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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 631 records · Page 35
All sourcesNASA NTRSDOE OSTI
NASA NTRS1992

Toxic substances registry system: Index of material safety data sheets

The Oct. 1992 Revision of the KSC Toxic Substances Registry System (TSRS) Index of Material Safety Data Sheets (MSDS's) is presented. The listed MSDS's reflect product inventories and associated MSDS's which were submitted to the Toxic Substance Registry Data Base maintained by the Base Operations Contractors of the Biomedical Operations and Research Office of KSC. The purpose of the index is to provide a means of accessing information on the hazards associated with the toxic and otherwise hazardous chemicals stored and used at KSC. Indices are provided for manufacturers, trademarks, and stock numbers.

Source record↗
NASA NTRS1993

Toxic substances registry system: Index of material safety data sheets

The Jan. 1993 Revision of the KSC Toxic Substances Registry System (TSRS) Index of Material Safety Data Sheets (MSDS's) is presented. The listed MSDS's reflect product inventories and associated MSDS's which were submitted to the Toxic Substance Registry Data Base maintained by the Base Operations Contractors of the Biomedical Operations and Research Office of KSC. The purpose of the index is to provide a means of accessing information on the hazards associated with the toxic and otherwise hazardous chemicals stored and used at KSC. Indices are provided for manufacturers, trademarks, and stock numbers.

Source record↗
DOE OSTI2017

Remote Monitoring System Design Requirements for Accountable Nuclear Materials at the Nevada National Security Site

The Nevada National Security Site (NNSS) worked with other sites within the Department of Energy National Nuclear Security Administration weapons complex to develop design requirements for a Remote Monitoring System. System objectives include: • Continuous monitoring of packaging (containers) within a Facility's buildings to meet Material Control and Accountability (MC&A) inventory requirements. • Remotely access and receive monitoring data for tamper detection/alarm, tracking information, environmental conditions, equipment metadata (serial number, date of manufacturer, etc.), and assessment video feeds. • All data processing, storage/retrieval, and communications will be protected in a manner commensurate with its trust level and classification. • Remotely collected and processed data will be securely stored, backed up, and archived. • Current and historical data will accessible within and outside of a Building (location). • Automated creation of reports and data visualization. • Design features to facilitate the potential future integration with the Facility's physical security alarm and display system. The requirements may be used to develop an integrated conceptual design or may be used in a modular fashion to inform separate designs. The guiding principles in developing the system objectives include: • For MC&A needs, remotely perform the physical inventory and evidence collection of tamper for Security Category I and II packaged material within a facility and be capable of satisfying guidelines establish by DOE M 470.4-6, “Nuclear Material Control and Accountability.” • For personnel safety needs: o Meet/satisfy Nuclear Explosive Safety requirements. o Minimize the exposure of personnel to radiation to be as low as reasonably achievable (ALARA) in accordance with NSTec Radiological Controls Manual (Ref TBD). • For DOE nuclear materials, Building environment shall be controlled to meet requirements for packaged nuclear materials specified in weapons laboratory literature.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2016

Cyber-Physical Security Assessment (CyPSA) Toolset

CyPSA seeks to organize and gain insight into the diverse sets of data that a critical infrastructure provider must manage. Specifically CyPSA inventories, manages, and analyzes assets and relations among those assets. A variety of interfaces are provided. CyPSA inventories assets (both cyber and physical). This may include the cataloging of assets through a common interface. Data sources used to generate a catalogue of assets include PowerWorld, NPView, NMap Scans, and device configurations. Depending upon the role of the person using the tool the types of assets accessed as well as the data sources through which asset information is accessed may vary. CyPSA allows practitioners to catalogue relations among assets and these may either be manually or programmatically generated. For example, some common relations among assets include the following: Topological Network Data: Which devices and assets are connected and how? Data sources for this kind of information include NMap scans, NPView topologies (via Firewall rule analysis). Security Metrics Outputs: The output of various security metrics such as overall exposure. Configure Assets:CyPSA may eventually include the ability to configure assets including relays and switches. For example, a system administrator would be able to configure and alter the state of a relay via the CyPSA interface. Annotate Assets: CyPSA also allows practitioners to manually and programmatically annotate assets. Sources of information with which to annotate assets include provenance metadata regarding the data source from which the asset was loaded, vulnerability information from vulnerability databases, configuration information, and the output of an analysis in general.

