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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 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
NASA NTRS1995

Prototype Videodisk-Based Part-Task Thermal Imaging Trainer

Thermal images, or infrared images, are representations of the world based on heat, instead of visible light. Research has shown that the resulting thermal image results in perceptual differences leading to difficulties in interpretation (e.g., the determination of slope angle, concavity/convexity), or increased identification latencies. A joint research project between the United States (NASA and U.S. Army) and Israel (Ministry of Defense and Israel Air Force) has resulted in the development of a prototype part-task trainer for the acquisition of perceptual skills associated with thermal imaging usage. This prototype system is videodisk-based under computer control, using recordings of thermal images. A lesson section introduces declarative knowledge, in which the basic physics and heuristics of thermal imagery are taught. An exercise section teaches procedural knowledge, with the user viewing dynamic, actual imagery, with an interactive detection/location determination task. The general philosophy and design of the trainer will be demonstrated.

Brickner, Michael S.↗
NASA NTRSDate not supplied

Expanding NeMO-Net Machine Learning Capabilities for Citizen Science

NASA NeMO-Net, the neural multi-modal observation and training network for global coral reef assessment, is an open-source deep convolutional neural network and interactive active learning training software aiming to accurately assess the present and past dynamics of coral reef ecosystems through determination of percent living cover and morphology as well as mapping of spatial distribution. We present an interactive citizen science video game, released this April, for desktop and iOS devices where users interactively label morphology classifications over mm-scale 3D coral reef imagery captured using diver photomosaic imagery, the UAV enabled NASA FluidCam instrument, and satellite datasets. To date, the application has had over 40,000 downloads and over 60,000 unique coral reef classifications, each filtered through a user-based rating and expert evaluation system. We also present results from NeMO-Net’s convolutional neural network (CNN) models used to semantically segment 2D satellite imagery as well as projections of 3D coral reconstructions using user input data as training datasets. Fusing datasets using machine learning from multiple remote sensing platforms presents novel methodologies for assessing the health of coral ecosystems, which are critically endangered by a changing climate. In partnering with Mission Blue, the National Oceanic and Atmospheric Administration (NOAA), and the Living Oceans Foundation (LOF), NeMO-Net leverages an international consortium of subject matter experts to provide both proper training for citizen scientists and the generation of a labeled datasets to ingest into machine learning algorithms for global coral reef identification.

NeMO-Net↗
NASA NTRSDate not supplied

Expanding NeMO-Net Machine Learning Capabilities for Citizen Science

NASA NeMO-Net, the neural multi-modal observation and training network for global coral reef assessment, is an open-source deep convolutional neural network and interactive active learning training software aiming to accurately assess the present and past dynamics of coral reef ecosystems through determination of percent living cover and morphology as well as mapping of spatial distribution. We present an interactive citizen science video game, released this April, for desktop and iOS devices where users interactively label morphology classifications over mm-scale 3D coral reef imagery captured using diver photomosaic imagery, the UAV enabled NASA FluidCam instrument, and satellite datasets. To date, the application has had over 40,000 downloads and over60,000 unique coral reef classifications, each filtered through a user-based rating and expert evaluation system. We also present results from NeMO-Net’s convolutional neural network (CNN) models used to semantically segment 2D satellite imagery as well as projections of 3D coral reconstructions using user input data as training datasets. Fusing datasets using machine learning from multiple remote sensing platforms presents novel methodologies for assessing the health of coral ecosystems, which are critically endangered by a changing climate. In partnering with Mission Blue, the National Oceanic and Atmospheric Administration (NOAA), and the Living Oceans Foundation (LOF), NeMO-Net leverages an international consortium of subject matter experts to provide both proper training for citizen scientists and the generation of a labeled datasets to ingest into machine learning algorithms for global coral reef identification.

