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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 541 records · Page 30
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

DC Fast Charging Infrastructure for Electrified Road Trips

To assess DC fast charging station network required for electrified road trips by 2030 in California, a new charging infrastructure simulation tool/model, EVI-Pro (Electric Vehicle Infrastructure Projection) RoadTrip, has been developed. In contrast to the existing EVI-Pro model that is primarily for short-distance travels, EVI-Pro RoadTrip is exclusively focused on road trips (long-distance travels, 100 or miles per day per vehicle). Also, the charging paradigm or strategy is different. EVI-Pro RoadTrip is built upon waypoint charging, in which vehicles are forced to stop to charge or replenish the on-board batteries, along the routes between origins and destinations. On the other hand, EVI-Pro is based on destination charging, in which charging is conducted when vehicles are parked in destinations (e.g., work, home). EVI-Pro RoadTrip takes coordinate-level origin and destination data for road trips (intra-state as well as domestic or international out-of-state) and estimates energy consumption and charging needs along the routes between origins and destinations on a minute-by-minute resolution. Based on charging demands for electrified road trips across the state, the optimal locations of charging stations are determined accounting for preferred land use types (e.g., commercial areas) and station service area (e.g., 5 or less miles). Based on station-by-station charging load profiles, the required number of plugs/connectors is estimated for each station and entire state. By comparing hosting capacity of the electric grid (circuit-level) and the charging load output from EVI-Pro RoadTrip, capacity deficit is also evaluated.

ADVANCED PROPULSION SYSTEMS,ENERGY STORAGE↗
NASA NTRS2010

The Mothball, Sustainment, and Proposed Reactivation of the Hypersonic Tunnel Facility (HTF) at NASA Glenn Research Center Plum Brook Station

The Hypersonic Tunnel Facility (HTF) located at the NASA Glenn Research Center s Plum Brook Station in Sandusky, Ohio, is the nation s only large-scale, non-vitiated, hypersonic propulsion test facility. The HTF, with its 4-story graphite induction heater, is capable of duplicating Mach 5, 6, and 7 flight conditions. This unique propulsion system test facility has experienced several standby and reactivation cycles. The intent of the paper is to overview the HTF capabilities to the propulsion community, present the current status of HTF, and share the lessons learned from putting a large-scale facility into mothball status for a later restart

Thomas, Scott R.↗
NASA NTRS2018

Natural and Induced Environment around the International Space Station (ISS) as Observed during On-Orbit Operations of the Robotic External Leak Locator (RELL)

Final Document is attached. The Robotic External Leak Locator (RELL) was deployed to the International Space Station (ISS) with the goal of detecting and locating on-orbit leaks around the ISS. Three activities to investigate and corroborate the background natural and induced environment of ISS were performed with RELL as part of the on-orbit validation and demonstration conducted in November – December 2016. The first demonstration activity pointed RELL directly in the ram and wake directions for one orbit each. The ram facing measurements showed high partial pressure for mass-to-charge ratio 16, corresponding to atomic oxygen (AO), as well as the presence of mass-to-charge ratio 17. RELL™s view in the wake-facing direction included more ISS structure and several Environmental Control and Life Support System (ECLSS) on-orbit vents were detected, including the Carbon Dioxide Removal Assembly (CDRA), Russian segment ECLSS, and Sabatier vents. The second demonstration activity pointed RELL at three faces of the P1 Truss segment. Effluents from ECLSS and European Space Agency (ESA) Columbus module on-orbit vents were detected by RELL. The partial pressures of mass-to-charge ratios 17 and 18 remained consistent with the first on-orbit activity of characterizing the natural environment. The third demonstration activity involved RELL scanning an Active Thermal Control System (ATCS) radiator. Three locations along the radiator were scanned and the angular position of RELL with respect to the radiator was varied. Mass-to-charge ratios 16 and 17 both had upward shifts in partial pressure when pointing toward the Radiator Beam Valve Modules (RBVMs), likely corresponding to a known, small ammonia leak.