Garcia, Luis↗
DOE OSTI2019

Development of a Comprehensive and Centralized Waste Management System - 19412

Information Systems Laboratories (ISL) has designed a new single, integrated, waste management and control system to administer all aspects of nuclear waste management. The overriding goal of the initiative is to provide federal, state, and local agencies with operational awareness, management, and programmatic support for all functions related to nuclear waste management. Over decades of waste management federal agencies have sponsored or directly paid for the development, operation, and control of multiple systems to track and control its waste - with varied success. Multiple contractors have generated disparate control systems/databases and literally mountains of data. Past approaches have not provided a single, integrated, real time data management system. ISL's analysis of past failed efforts has reveal four common symptoms: - Control/management systems that are not compatible; - Programmatic costs that increase with systems use and re-work; - Systems focused on specific sets of data; - Inaccurate or outdated data sets. An integrated waste management and control system that collects and displays real-time, accurate inventory, waste container certification, transportation certification, emplacement, and shipment related data improve operational awareness and overcomes these limitations. Using its vast knowledge and experience in developing numerous waste tracking and management systems, ISL has leveraged its own in-house knowledge and gathered requests from stakeholders all across the industry to design a system that meets the needs of users at all levels of the nuclear waste management process. Using the highly successful and widely used Waste Data System (WDS) designed for the Waste Isolation Pilot Plant as a core component, ISL has designed a system that greatly expands on the functionality of the WDS to exceed its current focus of management of Transuranic Waste shipments. The new system is designed to provide the ability to track a wide range of waste types from Transuranic, High Level, Low Level, Mixed, and any nuclear related material. The main focus of the system is to provide federal regulators a comprehensive and real-time oversight into the handling of all nuclear waste materials. Oversight activities include, but are not limited to, strategy development, projections, metrics, incentive development, tracking, budget review, government cost estimating, and integrated schedules. The major components of the system are summarized below: - The Centralized Waste Management System (CWMS), which will include assimilating and validating known sources of data into the CWMS. - The programmatic reporting support component, which will handle queries from regulators, track compliance with regulatory requirements, and maintain the dashboard for federal management. - Both the CWMS and the programmatic reporting support component will use a standard set of business rules that govern system operations and allow site and program specific needs and limits for all waste programs and types to be captured and maintained. This presentation will provide details of each component of the system detailing its use, interfaces with other components, and value to stakeholders. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
NASA NTRS1986

On the design of classifiers for crop inventories

Crop proportion estimators that use classifications of satellite data to correct, in an additive way, a given estimate acquired from ground observations are discussed. A linear version of these estimators is optimal, in terms of minimum variance, when the regression of the ground observations onto the satellite observations in linear. When this regression is not linear, but the reverse regression (satellite observations onto ground observations) is linear, the estimator is suboptimal but still has certain appealing variance properties. In this paper expressions are derived for those regressions which relate the intercepts and slopes to conditional classification probabilities. These expressions are then used to discuss the question of classifier designs that can lead to low-variance crop proportion estimates. Variance expressions for these estimates in terms of classifier omission and commission errors are also derived.

Heydorn, R. P.↗
DOE OSTI2016

Uncertainty quantification in (α,n) neutron source calculations for an oxide matrix

Here we present a methodology to propagate nuclear data covariance information in neutron source calculations from (α,n) reactions. The approach is applied to estimate the uncertainty in the neutron generation rates for uranium oxide fuel types due to uncertainties on 1) 17,18 O( α,n) reaction cross sections and 2) uranium and oxygen stopping power cross sections. The procedure to generate reaction cross section covariance information is based on the Bayesian fitting method implemented in the R-matrix SAMMY code. The evaluation methodology uses the Reich-Moore approximation to fit the 17,18 O(α,n) reaction cross-sections in order to derive a set of resonance parameters and a related covariance matrix that is then used to calculate the energydependent cross section covariance matrix. The stopping power cross sections and related covariance information for uranium and oxygen were obtained by the fit of stopping power data in the -energy range of 1 keV up to 12 MeV. Cross section perturbation factors based on the covariance information relative to the evaluated 17,18 O( α,n) reaction cross sections, as well as uranium and oxygen stopping power cross sections, were used to generate a varied set of nuclear data libraries used in SOURCES4C and ORIGEN for inventory and source term calculations. The set of randomly perturbed output (α,n) source responses, provide the mean values and standard deviations of the calculated responses reflecting the uncertainties in nuclear data used in the calculations. Lastly, the results and related uncertainties are compared with experiment thick target (α,n) yields for uranium oxide.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2017

SNF Data Visualization on the Centralized Used Fuel Resource for Information Exchange (CURIE) Website