NeMO-Net↗
NASA NTRS1972

Systems identification using a modified Newton-Raphson method: A FORTRAN program

A FORTRAN program is offered which computes a maximum likelihood estimate of the parameters of any linear, constant coefficient, state space model. For the case considered, the maximum likelihood estimate can be identical to that which minimizes simultaneously the weighted mean square difference between the computed and measured response of a system and the weighted square of the difference between the estimated and a priori parameter values. A modified Newton-Raphson or quasilinearization method is used to perform the minimization which typically requires several iterations. A starting technique is used which insures convergence for any initial values of the unknown parameters. The program and its operation are described in sufficient detail to enable the user to apply the program to his particular problem with a minimum of difficulty.

Taylor, L. W., Jr.↗
DOE OSTI2024

Weather radar utility in hazard detection and response

Publicly accessible weather radar data have significant capabilities for meteorological measurements and predictions and, further, have the potential to measure nonmeteorological events that include smoke, ash, and debris plumes as well as explosions. The ability to identify and track nonmeteorological events can be of assistance in emergency response, hazard mitigation, and related activities in locations where radar coverage both exists and is recorded and accessible to the user. Here, in this study, events from multiple locations in the United States that are reported in news outlets are assessed using a manual inspection process of Level 2 weather radar data to identify anthropogenic and nonbiological returns. Explosive events are also identified, and a large high-altitude debris cloud from the intentional destruction of the SpaceX Starship is tracked across a wide area. Finally, future efforts using a machine learning model are discussed as a means of automating the process and potentially enabling near-real-time nonmeteorological event identification in the same areas where the data are accessible. Using weather radar data can be a valuable new tool for Department of Defense systems to aid in military awareness, and for interagency emergency response and forensic mission experts to consider national weather service data in their mission profiles. Radar data can be effective in detecting several common types of emergencies and inform and aid response personnel.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRSDate not supplied

Overview of the NASA Earth Action Strategies Wildland Fire Initiative

As part of NASA’s new Earth Action strategy, the Wildland Fire initiative was established, which includes both the NASA Wildland Fire Program (WFP) and the FireSense project. NASA has over 50 years of experience generating data and technology to enhance fire science and operational management. The WFP’s mission is threefold: 1) assemble communities of practice through collaborative efforts with government, academia, and the private sector; 2) co-develop knowledge and applications with relevant partners and stakeholders in the wildfire community; and 3) improve wildland fire management through the transitioning of NASA data, technology, tools, and science to stakeholder organizations. The WFP is focusing on supporting proactive fire management, including situational awareness, preparedness, and risk mitigation. This will be accomplished through selected projects that identify management challenges, relevant to partners and end users, and the NASA data that will be utilized to deliver innovative solutions to enhance the management of wildland fires. Examples include: i) investigation of evaporative stress from OpenET to help predict the risk of wildfire occurrence in watersheds; ii) incorporation of space based LiDAR for the generation of 3-dimensional forest fuel metrics, used to improve wildfire risk and behavior models; iii) integration of global, multi-platform geostationary active-fire data in near-real-time into NASA’s Fire Information for Resource Management System (FIRMS); and iv) identification of post-fire ecohydrological conditions using thermal, multispectral, synthetic aperture radar (SAR), and hyperspectral remotely-sensed data to improve flood hazard forecast models. The FireSense project is a US-focused 5-year project that will focus on delivering NASA’s unique Earth science and technological capabilities to operational agencies, striving towards enhancing fire fighting and air quality management. The project will include airborne campaigns and new technology that will likely have global implications. Initial stakeholder engagement led FireSense to focus on four use-cases focused on the characterization and measurement of: (i) pre-fire fuels conditions, (ii) active fire-dynamics; (iii) post-fire impact and threats; and iv) air quality impacts and forecasting, each-developed with identified stakeholders.

