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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 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Drone Applications for Wildfires and Other Emergency Situations

Potential Solutions to Wildfires This project is looking at multiple aspects of the use of UAV’s during wildfire season. This project identifies multiple solutions to communication problems, early action response, and innovative tactics to fight wildfires during the dark hours of the second shift. This project will identify the features and innovations needed to create a second shift that can more effectively fight wildland fires at night. In addition, this project will look to find which satellite systems work best for detection of wildfires, with a special focus on remote locations with more rural communities. There will also be a focus on ways to improve current UAVs and sensors for aerial fire surveillance as well as the understanding on how to establish a safe airspace for these UAVs during wildfires. More specifically, unmanned ariel vehicles (UAV) or drones can be used during natural disasters and other situations to help first responders be a more efficient team, ultimately saving hundreds of more lives. Depending on the situation, drones can be equipped with many different accessories, each with their own advantages. When it comes to operating a drone, communication between the first responder, dispatcher, and the person flying the drone is very important when exchanging useful information. A focus on existing systems, and what changes could be made to create more novel systems will also be shown. Moreover, wildfires not only pose a hazard to human safety and a dent on communication methods, but it also has detrimental effects on the environment. Specifically, the use of common fire retardants have dangerous health effects on human health and the environment as a whole. Therefore, this project will also explore the use of alternative eco-friendly fire retardants and recent innovations to the use of sustainable retardants.

Drones↗
NASA NTRSDate not supplied

Performance Evaluation of a Shaped Sonic Boom Detector and Classifier

NASA will soon fly the X‑59 aircraft over selected communities to evaluate community responses to shaped sonic booms. Community tests will include dozens of deployed acoustic sensors capable of measuring and detecting shaped sonic boom waveforms in situ for rapid onboard analysis. To this end, we present a sonic boom detector and classifier. The sonic boom detector identifies a shaped sonic boom within a measured acoustical waveform by calculating the cross-correlation with a template shaped sonic boom waveform. The sonic boom classifier determines whether the identified event is indeed a shaped sonic boom based on the correlation coefficient and the calculated noise exposure level. We evaluate these algorithms using simulations of on- and off-design X-59 sonic boom waveforms injected into previously measured 30 s ambient noise recordings. Results of this case study indicate that the detector identifies a sonic boom with an accuracy of ±100 ms in 99.98% of the cases. Furthermore, for a given 30 s measurement, the classifier shows true-positive rates of approximately 0.9999 when the false-positive rate is 10e-3. The case study demonstrates that the recommended onboard sonic boom detector and classifier should be highly capable of identifying shaped sonic booms.

sonic boom↗
DOE OSTI2021

ExoMars Mars Organic Molecule Analyzer (MOMA) Laser Desorption/Ionization Mass Spectrometry (LDI-MS) Analysis of Phototrophic Communities from a Silica-Depositing Hot Spring in Yellowstone National Park, USA

The Mars Organic Molecule Analyzer (MOMA) is a key scientific instrument on the ExoMars Rover mission. MOMA is designed to detect and characterize organic compounds, over a wide range of volatility and molecular weight, in samples obtained from up to two meters below the martian surface. Thorough analog sample studies are required to best prepare to interpret MOMA data collected on Mars. We present here the MOMA characterization of Mars analog samples collected from an alkaline silica depositing hot spring in Yellowstone National Park, WY, USA. These samples contain microbial streamer communities composed primarily of oxygenic and anoxygenic phototrophs. Additionally, in a study focused on detection of key classes of nonvolatile organics, samples of microbial streamers and their total lipid extract (TLE) have been measured on a MOMA Engineering Test Unit (ETU) instrument using its laser desorption/ionization mass spectrometry (LDI-MS) mode. MOMA LDI-MS detected a variety of lipids and pigments in the TLE sample. Species such as chlorophyll a were also detected from the streamer sample with the help of mass isolation. The results add to the LDI-MS sample characterization database, as well as demonstrate the benefit of using mass isolation on the MOMA instrument to reveal the presence of complex organics, and potential biomarkers, preserved in a natural sample, providing guidance to the in situ analysis of surface samples during Mars operations.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

