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At least 415 records · Page 23
All sourcesNASA NTRSDOE OSTI
NASA NTRS2007

Solutions Network Formulation Report. NASA's Potential Contributions in Remote Quorum Sensing and the Management of Harmful Algal Blooms

This candidate solution proposes to use the night-imaging capabilities of the HSTC from SAC-C and of the HSC from SAC-D/Aquarius to detect bioluminescent events associated with HABs (harmful algal blooms). Once detected, this information could be fed to the NOAA CSCOR (Center for Sponsored Coastal Ocean Research) Harmful Algal Bloom Event Response Program, which acts quickly to fund the mobilization of research teams and to engage local agencies in a response. The HSC/HSTC data can serve as input to the HABSOS decision support system to provide information on location, extent, and duration of HAB events. Society will benefit from improved protection of the health of humans beings, aquatic ecosystems, and coastal economies. This work supports coastal management, public health, and homeland security applications.

Fletcher, Rose↗
NASA NTRS1972

Evidence for electron excitation of type III radio burst emission.

Type III radio bursts observed at kilometric wavelengths (less than or about equal to 0.35 MHz) by the Ogo-5 spacecraft are compared with greater than 45 keV solar electron events observed near 1 AU by the IMP-5 and Explorer 35 spacecraft for the period from March 1968 to November 1969. Fifty-six distinct type III bursts extending to less than or about equal to 0.35 MHz were observed above the threshold of the Ogo-5 detector; all but two were associated with solar flares. Twenty-six of the bursts were followed less than or about equal to 40 min later by greater than 45 keV solar electron events observed at 1 AU. All of these 26 bursts were identified with flares located west of W09 solar longitude. Of the bursts not associated with electron events only three were identified with flares west of W09, 18 were located east of W09, and seven occurred during times when electron events would be obscured by high background particle fluxes.

Alvarez, H.↗
DOE OSTI2021

Local Explosion Detection and Infrasound Localization by Reverse Time Migration Using 3-D Finite-Difference Wave Propagation

Infrasound data are routinely used to detect and locate volcanic and other explosions, using both arrays and single sensor networks. However, at local distances (< km) topography often complicates acoustic propagation, resulting in inaccurate acoustic travel times leading to biased source locations when assuming straight-line propagation. Here we present a new method, termed Reverse Time Migration-Finite-Difference Time Domain (RTM-FDTD), that integrates numerical modeling into the standard RTM back-projection process. Travel time information is computed across the entire potential source grid via FDTD modeling to incorporate the effects of topography. The waveforms are then back-projected and stacked at each grid point, with the stack maximum corresponding to the likely source. We apply our method to three volcanoes with different network configurations, source-receiver distances, and topography. At Yasur Volcano, Vanuatu, RTM-FDTD locates explosions within ~20 m of the source and differentiates between multiple vents. RTM-FDTD produces a more accurate location for the two Yasur subcraters than standard RTM and doubles the number of detected events. At Sakurajima Volcano, Japan, RTM-FDTD locates the source within 50 m of the active vent despite notable topographic blocking. The RTM-FDTD location is similar to that from the Time Reversal Mirror method, but is more computationally efficient. Lastly, at Shishaldin Volcano, Alaska, RTM and RTM-FDTD both produce realistic source locations (<50 m) for ground-coupled airwaves recorded on a four-station seismic network. We show that RTM is an effective method to detect and locate infrasonic sources across a variety of scenarios, and by integrating numerical modeling, RTM-FDTD produces more accurate source locations and increases the detection capability.

