DOCSLIB.ORG

Advanced Flow Visualization

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
Advanced Flow Visualization ADVANCED FLOW VISUALIZATION DISSERTATION Presented in Partial Ful¯llment of the Requirements for the Degree Doctor of Philosophy in the Graduate School of The Ohio State University By Liya Li, B.E., M.S. ***** The Ohio State University 2007 Dissertation Committee: Approved by Professor Han-Wei Shen, Adviser Professor Roger Craw¯s Adviser Professor Yusu Wang Graduate Program in Computer Science and Engineering °c Copyright by Liya Li 2007 ABSTRACT Flow visualization has been playing a substantial role in many engineering and scienti¯c applications, such as automotive industry, computational fluid dynamics, chemical processing, and weather simulation and climate modelling. Many meth- ods have been proposed in the past decade to visualize steady and time-varying flow ¯elds, in which textures-based and geometry-based visualization are widely used to explore the underlying fluid dynamics. This dissertation presents a view- dependent flow texture algorithm, an illustrative streamline placement algorithm on two-dimensional vector ¯elds, and an image-based streamline placement algorithm on three-dimensional vector ¯elds. Flow texture, generated through convolution and ¯ltering of texture values ac- cording to the local flow vectors, is a dense representation of the vector ¯eld to provide global information of the flow structure. A view-dependent algorithm for multi-resolution flow texture advection on two-dimensional structured rectilinear and curvilinear grid is presented. By using an intermediate representation of the under- lying flow ¯elds, the algorithm can adjust the resolutions of the output texture on the fly as the user zooms in and out of the ¯eld, which can avoid aliasing as well as ensure enough detail. Geometry-based methods use geometries, such as lines, tubes, or balls, to represent the motion paths advected from the vector ¯elds. It provides a sparse representation ii and an intuitive visualization of flow trajectory. For two-dimensional vector ¯elds, a streamline placement strategy is presented to generate representative and illustrative streamlines, which can e®ectively prevent the visual overload by emphasizing the essential and deemphasizing the trivial or repetitive flow patterns. A user study is performed to quantify the e®ectiveness of this visualization algorithm, and the results are provided. For three-dimensional vector ¯elds, an image-based streamline seeding algorithm is introduced to better display the streamlines and reduce visual cluttering in the output images. Various e®ects can be achieved to enhance the visual understanding of three-dimensional flow lines. iii To Tao, and my parents. iv ACKNOWLEDGMENTS I am grateful to my advisor Dr. Han-Wei Shen, who guided me expertly along the PhD study and helped me through many research di±culties. I would like to express my sincere gratitude to Dr. Roger Craw¯s, Dr. Yusu Wang, Dr. Garry McKenzie, and my other committee members. Thank you very much for your valuable time and e®ort, insightful criticism and advice. A heartfelt thanks to my colleagues Dr. Jinzhu Gao, Dr. Antonio Garcia, Teng- Yok Lee, Dr. Naeem Shareef, Dr. Chaoli Wang, and Jonathan Woodring, whose hard work and passion encouraged me. I enjoyed working with them and learning from them. I would like to extend my thanks to other members in the Computer Graphics group with whom I shared memorable experiences for the past ¯ve years. I wish you all the best in your respective research and career. My deepest gratitude is to my husband Tao Li, for everything. For love and for life. I am very grateful to my loyal friends for their encouragement. v VITA 1978 . .Born - Hubei, China 1999 . .B.E. Computer Science Beijing Institute of Technology, China 2002 . .M.S. Computer Science Beijing Institute of Technology, China 2006 . .M.S. Computer Science The Ohio State University September 2002 - August 2003 . .University Fellow The Ohio State University September 2003 - March 2004 . .Graduate Teaching Associate The Ohio State University April 2004 - August 2007 . Graduate Research Associate The Ohio State University June - September, 2005 . Research Intern The National Center for Atmospheric Research September - November, 2007 . .Intern NVIDIA vi PUBLICATIONS Refereed Papers Liya Li, Hsien-Hsi Hsieh, and Han-Wei Shen, \Illustrative Streamline Placement and Visualization". IEEE Paci¯c Visualization Symposium, March 2008. Liya Li and Han-Wei Shen, \Image-Based Streamline Generation and Rendering". IEEE Transactions on Visualization and Computer Graphics, 