PV Validation Hub

The Validation Hub will be a clearinghouse for the transfer of novel algorithms and software from the PV research community to industry. Potential algorithms tested in the Hub could include the estimation of various PV loss factors and the detection of various operational issues. The primary function of the Hub will be for developers to submit executable code which will run on hosted data sets. Developers will receive private reports on the accuracy and performance (e.g., run-time) of the submitted algorithms, and public high level summaries will be hosted. These summaries will indicate the organization who submitted the algorithm (e.g., links to GitHub pages, documentation websites, etc.), high-level accuracy metrics, and standardized performance metrics. These results will be stored in a publicly available database, accessible through the Hub, with the ability for users to sort and filter the results. In short, the Hub will be presented to public users as a collection of interactive leaderboards, organized around specific analysis tasks pertinent to the PV data science community. These tasks include things such as the estimation of various PV loss factors and the detection of various operational issues. We will present progress on the development of this hub, including preliminary results of comparative validation of PV data science algorithms and progress towards building the platform itself.

algorithm↗
DOE OSTI2020

Metagenomic Insight into Environmentally Challenged Methane-Fed Microbial Communities

In this study, we aimed to investigate, through high-resolution metagenomics and metatranscriptomics, the composition and the trajectories of microbial communities originating from a natural sample, fed exclusively with methane, over 14 weeks of laboratory incubation. This study builds on our prior data, suggesting that multiple functional guilds feed on methane, likely through guild-to-guild carbon transfer, and potentially through intraguild and intraspecies interactions. We observed that, under two simulated dioxygen partial pressures—low versus high—community trajectories were different, with considerable variability among the replicates. In all microcosms, four major functional guilds were prominently present, representing Methylococcaceae (the true methanotrophs), Methylophilaceae (the nonmethanotrophic methylotrophs), Burkholderiales, and Bacteroidetes. Additional functional guilds were detected in multiple samples, such as members of Opitutae, as well as the predatory species, suggesting additional complexity for methane-oxidizing communities. Metatranscriptomic analysis suggested simultaneous expression of the two alternative types of methanol dehydrogenases in both Methylococcaceae and Methylophilaceae, while high expression of the oxidative/nitrosative stress response genes suggested competition for dioxygen among the community members. The transcriptomic analysis further suggested that Burkholderiales likely feed on acetate that is produced by Methylococcaceae under hypoxic conditions, while Bacteroidetes likely feed on biopolymers produced by both Methylococcaceae and Methylophilaceae.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRSDate not supplied

Cloud-Based Solutions for Monitoring Coastal Ecosystems and Prioritization of Restoration Efforts Across Belize

In recent years the availability of automated change detection algorithms in Google Earth Engine has permitted cloud-based processing of large time series of satellite imagery. Models such as the Continuous Change Detection and Classification (CCDC), CCDC-Spectral Mixture Analysis (CCDC-SMA), and Landsat-based Detection of Trends in Disturbance and Recovery (LandTrendr) allow users to exploit decades of Earth Observations (EO) , leveraging the Landsat archive and data from other sensors to detect disturbance in forest ecosystems. Despite the wide adoption of these methods, robust documentation and growing community of users, little research has explored their use in mangrove environments. Mangroves are dynamic environments subject to changes due to not only the natural migration of mudflats but also coastal erosion, urban expansion, aquaculture practices, etc. This work aims to identify best practices for the application of these models to identify and monitor changes in the Belizean mangroves, which experienced an estimated 5.4% decrease in extent between 1980 and 2017 (Cherrington et al. 2020). Partnering directly with the Belizean Forest Department, our team will develop a replicable, efficient methodology to annually update the country’s mangrove extent employing EO-based change detection. This collaboration supports Belize’s marine conservation and climate resilience efforts, such as its Blue Bond agreement with the Nature Conservancy, building on national processes to monitor these critical ecosystems.

Mangroves↗
DOE OSTI2022

Sandwich Hybridization Assay for In Situ Real-Time Cyanobacterial Detection and Monitoring: A Review

As cyanobacterial harmful algal bloom (cHAB) events increase in scale, severity, frequency, and duration around the world, rapid and accurate monitoring and characterization tools have become critically essential for regulatory and management decision-making. The composition of cHAB-forming cyanobacteria community can change significantly over time and space and be altered by sample preservation and transportation, making in situ monitoring necessary to obtain real-time and localized information. Sandwich hybridization assay (SHA) utilizes capture oligonucleotide probes for sensitive detection of target-specific nucleic acid sequences. As an amplification-free molecular biology technology, SHA can be adapted for in-situ, real-time or near real-time detection and qualitatively or semi-quantitatively monitoring of cHAB-forming cyanobacteria, owing to its characteristics such as being rapid, portable, inexpensive, and amenable to automation, high sensitivity, specificity and robustness, and multiplexing (i.e., detecting multiple targets simultaneously). Despite its successful application in the monitoring of marine and freshwater phytoplankton, there is still room for improvement. The ability to identify a cHAB community rapidly would decrease delays in cyanotoxin analyses, reduce costs, and increase sample throughput, allowing for timely actions to improve environmental and human health and the understanding of short- and long-term bloom dynamics. Real-time detection and quantitation of HAB-forming cyanobacteria is essential for improving environmental and public health and reducing associated costs. We review and propose to apply SHA for in situ cHABs monitoring.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Density Dependence in Three Snake River Sockeye Salmon Nursery Lakes in Central Idaho

