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At least 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS2018

Learning Reverse Engineering and Simulation with Design Visualization

The Design Visualization (DV) group supports work at the Kennedy Space Center by utilizing metrology data with Computer-Aided Design (CAD) models and simulations to provide accurate visual representations that aid in decision-making. The capability to measure and simulate objects in real time helps to predict and avoid potential problems before they become expensive in addition to facilitating the planning of operations. I had the opportunity to work on existing and new models and simulations in support of DV and NASA’s Exploration Ground Systems (EGS).

Hemsworth, Paul J.↗
NASA NTRS2014

Design Visualization Internship Overview

This is a report documenting the details of my work as a NASA KSC intern for the Summer Session from June 2nd to August 8th, 2014. This work was conducted within the Design Visualization Group, a Contractor staffed organization within the C1 division of the IT Directorate. The principle responsibilities of the KSC Design Visualization Group are the production of 3D simulations of NASA equipment and facilities for the purpose of planning complex operations such as hardware transportation and vehicle assembly. My role as an intern focused on aiding engineers in using 3D scanning equipment to obtain as-built measurements of NASA facilities, as well as using CATIA and DELMIA to process this data. My primary goals for this internship focused on expanding my CAD knowledge and capabilities, while also learning more about technologies I was previously unfamiliar with, such as 3D scanning. An additional goal of mine was to learn more about how NASA operates, and how the U.S. Space Program operates on a day-to-day basis. This opportunity provided me with a front-row seat to the daily maneuvers and operations of KSC and NASA as a whole. Each work day, I was able to witness, and even take part of, a small building block of the future systems that will take astronauts to other worlds. After my experiences this summer, not only can I say that my goals have been met, but also that this experience has been the highlight of my experience in higher education.

Telescience↗
DOE OSTI2021

A Visual Designer of Layer‐wise Relevance Propagation Models

Abstract Layer‐wise Relevance Propagation (LRP) is an emerging and widely‐used method for interpreting the prediction results of convolutional neural networks (CNN). LRP developers often select and employ different relevance backpropagation rules and parameters, to compute relevance scores on input images. However, there exists no obvious solution to define a “best” LRP model. A satisfied model is highly reliant on pertinent images and designers' goals. We develop a visual model designer, named as VisLRPDesigner, to overcome the challenges in the design and use of LRP models. Various LRP rules are unified into an integrated framework with an intuitive workflow of parameter setup. VisLRPDesigner thus allows users to interactively configure and compare LRP models. It also facilitates relevance‐based visual analysis with two important functions: relevance‐based pixel flipping and neuron ablation. Several use cases illustrate the benefits of VisLRPDesigner. The usability and limitation of the visual designer is evaluated by LRP users.

Huang, Xinyi↗
DOE OSTI2021

A Visual Designer of Layer-wise Relevance Propagation Models

Layer-wise Relevance Propagation (LRP) is an emerging and widely-used method for interpreting the prediction results of convolutional neural networks (CNN). LRP developers often select and employ different relevance backpropagation rules and parameters, to compute relevance scores on input images. However, there exists no obvious solution to define a "best" LRP model. A satisfied model is highly reliant on pertinent images and designers' goals. We develop a visual model designer, named as VisLRPDesigner, to overcome the challenges in the design and use of LRP models. Various LRP rules are unified into an integrated framework with an intuitive workflow of parameter setup. VisLRPDesigner thus allows users to interactively configure and compare LRP models. It also facilitates relevance-based visual analysis with two important functions: relevance-based pixel flipping and neuron ablation. Several use cases illustrate the benefits of VisLRPDesigner. The usability and limitation of the visual designer is evaluated by LRP users.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Experts’ Familiarity Versus Optimality of Visualization Design: How Familiarity Affects Perceived and Objective Task Performance

Experts, cutting across domains like biology, climate science, cyber, energy, etc., frequently use visualizations as the principal medium for making analytical judgments or for presenting the results of their analysis. However, scientists are often skeptical about adopting new visualization methods over familiar ones, although the latter might be perceptually sub-optimal. This is due to the use of the familiarity heuristic, where the perceived cognitive ease in processing familiar representations of information leads scientists to undermine the effect of visualization best practices. Recent studies have shown that this often results in a discrepancy between scientists’ perceived and actual performance quality. It has also been shown that in some cases, participatory design sessions and qualitative and quantitative user studies are able to mitigate the effects of such bias. In this paper, we discuss the potential causes and effects of familiarity related biases with examples from recent studies and reflect on the related research questions.

visualization, climate science, cognitive bias, fa↗
NASA NTRS1986

Visualization design and verification of Ada tasking using timing diagrams

The use of timing diagrams is recommended in the design and testing of multi-task Ada programs. By displaying the task states vs. time, timing diagrams can portray the simultaneous threads of data flow and control which characterize tasking programs. This description of the system's dynamic behavior from conception to testing is a necessary adjunct to other graphical techniques, such as structure charts, which essentially give a static view of the system. A series of steps is recommended which incorporates timing diagrams into the design process. Finally, a description is provided of a prototype Ada Execution Analyzer (AEA) which automates the production of timing diagrams from VAX/Ada debugger output.

