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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 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Rapid Response Data Science for COVID-19

This report describes the results of a seven day effort to assist subject matter experts address a problem related to COVID-19. In the course of this effort, we analyzed the 29K documents provided as part of the White House's call to action. This involved applying a variety of natural language processing techniques and compression-based analytics in combination with visualization techniques and assessment with subject matter experts to pursue answers to a specific question. In this paper, we will describe the algorithms, the software, the study performed, and availability of the software developed during the effort.

60 APPLIED LIFE SCIENCES↗
NASA NTRSDate not supplied

An Introduction to Data Visualization

Data visualization can be used to present findings, explore data, and use the human eye to find patterns that a computer would struggle to locate. Borrowing tools from art, storytelling, data analytics and software development, data visualization is an indispensable part of the analysis process. While data visualization usage spans across multiple disciplines and sectors, most never receive formal training in the subject. As such, this tutorial will introduce key data visualization building blocks and how to best use those building blocks for different scenarios and audiences. We will also go over tips on accessibility, design and interactive elements. While this will by no means be a complete overview of the data visualization field, by building a foundation and introducing some rules of thumb, attendees will be better equipped for communicating their findings to their audience.

data visualization↗
DOE OSTI2026

Grid Operator Analytics and Assessment Tools for Inverter- Based Resources Dominated Grid (GOAAT-IBR) Project Update

This presentation provides an update on the OPTIMA GOAAT project, with emphasis on the cloud-native data platform developed in-house to ingest, manage, and operationalize high-resolution power system data. Since our last NASPI presentation, accessible via OSTI ID #2671437, the project team advanced the design and deployment of a scalable architecture capable of handling both synchronized and non-synchronized streams, including PMU, point-on-wave (POW), COMTRADE, and SCADA data. These materials review the project status, recent progress, and key lessons learned. The core of the presentation examines the architecture and engineering of our cloud-native ingestion and data management platform. We then explain how pipelines were designed to collect, normalize, time-align, store, and serve heterogeneous data at scale. We will discuss design choices such as data models, streaming versus batch ingestion, storage tiers, and interoperability with analytics applications. Practical experiences with cloud-native technologies were shared during the event, including benefits, limitations, and integration challenges in a utility environment, along with methods used to improve performance, reduce latency, and optimize resource usage. The presentation also showcases user interface designs and visualization tools that convert raw measurements and analytics results into intuitive, actionable insights for operators and engineers. During the presentation examples were provided demonstrating how visualization, event views, and summarized analytics enhance situational awareness and support operational decision-making. These use cases illustrate how a well-designed data infrastructure can bridge the gap between high-volume measurements and practical grid operations.

Aminifar, Farrokh↗
NASA NTRS1972

A method for increasing thrust reverser utilization on STOL aircraft.

A technique for increasing the utilization of thrust reversers on STOL aircraft is described. The technique involves asymmetric orientation of the reversed exhaust in such a manner as to avoid the problems of self-ingestion, even in the presence of a cross wind, and cross ingestion between adjacent engines. Experimental results of ingestion in a single nacelle inlet are discussed and flow visualization pictures are presented. An analytical model of ingestion is described and sample results are shown.

Tatom, J. W.↗
NASA NTRS1992

Electroencephalographic monitoring of complex mental tasks

Outlined here is the development of neurophysiological procedures to monitor operators during the performance of cognitive tasks. Our approach included the use of electroencepalographic (EEG) and rheoencephalographic (REG) techniques to determine changes in cortical function associated with cognition in the operator's state. A two channel tetrapolar REG, a single channel forearm impedance plethysmograph, a Lead I electrocardiogram (ECG) and a 21 channel EEG were used to measure subject responses to various visual-motor cognitive tasks. Testing, analytical, and display procedures for EEG and REG monitoring were developed that extend the state of the art and provide a valuable tool for the study of cerebral circulatory and neural activity during cognition.

