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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 919 records · Page 51
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Compilation and Evaluation of Data from Groundwater Impounded within the U12n and U12t Tunnels, Rainier and Aqueduct Mesas, Nevada National Security Site

The Department of Defense (DOD) Defense Threat Reduction Agency (DTRA) and the U.S. Department of Energy (DOE) Office of Environmental Management Nevada Program (EM NV) conducted routine physical and geochemical monitoring of water impounded behind impermeable structures placed within the U12n and U12t tunnels on the Nevada National Security Site (NNSS) (formerly the Nevada Test Site [NTS]). Desert Research Institute (DRI) conducted a semiquantitative evaluation of pressure data to determine the extent to which the tunnels have been inundated and a qualitative evaluation of monitored geochemical parameters to determine if trends exist that were indicative of hydrologic and/or geochemical processes operating behind the tunnel plugs. Data were also evaluated to determine if monitored radiological parameters exceeded primary standards associated with the Environmental Protection Agency’s (EPA) Safe Drinking Water Act (SDWA) (40 C.F.R. § 141.66).

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2011

The Invasive Species Forecasting System

The Invasive Species Forecasting System (ISFS) provides computational support for the generic work processes found in many regional-scale ecosystem modeling applications. Decision support tools built using ISFS allow a user to load point occurrence field sample data for a plant species of interest and quickly generate habitat suitability maps for geographic regions of management concern, such as a national park, monument, forest, or refuge. This type of decision product helps resource managers plan invasive species protection, monitoring, and control strategies for the lands they manage. Until now, scientists and resource managers have lacked the data-assembly and computing capabilities to produce these maps quickly and cost efficiently. ISFS focuses on regional-scale habitat suitability modeling for invasive terrestrial plants. ISFS s component architecture emphasizes simplicity and adaptability. Its core services can be easily adapted to produce model-based decision support tools tailored to particular parks, monuments, forests, refuges, and related management units. ISFS can be used to build standalone run-time tools that require no connection to the Internet, as well as fully Internet-based decision support applications. ISFS provides the core data structures, operating system interfaces, network interfaces, and inter-component constraints comprising the canonical workflow for habitat suitability modeling. The predictors, analysis methods, and geographic extents involved in any particular model run are elements of the user space and arbitrarily configurable by the user. ISFS provides small, lightweight, readily hardened core components of general utility. These components can be adapted to unanticipated uses, are tailorable, and require at most a loosely coupled, nonproprietary connection to the Web. Users can invoke capabilities from a command line; programmers can integrate ISFS's core components into more complex systems and services. Taken together, these features enable a degree of decentralization and distributed ownership that have helped other types of scientific information services succeed in recent years.

Schnase, John↗
DOE OSTI2020

Meteorological Tower Network Expansion Pilot Project Siting Considerations to Ensure Data Quality and Representativeness of Three New Meteorological Towers at Los Alamos National Laboratory

Associated with the Meteorological Tower Network Expansion Pilot Project by the Environmental Protection and Compliance (EPC) Compliance Programs (CP) Meteorology and Air Quality (MAQ) team, the purpose of this technical report is to establish requisite justification for the siting of three 10-meter high instrumented meteorological towers at three new locations on the Los Alamos National Laboratory (LANL) site. These towers and their associated instrumentation are similar in scope to the existing 10-meter meteorological tower that is collecting meteorological data in Mortandad Canyon (MDCN). The conclusions and recommendations in this technical report will inform LANL management, EPC-CP MAQ staff, and other LANL divisions of the criteria employed for the selection of the final location for siting these three new towers. Meeting such comprehensive criteria will ensure that all data acquired will be spatially representative for meeting the diverse Safety Basis (SB), emergency management, and operations organizations programmatic needs and analytical data input requirements to its codes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

EMP, Attachment 2: Data Management Plan

This Data Management Plan (DMP) is an attachment to the Pacific Northwest National Laboratory Environmental Radiological Air Monitoring Plan (EMP). PNNL is a U.S. Department of Energy Office of Science national laboratory. Radioactive effluent monitoring and environmental surveillance for PNNL operations in Washington State are the responsibility of the PNNL Environmental Protection and Regulatory Programs division and are conducted by the Environmental Radiation Task staff. This DMP describes the data management processes for PNNL radioactive air emissions (stack) monitoring and environmental radiological ambient air surveillance activities.