Vidale, R. F.↗
NASA NTRS2013

Kennedy Space Center Design Visualization

Perform simulations of ground operations leading up to launch at Kennedy Space Center and Vandenberg Air Force Base in CA since 1987. We use 3D Laser Scanning, Modeling and Simulations to verify that operations are feasible, efficient and safe.

Humeniuk, Bob↗
DOE OSTI2015

Bridging Theory with Practice: An Exploratory Study of Visualization Use and Design for Climate Model Comparison

Evaluation methodologies in visualization have mostly focused on how well the tools and techniques cater to the analytical needs of the user. While this is important in determining the effectiveness of the tools and advancing the state-of-the-art in visualization research, a key area that has mostly been overlooked is how well established visualization theories and principles are instantiated in practice. This is especially relevant when domain experts, and not visualization researchers, design visualizations for analysis of their data or for broader dissemination of scientific knowledge. There is very little research on exploring the synergistic capabilities of cross-domain collaboration between domain experts and visualization researchers. To fill this gap, in this paper we describe the results of an exploratory study of climate data visualizations conducted in tight collaboration with a pool of climate scientists. The study analyzes a large set of static climate data visualizations for identifying their shortcomings in terms of visualization design. The outcome of the study is a classification scheme that categorizes the design problems in the form of a descriptive taxonomy. The taxonomy is a first attempt for systematically categorizing the types, causes, and consequences of design problems in visualizations created by domain experts. We demonstrate the use of the taxonomy for a number of purposes, such as, improving the existing climate data visualizations, reflecting on the impact of the problems for enabling domain experts in designing better visualizations, and also learning about the gaps and opportunities for future visualization research. We demonstrate the applicability of our taxonomy through a number of examples and discuss the lessons learnt and implications of our findings.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1989

Visions of visualization aids - Design philosophy and observations

Aids for the visualization of high-dimensional scientific or other data must be designed. Simply casting multidimensional data into a two-dimensional or three-dimensional spatial metaphor does not guarantee that the presentation will provide insight or a parsimonious description of phenomena implicit in the data. Useful visualization, in contrast to glitzy, high-tech, computer-graphics imagery, is generally based on preexisting theoretical beliefs concerning the underlying phenomena. These beliefs guide selection and formatting of the plotted variables. Visualization tools are useful for understanding naturally three-dimensional data bases such as those used by pilots or astronauts. Two examples of such aids for spatial maneuvering illustrate that informative geometric distortion may be introduced to assist visualization and that visualization of complex dynamics alone may not be adequate to provide the necessary insight into the underlying processes.

Ellis, Stephen R.↗
DOE OSTI2017

Human Factors in Streaming Data Analysis: Challenges and Opportunities for Information Visualization: Human Factors in Streaming Data Analysis

State-of-the-art visual analytics models and frameworks mostly assume a static snapshot of the data, while in many cases it is a stream with constant updates and changes. Exploration of streaming data poses unique challenges as machine-level computations and abstractions need to be synchronized with the visual representation of the data and the temporally evolving human insights. In the visual analytics literature, we lack a thorough characterization of streaming data and analysis of the challenges associated with task abstraction, visualization design, and adaptation of the role of human-in-the-loop for exploration of data streams. We aim to fill this gap by conducting a survey of the state-of-the-art in visual analytics of streaming data for systematically describing the contributions and shortcomings of current techniques and analyzing the research gaps that need to be addressed in the future. Our contributions are: i) problem characterization for identifying challenges that are unique to streaming data analysis tasks, ii) a survey and analysis of the state-of-the-art in streaming data visualization research with a focus on the visualization design space for dynamic data and the role of the human-in-the-loop, and iii) reflections on the design-trade-offs for streaming visual analytics techniques and their practical applicability in real-world application scenarios.

streaming data↗
NASA NTRS1990

Visions of visualization aids: Design philosophy and experimental results

Aids for the visualization of high-dimensional scientific or other data must be designed. Simply casting multidimensional data into a two- or three-dimensional spatial metaphor does not guarantee that the presentation will provide insight or parsimonious description of the phenomena underlying the data. Indeed, the communication of the essential meaning of some multidimensional data may be obscured by presentation in a spatially distributed format. Useful visualization is generally based on pre-existing theoretical beliefs concerning the underlying phenomena which guide selection and formatting of the plotted variables. Two examples from chaotic dynamics are used to illustrate how a visulaization may be an aid to insight. Two examples of displays to aid spatial maneuvering are described. The first, a perspective format for a commercial air traffic display, illustrates how geometric distortion may be introduced to insure that an operator can understand a depicted three-dimensional situation. The second, a display for planning small spacecraft maneuvers, illustrates how the complex counterintuitive character of orbital maneuvering may be made more tractable by removing higher-order nonlinear control dynamics, and allowing independent satisfaction of velocity and plume impingement constraints on orbital changes.