58 GEOSCIENCES↗
NASA NTRS2015

Preliminary Flight Deck Observations During Flight in High Ice Water Content Conditions

In 2006, Mason et al. identified common observations that occurred in engine power-loss events attributed to flight in high concentrations of ice crystals. Observations included light to moderate turbulence, precipitation on the windscreen (often reported as rain), aircraft total temperature anomalies, lack of significant airframe icing, and no flight radar echoes at the location and altitude of the engine event. Since 2006, Mason et al. and others have collected information from pilots who experienced engine power-loss events via interviews and questionnaires to substantiate earlier observations and support event analyses. In 2011, Mason and Grzych reported that vertical acceleration data showed increases in turbulence prior to engine events, although the turbulence was usually light to moderate and not unique to high ice water content (HIWC) clouds. Mason concluded that the observation of rain on the windscreen was due to melting of ice high concentrations of ice crystals on the windscreen, coalescing into drops. Mason also reported that these pilot observations of rain on the windscreen were varied. Many pilots indicated no rain was observed, while others observed moderate rain with unique impact sounds. Mason concluded that the variation in the reports may be due to variation in the ice concentration, particle size, and temperature.

Wind Tunnel Tests↗
DOE OSTI2022

Searching for ultra-light bosons and constraining black hole spin distributions with stellar tidal disruption events

Stars that pass close to the supermassive black holes located in the center of galaxies can be disrupted by tidal forces, leading to flares that are observed as bright transient events in sky surveys. The rate for these events to occur depends on the black hole spins, which in turn can be affected by ultra-light bosons due to superradiance. We perform a detailed analysis of these effects and show that searches for stellar tidal disruptions have the potential to uncover the existence of ultra-light bosons. In particular, we find that upcoming stellar tidal disruption rate measurements by the Vera Rubin Observatory’s Legacy Survey of Space and Time can be used to either discover or rule out bosons with masses ranging from 10 –20 to 10 –18 eV. Our analysis also indicates that these measurements may be used to constrain a variety of supermassive black hole spin distributions and determine if close-to maximal spins are preferred.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
NASA NTRS1978

Ionospheric Doppler sounder as remote sensing for detection and prediction of severe storms

Atmospheric acoustic-gravity waves associated with severe storms are detected by a ground-based ionospheric sounding array, and the location of the severe storms responsible for the wave generation is determined by group ray path computation. Computations based on six events during the extreme tornado outbreak of April 3, 1974, and five single tornado events show that the wave sources are located near the location where tornadoes touchdown more than one hour later. In the hurricane case, the results indicate that waves were generated along the storm track more than 3 hours ahead of the actual location of the storm. The possibility of the development of the present system as a remote sensor for the detection and prediction of severe storms is discussed.

Hung, R. J.↗
DOE OSTI2020

Correlation between Generator Trips and Locational Marginal Prices (LMPs)

Generally, disturbances in an interconnected network have an influence the stability and the economy of the power grid. Some phenomenon such as load shedding have proven to have a huge impact on real time electricity prices. Generation trip is considered one of the most common events in a power grid that may change the wholesale electricity market. In this paper, a locational marginal price (LMP) measure is used to notice how the electricity prices change with generator trip events at different locations of U.S. power grid. The study results help to find whether there is a clear correlation between generator trips and the changes in the electricity real-time market.

Alharbi, Abdulelah↗
DOE OSTI2025

Applying Transfer Learning for Street-Scale Nuisance Flood Forecasting in Coastal-Urban Cities