International Space Station↗
NASA NTRS2009

Root Cause Assessment of Pressure Drop Rise of a Packed Bed of Lithium Hydroxide in the International Space Station Trace Contaminant Control System

The trace contaminant control system (TCCS) located in the International Space Station s (ISS) U.S. laboratory module employs physical adsorption, thermal catalytic oxidation, and chemical adsorption to remove trace chemical contamination produced by equipment offgassing and anthropogenic sources from the cabin atmosphere. The chemical adsorption stage, consisting of a packed bed of granular lithium hydroxide (LiOH), is located after the thermal catalytic oxidation stage and is designed to remove acid gas byproducts that may be formed in the upstream oxidation stage. While in service on board the ISS, the LiOH bed exhibited a change in flow resistance that leading to flow control difficulties in the TCCS. Post flight evaluation revealed LiOH granule size attrition among other changes. An experimental program was employed to investigate mechanisms hypothesized to contribute to the change in the packed bed s flow resistance. Background on the problem is summarized, including a discussion of likely mechanisms. The experimental program is described, results are presented, and implications for the future are discussed.

Aguilera, Tatiana↗
NASA NTRS2018

Natural and Induced Environment Around the International Space Station (ISS) as Observed During On-Orbit Operations of the Robotic External Leak Locator (RELL)

The Robotic External Leak Locator (RELL) was deployed to the International Space Station (ISS) with the goal of detecting and locating on-orbit leaks around the ISS. Three activities to characterize the background natural and induced environment of ISS were performed with RELL as part of the on-orbit validation and demonstration conducted in November and December 2016. The first demonstration activity pointed RELL directly in the ram (+X) and wake (-X) directions for one orbit each. The ram facing measurements showed high partial pressure for mass-to-charge ratio 16, corresponding to atomic oxygen (AO), as well as the presence of mass-to-charge ratio 17. RELL's view in the wake-facing direction included more ISS structure and several Environmental Control and Life Support System (ECLSS) on-orbit vents were detected, including the Carbon Dioxide Removal Assembly (CDRA), Russian segment ECLSS, and Sabatier vents. The second demonstration activity pointed RELL at three faces of the P1 Truss segment. Effluents from ECLSS and European Space Agency (ESA) Columbus module on-orbit vents were detected by RELL. The partial pressures of mass-to-charge ratios 17 and 18 remained consistent with the first on-orbit activity of characterizing the natural environment. The third demonstration activity involved RELL scanning an Active Thermal Control System (ATCS) radiator. Three locations along the radiator were scanned and the angular position of RELL with respect to the radiator was varied. Mass-to-charge ratios 16 and 17 both had upward shifts in partial pressure when pointing toward the Radiator Beam Valve Modules (RBVMs), likely corresponding to a known, small ammonia leak.

Fox, Katie L.↗
NASA NTRS2016

Mars Surface Systems Common Capabilities and Challenges for Human Missions

This paper describes the current status of common systems and operations as they are applied to actual locations on Mars that are representative of Exploration Zones (EZ) - NASA's term for candidate locations where humans could land, live and work on the Martian surface. Given NASA's current concepts for human missions to Mars, an EZ is a collection of Regions of Interest (ROIs) located within approximately 100 kilometers of a centralized landing site. ROIs are areas that are relevant for scientific investigation and/or development/maturation of capabilities and resources necessary for a sustainable human presence. An EZ also contains a habitation site that will be used by multiple human crews during missions to explore and utilize the ROIs within the EZ. The Evolvable Mars Campaign (EMC), a description of NASA's current approach to these human Mars missions, assumes that a single EZ will be identified within which NASA will establish a substantial and durable surface infrastructure that will be used by multiple human crews. The process of identifying and eventually selecting this single EZ will likely take many years to finalized. Because of this extended EZ selection process it becomes important to evaluate the current suite of surface systems and operations being evaluated for the EMC as they are likely to perform at a variety of proposed EZ locations and for the types of operations - both scientific and development - that are proposed for these candidate EZs. It is also important to evaluate proposed EZs for their suitability to be explored or developed given the range of capabilities and constraints for the types of surface systems and operations being considered within the EMC. Four locations identified in the Mars Exploration Program Analysis Group (MEPAG)'s Human Exploration of Mars Science Analysis Group (HEM-SAG) report are used in this paper as representative of candidate EZs that will emerge from the selection process that NASA has initiated. A field station site plan is developed for each of these four HEM-SAG sites. Because of the difficulty in getting equipment and supplies to the surface of Mars, specific assessments have been conducted to identify those systems and processes that can perform in multiple, sometimes completely unrelated, situations. Examples of common systems that are assessed at all of these sites include: (a) habitation and associated logistics storage systems, (b) a centralized power plant capable of supplying power to a geographically distributed (but within the central habitation zone) set of systems, (c) mobility systems that can be used to off-load and move payloads to specific locations at the central field station location that could also be used to traverse long distances to reach some of the more remote ROIs and (d) robotic systems that can support various activities (such as system set up and maintenance) at the field station that could also be used to explore scientific ROIs and used to support site-specific ISRU (In Situ Resource Utilization) production activities.

