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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 1,441 records · Page 80
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Tracking Restoration And Closure (TRAC): Status Update on Story Maps for Communicating Site Cleanup and Closure Status - 19033

The U.S. Department of Energy (DOE) Office of Environmental Management (EM) initiated the development of a customized, web-based mapping tool for communicating technical information on groundwater plumes at sites within the EM complex. Although the online tool was initially conceived to be a simple conversion of a paper report on contaminant plume sizes, remedial approaches, and regulatory status, it has advanced to providing specific information on cleanup status and site closure. The story maps provide robust geospatial visualization of plumes at DOE sites, as well as explanatory text, photographs, and video for an entire site, or for a management unit within the site. This collection of story maps is called TRAC (Tracking Restoration And Closure), and not only communicates information for each individual site, but also summarizes pertinent metrics on cleanup and remaining contaminants across all EM sites. TRAC is focused on communicating cleanup status, technical challenges, and needs for site closure, with a key challenge of transforming data into relevant, easily understood information. Although DOE managers are the target audience, the story maps can also be used to contribute to public understanding of groundwater cleanup progress at EM sites. Unlike the data access tools maintained at some EM sites (e.g., Hanford, Portsmouth, and Paducah), TRAC is neither a portal for data downloads, nor a tool for performing data analytics. Rather, the goal of TRAC is to provide relevant information on cleanup progress and closure that is consistent across all sites, allowing the user to view summary information across all sites, or examine information relevant to a particular site. This information sharing is needed to maintain open communications with interested parties and communicate efforts that ensure long-term protection of human health and the environment. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2017

Behavior of Americium in Simulated Wounds in Nonhuman Primates

An americium solution injected intramuscularly into several nonhuman primates (NHPs) was found to behave differently than predicted by the wound models described in the NCRP Report 156. This was because the injection was made along with a citrate solution, which is known to be more soluble than chlorides, oxides, or nitrates on which the NCRP Report was based. We developed a multi-exponential wound model specific to the injected americium solution based on the retention in the intramuscular sites. The model was coupled with the americium systemic model to interpret the urinary excretion data and assess the intake, and it was determined that the models were adequate to predict early urinary excretion in most cases but unable to predict late urinary excretion. This was attributed to the differences in the systemic handling of americium between humans and nonhuman primates. Furthermore, information on the type of wounds, solubility, particle size, mass, chemical form, etc., should always be considered when performing wound dosimetry.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2018

Nonpareil 3: Fast Estimation of Metagenomic Coverage and Sequence Diversity

Estimations of microbial community diversity based on metagenomic data sets are affected, often to an unknown degree, by biases derived from insufficient coverage and reference database-dependent estimations of diversity. For instance, the completeness of reference databases cannot be generally estimated since it depends on the extant diversity sampled to date, which, with the exception of a few habitats such as the human gut, remains severely undersampled. Further, estimation of the degree of coverage of a microbial community by a metagenomic data set is prohibitively time-consuming for large data sets, and coverage values may not be directly comparable between data sets obtained with different sequencing technologies. Here, we extend Nonpareil, a database-independent tool for the estimation of coverage in metagenomic data sets, to a high-performance computing implementation that scales up to hundreds of cores and includes, in addition, a k -mer-based estimation as sensitive as the original alignment-based version but about three hundred times as fast. Further, we propose a metric of sequence diversity ( N d ) derived directly from Nonpareil curves that correlates well with alpha diversity assessed by traditional metrics. We use this metric in different experiments demonstrating the correlation with the Shannon index estimated on 16S rRNA gene profiles and show that N d additionally reveals seasonal patterns in marine samples that are not captured by the Shannon index and more precise rankings of the magnitude of diversity of microbial communities in different habitats. Therefore, the new version of Nonpareil, called Nonpareil 3, advances the toolbox for metagenomic analyses of microbiomes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Evaluation of an open forecasting challenge to assess skill of West Nile virus neuroinvasive disease prediction