13(3):630-640, May 2007. Liya Li and Han-Wei Shen, \View-dependent Multi-resolutional Flow Texture Ad- vection". Visualization and Data Analysis, 2006. Chaoli Wang, Jinzhu Gao, Liya Li, and Han-Wei Shen, \A Multiresolution Volume Rendering Framework for Large-Scale Time-Varying Data Visualization". In Proceed- ings of International Workshop on Volume Graphics 2005, Stony Brook, New York, pages 11-19, June 2005. Jinzhu Gao, Chaoli Wang, Liya Li, and Han-Wei Shen, \A Parallel Multiresolution Volume Rendering Algorithm for Large Data Visualization". Parallel Computing (Special Issue on Parallel Graphics and Visualization), 31(2):185-204, February 2005. Unrefereed Papers Liya Li and Han-Wei Shen, \Image-Based Streamline Generation and Rendering". Technical Report OSU-CISRC8/06-TR71, Department of Computer Science and En- gineering, The Ohio State University, 2005. FIELDS OF STUDY Major Field: Computer Science and Engineering Studies in: Computer Graphics Professor Han-Wei Shen Computer Architecture Professor Gagan Agrawal Computer Networking Professor Dong Xuan vii TABLE OF CONTENTS Page Abstract . ii Dedication . iv Acknowledgments . v Vita . vi List of Tables . x List of Figures . xi Chapters: 1. Introduction . 1 2. Background . 9 2.1 Vector Fields . 9 2.1.1 Grids . 9 2.1.2 Integral Curves . 12 2.2 Critical Points and Flow Topology . 14 3. Related Work . 17 3.1 Flow Texture . 17 3.2 Two-dimensional Streamline Placement . 20 3.3 Simpli¯cation of Vector Fields . 23 3.4 Streamline Clustering . 25 3.5 Three-dimensional Streamline Placement . 25 3.6 Visualization Enhancement . 27 viii 4. View-dependent Multi-resolutional Flow Texture Advection . 29 4.1 Algorithm Overview . 29 4.2 Flow Field Representation . 30 4.3 Texture Advection . 31 4.4 Spatial Coherence . 34 4.5 Multi-resolutional Texture Avection . 35 4.5.1 Adjustment of Advection Step Size . 37 4.6 Results . 39 5. Illustrative Streamline Placement . 47 5.1 Algorithm Overview . 47 5.1.1 Distance Field . 49 5.1.2 Computation of Local Dissimilarity . 50 5.1.3 Influence from Multiple Streamlines . 52 5.1.4 Computation of Global Dissimilarity . 54 5.1.5 Selection of Candidate Seeds . 54 5.2 Topology-Based Enhancement . 57 5.3 Quality Analysis . 59 5.3.1 Quantitative Comparison . 59 5.3.2 User Study . 64 5.4 Results . 70 6. Image Based Streamline Generation and Rendering . 76 6.1 Algorithm Overview . 76 6.2 Image Space Streamline Placement . 78 6.2.1 Evenly-spaced Streamlines in Image Space . 79 6.2.2 Streamline Placement Strategies . 81 6.2.3 Additional Run Time Control . 90 6.3 Results . 98 7. Conclusions . 101 Bibliography . 106 ix LIST OF TABLES Table Page 4.1 Datasets used in the experiments. Note that the size for the vortex data includes all 31 time steps. The sizes are in KBytes. 39 4.2 The time for trace slice preprocessing and texture creation and loading (in seconds). .................................. 40 4.3 The size of trace slices (in MBytes) including all time steps. Note that Vortex dataset is time-varying. 44 5.1 The percentages of user rankings for each image based on the easiness to follow the underlying flow paths. ...................... 68 5.2 The percentages of user rankings for each image based on the easiness to locate the critical points by observing the streamlines. 69 5.3 The percentages of user rankings for each image based on the overall e®ec- tiveness of visualization considering the flow paths and critical points. 69 5.4 Information of four di®erent datasets, and the number of streamlines gen- erated by the algorithm. .......................... 71 5.5 Timings (in seconds) measured for generating streamlines. Each row corre- sponds to a data set listed in the same row of Table 5.4. 72 x LIST OF FIGURES Figure Page 1.1 Hand-drawn streamlines for a flow ¯eld around a cylinder. Image courtesy of Greg Turk [63]. ............................. 5 2.1 Di®erent types of grids (a) regular Cartesian grid (b) irregular Cartesian grid (c) structured grid (d) unstructured grid. 10 2.2 Classi¯cation of critical points of two-dimensional vector ¯elds. R1 and R2 denote the real part of the eigenvalues of the Jacobian matrix, while I1 and I2 denote the imaginary parts. Image courtesy of Helman and Hesselink [24]. 16 4.1 The creation of trace slices by backward advection. 32 4.2 Texture advection using two-stage texture lookups. 