Harinarayan Krishnan

Time and Streak Surfaces for Flow Visualization in Large Time-Varying Data Sets

Time and streak surfaces are ideal tools to illustrate time-varying vector fields since they directly appeal to the intuition about coherently moving particles. However, efficient generation of high-quality time and streak surfaces for complex, large and time-varying vector field data has been elusive due to the computational effort involved. In this work, we propose a novel algorithm for computing such surfaces. Our approach is based on a decoupling of surface advection and surface adaptation and yields improved efficiency over other surface tracking methods, and allows us to leverage inherent parallelization opportunities in the surface advection, resulting in more rapid parallel computation. Moreover, we obtain as a result of our algorithm the entire evolution of a time or streak surface in a compact representation, allowing for interactive, high-quality rendering, visualization and exploration of the evolving surface. Finally, we discuss a number of ways to improve surface depiction through advanced rendering and texturing, while preserving interactivity, and provide a number of examples for real-world datasets and analyze the behavior of our algorithm on them.

Effects of Particle Size, Electronic Connectivity, and Incoherent Nanoscale Domains on the Sequence of Lithiation in LiFePO4 Porous Electrodes

High-resolution X-ray microscopy is used to investigate the sequence of lithiation in LiFePO4 porous electrodes. For electrodes with homogeneous interparticle electronic connectivity via the carbon black network, the smaller particles lithiate first. For electrodes with heterogeneous connectivity, the better-connected particles preferentially lithiate. Correlative electron and X-ray microscopy also reveal the presence of incoherent nanodomains that lithiate as if they are separate particles.

Real-time procedural volumetric fire

We present a method for generating procedural volumetric fire in real time. By combining curve-based volumetric free-form deformation, hardware-accelerated volumetric rendering and Improved Perlin Noise or M-Noise we are able to render a vibrant and uniquely animated volumetric fire that supports bi-directional environmental macro-level interactivity. Our system is easily customizable by content artists. The fire is animated both on the macro and micro levels. Macro changes are controlled either by a prescripted sequence of movements, or by a realistic particle simulation that takes into account movement, wind, high-energy particle dispersion and thermal buoyancy. Micro fire effects such as individual flame shape, location, and flicker are generated in a pixel shader using three- to four-dimensional Improved Perlin Noise or M-Noise (depending on hardware limitations and performance requirements). Our method supports efficient collision detection, which, when combined with a sufficiently intelligent particle simulation, enables real-time bi-directional interaction between the fire and its environment. The result is a three-dimensional procedural fire that is easily designed and animated by content artists, supports dynamic interaction, and can be rendered in real time.

An Independent Assessment of Anthropogenic Attribution Statements for Recent Extreme Temperature and Rainfall Events

AbstractThe annual “State of the Climate” report, published in the Bulletin of the American Meteorological Society (BAMS), has included a supplement since 2011 composed of brief analyses of the human influence on recent major extreme weather events. There are now several dozen extreme weather events examined in these supplements, but these studies have all differed in their data sources as well as their approaches to defining the events, analyzing the events, and the consideration of the role of anthropogenic emissions. This study reexamines most of these events using a single analytical approach and a single set of climate model and observational data sources. In response to recent studies recommending the importance of using multiple methods for extreme weather event attribution, results are compared from these analyses to those reported in the BAMS supplements collectively, with the aim of characterizing the degree to which the lack of a common methodological framework may or may not influence overall ...

Analysis of Time-Dependent Flow-Sensitive PC-MRI Data

Many flow visualization techniques, especially integration-based methods, are problematic when the measured data exhibit noise and discretization issues. Particularly, this is the case for flow-sensitive phase-contrast magnetic resonance imaging (PC-MRI) data sets which not only record anatomic information, but also time-varying flow information. We propose a novel approach for the visualization of such data sets using integration-based methods. Our ideas are based upon finite-time Lyapunov exponents (FTLE) and enable identification of vessel boundaries in the data as high regions of separation. This allows us to correctly restrict integration-based visualization to blood vessels. We validate our technique by comparing our approach to existing anatomy-based methods as well as addressing the benefits and limitations of using FTLE to restrict flow. We also discuss the importance of parameters, i.e., advection length and data resolution, in establishing a well-defined vessel boundary. We extract appropriate flow lines and surfaces that enable the visualization of blood flow within the vessels. We further enhance the visualization by analyzing flow behavior in the seeded region and generating simplified depictions.