Abstract Snake River Sockeye Salmon Oncorhynchus nerka, listed as an endangered species in 1991, currently inhabit three nursery lakes (Redfish, Pettit, and Alturas lakes) in the Sawtooth Valley, Idaho. Conspecific kokanee (lacustrine Sockeye Salmon) are also present in the lakes. Snake River Sockeye Salmon recovery efforts, initially focused on genetic conservation, are now attempting to rebuild naturally spawning populations using hatchery supplementation. However, in Sockeye Salmon nursery lakes, density dependence is frequently observed when elevated O. nerka abundance leads to declines in zooplankton biomass, body size, and shifts in community composition. In turn, these changes lead to reductions in juvenile O. nerka growth rates, survival, and adult returns. We examined a long-term data set of O. nerka population metrics and associated zooplankton community metrics. We found evidence of density dependence within and among nursery lakes. We detected differences in zooplankton biomass, lengths of preferred zooplankton prey (Daphnia spp. and cyclopoid copepods), parr growth rates, and age-1 smolt size among the three lakes. We found negative relationships between O. nerka density and zooplankton biomass and size. We identified positive relationships between zooplankton biomass and two response variables: smolt size at migration and growth rates of hatchery parr. The relationships were generally similar among lakes. Variable outcomes were a result of differences in O. nerka density (or zooplankton biomass), controlled primarily by the relative proportion of spawning and rearing habitat in each lake. Understanding unique lake habitats, ecological interactions, and the role of density dependence is germane to management of Snake River Sockeye Salmon populations.

Griswold, Robert G.↗
DOE OSTI2023

Realistic application of short-lived fission product delayed neutron, gamma-ray analysis for simultaneous nondestructive trace quantification of U, Pu mixtures on cellulose swipes

Detection and characterization of fissile traces are of interest to the international nuclear nonproliferation community, including the International Atomic Energy Agency. Pre-inspection check samples are analyzed by neutron activation analysis at the High Flux Isotope Reactor operated by the Oak Ridge National Laboratory under the umbrella of the IAEA Network of Analytical Laboratories. The simultaneous quantification of U and Pu mixtures was accomplished using the combined delayed neutron (DN) delayed gamma-ray (DG) method to analyze cellulose swipes with actinide loading <1ng in a blind field trial. The total fissile quantity was measured by the DN counts and the relative proportions of U, Pu were determined by calibration of the 104 Tc / 141 Ba fission product count ratio using known mixtures. The DNDG method demonstrated high accuracy in flagging the presence of 239 Pu in uranium down to <100 pg mass loading. In conclusion, peak significance tests helped to control false positive Pu flagging and simultaneous quantification of U and Pu loading was accomplished on samples that passed the significance tests.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Foundation model framework for all tasks involving jet physics

Foundation models use large datasets to build an effective representation of data that can be deployed on diverse downstream tasks. Previous research developed the omnilearn foundation model for jet physics, using unique properties of particle physics, and showed that it could significantly advance discovery potential across collider experiments. This paper introduces a major upgrade, resulting in the omnilearned framework. This framework has three new elements: (1) updates to the model architecture and training, (2) using over 1 × 10 9 jets used for training, and (3) providing well-documented software for accessing all datasets and models. We demonstrate omnilearned with three representative tasks: top-quark jet tagging with the community delphes-based benchmark dataset, b tagging with ATLAS full simulation, and anomaly detection with CMS experimental data. In each case, omnilearned is the state of the art, further expanding the discovery potential of past, current, and future collider experiments.

