymer viscoelastic stress tensor is included in the equilibrium distribution function and the distribution function is updated using SRT-LBE model. Then, the local velocities from the distribution function are evaluated. These local velocities are used to evaluate local velocity gradients using a central difference method in space. Next, a forward difference scheme in time is used on the Maxwell Upper Convected model and the viscoelastic stress tensor is updated. Finally, using the proposed numerical method start-up Couette flow problem for Re = 0.5 and We = 1.1, is simulated. The velocity and stress results from these simulations agree very well with the analytical solutions

Visual Computing Tools for Studying Micro-scale Diffusion

In this dissertation, we present novel visual computing tools and techniques to facilitate the exploration, simulation, and visualization of micro-scale diffusion. Our research builds upon the latest advances in visualization, high-performance computing, medical imaging, and human perception. We validate our research using the driving applications of nano-assembly and diffusion kurtosis imaging (DKI). In both of these applications, diffusion plays a central role. In the former it mediates the process of transporting micron-sized particles through moving lasers, and in the latter it conveys brain micro-geometry. Nanocomponent-based devices, such as bio-sensors, electronic components, photonic devices, solar cells, and batteries, are expected to revolutionize health care, energy, communications, and the computing industry. However, in order to build such useful devices, nanoscale components need to be properly assembled together. We have developed a hybrid CPU/GPU-based computing tool to understand complex interactions between lasers, optical beads, and the suspension medium. We demonstrate how a high-performance visual computing tool can be used to accelerate an optical tweezers simulation to compute the force applied by a laser onto micro particles and study shadowing (refraction) behavior. This represents the first steps toward building a real-time nano-assembly planning system. A challenge in building such a system, however, is that optical tweezers systems typically lack stereo depth cues. We have developed a visual tool to provide an enhanced perception of a scene's 3D structure using the kinetic depth effect. The design of our tool has been informed by user studies of stereo perception using the kinetic-depth effect on monocular displays. Diffusion kurtosis imaging is gaining rapid adoption in the medical imaging community due to its ability to measure the non-Gaussian property of water diffusion in biological tissues. Compared with the traditional diffusion tensor imaging (DTI), DKI can provide additional details about the underlying microstructural characteristics of neural tissues. It has shown promising results in studies on changes in gray matter and mild traumatic brain injuries, where DTI is often found to be inadequate. However, the highly detailed spatio-angular fields in DKI datasets present a special challenge for visualization. Traditional techniques that use glyphs are often inadequate for expressing subtle changes in the DKI fields. In this dissertation, we outline a systematic way to manage, analyze, and visualize spatio-angular fields using spherical harmonics lighting functions to facilitate insights into the micro-structural properties of the brain

An integrated software approach to interactive exploration and steering of fluid flow simulations on many-core architectures

Traditionell werden numerische Strömungssimulationen in einer zyklischen Sequenz autonomer Teilschritte durchgeführt. Seitens Wissenschaftlern existiert jedoch schon lange der Wunsch nach mehr Interaktion mit laufenden Simulationen. Seit dem maßgeblichen Report der National Science Foundation im Jahre 1987 wurden daher neue Formen der wissenschaftlichen Visualisierung entwickelt, die sich grundlegend von den traditionellen Verfahren unterscheiden. Insbesondere hat der sogenannte Computational Steering-Ansatz reges Interesse bewirkt. Damals wie heute ist die Anwendung des Verfahrens jedoch eher die Ausnahme denn die Regel. Ursächlich dafür sind zu großen Teilen Komplexität und Restriktionen traditioneller Hochleistungssysteme. Im Rahmen dieser Arbeit wird daher als Alternative zu dem traditionellen Vorgehen die immense Leistungsfähigkeit moderner Grafikkartengenerationen für die Berechnungen herangezogen. Das sogenannte GPGPU-Computing eignet sich insbesondere für die Anwendung der Lattice-Boltzmann-Methode im Bereich numerischer Strömungssimulationen. Auf Grundlage des LBM-Verfahrens wird im Rahmen dieser Arbeit prototypisch eine interaktive Simulationsumgebung basierend auf dem Computational Steering-Paradigma entwickelt, das alle Prozesse zur Lösung von Strömungsproblemen innerhalb einer einzelnen Anwendung integriert. Durch die Konvergenz der hohen massiv parallelen Rechenleistung der GPUs und der Interaktionsfähigkeiten in einer einzelnen Anwendung kann eine erhebliche Steigerung der Anwendungsqualität erzielt werden. Dabei ist es durch Einsatz mehrerer GPUs möglich, dreidimensionale Strömungsprobleme mit praxisrelevanter Problemgröße zu berechnen und gleichzeitig eine interaktive Manipulation und Exploration des Strömungsgebiets zur Laufzeit zu ermöglichen. Dabei ist der erforderliche finanzielle Aufwand verglichen mit traditionellen massiv parallelen Verfahren verhältnismäßig gering.Traditionally, computational fluid dynamics is done in a cyclic sequence of independent steps. Howerver it is a long term wish of scientists and engineers to closely interact with their running simulations. Since the influential report of the US National Science Foundation in 1987 new forms of scientific visualization have evolved that are quite different from traditional post-processing. Especially the approach commonly referred to as computational steering has been the subject of widespread interest. Although it is a very powerful paradigm, the use of computational steering is still the exception rather than the rule. The reasons for this are more or less related to the complexity and restrictions of traditional HPC systems. As an alternative to the traditional massively parallel approach, in this thesis the parallel computational power of GPGPUs is used for general purpose applications. The so called GPGPU computing has gained large popularity in the CFD community, especially for its application to the lattice Boltzmann method. Using this technology this work demonstrates a single desktop application integrating a complete interactive CFD simulation environment for reasonable hardware costs. It shows that the convergence of massive parallel computational power and steering environment into a single system significantly improves the usability, application quality and user-friendliness. Using multiple GPUs, the efficiency of this approach allows for CFD simulations in three dimensional space evolving close to real-time even for reasonable grid sizes. Thereby, the simulation can be explored and also adjusted during runtime. The thesis also shows that the responsiveness significantly benefits from avoiding common bandwidth and latency bottlenecks inherent in traditional HPC approaches. Those can be avoided as GPGPU computing does not generally require network communication, which also reduces the complexity of the application