Abstract Background West Nile virus (WNV) is the leading cause of mosquito-borne illness in the continental USA. WNV occurrence has high spatiotemporal variation, and current approaches to targeted control of the virus are limited, making forecasting a public health priority. However, little research has been done to compare strengths and weaknesses of WNV disease forecasting approaches on the national scale. We used forecasts submitted to the 2020 WNV Forecasting Challenge, an open challenge organized by the Centers for Disease Control and Prevention, to assess the status of WNV neuroinvasive disease (WNND) prediction and identify avenues for improvement. Methods We performed a multi-model comparative assessment of probabilistic forecasts submitted by 15 teams for annual WNND cases in US counties for 2020 and assessed forecast accuracy, calibration, and discriminatory power. In the evaluation, we included forecasts produced by comparison models of varying complexity as benchmarks of forecast performance. We also used regression analysis to identify modeling approaches and contextual factors that were associated with forecast skill. Results Simple models based on historical WNND cases generally scored better than more complex models and combined higher discriminatory power with better calibration of uncertainty. Forecast skill improved across updated forecast submissions submitted during the 2020 season. Among models using additional data, inclusion of climate or human demographic data was associated with higher skill, while inclusion of mosquito or land use data was associated with lower skill. We also identified population size, extreme minimum winter temperature, and interannual variation in WNND cases as county-level characteristics associated with variation in forecast skill. Conclusions Historical WNND cases were strong predictors of future cases with minimal increase in skill achieved by models that included other factors. Although opportunities might exist to specifically improve predictions for areas with large populations and low or high winter temperatures, areas with high case-count variability are intrinsically more difficult to predict. Also, the prediction of outbreaks, which are outliers relative to typical case numbers, remains difficult. Further improvements to prediction could be obtained with improved calibration of forecast uncertainty and access to real-time data streams (e.g. current weather and preliminary human cases). Graphical Abstract

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Physics guided machine learning for multi-material decomposition of tissues from dual-energy CT scans of simulated breast models with calcifications

We introduce a physics guided data-driven method for image-based multi-material decomposition for dual-energy computed tomography (CT) scans. The method is demonstrated for CT scans of virtual human phantoms containing more than two types of tissues. The method is a physics-driven supervised learning technique. We take advantage of the mass attenuation coefficient of dense materials compared to that of muscle tissues to perform a preliminary extraction of the dense material from the images using unsupervised methods. We then perform supervised deep learning on the images processed by the extracted dense material to obtain the final multi-material tissue map. The method is demonstrated on simulated breast models with calcifications as the dense material placed amongst the muscle tissues. The physics-guided machine learning method accurately decomposes the various tissues from input images, achieving a normalized root-mean-squared error of 2.75%.

Gopalakrishnan Meena, Murali↗
NASA NTRS1995

Visual interface for space and terrestrial analysis

The management of large geophysical and celestial data bases is now, more than ever, the most critical path to timely data analysis. With today's large volume data sets from multiple satellite missions, analysts face the task of defining useful data bases from which data and metadata (information about data) can be extracted readily in a meaningful way. Visualization, following an object-oriented design, is a fundamental method of organizing and handling data. Humans, by nature, easily accept pictorial representations of data. Therefore graphically oriented user interfaces are appealing, as long as they remain simple to produce and use. The Visual Interface for Space and Terrestrial Analysis (VISTA) system, currently under development at the Naval Research Laboratory's Backgrounds Data Center (BDC), has been designed with these goals in mind. Its graphical user interface (GUI) allows the user to perform queries, visualization, and analysis of atmospheric and celestial backgrounds data.

Dombrowski, Edmund G.↗
NASA NTRS2010

Cascade Distillation Subsystem Development: Early Results from the Exploration Life Support Distillation Technology Comparison Test