Toups, Larry↗
NASA NTRS1972

Human performance capabilities in a simulated space station-like environment. 1: Fixed beam luminance and location

The effects of a fixed, intense, one-foot diameter beam of simulated sunlight imaged within the field of view, upon responses to a battery of visual, body balance and stability, eye-hand coordination, and mental tests were studied. Each subject's electrocardiogram and electro-oculograms (vertical and horizontal) were recorded throughout each two-hour testing period within the space-station-like environment. It is possible to say that both subjects adapted to the brightly illuminated white panels in approximately 30 seconds after their first exposure each day and thereafter did not experience ocular fatigue, eye strain, or other kinds of disturbances as a result of these viewing conditions.

Haines, R. F.↗
DOE OSTI2020

A data-driven model for thermodynamic properties of a steam generator under cycling operation

The varying electricity demand from coal power plants due to the intermittent nature of renewable sources leads to load-follow and on/off operations referred to as cycling. Cycling causes transients of properties such as pressure and temperature within various components of the steam generation system.These transients cause increased damage because of fatigue and creep-fatigue interactions shortening the life of components. An algorithm is developed to identify cycling operations from the gross power data. The data-driven model based on artificial neural networks (ANN) is developed using 10 years data from Coal Creek Station power plant located in North Dakota, USA to estimate properties of the steam generator components during cycling operations. Furthermore, the uniqueness of this model is the ability to predict component properties for the cycling as well as base-load operations and is reported for the first time. The ANN model estimates the component properties, for a given gross power profile and initial conditions, as they vary during cycling operations. As a representative example, the ANN estimates are presented for the superheater outlet pressure, reheater inlet temperature, and flue gas temperature at the air heater inlet. The changes in these variables as a function of the gross power over the time duration are compared with measurements to assess the predictive capability of the model. Mean square errors of 4.49E-04 for superheater outlet pressure, 1.62E-03 for reheater inlet temperature, and 4.14E-04 for flue gas temperature at the air heater inlet were observed.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2025

Electrifying education: Exploring the electrification potential of U.S. School bus fleets

We analyze the operations of 270 diesel school buses across the United States to assess their electrification potential and evaluate the impact of various charging strategies on electricity demand. We find that school buses typically follow a two-route schedule on weekdays, featuring extended dwell times between morning and evening trips. Weekday trip distances average 25 miles, while weekend trips average 42 miles. Charging simulations indicate over 90% of the U.S. school bus fleet could be electrified using current technologies (300-mile range at 1.21 kWh/mile with 19.2-kW depot charging) without modifying existing operating patterns. Depot charging is a key enabler of school bus electrification, however, the strategic placement of charging stations at other locations (e.g., schools) can further increase electrification potential. Additionally, we find electric school bus charging to be highly flexible, with charge management capable of reducing peak charging loads at depots by up to 77%.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Design Considerations to Ensure Robustness of the ITER Diagnostics Residual Gas Analyzer

Increasing robustness of the ITER diagnostic residual gas analyzer (DRGA) is critical for the potential control of plasma heating and fuel-cycle processing. Robustness is a requirement for a diagnostic to have a control function. The DRGA is a multisensor diagnostic system capable of resolving isotopic compositions of hydrogen and helium as well as other heavier elements and compounds. The divertor-specific DRGA system is intended to measure the composition of gases in the ITER subdivertor region and midplane. Its analysis station will be located in a port cell at the divertor level. From there, it will sample a slip stream of gas from the cryogenic pump duct. It will then exhaust into a shared roughing line where helium or other light gas impurities, some potentially from other diagnostic systems, are likely to be present. In order to provide reliable measurements, the DRGA must be robust in areas such as plasma optical emission source geometry for a compact design, mitigation of back-streaming from light gases and resilience to the ITER port cell environment, and radiation hardening of the DRGA electronics. By incorporating robustness into the design, areas of plasma heating and fuel-cycle control may be explored with the DRGA for ITER and next-generation fusion devices.