Wildland Fire program↗
NASA NTRS2004

An Ontology for Requesting Distant Robotic Action: A Case Study in Naming and Action Identification for Planning on the Mars Exploration Rover Mission

This paper focuses on the development and use of the abbreviated names as well as an emergent ontology associated with making requests for action of a distant robotic rover during the 2003-2004 NASA Mars Exploration Rover (MER) mission, run by the Jet Propulsion Laboratory. The infancy of the domain of Martian telerobotic science, in which specialists request work from a rover moving through the landscape, as well as the need to consider the interdisciplinary teams involved in the work required an empirical approach. The formulation of this ontology is grounded in human behavior and work practice. The purpose of this paper is to identify general issues for an ontology of action (specifically for requests for action), while maintaining sensitivity to the users, tools and the work system within a specific technical domain. We found that this ontology of action must take into account a dynamic environment, changing in response to the movement of the rover, changes on the rover itself, as well as be responsive to the purposeful intent of the science requestors. Analysis of MER mission events demonstrates that the work practice and even robotic tool usage changes over time. Therefore, an ontology must adapt and represent both incremental change and revolutionary change, and the ontology can never be more than a partial agreement on the conceptualizations involved. Although examined in a rather unique technical domain, the general issues pertain to the control of any complex, distributed work system as well as the archival record of its accomplishments.

Wales, Roxana C.↗
NASA NTRS1983

User manual of the CATSS system (version 1.0) communication analysis tool for space station

The Communication Analysis Tool for the Space Station (CATSS) is a FORTRAN language software package capable of predicting the communications links performance for the Space Station (SS) communication and tracking (C & T) system. An interactive software package was currently developed to run on the DEC/VAX computers. The CATSS models and evaluates the various C & T links of the SS, which includes the modulation schemes such as Binary-Phase-Shift-Keying (BPSK), BPSK with Direct Sequence Spread Spectrum (PN/BPSK), and M-ary Frequency-Shift-Keying with Frequency Hopping (FH/MFSK). Optical Space Communication link is also included. CATSS is a C & T system engineering tool used to predict and analyze the system performance for different link environment. Identification of system weaknesses is achieved through evaluation of performance with varying system parameters. System tradeoff for different values of system parameters are made based on the performance prediction.

Tsang, C. S.↗
NASA NTRS2008

Services, Perspective and Directions of the Space Physics Data Facility

The multi-mission data and orbit services of NASA's Space Physics Data Facility (SPDF) project offer unique capabilities supporting science of the Heliophysics Great Observatory and that are highly complementary to other services now evolving in the international heliophysics data environment. The VSPO (Virtual Space Physics Observatory) service is an active portal to a wide rage of distributed data sources. CDAWeb (Coordinated Data Analysis Web) offers plots, listings and file downloads for current data from many missions across the boundaries of missions and instrument types. CDAWeb now includes extensive new data from STEREO and THEMIS, plus new ROCSAT IPEI data, the latest data from all four TIMED instruments and high-resolution data from all DE-2 experiments. SSCWeb, Helioweb and out 3D Animated Orbit Viewer (TIPSOD) provide position data and identification of spacecraft and ground conjunctions. OMNI Web, with its new extension to 1- and 5-minute resolution, provides interplanetary parameters at the Earth's bow shock. SPDF maintains NASA's CDF (Common Data Format) standard and a range of associated tools including format translation services. These capabilities are all now available through web services based APIs, one element in SPDF's ongoing work to enable heliophysics community development of Virtual discipline Observatories (e.g. VITMO). We will demonstrate out latest data and capabilities, review the lessons we continue to learn in what science users need and value in this class of services, and discuss out current thinking to the future role and appropriate focus of the SPDF effort in the evolving and increasingly distributed heliophysics data environment.

McGuire, Robert E.↗
DOE OSTI2025

Automated tabletop exfoliation and identification of monolayer graphene flakes

Over the past two decades, graphene has been intensively studied because of its remarkable mechanical, optical, and electronic properties. Initial studies were enabled by manual “Scotch Tape” exfoliation; nearly two decades later, this method is still widely used to obtain chemically pristine flakes of graphene and other 2D van der Waals materials. Unfortunately, the yield of large, pristine flakes with uniform thickness is inconsistent. Thus, significant time and effort are required to exfoliate and locate flakes suitable for fabricating multilayer van der Waals heterostructures. Here, we describe a relatively affordable tabletop device (the “eXfoliator”) that can reproducibly control key parameters and largely automate the exfoliation process. In a typical exfoliation run, the eXfoliator produces 3 or more large (≥ 400 μm 2 ) high-quality graphene monolayer flakes, allowing new users to produce such flakes at a rate comparable to manual exfoliation by an experienced user. Furthermore, we use an automated mapping system and a computer vision algorithm to locate candidate flakes. Our results provide a starting point for future research efforts to identify more precisely which parameters matter for the success of exfoliation and to optimize them.