34 4.3 Comparison of particle position errors for travelling 1 to 10 time steps using the down-sampled trace slices and the down-sampled vortex dataset reduced from 100x100 to 50x50. X axis indicates the time steps that the particles have travelled, and Y axis indicates particle position errors compared to the accurate traces using the Euclidean distance in the ¯eld. 42 4.4 Comparison of particle position errors for travelling 1 to 10 time steps using the down-sampled trace slice and the down-sampled vortex dataset reduced from 100x100 to 25x25. X axis indicates the time steps that the particles have travelled, and Y axis indicates particle position errors compared to the accurate traces using the Euclidean distance in the ¯eld. 42 4.5 Rendering of the post dataset (a) with (b) without the multi-resolution level of detail control. .............................. 43 4.6 (a)With the correction of noise distribution, no stretched pattern can be seen (b) Rendering using LIC with the original resolution of 52x62. 44 xi 4.7 The image on the left was generated when zoomed in.
Load more

Recommended publications
  • Inviwo — a Visualization System with Usage Abstraction Levels
    IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS, VOL X, NO. Y, MAY 2019 1 Inviwo — A Visualization System with Usage Abstraction Levels Daniel Jonsson,¨ Peter Steneteg, Erik Sunden,´ Rickard Englund, Sathish Kottravel, Martin Falk, Member, IEEE, Anders Ynnerman, Ingrid Hotz, and Timo Ropinski Member, IEEE, Abstract—The complexity of today’s visualization applications demands specific visualization systems tailored for the development of these applications. Frequently, such systems utilize levels of abstraction to improve the application development process, for instance by providing a data flow network editor. Unfortunately, these abstractions result in several issues, which need to be circumvented through an abstraction-centered system design. Often, a high level of abstraction hides low level details, which makes it difficult to directly access the underlying computing platform, which would be important to achieve an optimal performance. Therefore, we propose a layer structure developed for modern and sustainable visualization systems allowing developers to interact with all contained abstraction levels. We refer to this interaction capabilities as usage abstraction levels, since we target application developers with various levels of experience. We formulate the requirements for such a system, derive the desired architecture, and present how the concepts have been exemplary realized within the Inviwo visualization system. Furthermore, we address several specific challenges that arise during the realization of such a layered architecture, such as communication between different computing platforms, performance centered encapsulation, as well as layer-independent development by supporting cross layer documentation and debugging capabilities. Index Terms—Visualization systems, data visualization, visual analytics, data analysis, computer graphics, image processing. F 1 INTRODUCTION The field of visualization is maturing, and a shift can be employing different layers of abstraction.
    [Show full text]
  • Stevens Dot Patterns for 2D Flow Visualization
    Stevens Dot Patterns for 2D Flow Visualization Laura G. Tateosian Brent M. Dennis Christopher G. Healey∗ Computer Science Department, North Carolina State University Figure 1: A Stevens-based dot pattern visualizing flow orientations in a 2D slice through a simulated supernova collapse Abstract comes from perceptual experiments designed to study how the hu- man visual system “sees” local orientation in a sparse collection of This paper describes a new technique to visualize 2D flow fields dots. Initial work by Glass suggested that a global autocorrelation with a sparse collection of dots. A cognitive model proposed by is used to identify orientation [Glass 1969; Glass and Perez 1973]. Kent Stevens describes how spatially local configurations of dots Later work by Stevens hypothesized that the orientation of virtual are processed in parallel by the low-level visual system to perceive lines between pairs of dots around a target position defines the lo- orientations throughout the image. We integrate this model into a cal orientation we perceive at that position [Stevens 1978]. This visualization algorithm that converts a sparse grid of dots into pat- distinction is important, because it implies that different types of terns that capture flow orientations in an underlying flow field. We flow patterns can be rapidly perceived in different parts of a single describe how our algorithm supports large flow fields that exceed image (Fig. 1). Stevens presented both experimental results and a the capabilities of a display device, and demonstrate how to include software system to support his vision model. properties like direction and velocity in our visualizations.