Guisado, Raul↗
NASA NTRS1997

Graphic Three-Axes Presentation of Residual Gas Analyzer Data

Residual gas analyzers (RGA) are commonly used to measure the composition of residual gases in thermal-vacuum test chambers. Measurements from RGA's are often used to identify and quantify outgassing contaminants from a test article during thermal-vacuum testing. RGA data is typically displayed as snapshots in time, showing instantaneous concentrations of ions from ionized residual gas molecules at different atomic masses. This ion concentration information can be interpreted to be representative of the composition of the residual gas in the chamber at the instant of analysis. Typically, test personnel are most interested in tracking the time history of changes in the composition of chamber residual gas to determine the relative cleanliness and the clean-up rate of the test article under vacuum. However, displays of instantaneous RGA data cannot provide test personnel with the preferred time history information. In order to gain an understanding of gas composition trends, a series of plots of individual data snapshots must be analyzed. This analysis is cumbersome and still does not provide a very satisfactory view of residual gas composition trends. A method was devised by the authors to present RCA data in a three-axis format, plotting Atomic Mass Unit (AMU), the Ionization Signal Response (ISR) as amps/torr as a function of AMU, and Time, to provide a clear graphic visualization of trends of changes in ISR with respect to time and AMU (representative of residual gas composition). This graphic visualization method provides a valuable analytical tool to interpret test article outgassing rates during thermal vacuum tests. Raw RGA data was extracted from a series of delimited ASCII files and then converted to a data array in a spreadsheet. Consequently, using the 3-D plotting functionality provided by the spreadsheet program, 3-D plots were produced. After devising the data format conversion process, the authors began developing a program to provide real-time 3-D plotting of RGA data. The intent of this program is to automate the RGA data acquisition process and to generate up-to-the-minute time history 3-D displays of stored RGA data (development of this program was not complete at the time of this writing). This paper provides a brief description of the data format conversion process and presents results from a recent test to illustrate the usefulness of this 3-D RGA data plotting technique.

Johnson, Kenneth R.↗
NASA NTRSDate not supplied

Machine Learning for NASA Advanced Information Systems

NASA's Advanced Information Systems Technology (AIST) Program is one of several Technology programs managed by the Earth Science Technology Office (ESTO) in the Earth Science Division (ESD). The AIST Program focuses on advanced information systems and novel computer science technologies that will be needed by NASA Earth Science in the next 5 to 10 years. The three main thrusts of the AIST Program deal with Novel Observing Strategies (NOS), Analytic Collaborative Frameworks (ACF) and Earth System Digital Twins (ESDT). For all these thrusts, Machine Learning (ML) is increasingly being used in multiple aspects of Earth science systems, e.g., for onboard autonomy and decision making, for the analysis of massive and diverse datasets as well as more recently for developing surrogate models that will represent one of the main components of future Digital Twins of the Earth. Particularly, ESDT technologies developed by the AIST Program will allow to develop integrated Earth Science frameworks that will mirror the Earth with state-of-the-art models (Earth system models and others), timely and relevant observations, and analytic tools. These information systems will be used for supporting near- and long-term science and policy decisions. ESDT frameworks will build on previously developed AIST capabilities and technologies to integrate interconnected models with continuous streams of observations, data analytics, data assimilation, simulations, advanced visualizations and the ability to conduct "what-if" scenarios. This talk will describe the three thrusts of the AIST Program with a special focus on Machine Learning and how it is being used at all steps of the Earth Science data lifecycle.

Mathematical and Computer Sciences (General)↗
NASA NTRSDate not supplied

Upcoming Lunar Mission Landing Sites: Viewing and Analysis with Celestial Mapping System

The Celestial Mapping System (CMS) is a powerful software platform designed to create virtual 3D globes for celestial bodies within our solar system, with a specific focus on lunar mapping. CMS offers a rich array of functionalities, including high-resolution imagery visualization, precise measurement tools, and analytical capabilities that cater to the needs of planetary scientists and mission planners. This abstract explores how CMS has been leveraged to conduct in-depth analyses of 12 lunar missions to the South Pole, including missions like Chandraayan 3, Russian Space Agency's Luna 25, Xelene 1, and Intuitive Machines Nova-C lander I. Moreover, the integration of HORUS (Hyper-effective nOise Removal Unit Software) into CMS enhances its capabilities, allowing for the rendering of images in a 3D globe format and providing visibility into permanently shadowed regions. CMS represents a cutting-edge tool for lunar surface awareness, equipment placement planning, and traverse path optimization

Moon↗
DOE OSTI2022

1D Heat Loss Models Validation Experiment

Contains data from the model validation in the 1D Heat Loss Models to Predict the Aquifer Temperature Profile during Hot/Cold Water Injection Project. The data include two COMSOL models (2D axisymmetric benchmark model and 2D Vinsome model), one python code (1D Vinsome based FEM numerical simulation), one matlab main code (1D Newton analytical solution and all results comparison visualization), and output files generated from the above models.

