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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 1,297 records · Page 72
All sourcesNASA NTRSDOE OSTI
NASA NTRS1997

Multitemporal and Multiscaled Fractal Analysis of Landsat Satellite Data Using the Image Characterization and Modeling System (ICAMS)

The Image Characterization And Modeling System (ICAMS) is a public domain software package that is designed to provide scientists with innovative spatial analytical tools to visualize, measure, and characterize landscape patterns so that environmental conditions or processes can be assessed and monitored more effectively. In this study ICAMS has been used to evaluate how changes in fractal dimension, as a landscape characterization index, and resolution, are related to differences in Landsat images collected at different dates for the same area. Landsat Thematic Mapper (TM) data obtained in May and August 1993 over a portion of the Great Basin Desert in eastern Nevada were used for analysis. These data represent contrasting periods of peak "green-up" and "dry-down" for the study area. The TM data sets were converted into Normalized Difference Vegetation Index (NDVI) images to expedite analysis of differences in fractal dimension between the two dates. These NDVI images were also resampled to resolutions of 60, 120, 240, 480, and 960 meters from the original 30 meter pixel size, to permit an assessment of how fractal dimension varies with spatial resolution. Tests of fractal dimension for two dates at various pixel resolutions show that the D values in the August image become increasingly more complex as pixel size increases to 480 meters. The D values in the May image show an even more complex relationship to pixel size than that expressed in the August image. Fractal dimension for a difference image computed for the May and August dates increase with pixel size up to a resolution of 120 meters, and then decline with increasing pixel size. This means that the greatest complexity in the difference images occur around a resolution of 120 meters, which is analogous to the operational domain of changes in vegetation and snow cover that constitute differences between the two dates.

Quattrochi, Dale A.↗
NASA NTRS2015

Online Tools for Uncovering Data Quality (DQ) Issues in Satellite-Based Global Precipitation Products

Data quality (DQ) has many attributes or facets (i.e., errors, biases, systematic differences, uncertainties, benchmark, false trends, false alarm ratio, etc.)Sources can be complicated (measurements, environmental conditions, surface types, algorithms, etc.) and difficult to be identified especially for multi-sensor and multi-satellite products with bias correction (TMPA, IMERG, etc.) How to obtain DQ info fast and easily, especially quantified info in ROI Existing parameters (random error), literature, DIY, etc.How to apply the knowledge in research and applications.Here, we focus on online systems for integration of products and parameters, visualization and analysis as well as investigation and extraction of DQ information.

precipitation↗
DOE OSTI2020

Database Management Module Framework for Dynamic Contingency Analysis and Visualization

The Dynamic Contingency Analysis Tool (DCAT) is being developed to mimic the response of generation dynamics, protection, and load components to extreme contingencies in power systems. Currently, DCAT generates a huge data set, with the analysis results stored in multiple subfolders using a great many files in different formats (power flow cases, time series, figures, spreadsheets). To help power system engineers thoroughly understand and analyze system behavior under many scenarios and contingencies, we developed a database management module (DBM) that enables future integration of DCAT with industry-grade Big Data analytical and interactive visualization platforms. In this paper, we demonstrate the DBM framework with interactive analytics and visualization for DCAT on the synthetic South Carolina 500-bus power system model using hurricane contingencies that capture possibilities for an extreme contingency. DCAT’s advanced data management and interactive visualization can help planning engineers to visually explore and analyze system behavior, all in one view.

Cascading, dynamic simulations, database managemen↗
NASA NTRS1991

Improved visualization of flow field measurements

A capability is proposed that makes it feasible to apply to measured flow field data the visualization tools developed to display numerical solutions for computational fluid dynamic problems. The measurement monitor surface (MMS) methodology was used for the analysis of flow field measurements within a low-aspect-ratio transonic axial-flow fan rotor acquired with two-dimensional laser anemometry. It is shown that the MMS method may be utilized to generate input for the multidimensional processing and analytical tools developed for numerical flow field simulation data. Thus an experimenter utilizing an interactive graphics program could illustrate scalar quantities such as Mach number by profiles, contour lines, carpet plots, and surfaces employing various color intensities. Also, flow directionality can be shown by the display of vector fields and particle traces.

Miles, Jeffrey Hilton↗
DOE OSTI2022

Accelerated Probabilistic Marching Cubes by Deep Learning for Time-Varying Scalar Ensembles

Visualizing the uncertainty of ensemble simulations is challenging due to the large size and multivariate and temporal features of en-semble data sets. One popular approach to studying the uncertainty of ensembles is analyzing the positional uncertainty of the level sets. Probabilistic marching cubes is a technique that performs Monte Carlo sampling of multivariate Gaussian noise distributions for positional uncertainty visualization of level sets. However, the technique suffers from high computational time, making interactive visualization and analysis impossible to achieve. This paper introduces a deep-learning-based approach to learning the level-set uncertainty for two-dimensional ensemble data with a multivariate Gaussian noise assumption. We train the model using the first few time steps from time-varying ensemble data in our workflow. We demonstrate that our trained model accurately infers uncertainty in level sets for new time steps and is up to 170X faster than that of the original probabilistic model with serial computation and 10X faster than that of the original parallel computation.