    [Show full text]
  • Flow Visualization of the Airwake Around a Model of a DD-963 Class Destroyer in a Simulated Atmospheric Boundary Layer
    Calhoun: The NPS Institutional Archive Theses and Dissertations Thesis Collection 1988 Flow visualization of the airwake around a model of a DD-963 class destroyer in a simulated atmospheric boundary layer. Johns, Michael K. http://hdl.handle.net/10945/23240 \f\$ NAVAL POSTGRADUATE SCHOOL Monterey, California j5*/% Flow Visualization of the Airwake Around a Model of a DD-963 Class Destroyer in a Simulated Atmospheric Boundary Layer by Michael K. Johns September 1988 Thesis Advisor: J. Val Healey Approved for public release; distribution is unlimited. T241983 Unclassified Security Classification of this page REPORT DOCUMENTATION PAGE la Report Security Classification Unclassified lb Restrictive Markings 2a Security Classification Authority 3 Distribution Availability of Report 2 b Declassification/Downgrading Schedule Approved for public release; distribution is unlimited. 4 Performing Organization Report Number(s) 5 Monitoring Organization Report Number(s) 6 a Name of Performing Organization 6b Office Symbol 7a Name of Monitoring Organization Naval Postgraduate School (If Applicable) 67 Naval Postgraduate School 6c Address (city, state, and ZIP code) 7b Address (city, state, and ZIP code) Monterey, CA 93943-5000 Monterey, CA 93943-5000 8a Name of Funding/Sponsoring Organization 8b Office Symbol 9 Procurement Instrument Identification Number (If Applicable) 8c Address (city, state, and ZIP code) 1 Source of Funding Numbers Program Element Number Project No | Task No I Work Unit Accession No 1 1 Title (Include Security Classification) FLOW VISUALIZATION OF THE AIRWAKE AROUND A MODEL OF A DD-963 CLASS DESTROYER IN A SIMULATED ATMOSPHERIC BOUNDARY LAYER 12 Personal Author(s) Johns, Michael K. 13a Type of Report 13b Time Covered 14 Date of Report (year, monlh.day) 15 Page Count Master's Thesis From To 1988, September 58 16 Supplementary Notation The views expressed in this thesis are those of the author and do not reflect the official policy or position of the Department of Defense or the U.S.
    [Show full text]
  • Visualizing Multivalued Data from 2D Incompressible Flows Using Concepts from Painting
    Visualizing Multivalued Data from 2D Incompressible Flows Using Concepts from Painting R.M. Kirby, H. Marmanis D.H. Laidlaw Division of Applied Mathematics Department of Computer Science Brown University Abstract rotational component of the flow. The latter is clearly demonstrated in Figure 1, where the rotational component is not apparent when We present a new visualization method for 2d flows which allows one merely views the velocity. us to combine multiple data values in an image for simultaneous In the same way that vorticity as a derived quantity provides viewing. We utilize concepts from oil painting, art, and design as us with additional information about the flow characteristics, other introduced in [1] to examine problems within fluid mechanics. We derived quantities such as the rate of strain tensor, the turbulent use a combination of discrete and continuous visual elements ar- charge and the turbulent current could be of equal use. Because the ranged in multiple layers to visually represent the data. The repre- examination of the rate of strain tensor, the turbulent charge and sentations are inspired by the brush strokes artists apply in layers to the turbulent current within the fluids community is relatively new, create an oil painting. We display commonly visualized quantities few people have ever seen visualizations of these quantities in well such as velocity and vorticity together with three additional math- known fluid mechanics problems. Simultaneous display of both ematically derived quantities: the rate of strain tensor (defined in the velocity and quantities derived from it is done both to allow the section 4), and the turbulent charge and turbulent current (defined fluids’ researcher to examine these new quantities against the can- in section 5).