1D↗
DOE OSTI2019

Separating the Wheat from the Chaff: Comparative Visual Cues for Transparent Diagnostics of Competing Models

Experts in data and physical sciences have to regularly grapple with the problem of competing models. Be it analytical or physics-based models, a cross-cutting challenge for experts is to reliably diagnose which model outcomes appropriately predict or simulate real-world phenomena. Expert judgment involves reconciling information across many, and often, conflicting criteria that describe the quality of model outcomes. In this paper, through a design study with climate scientists, we develop a deeper understanding of the problem and solution space of model diagnostics, resulting in the following contributions: i) a problem and task characterization using which we map experts’ model diagnostics goals to multi-way visual comparison tasks, ii) a design space of comparative visual cues for letting experts quickly understand the degree of disagreement among competing models and gauge the degree of stability of model outputs with respect to alternative criteria, and iii) design and evaluation of MyriadCues, an interactive visualization interface for exploring alternative hypotheses and insights about good and bad models by leveraging comparative visual cues. Here, we present case studies and subjective feedback by experts, which validate how MyriadCues enables more transparent model diagnostic mechanisms, as compared to the state of the art.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1979

Analytic modeling of aerosol size distributions

Mathematical functions commonly used for representing aerosol size distributions are studied parametrically. Methods for obtaining best fit estimates of the parameters are described. A catalog of graphical plots depicting the parametric behavior of the functions is presented along with procedures for obtaining analytical representations of size distribution data by visual matching of the data with one of the plots. Examples of fitting the same data with equal accuracy by more than one analytic model are also given.

Deepack, A.↗
NASA NTRS1993

Verification of a two-dimensional infiltration model for the resin transfer molding process

A two-dimensional finite element model for the infiltration of a dry textile preform by an injected resin was verified. The model, which is based on the finite element/control volume technique, determines the total infiltration time and the pressure increase at the mold inlet associated with the RTM process. Important input data for the model are the compaction and permeability behavior of the preform along with the kinetic and rheological behavior of the resin. The compaction behavior for several textile preforms was determined by experimental methods. A power law regression model was used to relate fiber volume fraction to the applied compaction pressure. Results showed a large increase in fiber volume fraction with the initial application of pressure. However, as the maximum fiber volume fraction was approached, the amount of compaction pressure required to decrease the porosity of the preform rapidly increased. Similarly, a power law regression model was used to relate permeability to the fiber volume fraction of the preform. Two methods were used to measure the permeability of the textile preform. The first, known as the steady state method, measures the permeability of a saturated preform under constant flow rate conditions. The second, denoted the advancing front method, determines the permeability of a dry preform to an infiltrating fluid. Water, corn oil, and an epoxy resin, Epon 815, were used to determine the effect of fluid type and viscosity on the steady state permeability behavior of the preform. Permeability values measured with the different fluids showed that fluid viscosity had no influence on the permeability behavior of 162 E-glass and TTI IM7/8HS preforms. Permeabilities measured from steady state and advancing front experiments for the warp direction of 162 E-glass fabric were similar. This behavior was noticed for tests conducted with corn oil and Epon 815. Comparable behavior was observed for the warp direction of the TTI IM7/8HS preform and corn oil. Mold filling and flow visualization experiments were performed to verify the analytical computer model. Frequency dependent electromagnetic sensors were used to monitor the resin flow front as a function of time. For the flow visualization tests, a video camera and high resolution tape recorder were used to record the experimental flow fronts. Comparisons between experimental and model predicted flow fronts agreed well for all tests. For the mold filling tests conducted at constant flow rate injection, the model was able to accurately predict the pressure increase at the mold inlet during the infiltration process. A kinetics model developed to predict the degree of cure as a function of time for the injected resin accurately calculated the increase in the degree of cure during the subsequent cure cycle.