Han, Mengjiao↗
NASA NTRS2024

Celestial Mapping System Videos

The Celestial Mapping System (CMS) is a software platform to generate virtual 3D globes for celestial bodies within our solar system. Multiple planetary data layers can be added to the virtual globe to provide visualization of high-resolution imagery and elevation data, which enables precise measurements, tools for analytical capabilities and a broad range of other functionalities to assist planetary scientists and mission planners. Third-party planetary data can be ingested into CMS with minimal effort. The present focus of CMS is on developing lunar mapping tools to provide features such as: 3D first person view with zoom and navigational capabilities, realistic terrain visualization based on LRO data, measurement tools, Apollo, CLPS and international mission landing site annotations, 3D Models, stereoscopic view, terrain profiling, line of sight analysis, sunlight shading and many more. The application has been developed to provide situational and domain awareness on the Lunar surface, planning capabilities for equipment placement and traverse path optimization.

Mapping↗
DOE OSTI2018

Using Stage Level Microseismic Analysis to Gain Insight into Fracture Efficiency and Completion Effectiveness

Microseismic event density heat maps at sequential time intervals during the treatment of individual completion stages have been developed to better understand fracture behavior on a stage level. Animating these heat maps through time on a single stage provides fascinating visual insights into the dynamic sequencing of populations of events, event timing and their likely genesis, providing a new way of visualizing and interpreting microseismic data sets. This technique leverages heat-map benefits from URTEC 2674376, excluding microseismic event clusters that may obscure or skew statistical analysis of the event densities, thus allowing for more accurate assessment of geologic features, stimulated rock volume, near-field concentration of events due to varying cluster spacing, fracture efficiency and stress shadowing. Far-field microseismic events prior to ramp up of treatment pressure are clearly indicated from this technique that cannot be observed with standard heat maps with certain completion designs. Unambiguous changes in microseismic event character from these far-field pre-ramp up events to those near-field events occurring at the onset of pressure are also observed. Applying a stage by stage approach on packages of wells and different locations provides robust statistical conclusions pertaining to reservoir behavior during well completion.

Wang, Iris↗
NASA NTRSDate not supplied

GeneLab: Current and Future Omics Data Integration Between Space Biology and HRP

For the past five years, the Biological and Physical Sciences Division has pioneered Open Science in Space Biology by funding the NASA GeneLab project. Along with the Ames Life Sciences Data Archive, GeneLab has quickly become the world leader in archiving and scientifically curating spaceflight and spaceflight relevant multi-omics data. Specifically, the GeneLab Data System has become a full enterprise solution providing advanced mining capabilities, several application programming interfaces for data federation and machine learning approaches, and delivering to the world an analytical and visualization platform which has enabled collaboration within the scientific community. Over the past three years, large meta-analysis and modeling studies have been published by the GeneLab Analysis Working Groups (AWGs), which are comprised of ~200 volunteer scientists. One natural extension of GeneLab data reuse has recently turned towards linking animal data with human data, which is the next necessary step to further validate animal models for inferring biological risks to humans conducting LEO, lunar or Martian missions. As such, data from the Human Research Program are an essential component of GeneLab and ALSDA. At the moment, simulated space radiation experiments conducted at Brookhaven National Laboratory make the most of HRP GeneLab data, and the scientific community has been eager to also link their animal spaceflight results to actual Astronaut data and human analog data. We will discuss further the current status of knowledge and future approaches to accelerate our basics understanding of the impact of space stressors on humans using latest omics technology.

omics↗
DOE OSTI2024

Automated pipeline processing X-ray diffraction data from dynamic compression experiments on the Extreme Conditions Beamline of PETRA III

Presented and discussed here is the implementation of a software solution that provides prompt X-ray diffraction data analysis during fast dynamic compression experiments conducted within the dynamic diamond anvil cell technique. It includes efficient data collection, streaming of data and metadata to a high-performance cluster (HPC), fast azimuthal data integration on the cluster, and tools for controlling the data processing steps and visualizing the data using the DIOPTAS software package. This data processing pipeline is invaluable for a great number of studies. The potential of the pipeline is illustrated with two examples of data collected on ammonia–water mixtures and multiphase mineral assemblies under high pressure. The pipeline is designed to be generic in nature and could be readily adapted to provide rapid feedback for many other X-ray diffraction techniques, e.g. large-volume press studies, in situ stress/strain studies, phase transformation studies, chemical reactions studied with high-resolution diffraction etc.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Energy Modeling in Urban Districts: Forecast of Multi-Sector Energy Use and GHG Emissions

