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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
NASA NTRS2014

A Model-Driven Visualization Tool for Use with Model-Based Systems Engineering Projects

Model-Based Systems Engineering (MBSE) promotes increased consistency between a system's design and its design documentation through the use of an object-oriented system model. The creation of this system model facilitates data presentation by providing a mechanism from which information can be extracted by automated manipulation of model content. Existing MBSE tools enable model creation, but are often too complex for the unfamiliar model viewer to easily use. These tools do not yet provide many opportunities for easing into the development and use of a system model when system design documentation already exists. This study creates a Systems Modeling Language (SysML) Document Traceability Framework (SDTF) for integrating design documentation with a system model, and develops an Interactive Visualization Engine for SysML Tools (InVEST), that exports consistent, clear, and concise views of SysML model data. These exported views are each meaningful to a variety of project stakeholders with differing subjects of concern and depth of technical involvement. InVEST allows a model user to generate multiple views and reports from a MBSE model, including wiki pages and interactive visualizations of data. System data can also be filtered to present only the information relevant to the particular stakeholder, resulting in a view that is both consistent with the larger system model and other model views. Viewing the relationships between system artifacts and documentation, and filtering through data to see specialized views improves the value of the system as a whole, as data becomes information

relational databases↗
DOE OSTI2022

Web application for machining parameter recommendation using visual analytics

The computer codes create a web application including multiple user interfaces, visualizations, interaction modules between the user, and visualizations. The visualizations will be interactive, allowing users to query the data directly, and they will be arranged in a dashboard. When selections are made in one visualization, filters will be applied to all other visualizations providing a coordinated system for asking questions about the data. The visualization can be utilized for manufacturing data management, analysis, and recommendation.

Chae, Junghoon↗
DOE OSTI2025

Visualizing interaction-driven restructuring of quantum Hall edge states

Many topological phases host gapless boundary modes that can be dramatically modified by electronic interactions. Even for the long-studied edge modes of quantum Hall phases, forming at the boundaries of two-dimensional (2D) electron systems, the nature of such interaction-induced changes has been elusive. Despite advances made using local probes, key experimental challenges persist: the lack of direct information about the internal structure of edge states on microscopic scales, and complications from edge disorder. Here, we use scanning tunneling microscopy (STM) to image pristine electrostatically defined quantum Hall edge states in graphene with high spatial resolution and demonstrate how correlations dictate the structures of edge channels on both magnetic and atomic length scales. For integer quantum Hall states in the zeroth Landau level, we show that interactions renormalize the edge velocity, dictate the spatial profile for copropagating modes, and induce unexpected edge valley polarization that differ from those of the bulk. While some of our findings can be understood by mean-field theory, others show breakdown of this picture, highlighting the roles of edge fluctuations and inter-channel couplings. We also extend our measurements to spatially resolve the edge state of fractional quantum Hall phases and detect spectroscopic signatures of interactions in this chiral Luttinger liquid. Furthermore, our study establishes STM as a promising tool for exploring edge physics of the rapidly expanding 2D topological phases, including newly realized fractional Chern insulators.

Electronic properties and materials↗
NASA NTRS2004

Interactive Terascale Particle Visualization

This paper describes the methods used to produce an interactive visualization of a 2 TB computational fluid dynamics (CFD) data set using particle tracing (streaklines). We use the method introduced by Bruckschen et al. [2001] that pre-computes a large number of particles, stores them on disk using a space-filling curve ordering that minimizes seeks, and then retrieves and displays the particles according to the user's command. We describe how the particle computation can be performed using a PC cluster, how the algorithm can be adapted to work with a multi-block curvilinear mesh, and how the out-of-core visualization can be scaled to 296 billion particles while still achieving interactive performance on PG hardware. Compared to the earlier work, our data set size and total number of particles are an order of magnitude larger. We also describe a new compression technique that allows the lossless compression of the particles by 41% and speeds the particle retrieval by about 30%.