Quinlan, Brendan↗
DOE OSTI2020

Assessment of Spatiotemporal Variability of Evapotranspiration and Its Governing Factors in a Mountainous Watershed at the East River, Colorado, Water: Dataset

This data package contains simulation results of daily evapotranspiration for 17 locations of meteorological stations with different precipitation, air temperature and vegetation within the East River Watershed, Colorado (CLMResult.csv). Daily precipitation data is included for reference. These are the main results of the paper Tran, 2019. Meteorological stations names, latitude and longitude coordinates of meteorological stations, types of lands from the National Land Cover Database, and a comparison with the community land model (CLM) data are also included (Met_LC.csv). The purpose of this data is to analyze the spatio-temporal variations of evapotranspiration at the East River Watershed and understand the factors that control these variations. More information regarding the study, methods, and findings can be found in the Related Reference paper.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

AmeriFlux US-SHC Sagehen Creek Field Station

This is the AmeriFlux version of the carbon flux data for the site US-SHC Sagehen Creek Field Station. Site Description - This tower is located at the Sagehen Creek Field Station of UC Berkeley. The 30m tower near the station has been used for meteorological measurements since at least 2006 and EC flux measurements were started in late June 2017. The area is dominated by coniferous forest with patches of grassland in between.

Wolf, Sebastian [ETH Zurich]↗
DOE OSTI2022

Monitoring Operational States of a Nuclear Reactor Using Seismoacoustic Signatures and Machine Learning

Monitoring nuclear reactors is an important safety and security task with growing requirements. We explore the possibility of using seismic and acoustic data for inferring the power level of an operating reactor. Continuous data recorded at a single seismoacoustic station that is located about 50 m away from a research reactor was visualized and analyzed. The data show a clear correlation between seismoacoustic features and reactor main operational states. We designed a workflow that includes two machine learning (ML) models to classify the reactor operational states (OFF, transition, and ON) and estimate reactor power levels (10%, 30%, 50%, 70%, and 90%). We applied and compared five ML algorithms for the reactor OFF-transition-ON and four approaches for the power level classification. We also compared the performance of ML models trained with seismic-only, acoustic-only, and both types of data. Five-fold cross validations were implemented to assure a thorough evaluation of the model performances. Additionally, the results show the extreme boosting gradient algorithm worked best for the first model, whereas random forests performed best for the second model. Combining seismic and acoustic data leads to better performance than using a single type of data. Seismic data contributed more than acoustic data for both models. We reached an accuracy of 0.98 for reactor OFF and ON. The accuracies for the transition state and power levels are less optimal with a minimum accuracy of 0.66. However, our results suggest seismic and acoustic data contain useful information about the transition state as well as power levels. Seismic and acoustic data could be integrated with other observations to improve monitoring performance.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2022

Cyber Physical Protection for Natural Gas Compression

The secure transport of natural gas through North American pipelines is vital for both home and industrial purposes. GE in collaboration with Baker Hughes and Idaho National Laboratory, completed a US Department of Energy grant program to develop a new cyber-physical protection system that monitors the large compressor stations used to boost pressure and maintain proper gas flow. Algorithms were developed to detect the presence of a cyber-attack that impacts the compressor station physical processes, locate the critical functions being manipulated, and potentially neutralize the attack allowing continued operations. The technology was successfully demonstrated at an operating compressor facility located in New York state.