This document reports the findings of the energy use and greenhouse gases (GHG) emissions model loosely based on three districts in the San Francisco Bay Area, District A, District B, and District C. Modeling platforms exist for city energy benchmarking, inventorying, and GHG emissions forecasting and planning. However, the wide variety and features of today’s tools, their focus on a sub-set or snapshot data from various energy generation and consumption sectors, and the fact that many of them are not open data models, create sub-optimal environments for the energy analysis districts are seeking to conduct. Hence, we have developed a new software tool with customized data and dynamic visualization; DEPICT (Decision-support and Emissions Prediction Interactive Cities Tool) to obtain energy and emissions forecasts at different stages of the districts’ build-out by varying selected design parameters. This report presents the methodology and framework we have developed to estimate whole district emissions and details the results by district, with the objective of finding insights into the main sources of emissions, and the available levers to reduce them efficiently. This document details the impact of each emissions mitigation measure investigated, along with the assumption and models that were used to reach these values

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Integrated Research Infrastructure Architecture Blueprint Activity (Final Report 2023)

The complexity of scientific pursuits is increasing rapidly with aspects that require dynamic integration of experiment, observation, theory, modeling, simulation, visualization, machine learning (ML), artificial intelligence (AI), and analysis. Research projects across the Department of Energy (DOE) are increasingly data and compute intensive. Innovative research teams are accelerating the pace of discovery by using high-performance computational and data tools in their research workflows and leveraging multiple research infrastructures. Additionally, several recent high-level U.S. government reports underscore the necessity of a new advanced computing ecosystem for international competitiveness and national security. International competitors are moving forward with major research infrastructure integration efforts that seek to capture a competitive advantage in the global innovation race. Owing to its unparalleled constellation of world-class experimental and observational facilities and high-performance and extreme-scale computational, data, and networking infrastructure, DOE is positioned to be a global leader in this new era of integrated science. However, this new integration paradigm will demand continuing evolution to ensure the U.S. remains a global leader in research and innovation. The DOE Office of Science (SC) has seized on the strategic importance of integration and has adopted a vision for Integrated Research Infrastructure (IRI): To empower researchers to meld DOE’s world-class research tools, infrastructure, and user facilities seamlessly and securely in novel ways to radically accelerate discovery and innovation. To respond to the evolving computational requirements of research and the competitive international innovation landscape, experimental facilities could be connected with high performance computing resources for near real-time analysis, and resources should be provided for merging enormous and diverse data for AI/ML techniques and analysis.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1978

An analysis of flight data from aircraft landings with and without the aid of a painted diamond on the same runway

The usefulness of a painted diamond on a runway as a visual aid to perform safe landings of aircraft was studied. Flight data on glideslope intercepts, flight path elevation angles, and touchdown distances were collected and analyzed. It is concluded that an appropriately painted diamond on a runway has the potential of providing glideslope information for the light weight class of general aviation aircraft. This conclusion holds irrespective of the differences in landing techniques used by the pilots.

Swaroop, R.↗
NASA NTRS1984

Software used with the flux mapper at the solar parabolic dish test site

Software for data archiving and data display was developed for use on a Digital Equipment Corporation (DEC) PDP-11/34A minicomputer for use with the JPL-designed flux mapper. The flux mapper is a two-dimensional, high radiant energy scanning device designed to measure radiant flux energies expected at the focal point of solar parabolic dish concentrators. Interfacing to the DEC equipment was accomplished by standard RS-232C serial lines. The design of the software was dicated by design constraints of the flux-mapper controller. Early attemps at data acquisition from the flux-mapper controller were not without difficulty. Time and personnel limitations result in an alternative method of data recording at the test site with subsequent analysis accomplished at a data evaluation location at some later time. Software for plotting was also written to better visualize the flux patterns. Recommendations for future alternative development are discussed. A listing of the programs used in the anaysis is included in an appendix.

Miyazono, C.↗
NASA NTRS1992

An experimental/computational study of sharp fin induced shock wave/turbulent boundary layer interactions at Mach 5 - Experimental results

A combined experimental/computational study has been performed of sharp fin induced shock wave/turbulent boundary layer interactions at Mach 5. The current paper focuses on the experiments and analysis of the results. The experimental data include mean surface heat transfer, mean surface pressure distributions and surface flow visualization for fin angles of attack of 6, 8, 10, 12, 14 and 16-degrees at Mach 5 under a moderately cooled wall condition. Comparisons between the results and correlations developed earlier show that Scuderi's correlation for the upstream influence angle (recast in a conical form) is superior to other such correlations in predicting the current results, that normal Mach number based correlations for peak pressure heat transfer are adequate and that the initial heat transfer peak can be predicted using pressure-interaction theory.