In 2009, the Cascade Distillation Subsystem (CDS) wastewater processor (Honeywell International, Torrance, California) was assessed in the National Aeronautics and Space Administration (NASA) Exploration Life Support (ELS) distillation comparison test. The purpose of the test was to collect data to support down-selection and development of a primary distillation technology for application in a lunar outpost water recovery system. The CDS portion of the comparison test was conducted between May 6 and August 19, 2009. The system was challenged with two pretreated test solutions, each intended to represent a feasible wastewater generated in a surface habitat. The 30-day equivalent wastewater loading volume for a crew of four was intended to be processed for each wastewater solution. Test Solution 1 consisted of a mixed stream containing human-generated urine and humidity condensate. Test Solution 2 contained the addition of human-generated hygiene wastewater to the solution 1 waste stream components. Approximately 1500 kg of total wastewater was processed through the CDS during testing. Respective recoveries per solution were 93.4 +/- 0.7 and 90.3 +/- 0.5 percent. The average specific energy of the system during testing was calculated to be less than 120 W-hr/kg. The following paper provides detailed information and data on the performance of the CDS as challenged per the ELS distillation comparison test.

Callahan, Michael R.↗
NASA NTRS2011

Human Thermal Model Evaluation Using the JSC Human Thermal Database

The human thermal database developed at the Johnson Space Center (JSC) is used to evaluate a set of widely used human thermal models. This database will facilitate a more accurate evaluation of human thermoregulatory response using in a variety of situations, including those situations that might otherwise prove too dangerous for actual testing--such as extreme hot or cold splashdown conditions. This set includes the Wissler human thermal model, a model that has been widely used to predict the human thermoregulatory response to a variety of cold and hot environments. These models are statistically compared to the current database, which contains experiments of human subjects primarily in air from a literature survey ranging between 1953 and 2004 and from a suited experiment recently performed by the authors, for a quantitative study of relative strength and predictive quality of the models. Human thermal modeling has considerable long term utility to human space flight. Such models provide a tool to predict crew survivability in support of vehicle design and to evaluate crew response in untested environments. It is to the benefit of any such model not only to collect relevant experimental data to correlate it against, but also to maintain an experimental standard or benchmark for future development in a readily and rapidly searchable and software accessible format. The Human thermal database project is intended to do just so; to collect relevant data from literature and experimentation and to store the data in a database structure for immediate and future use as a benchmark to judge human thermal models against, in identifying model strengths and weakness, to support model development and improve correlation, and to statistically quantify a model s predictive quality.

Cognata, T.↗
NASA NTRS2019

Discovery of Activities via Statistical Clustering of Fixation Patterns

Human behavior often consists of a series of distinct activities, each characterized by a unique pattern of interaction with the visual environment. This is true even in a restricted domain, such as a pilot flying an airplane; in this case, activities with distinct visual signatures might be things like communicating, navigating, monitoring, etc. We propose a novel analysis method for gaze-tracking data, to perform blind discovery of these hypothetical activities. We compare, not individual fixations, but groups of fixations aggregated over a fixed time interval (Tau). We assume that the environment has been divided into a finite set of discrete areas-of-interest (AOIs). For a given time interval, we compute the proportion of time spent fixating each AOI, resulting in an N-dimensional vector, where N is the number of AOIs. These proportions can be converted to integer counts by multiplying by Tau divided by the average fixation duration, a parameter that we fix at 283 milliseconds. We compare different intervals by computing the chi-squared statistic. The p-value associated with the statistic is the likelihood of observing the data under the hypothesis that the data in the two intervals were generated by a single process with a single set of probabilities governing the fixation of each AOI. We cluster the intervals, first by merging adjacent intervals that are sufficiently similar, optionally shifting the boundary between non-merged intervals to maximize the difference. Then we compare and cluster non-adjacent intervals. The method is evaluated using synthetic data generated by a hand-crafted set of activities. While the method generally finds more activities than put into the simulation, we have obtained agreement as high as 80 percent between the inferred activity labels and ground truth.