40 CFR 61 Subpart H↗
NASA NTRS2013

Assessing 'Dangerous Climate Change': Required Reduction of Carbon Emissions to Protect Young People, Future Generations and Nature

We assess climate impacts of global warming using ongoing observations and paleoclimate data. We use Earth's measured energy imbalance, paleoclimate data, and simple representations of the global carbon cycle and temperature to define emission reductions needed to stabilize climate and avoid potentially disastrous impacts on today's young people, future generations, and nature. A cumulative industrial-era limit of approx.500 GtC fossil fuel emissions and 100 GtC storage in the biosphere and soil would keep climate close to the Holocene range to which humanity and other species are adapted. Cumulative emissions of approx.1000 GtC, sometimes associated with 2 C global warming, would spur "slow" feedbacks and eventual warming of 3-4 C with disastrous consequences. Rapid emissions reduction is required to restore Earth's energy balance and avoid ocean heat uptake that would practically guarantee irreversible effects. Continuation of high fossil fuel emissions, given current knowledge of the consequences, would be an act of extraordinary witting intergenerational injustice. Responsible policymaking requires a rising price on carbon emissions that would preclude emissions from most remaining coal and unconventional fossil fuels and phase down emissions from conventional fossil fuels.

climate↗
DOE OSTI2023

Machine Learning in Power System Operations: Training Data

Reliability and stability of the electric grid today has depended upon operations of the grid which include the protective relay. Today, the electricity sector faces new challenges with the shift of generation resource characteristics away from the traditional “big iron” generation to inverter-based resources (IBR) which shift the physics and assumption used in grid operation and protection. These changing conditions represent new challenges for protective relays (identification of faults) and increased challenges for protection engineers (correct settings and configuration, reduction of mis-operations), both issues recognized in research and industry. Finding new approaches to reduce mis-operations in relaying and new approaches to fault identification is critical to grid operations. Using today’s modern technology of embedded systems, edge computing, machine learning (ML), and communications we can help address challenges and augment and improve on existing power system operations methodologies.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS1976

Some effects of adverse weather conditions on performance of airplane antiskid braking systems

The performance of current antiskid braking systems operating under adverse weather conditions was analyzed in an effort to both identify the causes of locked-wheel skids which sometimes occur when the runway is slippery and to find possible solutions to this operational problem. This analysis was made possible by the quantitative test data provided by recently completed landing research programs using fully instrumented flight test airplanes and was further supported by tests performed at the Langley aircraft landing loads and traction facility. The antiskid system logic for brake control and for both touchdown and locked-wheel protection is described and its response behavior in adverse weather is discussed in detail with the aid of available data. The analysis indicates that the operational performance of the antiskid logic circuits is highly dependent upon wheel spin-up acceleration and can be adversely affected by certain pilot braking inputs when accelerations are low. Normal antiskid performance is assured if the tire-to-runway traction is sufficient to provide high wheel spin-up accelerations or if the system is provided a continuous, accurate ground speed reference. The design of antiskid systems is complicated by the necessity for tradeoffs between tire braking and cornering capabilities, both of which are necessary to provide safe operations in the presence of cross winds, particularly under slippery runway conditions.

Horne, W. B.↗
DOE OSTI2024

Water Resource Assessment In The New Mexico Permian Basin: BLM 2023 Assessment Report

The Permian Basin is the highest producing oil field in the United States and is comprised of three component basins including; the Midland Basin, Delaware Basin and the Marfa Basin. This report describes the work conducted by Sandia National Laboratories (SNL) for the Bureau of Land Management (BLM) to investigate the occurrence of usable water (quality, and depth to water) in the Delaware Sub-basin of the Permian Basin. High Production Areas (HPAs) were identified for the region based on Reasonable Foreseeable Development Scenario (RFD) published by New Mexico Tech University. HPAs were established based on potential for future development of oil reserves. The study was initiated by the BLM-Carlsbad Field Office (CFO) based on concerns that special protections for groundwater in these HPAs may be warranted. A combination of analysis of existing data and field work to collect new data for analysis were used to complete the investigation objectives. This study summarizes the most recent analyses in an ongoing project and builds on previously completed work as listed in Table 1. Advancements in directional drilling and well completion technologies have resulted in an exponential growth in the use of hydraulic fracturing for oil and gas extraction in the Permian Basin. Within the New Mexico portion of the Delaware Sub-basin, water demand to complete each hydraulically fractured well is estimated to average 7.3 acre-feet (2.4 million gallons), resulting in 30 billion barrels of water over the life of the plan or 1.5 billion barrels per year. This rising demand is creating concern for the regions ability to provide the necessary water in a manner that fulfills BLM’s role of protecting human health and the environment while sustainably meeting the needs of various water users in the region. This report documents water-level and water chemistry baselines to aid the BLM in understanding the regional water supply dynamics under various management, policy, and growth scenarios and to pre-emptively identify risks to water sustainability.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1989