To better inform stakeholders regarding the nature of spent nuclear fuel (SNF) at utility sites, an online data visualization system has been created for the U.S. Department of Energy's Office of Nuclear Energy (DOENE). The data visualization system is part of the Centralized Used Fuel Resource for Information Exchange (CURIE) website, hosted by the Oak Ridge National Laboratory (ORNL) for DOE-NE. The visualization employs a database that is part of an analysis tool known as the Used Nuclear Fuel Storage, Transportation and Disposal Analysis Resource and Data System (UNF-ST[and]DARDS). Because many of the previous document management and sharing tools related to SNF have been terminated (or are inaccessible), a new tool, the CURIE, was developed for DOE-NE and launched on March 1, 2013 at http://curie.ornl.gov. In addition to supporting DOE SNF programs, CURIE is a national resource that is accessible to industry, vendor, federal, and laboratory partners, as well as other stakeholders. CURIE's architecture was initially based on previous work that supported DOE's Bioenergy Technologies Office on the Bioenergy Knowledge Discovery Framework (KDF). The site uses an open-source search engine, Apache Solr, which provides intuitive search results based on a faceted search method similar to that used by Amazon.com{sup R}. This algorithm helps to ensure that finding documents and data is straightforward. SNF data visualization capability was added to the CURIE website which provides a capability to post and access documents and data related to the management of SNF. CURIE currently maintains over 4,100 documents and the Siting Experience Database (SED), which was developed in response to a near-term recommendation by the Blue Ribbon Commission on America's Nuclear Future (BRC). The SED is a database of the experience that has been gained and relevant documentation that has been produced in efforts to site nuclear waste facilities, both in the US and abroad. Most of these documents are publicly accessible. In addition, CURIE maintains a current calendar of related events, an SNF image gallery, featured documents, and external links to related databases and websites. CURIE also maintains private groups (or communities) to facilitate collaborative development through sharing and editing documents that are not publicly available. There are more than 250 registered users in 23 different communities within CURIE.ORNL has also been developing UNF-ST[and]DARDS to provide a controlled source of technical data for various waste management system analysis/evaluation tools, access to key technical data, and analysis capabilities for characterizing the SNF inventory. UNF-ST[and]DARDS also provides enhanced capabilities to assess safety, risk, and uncertainty throughout the integrated waste management system. This paper describes the UNF-ST[and]DARDS data available for visualization and the associated visualization techniques used by CURIE to display this data.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
NASA NTRS2012

Preliminary Crater Retention Ages for an Expanded Inventory of Large Lunar Basins

Based on LOLA topography and a new crustal thickness model, the number of candidate lunar basins greater than 300 km in diameter is at least a factor 2 larger than the traditional number based on photogeology alone, and may be as high as 95. Preliminary N(50) crater retention ages for this population of candidate basins shows two distinct peaks. Frey [1] suggested, based on Clementine-era topography (ULCN2005) and a crustal thickness model based on Lunar Prospector data [2], that there could be as many as 98 lunar basins greater than 300 km diameter. Many of the weaker cases have not stood up to recent testing [3,4,5] using LOLA data and a newer crustal thickness model based on Kaguya gravity data and LOLA topography data [6]. As described in companion abstracts [4,5], we have deleted from the earlier inventory 1 more named feature (Sikorsky- Rittenhouse; LOLA data show that its diameter is actually less than 300 km), 11 Quasi-Circular Depressions (QCDs) identified in the ULCN topography, and 11 Circular Thin Areas (CTAs) found in the earlier crustal thickness model [2]. We did this by repeating the scoring exercise originally done in [1] but with the new data [4,5]. Topographic Expression (TE) and Crustal Thickness Expression (CTE) scores were determined for each candidate on a scale of 0 to 5 (5 being a strong, circular signature, 0 for those with no discernible circular topographic or crustal thickness signature). These scores are added together to produce a Summary Score which has a range of 0 to 10. We eliminated all candidates with a Summary Score less than 3, as well as other cases where, for example, the TE went to zero because what looked like a single large circular QCD in the lower resolution ULCN data was in fact a cluster of smaller deep impacts readily apparent in the newer higher resolution LOLA data. This process reduced the original inventory from 98 to 75 candidates.