Ellsworth, David↗
NASA NTRS1995

Visualization and Tracking of Parallel CFD Simulations

We describe a system for interactive visualization and tracking of a 3-D unsteady computational fluid dynamics (CFD) simulation on a parallel computer. CM/AVS, a distributed, parallel implementation of a visualization environment (AVS) runs on the CM-5 parallel supercomputer. A CFD solver is run as a CM/AVS module on the CM-5. Data communication between the solver, other parallel visualization modules, and a graphics workstation, which is running AVS, are handled by CM/AVS. Partitioning of the visualization task, between CM-5 and the workstation, can be done interactively in the visual programming environment provided by AVS. Flow solver parameters can also be altered by programmable interactive widgets. This system partially removes the requirement of storing large solution files at frequent time steps, a characteristic of the traditional 'simulate (yields) store (yields) visualize' post-processing approach.

Vaziri, Arsi↗
NASA NTRS2001

Visual assessment of the radiation distribution in the ISS Lab module: visualization in the human body

The US Lab module of the International Space Station (ISS) is a primary working area where the crewmembers are expected to spend majority of their time. Because of the directionality of radiation fields caused by the Earth shadow, trapped radiation pitch angle distribution, and inherent variations in the ISS shielding, a model is needed to account for these local variations in the radiation distribution. We present the calculated radiation dose (rem/yr) values for over 3,000 different points in the working area of the Lab module and estimated radiation dose values for over 25,000 different points in the human body for a given ambient radiation environment. These estimated radiation dose values are presented in a three dimensional animated interactive visualization format. Such interactive animated visualization of the radiation distribution can be generated in near real-time to track changes in the radiation environment during the orbit precession of the ISS.

NASA Center JSC↗
NASA NTRS1997

Out-of-Core Streamline Visualization on Large Unstructured Meshes

It's advantageous for computational scientists to have the capability to perform interactive visualization on their desktop workstations. For data on large unstructured meshes, this capability is not generally available. In particular, particle tracing on unstructured grids can result in a high percentage of non-contiguous memory accesses and therefore may perform very poorly with virtual memory paging schemes. The alternative of visualizing a lower resolution of the data degrades the original high-resolution calculations. This paper presents an out-of-core approach for interactive streamline construction on large unstructured tetrahedral meshes containing millions of elements. The out-of-core algorithm uses an octree to partition and restructure the raw data into subsets stored into disk files for fast data retrieval. A memory management policy tailored to the streamline calculations is used such that during the streamline construction only a very small amount of data are brought into the main memory on demand. By carefully scheduling computation and data fetching, the overhead of reading data from the disk is significantly reduced and good memory performance results. This out-of-core algorithm makes possible interactive streamline visualization of large unstructured-grid data sets on a single mid-range workstation with relatively low main-memory capacity: 5-20 megabytes. Our test results also show that this approach is much more efficient than relying on virtual memory and operating system's paging algorithms.

Ueng, Shyh-Kuang↗
NASA NTRS1995

elVis: An Interactive System For Visualization of Unsteady Fluid Flow

ElVis is a prototype system with allows for the interactive visualization of unsteady fluid flow. The increasing computational power applied to fluid dynamics simulations presents the enormous challenge to the visualization system designer to apply a wide range of technologies to the analysis process with ever increasing demands on performance. Visualization of the results of unsteady fluid flow simulations presents the challenge of exploring very large and complex data sets. Since exploration is a trial and error process, it is of utmost importance that the time required to execute a trial (i.e., create a visualization) be at a minimum in order to provide real time interaction.

Gerald-Yamasaki, Michael↗
DOE OSTI2024

DEIMoS GUI: An Open-Source User Interface for a High-Dimensional Mass Spectrometry Data Processing Tool

In this paper, we report the creation of a graphical user interface (GUI) for the Data Extraction for Integrated Multidimensional Spectrometry (DEIMoS) tool. DEIMoS is a Python package to process data from high-dimensional mass spectrometry measurements. It is divided into several modules, each representing a data processing step, such as peak detection, alignment, and tandem mass spectra extraction and deconvolution. The inputs for and outputs from DEIMoS can include millions of N-dimensional data points, which can be challenging to visualize in a way that is interactive, informative, and responsive. Here, we used the HoloViz Python data stack, including DataShader and Param, to create an interactive visualization of mass spectrometry data. We believe the GUI will increase the accessibility of DEIMoS, and the visualization methods could be useful for other open-source mass spectrometry tools.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Scalable Volume Visualization for Big Scientific Data Modeled by Functional Approximation