Eye Movements↗
NASA NTRSDate not supplied

Space Launch System Artemis I CubeSats: SmallSat Vanguards of Exploration, Science and Technology

When NASA’s Space Launch System (SLS) rocket launches in 2021 with the Orion crew vehicle, it will lay the foundation for NASA’s goal of landing the first woman and the next man on the Moon as part of the Artemis program. This first flight—Artemis I—will also mark a milestone for smallsats. Thirteen6U CubeSats are manifested on the Artemis I flight, the first fleet of CubeSats carried as a ride share opportunity to deep space.(NASA’s first CubeSats to deep space, the twin Mars Cube One [MarCO] spacecraft, were an integral part of the InSight Mars lander mission). The Artemis I CubeSat manifest represents a diverse collection of smallsats performing an array of science missions and technology demonstrations. Payloads from NASA, international partners, academia and industry will execute a variety of experiments. Several smallsats will perform lunar-focused missions that may return data that addresses Strategic Knowledge Gaps (SKGs) in the agency’s lunar exploration program. Indeed, the Artemis I CubeSats will be in the vanguard of the agency’s 21st-century lunar program. The Artemis I missions will produce data to support space radiation awareness,crewed landings and in-situ resource utilization, helping to support a sustained human lunar presence. Several of the Artemis I CubeSats are demonstrating new technologies, including propulsion capabilities. Among the Artemis I CubeSats are three selected through NASA’s Cube Quest Challenge, part of the Centennial Challenges program. These three missions will compete for prize money while meeting specific technical development goals. Payloads from the Japanese and Italian space agencies provide an early opportunity for international involvement in the Artemis program. Student involvement in almost half of the payloads allow STEM engagement with NASA’s Artemis program. The SLS Block 1 vehicle for the Artemis I flight is manufactured with several elements delivered to Kennedy Space Center (KSC) and being prepared for stacking and integration. The new-development of the program, the 212-footcore stage with its four RS-25 engines installed is currently at Stennis Space Center (SSC) for “green run” testing. Following the green run test campaign, the stage will ship to KSC, where it will be integrated with the rest of the vehicle, including the upper stage adapter, where the Artemis I smallsats will be housed.

Kimberly F Robinson↗
DOE OSTI2016

Net-Zero Energy Home Grows Up: Lessons and Puzzles from 10 Years of Data; Preprint

In 2005, Habitat for Humanity of Metro Denver, with support from NREL and other partners, built one of the first homes in the US to achieve net-zero energy based on monitored data. A family of three moved into the house when it was completed and lives there still. The home has been monitored continuously for the past ten years. Although PV production has remained steady, net energy performance has varied each year. The home was a net producer of energy annually in each of the first three years and in the ninth year, but not in years four through eight. Over the years, the PV system provided between 124% and 64% of the home source energy use. Electricity use in the home increased steadily during the first eight years, even though no significant new appliance was introduced into the house, such as a window air conditioner. Miscellaneous electric loads and space heating, both strongly dependent on occupant behavior, appear to be primarily responsible for the observed increase in energy use. An interesting aspect of this case study is how, even within a single family, natural changes in occupant lifestyles over time (e.g., kids growing up, schedules changing) can substantially impact the overall energy intensity of a home. Data from the last ten years will be explored for lessons learned that can improve the way we design low-load homes without sacrificing comfort or convenience for the occupants, and how we can make realistic predictions of long-term energy performance.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2016

A Net-Zero Energy Home Grows Up: Lessons and Puzzles from 10 Years of Data

In 2005, Habitat for Humanity of Metro Denver, with support from NREL and other partners, built one of the first homes in the US to achieve net-zero energy based on monitored data. A family of three moved into the house when it was completed and lives there still. The home has been monitored continuously for the past ten years. Although PV production has remained steady, net energy performance has varied each year. The home was a net producer of energy annually in each of the first three years and in the ninth year, but not in years four through eight. Over the years, the PV system provided between 124% and 64% of the home source energy use. Electricity use in the home increased steadily during the first eight years, even though no significant new appliance was introduced into the house, such as a window air conditioner. Miscellaneous electric loads and space heating, both strongly dependent on occupant behavior, appear to be primarily responsible for the observed increase in energy use. An interesting aspect of this case study is how, even within a single family, natural changes in occupant lifestyles over time (e.g., kids growing up, schedules changing) can substantially impact the overall energy intensity of a home. Data from the last ten years will be explored for lessons learned that can improve the way we design low-load homes without sacrificing comfort or convenience for the occupants, and how we can make realistic predictions of long-term energy performance.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Cyberattack Scenarios for the Rancor Microworld Simulator

