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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 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
NASA NTRS1986

Speculations on nature and extent of Archean basement in Labrador as indicated by SR, ND and PB isotopic systematics of proterozoic intrusives

The Sm-Nd and Rb-Sr isotopic compositions of mid to late Proterozoic (approximately 1.6 to 1.1 Ga) massif-type anorthosites and mafic intrusives in the eastern Canadian shield are correlated with geographic location. Complexes in the Grenville province have positive epsilon sub Nd values and initial Sr-87/Sr-86 (I sub Sr) generally less than 0.703, suggesting derivation from depleted mantle. In Labrador, similar complexes close to or northwest of a line roughly corresponding to the Grenville Front have negative epsilon sub Nd values and I sub Sr 0.703. This contrast was intrepreted as reflecting either enriched mantle under the Nain Province, or contamination of the Nain intrusives with older crustal components. Lead isotopic compositions, however, favor the latter. The possibility of using these Proterozoic intrusives as tracers to characterize the nature and extent of older basement types in Labrador is discussed.

Ashwal, L. D.↗
NASA NTRS1989

Applications of Landsat Thematic Mapper and ground-based spectrometer data to a study of the Skaergaard and other mafic intrusions of East Greenland

Landsat TM data have been used in conjunction with field spectrometer data to map the lithologic units associated with a series of gabbroic intrusions in the East Greenland Tertiary Igneous Province. The general lack of vegetation combined with the difficulty of access to these intrusions make them ideal candidates for lithologic mapping using remote sensing techniques. In addition, these bodies are of interest as possible precious metal ore deposits. The intrusions are spectrally distinct from the surrounding Precambrian gneisses; however, subpixel contamination by snow, oxide surface coatings, and lichen cover and severe topography limit the discrimination of lithologic units within the gabbro. The spectral nature of the surface contaminants was evaluated with a Barringer Hand Held Ratioing Radiometer (HHRR). These HHRR data indicate that bare rock exposures have distinct TM signatures for each lithologic unit but that even small amounts of subpixel contamination are enough to mask these differences because of the large differences between the TM signatures of the rocks and the contaminants.

Birnie, Richard W.↗
NASA NTRS1991

Igneous intrusion models for floor fracturing in lunar craters

Lunar floor-fractured craters are primarily located near the maria and frequently contain ponded mare units and dark mantling deposits. Fracturing is confined to the crater interior, often producing a moat-like feature near the floor edge, and crater depth is commonly reduced by uplift of the crater floor. Although viscous relaxation of crater topography can produce such uplift, the close association of modification with surface volcanism supports a model linking floor fracture to crater-centered igneous intrusions. The consequences of two intrusion models for the lunar interior are quantitatively explored. The first model is based on terrestrial laccoliths and describes a shallow intrusion beneath the crater. The second model is based on cone sheet complexes where surface deformation results from a deeper magma chamber. Both models, their fit to observed crater modifications and possible implications for local volcanism are described.

Wichman, R. W.↗
NASA NTRS1998

Magmatic Intrusions and a Hydrothermal Origin for Fluvial Valleys on Mars

Numerical models of Martian hydrothermal systems demonstrate that systems associated with magmatic intrusions greater than several hundred cubic kilometers can provide sufficient groundwater outflow to form the observed fluvial valleys, if subsurface permeability exceeds about 1.0 darcy. Groundwater outflow increases with increasing intrusion volume and subsurface permeability and is relatively insensitive to intrusion depth and subsurface porosity within the range considered here. Hydrothermally-derived fluids can melt through 1 to 2 km thick ice-rich permafrost layers in several thousand years. Hydrothermal systems thus provide a viable alternative to rainfall for providing surface water for valley formation. This mechanism can form fluvial valleys not only during the postulated early warm, wet climatic epoch, but also during more recent epochs when atmospheric conditions did not favor atmospheric cycling of water. The clustered distribution of the valley networks on a given geologic surface or terrain unit of Mars may also be more compatible with localized, hydrothermally-driven groundwater outflow than regional rainfall. Hydrothermal centers on Mars may have provided appropriate environments for the initiation of life or final oases for the long-term persistence of life.