A system architecture for a planetary rover

Each planetary mission requires a complex space vehicle which integrates several functions to accomplish the mission and science objectives. A Mars Rover is one of these vehicles, and extends the normal spacecraft functionality with two additional functions: surface mobility and sample acquisition. All functions are assembled into a hierarchical and structured format to understand the complexities of interactions between functions during different mission times. It can graphically show data flow between functions, and most importantly, the necessary control flow to avoid unambiguous results. Diagrams are presented organizing the functions into a structured, block format where each block represents a major function at the system level. As such, there are six blocks representing telecomm, power, thermal, science, mobility and sampling under a supervisory block called Data Management/Executive. Each block is a simple collection of state machines arranged into a hierarchical order very close to the NASREM model for Telerobotics. Each layer within a block represents a level of control for a set of state machines that do the three primary interface functions: command, telemetry, and fault protection. This latter function is expanded to include automatic reactions to the environment as well as internal faults. Lastly, diagrams are presented that trace the system operations involved in moving from site to site after site selection. The diagrams clearly illustrate both the data and control flows. They also illustrate inter-block data transfers and a hierarchical approach to fault protection. This systems architecture can be used to determine functional requirements, interface specifications and be used as a mechanism for grouping subsystems (i.e., collecting groups of machines, or blocks consistent with good and testable implementations).

Smith, D. B.↗
DOE OSTI2020

Estimating the Timing of Early Simian-Human Immunodeficiency Virus Infections: a Comparison between Poisson Fitter and BEAST

Many HIV prevention strategies are currently under consideration where it is highly informative to know the study participants’ times of infection. These can be estimated using viral sequence data sampled early in infection. However, there are several scenarios that, if not addressed, can skew timing estimates. These include multiple transmitted/founder (TF) viruses, APOBEC (apolipoprotein B mRNA editing enzyme, catalytic polypeptide-like)-mediated mutational enrichment, and recombination. Here, we suggest a pipeline to identify these problems and resolve the biases that they introduce. We then compare two modeling strategies to obtain timing estimates from sequence data. The first, Poisson Fitter (PF), is based on a Poisson model of random accumulation of mutations relative to the TF virus (or viruses) that established the infection. The second uses a coalescence-based phylogenetic strategy as implemented in BEAST. The comparison is based on timing predictions using plasma viral RNA (cDNA) sequence data from 28 simian-human immunodeficiency virus (SHIV)-infected animals for which the exact day of infection is known. In this particular setting, based on nucleotide sequences from samples obtained in early infection, the Poisson method yielded more accurate, more precise, and unbiased estimates for the time of infection than did the explored implementations of BEAST. The inference of the time of infection is a critical parameter in testing the efficacy of clinical interventions in protecting against HIV-1 infection. For example, in clinical trials evaluating the efficacy of passively delivered antibodies (Abs) for preventing infections, accurate time of infection data are essential for discerning levels of the Abs required to confer protection, given the natural Ab decay rate in the human body. In such trials, genetic sequences from early in the infection are regularly sampled from study participants, generally prior to immune selection, when the viral population is still expanding and genetic diversity is low. In this particular setting of early viral growth, the Poisson method is superior to the alternative approach based on coalescent methods. This approach can also be applied in human vaccine trials, where accurate estimates of infection times help ascertain if vaccine-elicited immune protection wanes over time.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