Considering the challenges posed by the space and time complexities in handling extensive scientific volumetric data, various data representations have been developed for the analysis of large-scale scientific data. Multivariate functional approximation (MFA) is an innovative data model designed to tackle substantial challenges in scientific data analysis. It computes values and derivatives with high-order accuracy throughout the spatial domain, mitigating artifacts associated with zero- or first-order interpolation. However, the slow query time through MFA makes it less suitable for interactively visualizing a large MFA model. In this work, we develop the first scalable interactive volume visualization pipeline, MFA-DVV, for the MFA model encoded from large-scale datasets. Our method achieves low input latency through distributed architecture, and its performance can be further enhanced by utilizing a compressed MFA model while still maintaining a high-quality rendering result for scientific datasets. We conduct comprehensive experiments to show that MFA-DVV can decrease the input latency and achieve superior visualization results for big scientific data compared with existing approaches.

big scientific dataset↗
NASA NTRS2005

Parallel Rendering of Large Time-Varying Volume Data

Interactive visualization of large time-varying 3D volume datasets has been and still is a great challenge to the modem computational world. It stretches the limits of the memory capacity, the disk space, the network bandwidth and the CPU speed of a conventional computer. In this SURF project, we propose to develop a parallel volume rendering program on SGI's Prism, a cluster computer equipped with state-of-the-art graphic hardware. The proposed program combines both parallel computing and hardware rendering in order to achieve an interactive rendering rate. We use 3D texture mapping and a hardware shader to implement 3D volume rendering on each workstation. We use SGI's VisServer to enable remote rendering using Prism's graphic hardware. And last, we will integrate this new program with ParVox, a parallel distributed visualization system developed at JPL. At the end of the project, we Will demonstrate remote interactive visualization using this new hardware volume renderer on JPL's Prism System using a time-varying dataset from selected JPL applications.

Garbutt, Alexander E.↗
DOE OSTI2022

An overview of visualization and visual analytics applications in water resources management

Recent advances in information, communication, and environmental monitoring technologies have increased the availability, spatiotemporal resolution, and quality of water-related data, thereby leading to the emergence of many innovative big data applications. Among these applications, visualization and visual analytics, also known as the visual computing techniques, empower the synergy of computational methods (e.g., machine learning and statistical models) with human reasoning to improve the understanding and solution toward complex science and engineering problems. These approaches are frequently integrated with geographic information systems and cyberinfrastructure to provide new opportunities and methods for enhancing water resources management. Here, we present a comprehensive review of recent hydroinformatics applications that employ visual computing techniques to (1) support complex data-driven research problems, and (2) support the communication and decision-makings in the water resources management sector. Then, we conduct a technical review of the state-of-the-art web-based visualization technologies and libraries to share our experiences on developing shareable, adaptive, and interactive visualizations and visual interfaces for water resources management applications. We close with a vision that applies the emerging visual computing technologies and paradigms to develop the next generation of hydroinformatics applications.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1999

Parallel Visualization Co-Processing of Overnight CFD Propulsion Applications

An interactive visualization system pV3 is being developed for the investigation of advanced computational methodologies employing visualization and parallel processing for the extraction of information contained in large-scale transient engineering simulations. Visual techniques for extracting information from the data in terms of cutting planes, iso-surfaces, particle tracing and vector fields are included in this system. This paper discusses improvements to the pV3 system developed under NASA's Affordable High Performance Computing project.

Edwards, David E.↗
NASA NTRS1989

Visualizing large data sets in the earth sciences

The authors describe the capabilities of McIDAS, an interactive visualization system that is vastly increasing the ability of earth scientists to manage and analyze data from remote sensing instruments and numerical simulation models. McIDAS provides animated three-dimensionsal images and highly interactive displays. The software can manage, analyze, and visualize large data sets that span many physical variables (such as temperature, pressure, humidity, and wind speed), as well as time and three spatial dimensions. The McIDAS system manages data from at least 100 different sources. The data management tools consist of data structures for storing different data types in files, libraries of routines for accessing these data structures, system commands for performing housekeeping functions on the data files, and reformatting programs for converting external data to the system's data structures. The McIDAS tools for three-dimensional visualization of meteorological data run on an IBM mainframe and can load up to 128-frame animation sequences into the workstations. A highly interactive version of the system can provide an interactive window into data sets containing tens of millions of points produced by numerical models and remote sensing instruments. The visualizations are being used for teaching as well as by scientists.