Gulick, Virginia C↗
NASA NTRS2002

Analysis of Salinity Intrusion in the San Francisco Bay-Delta using a GA- Optimized Neural Net, and Application of the Model to Prediction in the Elkhorn Slough Habitat

The San Francisco Bay Delta is a large hydrodynamic complex that incorporates the Sacramento and San Joaquin Estuaries, the Burman Marsh, and the San Francisco Bay proper. Competition exists for the use of this extensive water system both from the fisheries industry, the agricultural industry, and from the marine and estuarine animal species within the Delta. As tidal fluctuations occur, more saline water pushes upstream allowing fish to migrate beyond the Burman Marsh for breeding and habitat occupation. However, the agriculture industry does not want extensive salinity intrusion to impact water quality for human and plant consumption. The balance is regulated by pumping stations located alone the estuaries and reservoirs whereby flushing of fresh water keeps the saline intrusion at bay. The pumping schedule is driven by data collected at various locations within the Bay Delta and by numerical models that predict the salinity intrusion as part of a larger model of the system. The Interagency Ecological Program (IEP) for the San Francisco Bay/Sacramento-San Joaquin Estuary collects, monitors, and archives the data, and the Department of Water Resources provides a numerical model simulation (DSM2) from which predictions are made that drive the pumping schedule. A problem with this procedure is that the numerical simulation takes roughly 16 hours to complete a C:~ prediction. We have created a neural net, optimized with a genetic algorithm, that takes as input the archived data from multiple stations and predicts stage, salinity, and flow at the Carquinez Straits (at the downstream end of the Burman Marsh). This model seems to be robust in its predictions and operates much faster than the current numerical DSM2 model. Because the system is strongly tidal driven, we used both Principal Component Analysis and Fast Fourier Transforms to discover dominant features within the IEP data. We then filtered out the dominant tidal forcing to discover non-primary tidal effects, and used this to enhance the neural network by mapping input-output relationships in a more efficient manner. Furthermore, the neural network implicitly incorporates both the hydrodynamic and water quality models into a single predictive system. Although our model has not yet been enhanced to demonstrate improve pumping schedules, it has the possibility to support better decision-making procedures that may then be implemented by State agencies if desired. Our intention is now to use this model in the smaller Elkhorn Slough complex near Monterey Bay where no such hydrodynamic model currently exists. At the Elkhorn Slough, we are fusing the neural net model of tidally-driven flow with in situ flow data and airborne and satellite remote sensation data. These further constrain the behavior of the model in predicting the longer-term health and future of this vital estuary.

Thompson, David E.↗
NASA NTRS2004

Warm Core Structure and Mid-Level Intrusion in Hurricane Bonnie (1998) During Landfalling on 26 August 1998

On 26 August 1998 during CAMEX-3, Hurricane Bonnie was overflown by the NASA ER-2 aircraft instrumented with the EDOP X-Band radar and other instrumentation. Bonnie was an asymmetric storm on this day with several prominent features during its brush with the East coast. One of these features was strong intrusion of dry air on the west side of the storm. During the interaction of this westerly shear with the storm, the precipitation band rotates cyclonically from northwest to the south of the storm center. In this paper, we examine the structure of this dry intrusion and its effect on the storm. The EDOP observations are analyzed along with dropsondes, flight-level observations (NASA DC-8 and NOAA P3), and satellite data. The most apparent feature of the EDOP observations are the strong shears in the interface between the western eyewall updraft, and the dry intrusion. Mammatus are formed along this interface reminiscent of convective rear inflows, and suggestive of intense drying of the air through subsidence. This observation as well as other aspects of the analysis are related to recent numerical simulations of Hurricane Bonnie.

Heymsfield, G. M.↗
NASA NTRSDate not supplied

Model-data Comparison of Stratospheric Intrusions Over Hampton, Virginia

Stratospheric intrusions are the transport of ozone from the stratosphere to the troposphere. These intrusions are frequent in spring; they can affect local air quality as well as satellites observations, notably limb sounding instruments such as SAGE III. Complex models such as GEOS-CF are used to assess the magnitude and the impact of SI. We present the model-data comparison of several stratospheric intrusion above Hampton, Virginia, in 2019, using the NASA Langley Mobile Ozone Lidar and the GEOS-CF model. We show the limits of the model-data agreement for these events and suggest a method to correct limb-sounding observations.