The Importance of Inventory for Informing Waste Strategy - 20280

A waste inventory aims to present the best available information about the nature, quantity and location of radioactive wastes and materials at a facility, site or in a country. Quality inventory data is necessary for developing appropriate strategies and plans for managing radioactive wastes and materials, with high standards of protection for people and the environment. The inventory of wastes will change over time due to a wide range of technical, commercial or policy reasons, for example, if reactor lifetimes are extended, if decommissioning strategies change or if new technologies are introduced for managing waste. Inventory information can also improve as better waste characterisation data becomes available. At a facility or site level, good quality inventory data are needed to underpin decision making about the waste management options and to demonstrate compliance with the chosen treatment or disposal route. At a site and country level, knowledge of the inventory can drive the improvement to waste strategy; waste management asset and service planning; and implementation. (authors)

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

Convective Heating Predictions of Apollo IV Flight Data

It has been more than 50 years since NASA engineers have attempted to design a manned space vehicle with the capability to return from beyond low Earth orbit. In this interval, our methodologies for designing the thermal protection system (TPS) to protect humans from the extremely high temperatures of re-entry have changed significantly. With these considerations in mind, we return to the Apollo IV (AS-501) flight data. This incredible data set allows us to assess the current tools and methodologies being used to design Orion MPCV. In particular, our ability to predict the aftbody separated region convective heating environments for MPCV is critical. The design uses reusable TPS in this area, whereas Apollo designers used ablative TPS which can withstand much more severe environments. This presentation will revisit the flight data, summarize the assumptions going into the analysis, present the results and draw conclusions regarding how accurately we can currently predict the heating in the aftbody separated region of a re-entry capsule.

White, Molly E.↗
NASA NTRS2021

Large-Scale High-Resolution Coastal Mangrove Forests Mapping Across West Africa With Machine Learning Ensemble and Satellite Big Data

Coastal mangrove forests provide important ecosystem goods and services, including carbon sequestration, biodiversity conservation, and hazard mitigation. However, they are being destroyed at an alarming rate by human activities. To characterize mangrove forest changes, evaluate their impacts, and support relevant protection and restoration decision making, accurate and up-to-date mangrove extent mapping at large spatial scales is essential. Available large-scale mangrove extent data products use a single machine learning method commonly with 30 m Landsat imagery, and significant inconsistencies remain among these data products. With huge amounts of satellite data involved and the heterogeneity of land surface characteristics across large geographic areas, finding the most suitable method for large-scale high-resolution mangrove mapping is a challenge. The objective of this study is to evaluate the performance of a machine learning ensemble for mangrove forest mapping at 20 m spatial resolution across West Africa using Sentinel-2 (optical) and Sentinel-1 (radar) imagery. The machine learning ensemble integrates three commonly used machine learning methods in land cover and land use mapping, including Random Forest (RF), Gradient Boosting Machine (GBM), and Neural Network (NN). The cloud-based big geospatial data processing platform Google Earth Engine (GEE) was used for pre-processing Sentinel-2 and Sentinel-1 data. Extensive validation has demonstrated that the machine learning ensemble can generate mangrove extent maps at high accuracies for all study regions in West Africa (92%–99% Producer’s Accuracy, 98%–100% User’s Accuracy, 95%–99% Overall Accuracy). This is the first-time that mangrove extent has been mapped at a 20 m spatial resolution across West Africa. The machine learning ensemble has the potential to be applied to other regions of the world and is therefore capable of producing high-resolution mangrove extent maps at global scales periodically.

coastal environment↗
NASA NTRS2004

Overview of High Speed Close-Up Imaging in an Icing Environment

The Icing Branch and Imaging Technology Center at NASA Glenn Research Center have recently been involved in several projects where high speed close-up imaging was used to investigate water droplet impact/splash, and also ice particle impact/bounce in an icing wind tunnel. The combination of close-up and high speed imaging capabilities were required because the particles being studied were relatively small (d < 1 mm in diameter), and the impact process occurred in a very short time period (t(sub impact) << 1 sec). High speed close-up imaging was utilized to study the dynamics of droplet impact and splash in simulated Supercooled Large Droplet (SLD) icing conditions. The objective of this test was to evaluate the capability of a ultra high speed camera system to acquire quantitative information about the impact process (e.g., droplet size, velocity). Imaging data were obtained in an icing wind tunnel for spray cloud MVD > 50 m. High speed close-up imaging was also utilized to characterize the impact of ice particles on an airfoil with a thermally protected leading edge. The objective of this investigation was to determine whether ice particles tend to "stick" or "bounce" after impact. Imaging data were obtained for cases where the airfoil surface was heated and unheated. Based on the results from this test, follow on tests were conducted to investigate ice particle impact on the sensing elements of water content measurement devices. This paper will describe the use of the imaging systems to support these experimental investigations, present some representative results, and summarize what was learned about the use of these systems in an icing environment.

