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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 1,063 records · Page 59
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

The Medical Science DMZ

Objective We describe use cases and an institutional reference architecture for maintaining high-capacity, data-intensive network flows (e.g., 10, 40, 100 Gbpsþ) in a scientific, medical context while still adhering to security and privacy laws and regulations. Materials and Methods High-end networking, packet filter firewalls, network intrusion detection systems. Results We describe a “Medical Science DMZ” concept as an option for secure, high-volume transport of large, sensitive data sets between research institutions over national research networks. Discussion The exponentially increasing amounts of “omics” data, the rapid increase of high-quality imaging, and other rapidly growing clinical data sets have resulted in the rise of biomedical research “big data.” The storage, analysis, and network resources required to process these data and integrate them into patient diagnoses and treatments have grown to scales that strain the capabilities of academic health centers. Some data are not generated locally and cannot be sustained locally, and shared data repositories such as those provided by the National Library of Medicine, the National Cancer Institute, and international partners such as the European Bioinformatics Institute are rapidly growing. The ability to store and compute using these data must therefore be addressed by a combination of local, national, and industry resources that exchange large data sets. Maintaining data-intensive flows that comply with HIPAA and other regulations presents a new challenge for biomedical research. Recognizing this, we describe a strategy that marries performance and security by borrowing from and redefining the concept of a “Science DMZ”—a framework that is used in physical sciences and engineering research to manage high-capacity data flows. Conclusion By implementing a Medical Science DMZ architecture, biomedical researchers can leverage the scale provided by high-performance computer and cloud storage facilities and national high-speed research networks while preserving privacy and meeting regulatory requirements.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Procedure for locating oil and gas wells in the Appalachian Basin

Locating undocumented (or poorly documented) oil and gas wells for environmental assessment is often difficult. Remnant features that confirm the presence of a well (intact casing/wellhead, well bore, etc.) are typically less than a meter in size and often are obscured from direct observation on the ground or from the air (by dense vegetation, for example). To efficiently find such features, it is useful to first systematically compile publicly available digital data at progressively smaller scales prior to embarking on field campaigns. Further, the information presented here describes the procedure developed and used by the U.S. Department of Energy's National Energy Technology Laboratory to locate potential oil and gas well sites for follow-up field verification and characterization. Digital data are first compiled from national and state resources such as well location/production databases, historical topographic maps, historical aerial photographs, and LiDAR data. Although each data set is likely to be incomplete or inaccurate to some extent, combining the data resources using geographic information system technology can generate potential well site targets with a higher degree of confidence, which improves the efficiency of fieldwork activities. This workflow was developed in the Appalachian Basin region, and although certain aspects may be unique, the general process would be applicable to locating undocumented wells in other regions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

Performance analysis of data intensive cloud systems based on data management and replication: a survey

As we delve deeper into the ‘Digital Age’, we witness an explosive growth in the volume, velocity, and variety of the data available on the Internet. For example, in 2012 about 2.5 quintillion bytes of data was created on a daily basis that originated from myriad of sources and applications including mobiledevices, sensors, individual archives, social networks, Internet of Things, enterprises, cameras, software logs, etc. Such ‘Data Explosions’ has led to one of the most challenging research issues of the current Information and Communication Technology era: how to optimally manage (e.g., store, replicated, filter, and the like) such large amount of data and identify new ways to analyze large amounts of data for unlocking information. It is clear that such large data streams cannot be managed by setting up on-premises enterprise database systems as it leads to a large up-front cost in buying and administering the hardware and software systems. Therefore, next generation data management systems must be deployed on cloud. The cloud computing paradigm provides scalable and elastic resources, such as data and services accessible over the Internet Every Cloud Service Provider must assure that data is efficiently processed and distributed in a way that does not compromise end-users’ Quality of Service (QoS) in terms of data availability, data search delay, data analysis delay, and the like. In the aforementioned perspective, data replication is used in the cloud for improving the performance (e.g., read and write delay) of applications that access data. Through replication a data intensive application or system can achieve high availability, better fault tolerance, and data recovery. In this paper, we survey data management and replication approaches (from 2007 to 2011) that are developed by both industrial and research communities. The focus of the survey is to discuss and characterize the existing approaches of data replication and management that tackle the resource usage and QoS provisioning with different levels of efficiencies. Moreover, the breakdown of both influential expressions (data replication and management) to provide different QoS attributes is deliberated. Furthermore, the performance advantages and disadvantages of data replication and management approaches in the cloud computing environments are analyzed. Open issues and future challenges related to data consistency, scalability, load balancing, processing and placement are also reported.