Frey, H. V.↗
NASA NTRS1974

Statistical theory and methodology for remote sensing data analysis

A model is developed for the evaluation of acreages (proportions) of different crop-types over a geographical area using a classification approach and methods for estimating the crop acreages are given. In estimating the acreages of a specific croptype such as wheat, it is suggested to treat the problem as a two-crop problem: wheat vs. nonwheat, since this simplifies the estimation problem considerably. The error analysis and the sample size problem is investigated for the two-crop approach. Certain numerical results for sample sizes are given for a JSC-ERTS-1 data example on wheat identification performance in Hill County, Montana and Burke County, North Dakota. Lastly, for a large area crop acreages inventory a sampling scheme is suggested for acquiring sample data and the problem of crop acreage estimation and the error analysis is discussed.

Odell, P. L.↗
NASA NTRS1978

Large Area Crop Inventory Experiment (LACIE). Detecting and monitoring agricultural vegetative water stress over large areas using LANDSAT digital data

The author has identified the following significant results. The Green Number Index technique which uses LANDSAT digital data from 5X6 nautical mile sampling frames was expanded to evaluate its usefulness in detecting and monitoring vegetative water stress over the Great Plains. At known growth stages for wheat, segments were classified as drought or non drought. Good agreement was found between the 18 day remotely sensed data and a weekly ground-based crop moisture index. Operational monitoring of the 1977 U.S.S.R. and Australian wheat crops indicated drought conditions. Drought isoline maps produced by the Green Number Index technique were in good agreement with conventional sources.

Thompson, D. R.↗
NASA NTRS2014

Global Inventory and Characterization of Pyroclastic Deposits on Mercury: New Insights into Pyroclastic Activity from MESSENGER Orbital Data

We present new observations of pyroclastic deposits on the surface of Mercury from data acquired during the orbital phase of the MErcury Surface, Space ENvironment, GEochemistry, and Ranging (MESSENGER) mission. The global analysis of pyroclastic deposits brings the total number of such identified features from 40 to 51. Some 90% of pyroclastic deposits are found within impact craters. The locations of most pyroclastic deposits appear to be unrelated to regional smooth plains deposits, except some deposits cluster around the margins of smooth plains, similar to the relation between many lunar pyroclastic deposits and lunar maria. A survey of the degradation state of the impact craters that host pyroclastic deposits suggests that pyroclastic activity occurred on Mercury over a prolonged interval. Measurements of surface reflectance by MESSENGER indicate that the pyroclastic deposits are spectrally distinct from their surrounding terrain, with higher reflectance values, redder (i.e., steeper) spectral slopes, and a downturn at wavelengths shorter than approximately 400nm (i.e., in the near-ultraviolet region of the spectrum). Three possible causes for these distinctive characteristics include differences in transition metal content, physical properties (e.g., grain size), or degree of space weathering from average surface material on Mercury. The strength of the near-ultraviolet downturn varies among spectra of pyroclastic deposits and is correlated with reflectance at visible wavelengths. We suggest that this interdeposit variability in reflectance spectra is the result of either variable amounts of mixing of the pyroclastic deposits with underlying material or inherent differences in chemical and physical properties among pyroclastic deposits.

Stratigraphic relationships↗
DOE OSTI2018

Department of Energy Office of Legacy Management Progress on Defense-Related Uranium Mines Program - 18119

The Defense-Related Uranium Mines (DRUM) Program provides the structure and basis for the US Department of Energy Office of Legacy Management (LM) to manage the verification and validation (V and V) of defense-related uranium mines (mines) that provided ore to the Atomic Energy Commission from 1947 to 1970. V and V activities are conducted to fully understand the scope of potential problems posed by these mines by determining their location, reclamation or remediation status, and potential impacts to public safety, human health, and the environment. Land management agencies have limited resources and have generally not conducted comprehensive inventories of abandoned uranium mines, thus adding to the need to undertake this program. LM has entered into memoranda of understanding (MOUs) with the US Bureau of Land Management (BLM) and US Forest Service (USFS) to facilitate a better understanding of the scope of the problem posed by these mines. Currently, LM has executed MOUs with the BLM state offices in Colorado, New Mexico, Utah, and Wyoming and the USFS Rocky Mountain Region, which includes the national forests in Colorado, Wyoming, and South Dakota. This collaborative effort with partner agencies has led LM to develop a V and V Work Plan that describes the numerous activities and types of data to be collected at the mines. V and V activities verify actual mine location, collect coordinates of mining-related features, collect radiological data and soil samples, identify potential physical safety hazards, prioritize mines using a risk-based screening approach, and report the information to partner agencies. The partner agencies may use the reports to assess priorities and determine if any further action is warranted. The DRUM Program goals are to: - Improve data quality and content in the LM national inventory of abandoned uranium mines; - Conduct site-specific reconnaissance at mines for data verification and validation; - Exchange mine information with other federal agencies and state governments to help address mines presenting the greatest risks; - Develop reports for each mine that will contain a risk scoring assessment to help each agency develop priorities. The preliminary risk screening methodology was based on a joint effort between LM and BLM to develop factors that would be based on field observations, field data, and laboratory data using a multiple-lines-of-evidence approach. The multiple-lines-of-evidence assessment allows land managers the opportunity and flexibility to query specific criteria and make rankings based on specific priorities. The risk screening for each mine is based on evaluating the primary hazards of physical safety and risks to human health and several modifying factors that include accessibility and ecological/environmental risks. Gamma radiation scans are performed across the disturbed area of the mine, and soil samples are taken from waste rock piles and drainages, when applicable. This paper presents the results of performing inventory, environmental sampling, and risk ranking along with other accomplishments and lessons learned during the initial year of V and V activities and reporting. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
NASA NTRS1980