47 OTHER INSTRUMENTATION↗
NASA NTRS2012

Social Semantics for an Effective Enterprise

An evolution of the Semantic Web, the Social Semantic Web (s2w), facilitates knowledge sharing with "useful information based on human contributions, which gets better as more people participate." The s2w reaches beyond the search box to move us from a collection of hyperlinked facts, to meaningful, real time context. When focused through the lens of Enterprise Search, the Social Semantic Web facilitates the fluid transition of meaningful business information from the source to the user. It is the confluence of human thought and computer processing structured with the iterative application of taxonomies, folksonomies, ontologies, and metadata schemas. The importance and nuances of human interaction are often deemphasized when focusing on automatic generation of semantic markup, which results in dissatisfied users and unrealized return on investment. Users consistently qualify the value of information sets through the act of selection, making them the de facto stakeholders of the Social Semantic Web. Employers are the ultimate beneficiaries of s2w utilization with a better informed, more decisive workforce; one not achieved with an IT miracle technology, but by improved human-computer interactions. Johnson Space Center Taxonomist Sarah Berndt and Mike Doane, principal owner of Term Management, LLC discuss the planning, development, and maintenance stages for components of a semantic system while emphasizing the necessity of a Social Semantic Web for the Enterprise. Identification of risks and variables associated with layering the successful implementation of a semantic system are also modeled.

Berndt, Sarah↗
NASA NTRS2018

Developing a Community of Practice for Applied Uses of Future PACE Data to Address Food Security Challenges

Ocean color satellite measurements have yielded valuable information about the base of the marine food web for over 20 years. The Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) mission is building an advanced spectrometer to further refine ecosystem monitoring. Higher spectral resolution data from PACE will enable identification of additional marine biological indicators and their response to multiple stressors to guide sustainable management. Seafood is an important source of protein for a significant number of people. Wild catches cannot match increasing demand and their sustainability is in question. Aquaculture is an ever more important industry to feed the world's population. We share early efforts to engage a community of practice around food security to increase satellite data product use in support of resource management, business decisions, and policy analysis. Understanding the needs of applied scientists as well as non-traditional users of satellite data early in the PACE mission process will improve planning and preparation for a broader user base and hopefully help to mitigate food insecurity.

Schollaert Uz, Stephanie↗
DOE OSTI2025

FIRM image analysis: A machine learning workflow for quantifying extracellular matrix components from electron microscopy images

The extracellular matrix (ECM) is a complex network of biomolecules that plays an integral role in the structure, processes, and signaling mechanisms of cells and tissues. Identifying and quantifying changes in these matrix components provides insight into the mechanisms behind specific tissue remodeling processes; however, quantifying these changes is challenging due to difficult imaging conditions, complexity of the ECM, and the subtlety of these changes. Current imaging techniques allow us to visualize these critical remodeling events and developments in image analysis have employed a combination of analysis software and machine learning techniques to improve the efficiency and accuracy with which features are measured. Although image analysis has seen much improvement in recent years, there has been no technique developed to address ambiguity in feature edges in electron microscopy images. Presented here is a new machine learning-based workflow for the analysis of microscopy images named FIRM (Feature Identification from Raw Microscopy) that uses a random forest classifier to identify ECM features of interest and generate binary segmentation masks for quantification with ImageJ-FIJI. FIRM performed with an F1 score of 0.794 and greater than 80% accuracy for number and size of features detected. FIRM had similar deviation from the ground truth in the number of identified fibrils, fibril size, and size distributions when compared to human analyses. The results suggest that FIRM performs as well as manual analysis and requires a fraction of the time. This analysis technique is more efficient, eliminates user bias, and can be easily optimized to identify a variety of features, making it useful for any discipline requiring image analysis.