Malik, Saif Ur Rehman↗
DOE OSTI2013

Analysis of Gaps in Geothermal Exploration Data in the Western United States

The USGS Resource Assessment (Williams et al. 2008) outlined a mean 30 GW, of Undiscovered Hydrothermal Resource in the western U.S. One goal of the Geothermal Technology Office (GTO) is to accelerate the development of this undiscovered resource. To help guide its future data collection efforts, GTO funded a data gap analysis in FY2012 to identify high potential hydrothermal areas where critical data are needed. For the gap analysis, information was collected about existing data and data coverage maps were created with this information. Next, these maps were compared with the USGS resource potential maps to identify priority sites for exploration data collection. Though there are many types of data that can be used for hydrothermal exploration, five types of exploration data were targeted for this analysis. These data types were elected for their regional reconnaissance potential, and include many of the primary exploration echniques currently used by the geothermal industry. The data types include: 1) well data; 2) geologic maps; 3) fault maps; 4) geochemistry data; and 5) geophysical data. To determine data coverage, metadata for exploration data (including data type, data status, and coverage information) were collected and catalogued. Many industry, university, laboratory, and agency personnel were contacted in order to collect metadata for this effort. Data and metadata provided by the contributors to the National Geothermal Data System (NGDS) were also incorporated in the gap analysis. An online tool was developed to allow all geothermal data providers to directly add metadata themselves and view the results of the analys is via maps of data coverage in Geothermal Prospector (http://maps.nrel.gov/gt_prospector). A grid of the contiguous U.S. was created with 88,000 10-km by 10-km grid cells, and each cell was populated with the status of data availability corresponding to the five data types. Using these five data coverage maps and the USGS Resource Potential Map, sites were identified for future data collection efforts. These sites signify both that the USGS has indicated high favorability of occurrence of geothermal resources and that data gaps exist.

15 GEOTHERMAL ENERGY↗
DOE OSTI2020

An Evaluation of Advanced Tools for Distributed Wind Turbine Performance Estimation

We evaluate various classes of distributed wind turbine performance tools across two sites in the United States. The class of tools ranges from the simple mass conservation model to the coupled Reynolds-averaged Navier-Stokes model, all initiated by the WIND Toolkit data set. The resource estimation at the site is evaluated against measured data at the mast location. Taking a sample 100-kW wind turbine and constant losses, we evaluate Openwind, Continuum, and WindNinja tools and document annual energy production (AEP) and time-series statistics associated with the performance estimation of the wind turbine. Using a methodology that is consistent and unbiased across the three options currently available in the industry, we elaborate results at the two sample locations and discuss the probable sources of discrepancy in the AEP estimates. Two main sources of the discrepancy come from the input WIND Toolkit data and the spatial modeling techniques of the tools to capture atmospheric physics. The discussion includes additional values that these tools may bring into the energy assessment process to enhance the owners' confidence over the distributed wind power systems.

17 WIND ENERGY↗
NASA NTRS1973

Image data processing system requirements study. Volume 1: Analysis

Digital image processing, image recorders, high-density digital data recorders, and data system element processing for use in an Earth Resources Survey image data processing system are studied. Loading to various ERS systems is also estimated by simulation.

Honikman, T.↗
NASA NTRS1980

Applications of remote-sensing imagery

Compilation of reports discusses usefulness of aircraft and satellite data in land-development projects. Landsat and Earth Resources Technology Satellites data are available to general public. Much information on biological, geological, and hydrological features as well as land use can be determined by eye without sophisticated analyzers.