03 NATURAL GAS↗
DOE OSTI2024

A Computational Review of Privacy-Preserving Mechanisms for the Smart Grid

Smart grid technologies have rapidly become one of the largest and most comprehensive sources of data for the modern utility. For the most part, data streams are seen as an essential tool that enable utilities to carry their day-to-day business operations, but they also create the need for efficient and secure data management strategies. In the context of the smart grid, ensuring data privacy is becoming an increasing concern due to a combination of factors that range from shifts in operational paradigms and rapid technology evolution to changes in legislation. Furthermore, researchers have highlighted the risks associated with improperly protected energy records. For example, energy consumption data from homes could be used to infer the behaviors and habits of home occupants through activity recognition or user profiling (Fan, 2017), which may lead to unfair service pricing, targeted advertising, or other personal security violations. Similarly, Electric Vehicles’ (EVs) charging metadata could be used to reveal private information about the owner such as their payment methods, preferred charging stations, and other locational and timing information that could be used to reconstruct the vehicle owner’s behaviors. The privacy of user data, even when used for statistical analysis or machine learning training processes, also needs to be carefully considered, as an individual’s private traits may still be vulnerable if their inclusion/exclusion greatly impacts the result or could be linked to a public dataset through cross-reference. The breach of user privacy also has severe impacts for organizations that store, transmit, or work on the data in the form of diminishing the public’s trust in them while potentially incurring legal consequences (e.g., fines and suspensions under the European Union General Data Protection Regulation, Health Insurance Portability and Accountability Act, etc.). Because of these risks, several privacy-preserving mechanisms are available to help organizations comply with privacy legislations and prevent the unauthorized and malicious use of user data. In light of these concerns, this report focuses on performing a computational review of privacy-preserving mechanisms that have received a significant amount of interest in literature. It specifically focuses on 1) homomorphic encryption, 2) zero-knowledge proofs, 3) differential privacy, and 4) federated learning. It is worth noting that although many of the methods presented in this document rely on cryptographic primitives, their intent is not to provide perfect secrecy, but rather to enable users to maintain privacy, and thus they shall not be compared or equated to other constructs that are aimed to address cybersecurity constructs.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2026

Outdoor Deployment Data for a Four-Terminal GaAs//Si Tandem Solar Mini-Module

This dataset contains the complete outdoor measurement and analysis data for a mechanically stacked, four-terminal (4T) gallium arsenide (GaAs)//silicon (Si) tandem solar mini-module deployed from October 2019 to January 2021 at the Solar Radiation Research Laboratory (SRRL) in Golden, Colorado, USA. The data support a performance modeling and degradation analysis framework for tandem photovoltaic devices, as described in the accompanying publication. The dataset includes: (1) current–voltage (J–V) characteristics of each sub-cell measured approximately every five minutes, with extracted performance parameters; (2) spectral irradiance from an EKO MS-710 WISER spectroradiometer, along with derived spectral mismatch ratios (SMR) and average photon energy (APE); (3) one-minute resolution meteorological data from the co-located SRRL weather station and GPS-derived precipitable water vapor (PWV); (4) pre-deployment laboratory characterization (external quantum efficiency, J–V curves, standard test conditions parameters); (5) outdoor-extracted temperature and PWV correction coefficients; and (6) PVcircuit equivalent-circuit simulation outputs used for model validation. Degradation rates of −4.1 ± 0.2 %/year (GaAs) and −2.5 ± 0.9 %/year (Si) were determined using a filtering and normalization methodology adapted for fixed-tilt tandem modules. All data are provided in open, portable formats (Apache Parquet, CSV, JSON) to enable full reproducibility of the published analysis.

14 SOLAR ENERGY↗
NASA NTRS1968

Post-landing tracking data analysis

Surveyor 7 post-landing tracking data analysis, and determining selenocentric location of probe and geocentric locations of tracking stations

Winn, F. B.↗
NASA NTRS1969

Sferics

The properties of sferics (the electric and magnetic fields generated by electrified clouds and lightning flashes) are briefly surveyed; the source disturbance and the influence of propagation being examined. Methods of observing sferics and their meteorological implications are discussed. It is concluded that close observations of electrostatic and radiation fields are very informative, respectively, upon the charge distribution and spark processes in a cloud; that ground-level sferics stations can accurately locate the positions of individual lightning flashes and furnish valuable knowledge on the properties of the discharges; but that satellite measurements only provide general information on the level of thundery activity over large geographical regions.

Pierce, E. T.↗