G. Gronoff↗
DOE OSTI2024

Effects of Coatings on Water Intrusion and Strain Gauge Durability in Submerged Fatigue Conditions: Preprint

Marine energy structures are typically made using composite materials and are repeatedly loaded by currents and waves. Submersion and repeated loading lead to two environmental effects: moisture intrusion and mechanical fatigue. To understand the combined effects of moisture intrusion and mechanical fatigue on marine energy structures, submerged fatigue testing can be used. Submerged fatigue testing often requires submerged instrumentation to validate component manufacturing methods and models. Measuring strain is critical for understanding marine energy component loads. One common method for measuring strain is by using foil strain gauges, but the durability of strain gauges in submerged fatigue conditions was not well-understood. To increase strain gauge durability and protection from contamination, delamination, and water intrusion, strain gauge coatings may be applied over strain gauges and wire connections. In this study, strain gauges were adhered to composite coupons, coated, and mechanically tested in a water tank. Cycles to composite failure, cycles to strain gauge failure, strains, and strain gauge failure modes were used to measure the effects of strain gauge coatings on composite fatigue life and strain gauge durability. The methods developed and measurements taken at the coupon scale in this study will be used to inform methods and designs for subsequent submerged subcomponent testing, full-scale testing, and standards development. The benefits of designing marine energy structures to informed standards and designs are decreased lifetime costs and increased reliability and energy production, ultimately leading to a sustainable and low-carbon energy system.

composite fatigue testing↗
DOE OSTI2023

Proactive Intrusion Detection and Mitigation System

SAND2023-05661O The proactive intrusion detection and mitigation system (PIDMS) provides grid-edge situational awareness for cybersecurity defense by capturing real-time distributed energy resource (DER) network traffic and performance data with a novel approach that improves the detection and prevention of cyber-physical attacks. The PIDMS addresses the grid-edge security gap with real-time analysis of both network traffic and photovoltaic performance data to deliver a novel, cyber-physical intrusion detection system (IDS) approach that increases the accuracy and effectiveness of detection and mitigation. This hybrid IDS analysis enables dual monitoring that increases the workload of the adversary; both cyber and physical data would have to be simultaneously spoofed to evade detection. Furthermore, monitoring and analyzing cyber data are insufficient in some cases. For example, in an insider threat aimed at disrupting inverter grid-support functions where proper credentials and authentication are achieved, only the altered PV performance would indicate abnormal behavior. All in all, the PIDMS provides novel capabilities for: • Distributed, real-time cyber-physical detection and mitigation analysis • Cybersecurity defense for grid-edge systems • Analysis framework that can provide situational awareness across the transmission, distribution, and DER systems The PIDMS sensor is designed to collect cyber-physical data, process the data using machine-learning algorithms, detect abnormal events, and deploy mitigations. With these goals, the main functional PIDMS objectives are: • Capability to collect cyber-physical data • Onboard storage of cyber-physical data • Peer-to-peer communication • Computationally efficient machine-learning algorithms • Online cyber-physical data analysis • Alerting/visualization capabilities • Mitigation deployment capability with bump-in-the-wire (BITW) implementation Each of these functional objectives enable PIDMS to perform effective cyber-physical intrusion detection and mitigation. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Jones, Christian↗
DOE OSTI2023

Bayesian merging of numerical modeling and remote sensing for saltwater intrusion quantification in the Vietnamese Mekong Delta

Saltwater intrusion has become one of the most concerning issues in the Vietnamese Mekong Delta (VMD) due to its increasing impacts on agriculture and food security of Vietnam. Reliable estimation of salinity plays a crucial role to mitigate the impacts of saltwater intrusion. Here, this study developed a hybrid technique that merges satellite imagery with numerical simulations to improve the estimation of salinity in the VMD. The salinity derived from Landsat images and by numerical simulations was fused using the Bayesian inference technique. The results indicate that our technique significantly reduces the uncertainties and improves the accuracy of salinity estimates. The Nash–Sutcliffe coefficient is 0.74, which is much higher than that of numerical simulation (0.63) and Landsat estimation (0.6). The correlation coefficient between the ensemble and measured salinity is relatively high (0.88). The variance of the ensemble salinity errors (5.0 ppt 2 ) is lower than that of Landsat estimation (10.4 ppt 2 ) and numerical simulations (9.6 ppt 2 ). The proposed approach shows a great potential to combine multiple data sources of a variable of interest to improve its accuracy and reliability wherever these data are available.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Mechanism of Water Intrusion into Flexible ZIF-8: Liquid Is Not Vapor

Zeolitic Imidazolate Frameworks (ZIF) find applicationin storageand dissipation of mechanical energy. Their distinctive propertieslinked to their (sub)nanometer size and hydrophobicity allow for waterintrusion only under high hydrostatic pressure. Here we focus on thepopular ZIF-8 material investigating the intrusion mechanism in itsnanoscale cages, which is the key to its rational exploitation intarget applications. In this work, we used a joint experimental/theoreticalapproach combining in operando synchrotron experiments during high-pressureintrusion experiments, molecular dynamics simulations, and stochasticmodels to reveal that water intrusion into ZIF-8 occurs by a cascadefilling of connected cages rather than a condensation process as previouslyassumed. The reported results allowed us to establish structure/functionrelations in this prototypical microporous material, representingan important step to devise design rules to synthesize porous media.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