Hughes, T. H.↗
NASA NTRS1973

Interdisciplinary applications and interpretations of ERTS data within the Susquehanna River Basin; resources inventory, land use and pollution

The author has identified the following significant results. Identification and mapping of three major kinds of coal refuse targets based on spectral signatures in channels four through seven of the ERTS-1 MSS were conducted. Correlation of the placement of the coal refuse targets with an existing map of their location was accomplished. Digital processing of ERTS-1 data permitted identification of stripped areas including ones that are not discernible by visual analysis of ERTS imagery. Combined visual and digital techniques of analyzing ERTS-1 data for geologic formations have been tried on selected areas of Pennsylvania. Mapping of two major agriculture counties to show land forms, drainage patterns, water, and urban areas were made using positive transparencies of MSS data. Two frames of the same central Pennsylvania area were brought into registration by translation and then merged even though the frames were obtained 71 days apart.

Mcmurtry, G. J.↗
NASA NTRS2001

Microgravity Science Glovebox

The Microgravity Science Glovebox (MSG) is a versatile research facility designed to permit the flexibility of crew manipulated investigations on the International Space Station (ISS). The MSG configuration has been planned around the concept of an experimental workstation where a variety of experiments can be installed and operated in a fashion very similar to their operation in a ground-based laboratory. The approach has been to provide a large working volume with a significant set of power, data and imaging resources, all enclosed, but accessible by the crew through sealed glove ports. This arrangement allows the advantage of interactive experimentation without unduly compromising the experiment design with restrictions imposed by protective and containment challenges that normally arise in manned space-flight laboratories. In addition, the data and imaging resources allow cooperative monitoring of experiment progress between the crew and ground-based scientists. As ISS utilization evolves, the MSG is scheduled to become a major pathfinder for developing and exploiting the scientific advantages of truly enabling the coupling of experimentation in space with an evaluative response from the crew and investigators.

Roark, Walt↗
DOE OSTI2018

Water Hyacinth Report

Water hyacinth (Eichhornia crassipes) is a fast-growing, invasive aquatic species and represents a potential biomass resource for bioenergy production in the Togo and Kenya regions on the African continent. Literature shows multiple conversion pathways exist to produce energy from water hyacinth while supporting economic growth, job creation, and environmental sustainability. ECO2LIBRIUM (ECO2) is investigating the feasibility of developing feedstock logistics modelling capabilities to facilitate water hyacinth based bioenergy production. Developing a water hyacinth feedstock pipeline capable of supplying biomass at consistent quantity and quality requires sophisticated feedstock logistics modelling to minimize costs while maximizing ecosystem services. However, developing this type of modelling capability requires specific spatial data and analysis resources. Idaho National Laboratory (INL) maintains research capabilities in the areas of bioenergy, feedstock logistics, spatial analysis, and remote sensing. INL researchers have compiled spatial data and analysis resources in this report to back development of a water hyacinth biomass feedstock logistics model.

09 BIOMASS FUELS↗
DOE OSTI2022

MIRACL Co-Simulation Platform Lab assets and tools integration

Pacific Northwest National Laboratory's (PNNL) co-simulation platform (CSP) for the Microgrids, Infrastructure Resilience, and Advanced Controls Launchpad (MIRACL) project, also known as MIRACL-CSP, is a functional layer designed and developed to oversee the operational exchanges of data at the application level to and from different resources residing on the MIRACL Data Hub shared platform. MIRACL-CSP allows virtual interactions between various data hub resources during co-simulation runtime.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

The disCO2ver Platform: Curating Data and Tools for Geologic Carbon Sequestration and Deep Subsurface Research Systems