Science & Technology - Other Topics↗
NASA NTRS2012

QuakeSim 2.0

QuakeSim 2.0 improves understanding of earthquake processes by providing modeling tools and integrating model applications and various heterogeneous data sources within a Web services environment. QuakeSim is a multisource, synergistic, data-intensive environment for modeling the behavior of earthquake faults individually, and as part of complex interacting systems. Remotely sensed geodetic data products may be explored, compared with faults and landscape features, mined by pattern analysis applications, and integrated with models and pattern analysis applications in a rich Web-based and visualization environment. Integration of heterogeneous data products with pattern informatics tools enables efficient development of models. Federated database components and visualization tools allow rapid exploration of large datasets, while pattern informatics enables identification of subtle, but important, features in large data sets. QuakeSim is valuable for earthquake investigations and modeling in its current state, and also serves as a prototype and nucleus for broader systems under development. The framework provides access to physics-based simulation tools that model the earthquake cycle and related crustal deformation. Spaceborne GPS and Inter ferometric Synthetic Aperture (InSAR) data provide information on near-term crustal deformation, while paleoseismic geologic data provide longerterm information on earthquake fault processes. These data sources are integrated into QuakeSim's QuakeTables database system, and are accessible by users or various model applications. UAVSAR repeat pass interferometry data products are added to the QuakeTables database, and are available through a browseable map interface or Representational State Transfer (REST) interfaces. Model applications can retrieve data from Quake Tables, or from third-party GPS velocity data services; alternatively, users can manually input parameters into the models. Pattern analysis of GPS and seismicity data has proved useful for mid-term forecasting of earthquakes, and for detecting subtle changes in crustal deformation. The GPS time series analysis has also proved useful as a data-quality tool, enabling the discovery of station anomalies and data processing and distribution errors. Improved visualization tools enable more efficient data exploration and understanding. Tools provide flexibility to science users for exploring data in new ways through download links, but also facilitate standard, intuitive, and routine uses for science users and end users such as emergency responders.

Donnellan, Andrea↗
NASA NTRS1976

Evaluation of LANDSAT-1 image applications to geologic mapping, structural analysis and mineral resource inventory of South America with special emphasis on the Andes Mountain region

The author has identified the following significant results. The discovery of copper mineralization along a lineament mapped in Area 7 (La Paz) has lent credence to the use of LANDSAT 1 data as a basic step in mineral exploration. In Area 9 (Copiapo Region), a number of lineaments were found to be associated with the largest copper deposits of the region. In Area 12 (Magallanes), the identification of what is believed to be a tertiary basin from LANDSAT 1 data has resulted in a new area for petroleum exploration. Band 7 images, as black and white transparencies, were found to be the most useful for geologic interpretation in both tropical vegetated areas and desert regions. Color composites made by the diazochrome process, chromaline process, and from color additive viewers provided additional information. Mosaics of LANDSAT 1 data covering 4 x 6 degrees of latitude and longitude compiled at the 1:1,000,000 scale were found to be an ideal size and format for most users.

Carter, W. D.↗
NASA NTRS2021

PIXLISE-C: Exploring The Data Analysis Needs of NASA Scientists for Mineral Identification

NASA JPL scientists working on the micro x-ray fluorescence (microXRF) spectroscopy data collected from Mars surface perform data analysis to look for signs of past microbial life on Mars. Their data analysis workflow mainly involves identifying mineral com- pounds through the element abundance in spatially distributed data points. Working with the NASA JPL team, we identified pain points and needs to further develop their existing data visualization and analysis tool. Specifically, the team desired improvements for the process of creating and interpreting mineral composition groups. To address this problem, we developed an interactive tool that enables scientists to (1) cluster the data using either manual lasso-tool selection or through various machine learning clustering algorithms, and (2) compare the clusters and individual data points to make informed decisions about mineral compositions. Our preliminary tool supports a hybrid data analysis workflow where the user can manually refine the machine-generated clusters.