GPU acceleration of particle advection workloads in a parallel, distributed memory setting

Although there has been significant research in GPU acceleration, both of parallel simulation codes (i.e., GPGPU) and of single GPU visualization and analysis algorithms, there has been relatively little research devoted to visualization and analysis algorithms on GPU clusters. This oversight is significant: parallel visualization and analysis algorithms have markedly different characteristics -- computational load, memory access pattern, communication, idle time, etc. -- than the other two categories. In this paper, we explore the benefits of GPU acceleration for particle advection in a parallel, distributed-memory setting. As performance properties can differ dramatically between particle advection use cases, our study operates over a variety of workloads, designed to reveal insights about underlying trends. This work has a three-fold aim: (1) to map a challenging visualization and analysis algorithm -- particle advection -- to a complex system (a cluster of GPUs), (2) to inform its performance characteristics, and (3) to evaluate the advantages and disadvantages of using the GPU. In our performance study, we identify which factors are and are not relevant for obtaining a speedup when using GPUs. In short, this study informs the following question: if faced with a parallel particle advection problem, should you implement the solution with CPUs, with GPUs, or does it not matter?

CAMERA: The Center for Advanced Mathematics for Energy Research Applications

Advanced experimental facilities worldwide are probing structure and chemistry, disorder, dynamics and electronic properties, through time, over length scales spanning macroscopic to atomic resolution, in multiple dimensions (e.g., hyperspectral tomography, nano-spectroscopy), under extreme environmental conditions and stimulated reactions. In order to do so, they are collecting more and more data at faster and faster rates. One critical challenge is to build algorithms that can analyze, interpret, and understand the information contained within this experimental data.

Structure recognition from high resolution images of ceramic composites

Fibers provide exceptional strength-to-weight ratio capabilities when woven into ceramic composites, transforming them into materials with exceptional resistance to high temperature, and high strength combined with improved fracture toughness. Microcracks are inevitable when the material is under strain, which can be imaged using synchrotron X-ray computed micro-tomography (μ-CT) for assessment of material mechanical toughness variation. An important part of this analysis is to recognize fibrillar features. This paper presents algorithms for detecting and quantifying composite cracks and fiber breaks from high-resolution image stacks. First, we propose recognition algorithms to identify the different structures of the composite, including matrix cracks and fibers breaks. Second, we introduce our package F3D for fast filtering of large 3D imagery, implemented in OpenCL to take advantage of graphic cards. Results show that our algorithms automatically identify micro-damage and that the GPU-based implementation introduced here takes minutes, being 17x faster than similar tools on a typical image file.

Visual Data Analysis as an Integral Part of Environmental Management

The U.S. Department of Energys (DOE) Office of Environmental Management (DOE/EM) currently supports an effort to understand and predict the fate of nuclear contaminants and their transport in natural and engineered systems. Geologists, hydrologists, physicists and computer scientists are working together to create models of existing nuclear waste sites, to simulate their behavior and to extrapolate it into the future. We use visualization as an integral part in each step of this process. In the first step, visualization is used to verify model setup and to estimate critical parameters. High-performance computing simulations of contaminant transport produces massive amounts of data, which is then analyzed using visualization software specifically designed for parallel processing of large amounts of structured and unstructured data. Finally, simulation results are validated by comparing simulation results to measured current and historical field data. We describe in this article how visual analysis is used as an integral part of the decision-making process in the planning of ongoing and future treatment options for the contaminated nuclear waste sites. Lessons learned from visually analyzing our large-scale simulation runs will also have an impact on deciding on treatment measures for other contaminated sites.

Near-edge X-ray refraction fine structure microscopy

We demonstrate a method for obtaining increased spatial resolution and specificity in nanoscale chemical composition maps through the use of full refractive reference spectra in soft x-ray spectro-microscopy. Using soft x-ray ptychography, we measure both the absorption and refraction of x-rays through pristine reference materials as a function of photon energy and use these reference spectra as the basis for decomposing spatially resolved spectra from a heterogeneous sample, thereby quantifying the composition at high resolution. While conventional instruments are limited to absorption contrast, our novel refraction based method takes advantage of the strongly energy dependent scattering cross-section and can see nearly five-fold improved spatial resolution on resonance.