Bhimji, Wahid [Lawrence Berkeley National Laborato↗
DOE OSTI2020

Hyperspectral Raman Imaging using a Spatial Heterodyne Spectrometer (SHS)

Savannah River National Laboratory, and the larger community, has limited chemical-specific imaging capabilities, which would be beneficial for remote detection of threat chemicals or use in inaccessible and harsh environments, as well as in-line process monitoring. The project objective is to develop a novel, rugged, highly sensitive spectrometer to support real-time, chemically specific imaging using hyperspectral Raman spectroscopy.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRS1978

Interstellar contact in an evolving universe

The evolution of organization in the universe is considered. It is proposed that a circum-solar community, and eventually a galactic community represent the next levels of organization in this evolutionary process. Possible strategies for detecting other technological civilizations in the galaxy are discussed.

Kuiper, T. B. H.↗
NASA NTRS2013

Astrophysics of Super-Massive Black Hole Mergers

We present here an overview of recent work in the subject of astrophysical manifestations of super-massive black hole (SMBH) mergers. This is a field that has been traditionally driven by theoretical work, but in recent years has also generated a great deal of interest and excitement in the observational astronomy community. In particular, the electromagnetic (EM) counterparts to SMBH mergers provide the means to detect and characterize these highly energetic events at cosmological distances, even in the absence of a space-based gravitational-wave observatory. In addition to providing a mechanism for observing SMBH mergers, EM counterparts also give important information about the environments in which these remarkable events take place, thus teaching us about the mechanisms through which galaxies form and evolve symbiotically with their central black holes.

BLACK HOLE↗
DOE OSTI2024

Lambda baryon production in neutrino-nucleus interactions and light signals reconstruction in the Short-Baseline Near Detector

The field of neutrino physics is nowadays entering the era of precision measurements, with new detectors capable of capturing neutrino interactions with unprecedented detail and high intensity neutrino beams. Liquid Argon Time Projection Chambers (LArTPCs) have become one of the main neutrino detection technologies, providing excellent imaging capabilities and particle identification. The Short-Baseline Near Detector (SBND) at Fermilab is a LArTPC experiment designed to capture neutrinos from the Booster Neutrino Beam (BNB). Its proximity to the beam target (110\,m) and large size (112\,ton) enable the recording of millions of neutrino interactions annually. SBND provides the highest statistics worldwide for neutrino-argon cross-section measurements, facilitating the study of rare channels like Cabibbo-suppressed quasielastic hyperon production. Specifically, this thesis focuses on neutral $\Lambda$ baryon production for which only tens of events have been observed up to date. Our work introduces a novel selection strategy leveraging LArTPC imaging capabilities to identify the distinctive decay signatures of $\Lambda$ baryons, enhancing sensitivity to this channel. Besides being a very mature technology, LArTPCs are an evolving technology. Part of the focus of the new developments lies in harnessing the potential of scintillation light signals. The Photon Detection System (PDS) in SBND has been designed to provide an efficient detection of the scintillation light, representing a major R\&D opportunity in the LArTPC community. Its design provides a high and more uniform light yield, an excellent timing resolution and an independent 3D reconstruction of the events, including the drift coordinate, using exclusively the light signals. This work presents the first comprehensive study of the SBND PDS capabilities. The new developments in the simulation and reconstruction of the light signals in SBND are presented. The whole chain is applied to accurately tag neutrino events through timing information, with a predicted resolution $\mathcal{O}$(2\,ns), and ultimately retrieve the pulse structure of the BNB.

43 PARTICLE ACCELERATORS↗
NASA NTRSDate not supplied

Intelligent Change Detection System: Autonomous Intelligent Machine Agent Model Development

NASA’s significant role in facilitating the harmonious integration of unmanned aircraft systems (UAS), with other aerial vehicles operating in the National Airspace System (NAS), has revealed a need for more advanced technological tools than are being utilized currently. This technology would lend itself to significantly assisting Direct-Action Aviation Personnel (DAAP) with the ingress and egress of UAS operations within the NAS. Providing research findings that would reduce technical barriers, associated with UAS-NAS integration, has been a persistent effort by both NASA and the FAA. One such research effort, pursued by NASA’s Transformative Tools and Technologies – Revolutionary Aviation Mobility (T3-RAM) project, is the development of an autonomous intelligent machine (AIM) agent that would aid DAAP functioning as implemented in remote ground control stations (RGCS). This evolution of the “human-machine” symbiosis, within the aviation environment, is necessary for many reasons. For example, there are projections of large increases to the 864,000 registered UAS and 45,000 aviation operations taking place in the NAS each day. With a data output range from 1 to 20 terabytes per flight or each aerial vehicle, which is projected to have proportional rate increase to that of registered UASs. It is evident, that due to the projected increase of UASs and their generated data, the human-agent’s data managing capabilities will be quickly overwhelmed by the enormous amounts of data emanating in the NAS. The research efforts presented in this paper puts forward results from the development, assessment, and verification of a previously conceptualized AIM-Agent that combats actionable-data (information) errors resulting from the visual perception phenomenon known as “change blindness” (CB). CB has been identified as one of the main culprits of information erroring encountered within the ground control station operator (GCSO) community.