The digitization of new generation nuclear power plants increases the risk of cyber-physical attacks. Hence, the collection of data from operators that respond to realistic cyberattacks can provide a paramount insight on the correlation of cyber evidence and physical alerts. The simplicity and configurability of the Rancor Microworld Simulator, enables the training of non-expert operators in a PWR environment, and the extensive and tailored collection of data. Therefore, we develop the necessary tools and infrastructure in Rancor that allow such attacks to take place. Additionally, we perform these attacks to examine the attention and situation awareness of operators during malicious infiltrations.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRS1996

Noninvasive markers of bone metabolism in the rhesus monkey: normal effects of age and gender

Measurement of bone turnover in conditions such as osteoporosis has been limited by the need for invasive iliac bone biopsy to reliably determine parameters of bone metabolism. Recent advances in the area of serum and urinary markers of bone metabolism have raised the possibility for noninvasive measurements; however, little nonhuman primate data exist for these parameters. The purpose of this experiment was to define the normal range and variability of several of the newer noninvasive bone markers which are currently under investigation in humans. The primary intent was to determine age and gender variability, as well as provide some normative data for future experiments in nonhuman primates. Twenty-four rhesus macaques were divided into equal groups of male and female according to the following age groupings: 3 years, 5-10 years, 15-20 years, and > 25 years. Urine was collected three times daily for a four-day period and measured for several markers of bone turnoverm including pyridinoline (PYD), deoxypyrodinoline (DPD), hydroxyproline, and creatinine. Bone mineral density measurements of the lumbar spine were performed at the beginning and end of the study period. Serum was also obtained at the time of bone densitometry for measurement of osteocalcin levels by radioimmunoassay. There were no significant differences in bone mineral density, urine PYD, or urine DPD based on gender. Bone density was lowest in the youngest animals, peaked in the 15-20-year group, but again decreased in the oldest animals. The osteocalcin, PYD, and DPD levels followed an inversely related pattern to bone density. The most important result was the relative age insensitivity of the ratio of PYD:DPD in monkeys up to age 20 years. Since bone density changes take months or years to become measurable and iliac biopsies are invasive, the PYD/DPD marker ratio may have important implications for rapid noninvasive measurement of the effects of potential treatments for osteoporosis in the non-human primate model.

NASA Discipline Musculoskeletal↗
DOE OSTI2014

A simplified HTc rf SQUID to analyze the human cardiac magnetic field

We have developed a four-channel high temperature radio-frequency superconducting quantum interference device (HT{sub c} rf SQUID) in a simple magnetically shielded room (MSR) that can be used to analyze the cardiac magnetic field. It is more robust and compact than existing systems. To achieve the high-quality magnetocardiographic signal, we explored new adaptive software gradiometry technology constructed by the first-order axial gradiometer with a baseline of 80mm, which can adjust its performance timely with the surrounding conditions. The magnetic field sensitivity of each channel was less than 100fT/√Hz in the white noise region. Especially, in the analysis of MCG signal data, we proposed the total transient mapping (TTM) technique to visualize current density map (CDM), then we focused to observe the time-varying behavior of excitation propagation and estimated the underlying currents at T wave. According to the clear 3D imaging, isomagnetic field and CDM, the position and distribution of a current source in the heart can be visualized. It is believed that our four-channel HT{sub c} rf SQUID magnetometer based on biomagnetic system is available to detect MCG signals with sufficient signal-to-noise (SNR) ratio. In addition, the CDM showed the macroscopic current activation pattern, in a way, it has established strong underpinnings for researching the cardiac microscopic movement mechanism and opening the way for its use in clinical diagnosis.