Davidoff, Scott↗
DOE OSTI2025

PERCEPTIVE: an R shiny $\underline{p}$ipelin$\underline{e}$ for the p$\underline{r}$edi$\underline{c}$tion of $\underline{ep}$igenetic modula$\underline{t}$ors $\underline{i}$n no$\underline{v}$el sp$\underline{e}$cies

Epigenetic processes are central to regulating gene expression, genome stability, and metabolic function across the tree of life; yet, their roles remain underexplored in microalgae, especially as new species continue to be identified and characterized. This is likely due to the cumbersome nature and species-dependent attributes of epigenetic wet-lab methodologies, which preclude the rapid identification of epigenetic modifications and modulators. However, there is high conservation of epigenetic processes from budding yeast to humans; in many cases, one may infer how behavior and function are epigenetically regulated in novel species by identifying epigenetic modulators, or the proteins responsible for conferring epigenetic modifications. Here, to this end, we have developed a graphical software package, titled PERCEPTIVE (pipeline for the prediction of epigenetic modulators in novel species). This platform solely uses the genomic sequence of an algal species, and preexisting information from other model organisms, to predict the epigenetic modulators and associated modifications in algae. Predictions are presented to the user in a graphical interface, which provides literature-based interpretation of results, enabling users to quickly understand potential epigenetic processes in their algal species of interest and plan follow-up experiments. To test PERCEPTIVE, we predicted epigenetic modulators in several feedstock candidate algae species. To validate these predictions, wet-lab studies were performed, including mass spectrometry; these results underscore the high accuracy of PERCEPTIVE predictions. Overall, PERCEPTIVE represents a powerful in silico tool for the research and manipulation of algal species, which does not require a priori knowledge of epigenetics and is accessible to a broad set of investigators.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2019

WWAO-WSWC Workshop Report 2019 Final

EXECUTIVE SUMMARY The Western States Water Council (WSWC) and the NASA Western Water Applications Office (WWAO) hosted a joint workshop on technology transfer for water management in the Western U.S. The goals of the workshop were to understand how different agencies approach the technology transfer and research to operations (R2O) process, identify best practices, and discuss existing barriers to successful technology infusion into operational water resource management systems at the state and federal level. The workshop took place August 7-9, 2019 in Irvine, CA. Key outcomes of the meeting include the following:• U.S. Rep. Grace Napolitano provided opening remarks for the workshop, where she highlighted the critical value of water data and the importance of collaboration between state and federal agencies in working to advance the use of water data in water management, planning and policy. • A total of 33 participants (including remote participants) were part of the workshop. They included principal investigators and project teams supported by NASA (Cyanobacteria Assessment Network, Evapotranspiration for Western States, Evaporative Stress Index, the Airborne Snow Observatory, Satellite-based Snow Water Equivalent in the Sierra Nevadas, and Fallowed Area Mapping) as well as representatives from federal (USGS, NOAA, USBR, EPA) and state (CA, WY, OR, NE) agency partners. • One main outcome of the meeting was the consensus that successful transitions of new applications and new technologies into operations require careful planning, effective communication within and across institutions, resources and considerable time investments. In addition, there was broad agreement that significant lead time is often required to allow for identification of financial and technical resources to sustain operational use of new data, information and tools.• The meeting included remarks from U.S. Rep. Napolitano and discussions during presentations and breakout groups about key opportunities to develop best practices and streamline the technology transfer process. • For example, one key set of best practices that emerged revolved around the the importance of building trust and establishing clear lines of communication between the research and operational institutions. The conversations led to defining two key components of trust-building. The first aspect is purely technical. It requires effectively demonstrating that the proposed application meets the end user’s needs in terms of accuracy, format, resolution, latency, metadata and documentation. The second aspect of building trust involves developing sustained, productive and mutually-beneficial relationships with the partner operational agency. The best practices presented here span both the technical as well as the relational aspects of cultivating trust. • This workshop served as a first step in developing a broader community discussion around R2O in western water management. Many of the best practices and lessons learned described in this report represent starting places for action within the WWAO, WSWC and our colleagues’ institutions. • Effective implementation of the best practices that emerged from this workshop will require sustained investments of time, resources and transition planning. In recognition of this, the WSWC and the WWAO proposed continuation of discussions begun at the workshop through a series of semi-annual or annual workshops.

Wilardson, Tony↗