Hammond, Vincent H.↗
DOE OSTI2024

Localized Evaluation for Constructing Discrete Vector Fields

Topological abstractions offer a method to summarize the behavior of vector fields, but computing them robustly can be challenging due to numerical precision issues. One alternative is to represent the vector field using a discrete approach, which constructs a collection of pairs of simplices in the input mesh that satisfies criteria introduced by Forman's discrete Morse theory. While numerous approaches exist to compute pairs in the restricted case of the gradient of a scalar field, state-of-the-art algorithms for the general case of vector fields require expensive optimization procedures. This paper introduces a fast, novel approach for pairing simplices of two-dimensional, triangulated vector fields that do not vary in time. The key insight of our approach is that we can employ a local evaluation, inspired by the approach used to construct a discrete gradient field, where every simplex in a mesh is considered by no more than one of its vertices. Specifically, we observe that for any edge in the input mesh, we can uniquely assign an outward direction of flow. We can further expand this consistent notion of outward flow at each vertex, which corresponds to the concept of a downhill flow in the case of scalar fields. Working with outward flow enables a linear-time algorithm that processes the (outward) neighborhoods of each vertex one-by-one, similar to the approach used for scalar fields. Here, we couple our approach to constructing discrete vector fields with a method to extract, simplify, and visualize topological features. Empirical results on analytic and simulation data demonstrate drastic improvements in running time, produce features similar to the current state-of-the-art, and show the application of simplification to large, complex flows.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Composite boson signature in the interference pattern of atomic dimer condensates

We predict the existence of high frequency modes in the interference pattern of two condensates made of fermionic-atom dimers. These modes, which result from fermion exchanges between condensates, constitute a striking signature of the dimer composite nature. From the 2-coboson spatial correlation function, that we derive analytically, and the Shiva diagrams that visualize many-body effects specific to composite bosons, we identify the physical origin of these high frequency modes and determine the conditions to see them experimentally by using bound fermionic-atom pairs trapped on optical lattice sites. The dimer granularity which appears in these modes comes from Pauli blocking that prevents two dimers to be located at the same lattice site.

74 ATOMIC AND MOLECULAR PHYSICS↗
NASA NTRSDate not supplied

Mining the Gravity Mutants of Arabidopsis

Gravity mutants are a valuable resource for understanding gravity perception, signaling, and response in plants. A review of 190 publications resulted in a list of 97 loci with mutations that caused a gravitropic phenotype. While all these mutants show some form of gravity phenotype, several are also generally defective in growth. After removing these nonspecific mutants, 76 loci were deemed to have true gravity mutants. The gene list was then used to create a sortable database containing key factors of gravity signaling as well as data on methodologies and the development of mutant lines. Indexing this database has allowed us to pull out trends that were not visible in individual publications. For example, mutants that are unable to rearrange starch statoliths make up a larger proportion of the described inflorescence stems mutants than any other organ. Comparing these statolith mutants across organs shows that root and inflorescence stems consistently display different phenotypes for the same class of defect. The more severe gravity defects are most commonly described in root tissue while other tissues are more likely to show only a delayed or reduced response to gravity. The experience of members of the GeneLab plant Analytics Working Group (AWG) in data visualization and gene mapping have sparked new ideas for utilizing this database. Knowledge of shared traits, mutant development, and growth can provide a new resource for the production of seed lines specialized for their response to gravity.

gravitropism↗
DOE OSTI2019

Exploration and Analysis of Legacy Data at the Hanford Site Using PHOENIX - 19044

Radioactive contaminants pose risks to human health and the environment. These risks are influenced by factors such as disposal/release and transport mechanisms, location in the environment, potential exposure receptors, and the presence of comingled contaminants. Understanding the behavior, transport, and distribution of radionuclides in the environment is essential to facilitating risk-informed decision-making related to remedial design, action, and monitoring. These decisions are based on significant amounts of complex data that must be accessed, integrated, and analyzed to effectively evaluate data and formulate appropriate conclusions and recommendations. Often, data volume, complexity, and legacy access issues pose severe challenges for analysts, regulators, and stakeholders interested in evaluating scientific data to support decision-making. To address these challenges at the U.S. Department of Energy Hanford Site, Pacific Northwest National Laboratory (PNNL) has developed PHOENIX (PNNL-Hanford Online Environmental Information exchange) to facilitate risk-informed decision-making by streamlining investigative and analytical processes through the integration and visualization of previously isolated datasets created under distinct regulatory or operational regimes, each serving a specific purpose. With the large volume of data dispersed across many Hanford environmental databases, finding the correct sources of relevant data, accessing them, and relating them in a meaningful way can prove challenging and time consuming. By analyzing Hanford databases, performing substantial optimization using modern data processing methods and developing extensive queries on the refactored data, PHOENIX enables users to access, integrate, display, visualize, and retrieve data that would have been historically unfeasible to examine. The data and information accessible through PHOENIX help inform remediation-related assessments and evaluations, predict and quantify the risks that radioactive and chemical contaminants pose to human health and the environment, and communicate this information to decision makers responsible for risk-based remediation actions. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