Change Blindness↗
NASA NTRS2014

Potential of Pest and Host Phenological Data in the Attribution of Regional Forest Disturbance Detection Maps According to Causal Agent

Near real time forest disturbance detection maps from MODIS NDVI phenology data have been produced since 2010 for the conterminous U.S., as part of the on-line ForWarn national forest threat early warning system. The latter has been used by the forest health community to identify and track many regional forest disturbances caused by multiple biotic and abiotic damage agents. Attribution of causal agents for detected disturbances has been a goal since project initiation in 2006. Combined with detailed cover type maps, geospatial pest phenology data offer a potential means for narrowing the candidate causal agents responsible for a given biotic disturbance. U.S. Aerial Detection Surveys (ADS) employ such phenology data. Historic ADS products provide general locational data on recent insect-induced forest type specific disturbances that may help in determining candidate causal agents for MODIS-based disturbance maps, especially when combined with other historic geospatial disturbance data (e.g., wildfire burn scars and drought maps). Historic ADS disturbance detection polygons can show severe and extensive regional forest disturbances, though they also can show polygons with sparsely scattered or infrequent disturbances. Examples will be discussed that use various historic disturbance data to help determine potential causes of MODIS-detected regional forest disturbance anomalies.

Spruce, Joseph↗
NASA NTRSDate not supplied

High Sensitive and Low Power Nanosensors for Space and Terrestrial Applications

Nanotechnology offers the ability to work at the molecular level, atom by atom, to create large structures with fundamentally new molecular organization. It is essentially concerned with materials, devices, and systems whose structures and components exhibit novel and significantly improved physical, chemical and biological properties, phenomena, and process control due to their nanoscale size. A nanosensor technology has been developed at NASA Ames using nanostructure, single walled carbon nanotubes (SWNTs). The nanosensors have achieved low detection limit of chemicals in the concentration range of ppm to ppb. Due to large surface area, low surface energy barrier and high thermal and mechanical stability, nanostructured chemical sensors offer higher sensitivity, lower power consumption and a more robust solution than most state-of-the-art systems making them attractive for space and terrestrial applications. An example of a sensor module, the first space flown nano device, will be introduced in this presentation. Such sensors have drawn attention from space community for global weather monitoring, space exploration, life search in the universe, and launch pad fuel leak detection and in-flight cabin air and life support system monitoring, and engine operation monitoring. Additionally, the wireless capability of such sensors can be leveraged to network mobile and fixed-base detection and warning systems for civilian population centers, military bases and battlefields, as well as other high-value or high-risk assets and areas in industry.

Jing Li↗
NASA NTRS2003

Multi-scale variation in spatial heterogeneity for microbial community structure in an eastern Virginia agricultural field

To better understand the distribution of soil microbial communities at multiple spatial scales, a survey was conducted to examine the spatial organization of community structure in a wheat field in eastern Virginia (USA). Nearly 200 soil samples were collected at a variety of separation distances ranging from 2.5 cm to 11 m. Whole-community DNA was extracted from each sample, and community structure was compared using amplified fragment length polymorphism (AFLP) DNA fingerprinting. Relative similarity was calculated between each pair of samples and compared using geostatistical variogram analysis to study autocorrelation as a function of separation distance. Spatial autocorrelation was found at scales ranging from 30 cm to more than 6 m, depending on the sampling extent considered. In some locations, up to four different correlation length scales were detected. The presence of nested scales of variability suggests that the environmental factors regulating the development of the communities in this soil may operate at different scales. Kriging was used to generate maps of the spatial organization of communities across the plot, and the results demonstrated that bacterial distributions can be highly structured, even within a habitat that appears relatively homogeneous at the plot and field scale. Different subsets of the microbial community were distributed differently across the plot, and this is thought to be due to the variable response of individual populations to spatial heterogeneity associated with soil properties. c2003 Federation of European Microbiological Societies. Published by Elsevier Science B.V. All rights reserved.

NASA Discipline Life Support Systems↗