Ellis, Stephen R.↗
NASA NTRSDate not supplied

Experiment Design and Visualization Techniques for an X-59 Low-boom Variability Study

This presentation outlines the design of experiments approach and data visualization techniques for a simulation study of sonic booms from NASA’s X-59 supersonic aircraft. The X-59 will soon be flown over communities across the contiguous USA as it produces a low-loudness sonic boom, or low-boom. Survey data on human perception of low-booms will be collected to support development of potential future commercial supersonic aircraft noise regulatory standards. The macroscopic atmosphere plays a critical role in the loudness of sonic booms. The extensive sonic boom simulation study presented herein was completed to assess climatological, geographical, and seasonal effects on the variability of the X-59’s low-boom loudness and noise exposure region size in order to inform X-59 community test planning. The loudness and extent of the noise exposure region make up the “sonic boom carpet.” Two spatial and temporal resolutions of atmospheric input data to the simulation were investigated. A Fast Flexible Space-Filling Design was used to select the locations across the USA for the two spatial resolutions. Analysis of simulated X-59 low-boom loudness data within a regional subset of the northeast USA was completed using a bootstrap forest to determine the final spatial and temporal resolution of the countrywide simulation study. Atmospheric profiles from NOAA’s Climate Forecast System Version 2 database were used to generate over one million simulated X-59 carpets at the final selected 138 locations across the USA. Effects of aircraft heading, season, geography, and climate zone on low-boom levels and noise exposure region size were analyzed. Models were developed to estimate loudness metrics throughout the USA for X-59 supersonic cruise overflight, and results were visualized on maps to show geographical and seasonal trends. These results inform regulators and mission planners on expected variations in boom levels and carpet extent from atmospheric variations. Understanding potential carpet variability is important when planning community noise surveys using the X-59.

X-59↗
DOE OSTI2019

Remote Sensor Design for Visual Recognition with Convolutional Neural Networks

While deep learning technologies for computer vision have developed rapidly since 2012, modeling of remote sensing systems has remained focused around human vision. In particular, remote sensing systems are usually constructed to optimize sensing cost-quality trade-offs with respect to human image interpretability. While some recent studies have explored remote sensing system design as a function of simple computer vision algorithm performance, there has been little work relating this design to the state-of-the-art in computer vision: deep learning with convolutional neural networks. We develop experimental systems to conduct this analysis, showing results with modern deep learning algorithms and recent overhead image data. Our results are compared to standard image quality measurements based on human visual perception, and we conclude not only that machine and human interpretability differ significantly, but that computer vision performance is largely self-consistent across a range of disparate conditions. This repository contains all the code required to replicate the results of our research paper, and the corresponding docker environment in which that code can be executed. All code is written in Python3 and utilizes the PyTorch library (v1.0) for neural network model training and evaluation. Jupyter notebooks are used to visualize images transformed with our code, in addition to plotting experimental results. We also include the specific parameter files used to execute our experiments, with the intent that these experiments can be replicated.

Zelinski, michaelE.↗
NASA NTRS1973

Space shuttle visual simulation system design study

A recommendation and a specification for the visual simulation system design for the space shuttle mission simulator are presented. A recommended visual system is described which most nearly meets the visual design requirements. The cost analysis of the recommended system covering design, development, manufacturing, and installation is reported. Four alternate systems are analyzed.

Source record↗
DOE OSTI2018

A Heuristic Approach to Value-Driven Evaluation of Visualizations

Recently, an approach for determining the value of a visualization was proposed, one moving beyond simple measurements of task accuracy and speed. The value equation contains components for the time savings a visualization provides, the insights and insightful questions it spurs, the overall essence of the data it conveys, and the confidence about the data and its domain it inspires. This articulation of value is purely descriptive, however, providing no actionable method of assessing a visualization's value. In this work, we create a heuristic-based evaluation methodology to accompany the value equation for assessing interactive visualizations. We refer to the methodology colloquially as ICE-T, based on an anagram of the four value components. Our approach breaks the four components down into guidelines, each of which is made up of a small set of low-level heuristics. Evaluators who have knowledge of visualization design principles then assess the visualization with respect to the heuristics. We conducted an initial trial of the methodology on three interactive visualizations of the same data set, each evaluated by 15 visualization experts. As a result, we found that the methodology showed promise, obtaining consistent ratings across the three visualizations and mirroring judgments of the utility of the visualizations by instructors of the course in which they were developed.

97 MATHEMATICS AND COMPUTING↗