Miller, Dean R.↗
NASA NTRS2011

Analysis of Noise Exposure Measurements Made Onboard the International Space Station

The International Space Station (ISS) is a unique workplace environment for U.S. astronauts and Russian cosmonauts to conduct research and live for a period of six months or more. Noise has been an enduring environmental physical hazard that has been a challenge for the U.S. space program since before the Apollo era. Noise exposure in ISS poses significant risks to the crewmembers, such as; hearing loss (temporary or permanent), possible disruptions of crew sleep, interference with speech intelligibility and communication, possible interference with crew task performance, and possible reduction in alarm audibility. Acoustic measurements are made aboard ISS and compared to requirements in order to assess the acoustic environment to which the crewmembers are exposed. The purpose of this paper is to describe in detail the noise exposure monitoring program as well as an assessment of the acoustic dosimeter data collected to date. The hardware currently being used for monitoring the noise exposure onboard ISS will be discussed. Acoustic data onboard ISS has been collected since the beginning of ISS (Increment 1, November 2000). Noise exposure data analysis will include acoustic dosimetry logged data from crew-worn during work and sleep periods and also fixed-location measurements from Increment 1 to present day. Noise exposure levels (8-, 16- and 24-hr), LEQ, will also be provided and discussed in this paper. Discussions related to hearing protection will also be included. Future directions and recommendations for the noise exposure monitoring program will be highlighted. This acoustic data is used to ensure a safe and healthy working and living environment for the crewmembers aboard the ISS.

Limardo, Jose G.↗
NASA NTRS1994

Advanced integrated life support system update

The Advanced Integrated Life Support System Program (AILSS) is an advanced development effort to integrate the life support and protection requirements using the U.S. Navy's fighter/attack mission as a starting point. The goal of AILSS is to optimally mate protection from altitude, acceleration, chemical/biological agent, thermal environment (hot, cold, and cold water immersion) stress as well as mission enhancement through improved restraint, night vision, and head-mounted reticules and displays to ensure mission capability. The primary emphasis to date has been to establish garment design requirements and tradeoffs for protection. Here the garment and the human interface are treated as a system. Twelve state-off-the-art concepts from government and industry were evaluated for design versus performance. On the basis of a combination of centrifuge, thermal manikin data, thermal modeling, and mobility studies, some key design parameters have been determined. Future efforts will concentrate on the integration of protection through garment design and the use of a single layer, multiple function concept to streamline the garment system.

Whitley, Phillip E.↗
DOE OSTI2024

Regularized Differentiation for Bioburden Density Estimation in Planetary Protection

In this paper, we propose and investigate the performance of two novel shrinkage estimators for bioburden density estimation in planetary protection. The estimators are based on the regularized differentiation of a cumulative count of colony forming units collected throughout the data collecting session or the life cycle of the entire mission. The regularized differentiation recasts the problem of bioburden density estimation as a linear least squares problem. The least squares problem is then solved through regularization techniques, such as truncated singular value decomposition and penalized least squares. The regularization is necessary to avoid noise amplification during the differentiation of noisy data. The two regularization estimators are compared with four other commonly used estimators to simultaneously evaluate the means of multivariable independent Poisson distributions: the maximum likelihood, noninformative Bayes estimator with Jeffreys prior, Empirical Bayes using conjugate gamma-Poisson model with gamma parameters selected by method of moments, and the Clevenson-Zidek estimator. It is shown through computer-simulated data that the regularized differentiation based on ridge regression has the smallest mean-squared error among all estimators. The analysis of shrinkage mechanism implemented by regularized differentiation is performed, and it is shown that the regularized differentiation amounts to performing a weighted averaging of all the samples. The weights are determined by the regularization parameter automatically selected by the L-curve technique. Since the method of least squares makes no distributional assumptions about the data, it presents an attractive technique for bioburden density estimation when there are concerns about the misspecification of the distributional model. The paper concludes with the analysis of the bioburden data collected during InSight mission and directions for future work.

97 - MATHEMATICS AND COMPUTING↗