    [Show full text]
  • Visualizing Carotid Blood Flow Simulations for Stroke Prevention
    Eurographics Conference on Visualization (EuroVis) 2021 Volume 40 (2021), Number 3 R. Borgo, G. E. Marai, and T. von Landesberger (Guest Editors) Visualizing Carotid Blood Flow Simulations for Stroke Prevention P. Eulzer1, M. Meuschke1;2, C. M. Klingner3 and K. Lawonn1 1University of Jena, Faculty of Mathematics and Computer Science, Germany 2 University of Magdeburg, Department of Simulation and Graphics, Germany 3 University Hospital Jena, Clinic for Neurology, Germany Abstract In this work, we investigate how concepts from medical flow visualization can be applied to enhance stroke prevention diag- nostics. Our focus lies on carotid stenoses, i.e., local narrowings of the major brain-supplying arteries, which are a frequent cause of stroke. Carotid surgery can reduce the stroke risk associated with stenoses, however, the procedure entails risks itself. Therefore, a thorough assessment of each case is necessary. In routine diagnostics, the morphology and hemodynamics of an afflicted vessel are separately analyzed using angiography and sonography, respectively. Blood flow simulations based on computational fluid dynamics could enable the visual integration of hemodynamic and morphological information and provide a higher resolution on relevant parameters. We identify and abstract the tasks involved in the assessment of stenoses and investigate how clinicians could derive relevant insights from carotid blood flow simulations. We adapt and refine a combination of techniques to facilitate this purpose, integrating spatiotemporal navigation, dimensional reduction, and contextual embedding. We evaluated and discussed our approach with an interdisciplinary group of medical practitioners, fluid simulation and flow visualization researchers. Our initial findings indicate that visualization techniques could promote usage of carotid blood flow simulations in practice.
    [Show full text]
  • Flow Visualization” Juxtaposed with “Visualization of Flow”: Synergistic Opportunities Between Two Communities
    \Flow Visualization" Juxtaposed With \Visualization of Flow": Synergistic Opportunities Between Two Communities Tiago Etiene,∗ Hoa Nguyen,y Robert M. Kirbyz SCI Institute { University of Utah, Salt Lake City, UT, 07041, USA Claudio T. Silvax Department of Computer Science and Engineering, Polytechnic Institute of NYU, USA Visualization is often employed as part of the simulation science pipeline. It is the window through which scientists examine their data for deriving new science, and the lens used to view modeling and discretization interactions within their simulations. We advo- cate that, as a component of the simulation science pipeline, visualization itself must be explicitly considered as part of the Validation and Verification (V&V) process. But what does this mean in a research area that has two \disciplinary" homes { “flow visualization" within the computer science / computational science visualization area and \visualization of flow" within the aeronautics community. Are aeronautics practitioners merely making use of algorithms developed within the visualization community that have now become \standard" through their incorporation into various visualization tools, or rather does one find both development of algorithms and their usage for studying fundamental and engineer- ing fluid mechanics in both communities, with possibly different focus. By narrowing the distance between research and development, and use of visualization techniques, one is left with a fertile ground for insights, and for increasing the reliability of results through V&V. In this paper, we explore “flow visualization" from the perspective of the visualization community and \visualization of flow" from the perspective of the aeronautics commu- nity in an attempt to understand how both communities can interact synergistically to bring visualization into the simulation science pipeline.