The U.S. DOE National Energy Technology Laboratory has invested 12+ years of development into the data repository and digital laboratory, the Energy Data eXchange (EDX, edx.netl.doe.gov). Supporting a variety of research areas across the DOE Office of Fossil Energy and Carbon Management, the platform has successfully curated and preserved thousands of data products from DOE research. The Carbon Storage Program has successfully supported data curation, upload, and publishing of data products on EDX for many years, demonstrating a success story of how resources like EDX can effectively help with long term preservation and publishing of DOE data products. EDX continues to shift towards cloud-supported infrastructure, taking a hybrid approach combining on-premises compute and storage integrated with cloud-hosted services. The integration of cloud compute and hybrid architecture enables the development of EDX-hosted platforms that tailor the data and tools hosted on them to a specific community, enables implementation of machine learning tools for data discovery and filtering, and enables the hosting of virtual (online user interface) tools. Geologic carbon sequestration (GCS) research continues to scale up in response to the current administration goals to reduce greenhouse gas emissions and transition the energy economy. Over the last year, EDX’s disCO2ver platform has been developed in response to the need for access to data products and tools to support the scaling up of GCS research. disCO2ver provides access to data resources and tools, produced by DOE and outside authoritative external resources. The platform also provides a user-access control component for the virtualization and cloud hosting of tools. Tools that need to be virtualized, to eliminate the need for users to download the tool and use local compute resources, is essential to supporting big-data analysis and machine learning that is becoming common place in carbon storage modeling, risk analysis, and data publishing practices. This talk will review the EDX’s disCO2ver platform and the current work ongoing to curate data and tools to support GCS and deep subsurface systems research.

Morkner, Paige↗
NASA NTRS1993

Resources Management System

Delta Data Systems, Inc. was originally formed by NASA and industry engineers to produce a line of products that evolved from ELAS, a NASA-developed computer program. The company has built on that experience, using ELAS as the basis for other remote sensing products. One of these is AGIS, a computer package for geographic and land information systems. AGIS simultaneously processes remotely sensed and map data. The software is designed to operate on a low cost microcomputer, putting resource management tools within reach of small operators.

Source record↗
DOE OSTI2021

Middle Kittanning Coal Waste and Underclay as an Alternative Rare Earth Elements Feedstock

In order to secure domestic sources of rare earth elements (REE) from coal related materials, there must be validation of representative feedstocks. Actively producing coal mines that target the Middle Kittanning coal seam in the Appalachian Basin were compiled. These mines were cross-referenced with publicly available geochemical data such as the U.S. Geological Survey (USGS) Earth Mapping Resources Initiative geochemical data along with samples evaluated and characterized by the National Energy Technology Laboratory (NETL). This work evaluated the extent of elevated Middle Kittanning underclay concentrations of REE in comparison to other underclay formations. Therefore, further up-scaling of research associated with the separation and extraction of REE and other critical minerals can be beneficial to utilizing domestic REE supplies for various technology sectors, to include energy, biomedical, and defense. Numerous current active mines targeting the Middle Kittanning coal seam represent a geographically significant opportunity for shared feedstocks and collaborations to further understand the role of Middle Kittanning underclay as a critical mineral feedstock.

01 COAL, LIGNITE, AND PEAT↗
NASA NTRS1978

Deforestation planning for cattle grazing in Amazon Basin using LANDSAT data

The author has identified the following significant results. This research did not show the total potential of the LANDSAT system, but tried to open up new research aspects for the utilization of LANDSAT data in natural resource control. Results obtained through this research showed that LANDSAT data can be used to develop monitoring programs in the tropical forest areas of Brazil.

Dejesusparada, N.↗
NASA NTRS2019

Collecting and Processing Earth Science Data Metrics at NASA ESDIS

Since the launch of Terra satellite in 1999, the number of Earth Science remote sensing data products created and distributed by NASA's Earth Observing System (EOS) Data and Information System (EOSDIS) has increased from a few hundred to nearly ten thousand. NASA's Earth Science Data and Information System (ESDIS) Metrics System (EMS) collects metrics on data ingest, archive, and distribution by its Distributed Active Archive Centers (DAACs) and the Science Investigator-led Systems (SIPS), known as Data Providers. These metrics are critical in helping NASA management as well as data producers in resource planning and gaining a wide range of knowledge of data users and data usage.EMS receives flat files, or log files of data archive, ingest, and distribution either in their raw format, such as Apache web logs, or text files of log records formatted by the Data Providers. Tens of millions of records are processed each day to extract metrics on data products, user information, distribution protocols and services, and so on. The metrics are then made available to designated parties.This presentation provides an overview of the EMS processing workflow and improvement efforts made in recent years to handle ever-increasing number of data records and new metrics requirements, discusses several key steps including mapping log records to data products and identifying user communities along with geo-distribution, and demonstrates typical metrics capabilities produced by the EMS system. Challenges and potential approaches to improve the system are also discussed.

Pan, Jianfu↗