Rodi, Patrick E.↗
NASA NTRS1993

Adaptive laser link reconfiguration using constraint propagation

This paper describes Harris AI research performed on the Adaptive Link Reconfiguration (ALR) study for Rome Lab, and focuses on the application of constraint propagation to the problem of link reconfiguration for the proposed space based Strategic Defense System (SDS) Brilliant Pebbles (BP) communications system. According to the concept of operations at the time of the study, laser communications will exist between BP's and to ground entry points. Long-term links typical of RF transmission will not exist. This study addressed an initial implementation of BP's based on the Global Protection Against Limited Strikes (GPALS) SDI mission. The number of satellites and rings studied was representative of this problem. An orbital dynamics program was used to generate line-of-site data for the modeled architecture. This was input into a discrete event simulation implemented in the Harris developed COnstraint Propagation Expert System (COPES) Shell, developed initially on the Rome Lab BM/C3 study. Using a model of the network and several heuristics, the COPES shell was used to develop the Heuristic Adaptive Link Ordering (HALO) Algorithm to rank and order potential laser links according to probability of communication. A reduced set of links based on this ranking would then be used by a routing algorithm to select the next hop. This paper includes an overview of Constraint Propagation as an Artificial Intelligence technique and its embodiment in the COPES shell. It describes the design and implementation of both the simulation of the GPALS BP network and the HALO algorithm in COPES. This is described using a 59 Data Flow Diagram, State Transition Diagrams, and Structured English PDL. It describes a laser communications model and the heuristics involved in rank-ordering the potential communication links. The generation of simulation data is described along with its interface via COPES to the Harris developed View Net graphical tool for visual analysis of communications networks. Conclusions are presented, including a graphical analysis of results depicting the ordered set of links versus the set of all possible links based on the computed Bit Error Rate (BER). Finally, future research is discussed which includes enhancements to the HALO algorithm, network simulation, and the addition of an intelligent routing algorithm for BP.

Crone, M. S.↗
NASA NTRS2014

Space Suit Performance: Methods for Changing the Quality of Quantitative Data

NASA is currently designing a new space suit capable of working in deep space and on Mars. Designing a suit is very difficult and often requires trade‐offs between performance, cost, mass, and system complexity. To verify that new suits will enable astronauts to perform to their maximum capacity, prototype suits must be built and tested with human subjects. However, engineers and flight surgeons often have difficulty understanding and applying traditional representations of human data without training. To overcome these challenges, NASA is developing modern simulation and analysis techniques that focus on 3D visualization. Early understanding of actual performance early on in the design cycle is extremely advantageous to increase performance capabilities, reduce the risk of injury, and reduce costs. The primary objective of this project was to test modern simulation and analysis techniques for evaluating the performance of a human operating in extra‐vehicular space suits.

Cowley, Matthew↗
NASA NTRS2018

Titan Trek and IcyMoons Trek: Two New Online NASA Visualization and Analysis Portals for Saturn's Moons

Saturn’s moons are the focus of two new online visualization and analysis tools produced by NASA. The Solar System Treks family of online portals provides a suite of interactive visualization and analysis tools. These enable mission planners, lunar scientists, engineers, students, and the general public to access mapped data products from past and current missions for a growing number of planetary bodies. They integrate data from a variety of instruments aboard a number of missions. This presentation will introduce two new portals in the Solar System Trek suite. Titan Trek highlights Saturn’s largest moon, and IcyMoons Trek features a number of Saturn’s other moons as studied by the Cassini mission.

Law, E.↗
NASA NTRSDate not supplied

Fluid for Thought: SLS Rocket Aerodynamics featuring Pressure Sensitive Paint

Combining computer vision algorithms, state-of-the-art high-speed cameras, pressure sensitive paint (PSP) and transonic wind tunnel facilities, teams at NASA and Boeing study unsteady pressure over the Space Launch System (SLS) rocket model with unprecedented temporal and spatial data resolution. Post-processing visualizes pressure fluctuations over a 3D model by converting intensity data from videos of the wind tunnel test. Additionally, data analysis creates predictions of buffet forcing and aeroacoustic activity over the rocket body with the accuracy of a CFD model! The development of the technique will revolutionize aerodynamics research and reveal uncharted insights into fluid behavior and vehicle performance, enhancing aerospace technology and design as they advance. The talk will focus on the impact of the PSP technique on the SLS design and other potential aerospace applications, as well as lay out the experimental process, from wind tunnel test to insights from the data analysis.

Lucy Zhonghui Tang↗