    [Show full text]
  • Image Based Flow Visualization for Curved Surfaces
    Image Based Flow Visualization for Curved Surfaces Jarke J. van Wijk Technische Universiteit Eindhoven Abstract 2 Related work A new method for the synthesis of dense, vector-field aligned tex- Many methods have been developed to visualize flow. Arrow plots are a standard method, but it is hard to reconstruct the flow from tures on curved surfaces is presented, called IBFVS. The method discrete samples. Streamlines and advected particles provide more is based on Image Based Flow Visualization (IBFV). In IBFV two- dimensional animated textures are produced by defining each frame insight, but also here important features of the flow can be over- of a flow animation as a blend between a warped version of the looked. previous image and a number of filtered white noise images. We The visualization community has spent much effort in the devel- produce flow aligned texture on arbitrary three-dimensional trian- opment of more effective techniques. Van Wijk [25] introduced the gle meshes in the same spirit as the original method: Texture is use of texture to visualize flow with Spot Noise. Cabral and Lee- dom [1] introduced Line Integral Convolution (LIC),which gives a generated directly in image space. We show that IBFVS is efficient and effective. High performance (typically fifty frames or more per much better image quality. second) is achieved by exploiting graphics hardware. Also, IBFVS Many extensions to and variations on these original methods, and can easily be implemented and a variety of effects can be achieved. especially LIC, have been published. The main issue is improve- Applications are flow visualization and surface rendering.
    [Show full text]
  • Flow Visualization Overview
    Flow Visualization Overview Daniel Weiskopf and Gordon Erlebacher Flow visualization is an important topic in scientific visualization and has been the subject of active research for many years. Typically, data originates from numerical simulations, such as those of computational fluid dynamics, and needs to be analyzed by means of visualization to gain an understanding of the flow. With the rapid increase of computational power for simulations, the demand for more advanced visualization methods has grown. This chapter presents an overview of important and widely used approaches to flow visualization, along with references to more detailed descriptions in the original scientific publications. Although the list of references covers a large body of research, it is by no means meant to be a comprehensive collection of articles in the field. Mathematical Description of a Flow We start with a rather abstract definition of a vector field and its corresponding flow by making use of concepts from differential geometry and the theory of differential equations. For more detailed background information on these topics we refer to textbooks on differential topology and geometry [45, 46, 66, 81]. Although this mathematical approach might seem quite abstract for many applica- tions, it has the advantage of being a flexible and generic description that is applicable to a wide range of problems. We first give the definition of a vector field.LetM be a smooth m-manifold with boundary, N be a n-D submanifold with boundary (N ⊂ M), and I ⊂ R be an open interval of real numbers. A map u : N × I −→ TM is a time-dependent vector field provided that u(x, t) ∈ TxM.
    [Show full text]
  • Empirical Studies in Information Visualization: Seven Scenarios Heidi Lam, Enrico Bertini, Petra Isenberg, Catherine Plaisant, Sheelagh Carpendale
    Empirical Studies in Information Visualization: Seven Scenarios Heidi Lam, Enrico Bertini, Petra Isenberg, Catherine Plaisant, Sheelagh Carpendale To cite this version: Heidi Lam, Enrico Bertini, Petra Isenberg, Catherine Plaisant, Sheelagh Carpendale. Empirical Studies in Information Visualization: Seven Scenarios. IEEE Transactions on Visualization and Computer Graphics, Institute of Electrical and Electronics Engineers, 2012, 18 (9), pp.1520–1536. 10.1109/TVCG.2011.279. hal-00932606 HAL Id: hal-00932606 https://hal.inria.fr/hal-00932606 Submitted on 17 Jan 2014 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. JOURNAL SUBMISSION 1 Empirical Studies in Information Visualization: Seven Scenarios Heidi Lam Enrico Bertini Petra Isenberg Catherine Plaisant Sheelagh Carpendale Abstract—We take a new, scenario based look at evaluation in information visualization. Our seven scenarios, evaluating visual data analysis and reasoning, evaluating user performance, evaluating user experience, evaluating environments and work practices, evaluating communication through visualization, evaluating visualization algorithms, and evaluating collaborative data analysis were derived through an extensive literature review of over 800 visualization publications. These scenarios distinguish different study goals and types of research questions and are illustrated through example studies. Through this broad survey and the distillation of these scenarios we make two contributions.