The Impact of Slantwise Descending Dry Intrusions on the Marine Boundary Layer and Air-Sea Interface Over the ARM Eastern North Atlantic Site

Dry intrusions (DIs) are synoptic-scale slantwise descending airstreams from the midlatitude upper troposphere toward the boundary layer at lower latitudes. Typically occurring behind cold fronts, such intrusions of dry air often reach the boundary layer and cause its deepening, thereby affecting boundary-layer clouds. Although subsidence is generally an inherent feature of the subtropical marine boundary layer (MBL), it is unclear how the MBL reacts to the transient, dynamically distinct DI. In this study, reanalysis data were combined with observations from the Atmospheric Radiation Measurement Eastern North Atlantic (ENA) site (39.1 degrees N,28.0 degrees W) to characterize the impact of DIs on MBL characteristics and clouds. Specifically, an objective criterion is applied to the observations made during the winter months of 2016-2018 to identify the DI days from those before and following DIs, and reference periods without DIs. The analyses suggest substantial deepening of the well-mixed boundary layer accompanied by changes in the cloud, precipitation and thermodynamic properties during the DI events. During the DI, the lower troposphere cooled and dried substantially thereby inducing strong surface sensible and latent heat fluxes. All while a strong inversion builds up at the elevated MBL top affecting cloud occurrence. The results show DIs to affect the boundary layer and cloud structure at the ENA site similar to 21% of the time in winter months, with the response of the cloud fields to the DI-fronts substantially different than that to the non-DI fronts. Hence, the DI events should be considered while studying boundary layer and cloud processes in the region.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Response of salt intrusion in a tidal estuary to regional climatic forcing

Abstract Salinity distribution in a large tidal estuary is subject to estuarine adjustment under the influences of multiple physical drivers such as freshwater pulses and sea level rise, and is crucial to upstream water quality, aquaculture, and ecosystem functions of the estuary. To better understand the estuarine salinity response to climate change, the unstructured-grid Finite Volume Community Ocean Model was implemented to simulate the salt intrusion in the Delaware Bay Estuary. The model was first validated by multiple observational data sets and subsequently applied in an idealized setting to examine the response of salt front to freshwater pulses in high flow conditions, followed by a long-term drought condition supported by a multi-decadal streamflow drought analysis in the estuary. The model results showed that after the freshwater pulses the salt front location moved further upstream with sea level rise. Under the simulated long-term drought condition, the adjustment timescale of salt intrusion varies nonlinearly with sea level rise. With a significant increase in sea level rise, the adjustment timescale starts to decrease. This shift suggests a transition into a different regime where the estuary becomes more stratified, as indicated by an increasing bulk Simpson number with rising sea levels.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

HIDES: Hybrid Intrusion Detector for Energy Systems

The establishment of a resilient electric grid accompanied by a secure communications network is an ongoing battle as advanced persistent threats continue to exploit existing vulnerabilities in legacy supervisory control and data acquisition system (SCADA) infrastructure. Traditional intrusion detection systems (IDSs) lack consistent performance because of the continuously evolving attack surface of SCADA systems. These shortcomings can be overcome by integrating logical system behavior, protocol-specific knowledge, and data-based learning to develop a comprehensive IDS solution. In this paper, we present a Hybrid Intrusion Detector for Energy Systems by integrating a network-based IDS, state-of-the-art machine learning-based IDS, and model-based IDS to detect unknown and stealthy cyberattacks targeting the SCADA networks. The proposed IDS uses synchrophasor measurements and cyber logs to learn patterns of different scenarios based on spatiotemporal behaviors of power systems. As a proof of concept, we implement and validate the proposed IDS by leveraging resources available at the National Renewable Energy Laboratory's Energy Systems Integration Facility test bed. Experimental results show promising performance in detecting cyberattacks while providing realtime visualization of power system measurements and cyber logs.

machine-learning intrusion detection system↗
NASA NTRS2002

Intrusion detection: systems and models

This paper puts forward a review of state of the art and state of the applicability of intrusion detection systems, and models. The paper also presents a classfication of literature pertaining to intrusion detection.