Using Landsat digital data to detect moisture stress in corn-soybean growing regions

As a part of a follow-on study to the moisture stress detection effort conducted in the Large Area Crop Inventory Experiment (LACIE), a technique utilizing transformed Landsat digital data was evaluated for detecting moisture stress in humid growing regions using sample segments from Iowa, Illinois, and Indiana. At known growth stages of corn and soybeans, segments were classified as undergoing moisture stress or not undergoing stress. The remote-sensing-based information was compared to a weekly ground-based index (Crop Moisture Index). This comparison demonstrated that the remote sensing technique could be used to monitor the growing conditions within a region where corn and soybeans are the major crop.

Thompson, D. R.↗
DOE OSTI2025

deadtrees.earth — An open-access and interactive database for centimeter-scale aerial imagery to uncover global tree mortality dynamics

Excessive tree mortality is a global concern and remains poorly understood as it is a complex phenomenon. We lack global and temporally continuous coverage on tree mortality data. Ground-based observations on tree mortality, e.g., derived from national inventories, are very sparse, and may not be standardized or spatially explicit. Earth observation data, combined with supervised machine learning, offer a promising approach to map overstory tree mortality in a consistent manner over space and time. However, global-scale machine learning requires broad training data covering a wide range of environmental settings and forest types. Low altitude observation platforms (e.g., drones or airplanes) provide a cost-effective source of training data by capturing high-resolution orthophotos of overstory tree mortality events at centimeter-scale resolution. Here, we introduce deadtrees.earth, an open-access platform hosting more than two thousand centimeter-resolution orthophotos, covering more than 1,000,000 ha, of which more than 58,000 ha are manually annotated with live/dead tree classifications. This community-sourced and rigorously curated dataset can serve as a comprehensive reference dataset to uncover tree mortality patterns from local to global scales using space-based Earth observation data and machine learning models. This will provide the basis to attribute tree mortality patterns to environmental changes or project tree mortality dynamics to the future. The open nature of deadtrees.earth, together with its curation of high-quality, spatially representative, and ecologically diverse data will continuously increase our capacity to uncover and understand tree mortality dynamics.

Citizen science↗
NASA NTRS1994

National Facilities Study. Volume 1: Facilities Inventory

The inventory activity was initiated to solve the critical need for a single source of site specific descriptive and parametric data on major public and privately held aeronautics and aerospace related facilities. This a challenging undertaking due to the scope of the effort and the short lead time in which to assemble the inventory and have it available to support the task group study needs. The inventory remains dynamic as sites are being added and the data is accessed and refined as the study progresses. The inventory activity also included the design and implementation of a computer database and analytical tools to simplify access to the data. This volume describes the steps which were taken to define the data requirements, select sites, and solicit and acquire data from them. A discussion of the inventory structure and analytical tools is also provided.

Source record↗
DOE OSTI2024

The Foundational Industry Energy Dataset: Unit-level Characterization and Derived Energy Estimates for Industrial Facilities in 2017

The Foundational Industry Energy Dataset (FIED) addresses several of the areas of growing disconnect between the demands of industrial energy analysis and the state of industrial energy data by providing unit-level characterization by facility. Each facility is identified by a unique registryID, based on the U.S. Environmental Protection Agency (EPA) Facility Registry Service, and includes its coordinates and other geographic identifiers. Energy-using units are characterized by design capacity, as well as their estimated energy use, greenhouse gas emissions, and physical throughput using 2017 data from the EPA's National Emissions Inventory and Greenhouse Gas Reporting Program. An overview of the derivation methods is provided in a separate technical report which will be linked after publication. The Python code used to compile the dataset is available in a GitHub repository. An updated 2020 version is under development.

Array↗