    [Show full text]
  • A Collaborative Ocean Visualization Environment
    The Design of COVE: a Collaborative Ocean Visualization Environment Keith Grochow A dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy University of Washington 2011 Program Authorized to Offer Degree: Computer Science & Engineering University of Washington Graduate School This is to certify that I have examined this copy of a doctoral dissertation by Keith Grochow and have found that it is complete and satisfactory in all respects, and that any and all revisions required by the final examining committee have been made. Chair of the Supervisory Committee: _____________________________________________________ Edward Lazowska Reading Committee: ______________________________________________________ Edward Lazowska ______________________________________________________ James Fogarty ______________________________________________________ John Delaney Date: ____________________________________________ In presenting this dissertation in partial fulfillment of the requirements for the doctoral degree at the University of Washington, I agree that the Library shall make its copies freely available for inspection. I further agree that extensive copying of the dissertation is allowable only for scholarly purposes, consistent with “fair use” as prescribed in the U.S. Copyright Law. Requests for copying or reproduction of this dissertation may be referred to ProQuest Information and Learning, 300 North Zeeb Road, Ann Arbor, MI 48106-1346, 1-800-521- 0600, to whom the author has granted “the right
    [Show full text]
  • Advanced Visualization of Experimental Data in Real Time Using Liveview3d
    Advanced Visualization of Experimental Data in Real Time Using LiveView3D Richard J. Schwartz1 Swales Aerospace, Hampton, VA, 23681 Gary A. Fleming2 NASA Langley Research Center, Hampton, VA, 23681 LiveView3D is a software application that imports and displays a variety of wind tunnel derived data in an interactive virtual environment in real time. LiveView3D combines the use of streaming video fed into a three-dimensional virtual representation of the test configuration with networked communications to the test facility Data Acquisition System (DAS). This unified approach to real time data visualization provides a unique opportunity to comprehend very large sets of diverse forms of data in a real time situation, as well as in post-test analysis. This paper describes how LiveView3D has been implemented to visualize diverse forms of aerodynamic data gathered during wind tunnel experiments, most notably at the NASA Langley Research Center Unitary Plan Wind Tunnel (UPWT). Planned future developments of the LiveView3D system are also addressed. I. Introduction ata Acquisition Systems (DAS) in modern wind tunnel facilities provide the ability to acquire vast D quantities of data during wind tunnel tests. It is not unusual for a wind tunnel model to be outfitted with dozens to hundreds of surface pressure taps, electronic pressure sensors, and a six-component force balance. Video-based flow diagnostic techniques1 such as schlieren imaging and laser light sheet flow visualization are also commonly used. Thus the volume of data collected during a single day of moderately intensive wind tunnel testing can reach multiple gigabytes. This leads to the associated problem of having to process, analyze, and visualize all of this data in order to identify and extract the important parts that will yield knowledge about the phenomena under test.
    [Show full text]
  • Talk9-2.3.4.13-ECP-DAV-BOF-2021
    VTK-m Approved for public release SAND 2021-3454 PE ECP Data Management, Data Analytics, and Visualization Overview Kenneth Moreland Sandia National LaBoratories ECP Annual Meeting March 30, 2021 This research was supported by the Exascale Computing Project (17-SC-20-SC), a joint project of the U.S. Department of Energy’s Office of Science and National Nuclear Security Administration, responsible for delivering a capable exascale ecosystem, including software, applications, and hardware technology, to support the nation’s exascale computing imperative. Sandia National Laboratories is a multi-mission laboratory managed and operated by National Technology and Engineering Solutions of Sandia, LLC., a wholly owned subsidiary of Honeywell International, Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525. Why VTK-m? 2 Visualization and Analysis for HPC: Current Status •Developed popular, open source tools (ParaView, VisIt) based on the Visualization ToolKit library (VTK) – Widespread usage in DOE and >1 million downloads worldwide – Hundreds of person years of effort •Two major problems for exascale: 1) Many-core architectures (as current VTK-Based investments are primarily ASCR highlight slide for VTK-based tools. only MPI parallelism) 2) I/O limitations will require in situ ECP/VTK-m proJect focused on proBlem #1. processing ECP ALPINE is focused on proBlem #2. Our approaches are complementary and coordinated. 3 Distributed Parallelism 4 Distributed Parallelism On Node Parallelism 5 VTK-m: the ’m’ is for many-core • VTK: – popular, open source, supported by a community – … but primarily single core only. • VTK-m: – name chosen to evoke the positive attributes of VTK – … but will support multi-core and many-core.
    [Show full text]