intrusion detection risk security↗
NASA NTRS2012

Towards Reliable Evaluation of Anomaly-Based Intrusion Detection Performance

This report describes the results of research into the effects of environment-induced noise on the evaluation process for anomaly detectors in the cyber security domain. This research was conducted during a 10-week summer internship program from the 19th of August, 2012 to the 23rd of August, 2012 at the Jet Propulsion Laboratory in Pasadena, California. The research performed lies within the larger context of the Los Angeles Department of Water and Power (LADWP) Smart Grid cyber security project, a Department of Energy (DoE) funded effort involving the Jet Propulsion Laboratory, California Institute of Technology and the University of Southern California/ Information Sciences Institute. The results of the present effort constitute an important contribution towards building more rigorous evaluation paradigms for anomaly-based intrusion detectors in complex cyber physical systems such as the Smart Grid. Anomaly detection is a key strategy for cyber intrusion detection and operates by identifying deviations from profiles of nominal behavior and are thus conceptually appealing for detecting "novel" attacks. Evaluating the performance of such a detector requires assessing: (a) how well it captures the model of nominal behavior, and (b) how well it detects attacks (deviations from normality). Current evaluation methods produce results that give insufficient insight into the operation of a detector, inevitably resulting in a significantly poor characterization of a detectors performance. In this work, we first describe a preliminary taxonomy of key evaluation constructs that are necessary for establishing rigor in the evaluation regime of an anomaly detector. We then focus on clarifying the impact of the operational environment on the manifestation of attacks in monitored data. We show how dynamic and evolving environments can introduce high variability into the data stream perturbing detector performance. Prior research has focused on understanding the impact of this variability in training data for anomaly detectors, but has ignored variability in the attack signal that will necessarily affect the evaluation results for such detectors. We posit that current evaluation strategies implicitly assume that attacks always manifest in a stable manner; we show that this assumption is wrong. We describe a simple experiment to demonstrate the effects of environmental noise on the manifestation of attacks in data and introduce the notion of attack manifestation stability. Finally, we argue that conclusions about detector performance will be unreliable and incomplete if the stability of attack manifestation is not accounted for in the evaluation strategy.

cyber defense↗
NASA NTRS2020

Evaluation of Stratospheric Intrusions and Biomass Burning Plumes on the Vertical Distribution of Tropospheric Ozone Over the Midwestern U.S.

Naturally occurring ozone rich Stratosphere-to-Troposphere Transport (STT) intrusions and biomass burning plumes reaching the surface can contribute to exceedances of the U.S. National Ambient Air Quality Standards (NAAQS) for ground-level ozone (70 ppbv implemented in 2015). In addition, fires can inject significant pollution into the free troposphere where it can be transported long distances. The combined air quality impacts from these sources on ozone has only been analyzed in a few case studies for the Midwest U.S. Here we study ozone impacts in a major Midwestern city, for the first time in St. Louis, Missouri, using a series of ozonesonde profiles taken during the SEAC4RS (Studies of Emissions and Atmospheric Composition, Clouds and Climate Coupling by Regional Surveys) field campaign in August-September 2013. All ozonesondes showed some enhancements above the background profile levels (~55 ppbv) throughout each tropospheric column. Two models were used to estimate and quantify ozone origins within the columns. A chemical transport model identified enhancements from STT equivalent to 10to15 ppbv over the background with a 10 to15% contribution overall to the column. Two FLEXPART-WRF simulations, one with smoke in the boundary layer and the other with smoke above, identified enhancements from biomass burning equivalent to 10to 80 ppbv. Overall, the total biomass burning contribution is 15to 30% of the total column. Five ozonesondes showed signatures of mixed biomass burning plumes and STT intrusions. During this study period, biomass burning in the western U.S. contributed 70% to ozone enhancements in the total column compared to 3% from the central U.S and 27% from other areas.

National Ambient Air Quality Standards for ground‐↗
DOE OSTI2020

Adaptive Neuro Fuzzy Inference System for Cyber-Intrusion Detection in a Smart Grid

The evolution of the power grid has brought increasing deployment of advance metering infrastructure, penetration of intelligent electronic devices, and integration of physical power system components with information and communications technologies. With the fast-expanding connectivity, cyber vulnerabilities arise due to the use of internet-based communication systems. These systems are targets of cyber-intrusions which attempt to disturb the normal power system functions. Traditional intrusion detection algorithms have been developed without an explicit model of the cyber components. In this paper, an algorithm to detect false data injections in the power system is proposed considering both cyber and physical models of the power system. The algorithm is based on an Adaptive Neuro Fuzzy Inference System (ANFIS) which collects information from state variables of the cyber-physical system to meet the performance requirements of the grid. Simulations of the proposed approach using the IEEE 13-bus test system validate the effectiveness of this artificial intelligence-based algorithm.

Adaptive Neuro Fuzzy Inference System (ANFIS), cyb↗