Kinetische Methoden zur numerischen Simulation von nichtlinearen Strömungen mit freien Oberflächen im Bau- und Umweltingenieurwesen

This thesis focuses on the numerical simulation of non-linear free surface flow problems. Different simulation kernels based on the Lattice Boltzmann method (LBM) have been developed or extended, implemented, and, after validation, applied to a number of applications in civil and environmental engineering. The LB model solves viscous and turbulent flows, essentially representing similar physics as Navier-Stokes or reduced shallow water models, but with specific solver advantages concerning data locality and parallel computing. The first part of this thesis deals with numerical simulations on high-performance GPU (graphics processing unit) hardware. Validations and applications of a reduced LB model for solving the shallow water equations are presented. The resulting GPU kernel has shown to be applicable to state-of-the-art benchmark problems, dealing with wave propagation and wave run-up. Subsequently, the GPU implementation of a 3D numerical wave tank for the simulation of various applications in civil engineering is presented. The second main target of this thesis is to develop and apply a novel model based on an enhanced representation and advection of the phase interface for the simulation of more complex and demanding free surface flow problems. A volume-of-fluid (VOF) approach in combination with a piecewise linear interface reconstruction (PLIC) has been coupled with the LBM. The resulting hybrid model has been successfully validated against various benchmark experiments. Even a breaking wave during shoaling on a slope, which is a demanding test case for VOF solvers, was successfully simulated. Apart from the model development and validation itself, a coupling to a rigid body engine for the simulation of FSI problems has been established. Finally, several techniques for the coupling to a potential flow solver are discussed and validated, in order to generate realistic wave profiles and for the efficient simulation of wave run-up and wave breaking.Die vorliegende Dissertation behandelt die numerische Simulation von nichtlinearen Strömungen mit freien Oberflächen. Dazu werden verschiedene Simulationskerne auf Basis der Gitter-Boltzmann-Methode (LBM) entwickelt, implementiert und nach ihrer Validierung auf zahlreiche Aufgabenstellungen im Bau- und Umweltingenieurwesen angewendet. Die LB-Methode wird verwendet, um viskose und turbulente Strömungen numerisch zu simulieren und bietet im Vergleich zu konventionellen Lösern deutliche Vorteile bezüglich Datenlokalität und parallelem Rechnen. Der erste Teil der Arbeit beschäftigt sich mit der Simulation von Strömungsproblemen auf High-Performance-GPU (Graphics Processing Unit) Hardware. Einleitend wird die Validierung und Anwendung eines LB-Modells für Flachwassergleichungen dargestellt. Im Anschluss wird eine GPU-Implementierung eines dreidimensionalen numerischen Wellenkanals für die Simulation turbulenter Wehrströmungen, Dammbruchszenarien, des Wellenschlages auf Pfahlbauwerke und anderer Anwendungen im Bauingenieurwesen präsentiert. Das zweite Ziel dieser Arbeit ist die Entwicklung und Anwendung eines neuartigen Modells für die Simulation von komplexeren Problemen mit freier Oberfläche unter Zuhilfenahme einer erweiterten Repräsentation der Phasengrenzfläche. Ein Volume-of-Fluid (VOF) Ansatz auf der Grundlage einer abschnittsweise linearen Interface-Rekonstruktion (PLIC) wird an die LBM gekoppelt. Das resultierende hybride Modell wird anhand verschiedener Benchmarks erfolgreich validiert. Im Anschluss wird eine Kopplung an einen Starrkörper-Löser realisiert, welche die Simulation von Problemstellungen aus dem Bereich der Fluid-Struktur-Interaktion ermöglicht. Abschließend werden Techniken zur Kopplung des hybriden Lösers an einen numerischen Wellenkanal auf Basis der Potentialströmungstheorie diskutiert und validiert, die die Erzeugung realistischer Wellenprofile und die effiziente Simulation von Wellenauflauf sowie Wellenbrechen ermöglichen