Hibbard, William↗
DOE OSTI2021

Bridging cognitive gaps between user and model in interactive dimension reduction

Interactive machine learning (ML) systems are difficult to design because of the "Two Black Boxes" problem that exists at the interface between human and machine. Many algorithms that are used in interactive ML systems are black boxes that are presented to users, while the human cognition represents a second black box that can be difficult for the algorithm to interpret. These two black boxes create cognitive gaps between the user and the interactive ML model when a user interacts with the system. In this paper, we identify several cognitive gaps that exist in a previously-developed interactive visual analytics (VA) system, Andromeda. These cognitive gaps that we are addressing in Andromeda are representative of common problems in other VA systems. Our goal with this work is to open both black boxes and bridge these cognitive gaps by making improvements to the original Andromeda system, including designing new visual features to help people better understand how Andromeda processes and interacts with data and improving the underlying algorithm so that the Andromeda system can better understand the intent of the user during the data exploration process. We evaluate our designs through both qualitative and quantitative analysis (i.e., user study and simulation analysis), and the results confirm that the improved Andromeda system outperforms the original version significantly in a series of high-dimensional data understanding tasks.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2016

MBSE-Driven Visualization of Requirements Allocation and Traceability

In a Model Based Systems Engineering (MBSE) infusion effort, there is a usually a concerted effort to define the information architecture, ontologies, and patterns that drive the construction and architecture of MBSE models, but less attention is given to the logical follow-on of that effort: how to practically leverage the resulting semantic richness of a well-formed populated model to enable systems engineers to work more effectively, as MBSE promises. While ontologies and patterns are absolutely necessary, an MBSE effort must also design and provide practical demonstration of value (through human-understandable representations of model data that address stakeholder concerns) or it will not succeed. This paper will discuss opportunities that exist for visualization in making the richness of a well-formed model accessible to stakeholders, specifically stakeholders who rely on the model for their day-to-day work. This paper will discuss the value added by MBSE-driven visualizations in the context of a small case study of interactive visualizations created and used on NASA's proposed Europa Mission. The case study visualizations were created for the purpose of understanding and exploring targeted aspects of requirements flow, allocation, and comparing the structure of that flow-down to a conceptual project decomposition. The work presented in this paper is an example of a product that leverages the richness and formalisms of our knowledge representation while also responding to the quality attributes SEs care about.

Model Based Systems Engineering↗
NASA NTRS2016

MBSE-Driven Visualization of Requirements Allocation and Traceability

In a Model Based Systems Engineering (MBSE) infusion effort, there is a usually a concerted effort to define the information architecture, ontologies, and patterns that drive the construction and architecture of MBSE models, but less attention is given to the logical follow-on of that effort: how to practically leverage the resulting semantic richness of a well formed populated model to enable systems engineers to work more effectively, as MBSE promises. While ontologies and patterns are absolutely necessary, an MBSE effort must also design and provide practical demonstration of value (through human-understandable representations of model data that address stakeholder concerns) or it will not succeed. This paper will discuss opportunities that exist for visualization in making the richness of a well-formed model accessible to stakeholders, specifically stakeholders who rely on the model for their day-to-day work. This paper will discuss the value added by MBSE-driven visualizations in the context of a small case study of interactive visualizations created and used on NASA’s proposed Europa Mission. The case study visualizations were created for the purpose of understanding and exploring targeted aspects of requirements flow, allocation, and comparing the structure of that flow-down to a conceptual project decomposition. The work presented in this paper is an example of a product that leverages the richness and formalisms of our knowledge representation while also responding to the quality attributes SEs care about.

Model Based Systems Engineering↗