36 MATERIALS SCIENCE↗
NASA NTRS2002

A quantitative comparison of simultaneous BOLD fMRI and NIRS recordings during functional brain activation

Near-infrared spectroscopy (NIRS) has been used to noninvasively monitor adult human brain function in a wide variety of tasks. While rough spatial correspondences with maps generated from functional magnetic resonance imaging (fMRI) have been found in such experiments, the amplitude correspondences between the two recording modalities have not been fully characterized. To do so, we simultaneously acquired NIRS and blood-oxygenation level-dependent (BOLD) fMRI data and compared Delta(1/BOLD) (approximately R(2)(*)) to changes in oxyhemoglobin, deoxyhemoglobin, and total hemoglobin concentrations derived from the NIRS data from subjects performing a simple motor task. We expected the correlation with deoxyhemoglobin to be strongest, due to the causal relation between changes in deoxyhemoglobin concentrations and BOLD signal. Instead we found highly variable correlations, suggesting the need to account for individual subject differences in our NIRS calculations. We argue that the variability resulted from systematic errors associated with each of the signals, including: (1) partial volume errors due to focal concentration changes, (2) wavelength dependence of this partial volume effect, (3) tissue model errors, and (4) possible spatial incongruence between oxy- and deoxyhemoglobin concentration changes. After such effects were accounted for, strong correlations were found between fMRI changes and all optical measures, with oxyhemoglobin providing the strongest correlation. Importantly, this finding held even when including scalp, skull, and inactive brain tissue in the average BOLD signal. This may reflect, at least in part, the superior contrast-to-noise ratio for oxyhemoglobin relative to deoxyhemoglobin (from optical measurements), rather than physiology related to BOLD signal interpretation.

Non-NASA Center↗
NASA NTRS2018

A Statistical Study of Solar Particle Events in Flux and Dose

The high-energy protons from solar energetic particle (SEP) events present a hazard to space systems: damage to science instruments/electronics/materials or to astronauts. A reliable estimate of the high-energy proton environment is critical to assure mission success. Important characteristics of an SEP event are fluence, peak flux, energy spectrum, time to reach the peak flux, time to reach peak dose, and properties of the cumulative dose profile after an event starts. All of these characteristics are important to understand in order to design space missions properly for both robotic and human missions. Because of the unpredictable and sporadic nature of SEP events, statistical models are often used to represent the SEP parameters described above. In a study by Jun et al. (2007), the statistics of event fluences, durations, and time intervals between events were investigated using the then available historical SEP dataset obtained from the instruments onboard the IMP-8 spacecraft. Since then, a more comprehensive SEP dataset based off of IMP-8 and GOES called Reference Data Set Version 2.0 (RDSv2.0) has become available covering the SEP events up to Year 2015 under a framework of the European Space Agency's (ESA's) Solar Energetic Particle Environment Modelling (SEPEM) project (Jiggens et al., 2018). The main objectives of this statistical study of SEP events are two-fold: First, the statistics of peak fluxes, event fluences, durations, and time intervals will be re-visited by using RDSv2.0; Second, the statistical analyses of flux and dose timing will be performed using the same dataset RDSv2.0. The results of this study will address the statistical properties of all key parameters for designing a spacecraft or a human mission where the SEP environment is an important consideration.

Whitman, K.↗
NASA NTRS1989

Building an environment model using depth information

Modeling the environment is one of the most crucial issues for the development and research of autonomous robot and tele-perception. Though the physical robot operates (navigates and performs various tasks) in the real world, any type of reasoning, such as situation assessment, planning or reasoning about action, is performed based on information in its internal world. Hence, the robot's intentional actions are inherently constrained by the models it has. These models may serve as interfaces between sensing modules and reasoning modules, or in the case of telerobots serve as interface between the human operator and the distant robot. A robot operating in a known restricted environment may have a priori knowledge of its whole possible work domain, which will be assimilated in its World Model. As the information in the World Model is relatively fixed, an Environment Model must be introduced to cope with the changes in the environment and to allow exploring entirely new domains. Introduced here is an algorithm that uses dense range data collected at various positions in the environment to refine and update or generate a 3-D volumetric model of an environment. The model, which is intended for autonomous robot navigation and tele-perception, consists of cubic voxels with the possible attributes: Void, Full, and Unknown. Experimental results from simulations of range data in synthetic environments are given. The quality of the results show great promise for dealing with noisy input data. The performance measures for the algorithm are defined, and quantitative results for noisy data and positional uncertainty are presented.

Roth-Tabak, Y.↗