An important challenge with Machine Learning (ML) is its transferability; that is, whether a ML model trained on one set of data can be applied to a second set of data without requiring a full re-training of the model. Transfer Learning (TL) addresses this challenge by transferring knowledge learned in the source domain (the data it was trained on) to the target domain (a second set of data that is statistically different but related, which the model was not trained on). This study investigates the use of TL for street-scale nuisance flood forecasting by exploring whether a ML model trained on data collected for one set of streets can effectively forecast flooding for another set of streets in the same city using TL. The envisioned use case is a city deploying a new flood depth monitoring sensor on a street and using TL to apply a ML model, trained on sensor data from an existing flood depth sensor network, to this new street. Eventually, the new flood depth sensor will have a sufficient dataset for training its own ML model, but TL can be used to fill the gap in time while this new dataset is being generated. This method is explored using a Long Short-Term Memory (LSTM) model trained on data for the flood-prone streets of Norfolk City, Virginia. The data used for training includes environmental time series (rainfall, tide), topographic features (Digital Elevation Model (DEM), Topographic Wetness Index (TWI), Depth To Water (DTW)), and street-scale flood depth time series obtained from a high-fidelity physics-based model, acting as a synthetic street-scale stream depth sensor dataset since actual stream depth sensor data is generally unavailable for most cities. A set of 180 flood-prone streets was used to train a base model, while another set of 180 flood-prone streets was used to re-train that model using different TL strategies. The results show that full-weight re-training proved most effective and minimal re-training of only the output layer was insufficient. The advantage of TL was most pronounced when target data was limited, meaning data collected at the new water depth sensor location included generally less than 18 flood events. As target data increased beyond 18 flood events, the benefit of TL diminished relative to training a ML model directly on the local flood events. These findings can assist cities as they implement street-scale flood sensing systems to create accurate forecasts for new sensing locations that do not yet have sufficient data records to train a local ML model.

Roy, Binata [Univ. of Virginia, Charlottesville, V↗
NASA NTRS1989

Identification and interpretation of patterns in rocket engine data: Artificial intelligence and neural network approaches

This paper describes an expert system which is designed to perform automatic data analysis, identify anomalous events, and determine the characteristic features of these events. We have employed both artificial intelligence and neural net approaches in the design of this expert system. The artificial intelligence approach is useful because it provides (1) the use of human experts' knowledge of sensor behavior and faulty engine conditions in interpreting data; (2) the use of engine design knowledge and physical sensor locations in establishing relationships among the events of multiple sensors; (3) the use of stored analysis of past data of faulty engine conditions; and (4) the use of knowledge-based reasoning in distinguishing sensor failure from actual faults. The neural network approach appears promising because neural nets (1) can be trained on extremely noisy data and produce classifications which are more robust under noisy conditions than other classification techniques; (2) avoid the necessity of noise removal by digital filtering and therefore avoid the need to make assumptions about frequency bands or other signal characteristics of anomalous behavior; (3) can, in effect, generate their own feature detectors based on the characteristics of the sensor data used in training; and (4) are inherently parallel and therefore are potentially implementable in special-purpose parallel hardware.

Ali, Moonis↗
NASA NTRS1994

Energetic helium particles trapped in the magnetosphere

High energy (approximately 40-100 MeV/nucleon) geomagnetically trapped helium nuclei have been measured, for the first time, by the ONR-604 instrument during the 1990/1991 Combined Release and Radiation Effects Satellite (CRRES) mission. The helium events observed at L less than 2.3 have a pitch angle distribution peaking perpendicular to the local magnetic field and are contained in peaks located at L = 1.2 and 1.9. The events in each peak can be characterized by power law energy spectra with indices of 10.0 +/- 0.7 for L = 1.9-2.3 and 6.8 +/- 1.0 for L = 1.15-1.3, before the large storm of 24 March 1991. CRRES was active during solar maximum when the anomalous component is excluded from the inner heliosphere, making it unlikely that the observed events derived from the anomalous component. The trapped helium counting rates decrease gradually with time indicating that these high energy ions were not injected by flares during the 1990/91 mission. Flare injection prior to mid-1990 may account for the highest energy particles, while solar wind injection during magnetic storms and subsequent acceleration could account for the helium at lower energies.

Chen, Jiasheng↗
DOE OSTI2026

Envelope-driven comfort risk in residential demand response

Residential demand response (DR) is a valuable resource for grid reliability, but remains challenging because the highly heterogeneous residential building stock leads to widely varying and hard-to-predict load and comfort responses during DR events. Although prior research has estimated the technical potential of DR-capable technologies for achieving energy demand savings, little is known about how they affect thermal comfort. In particular, it remains unclear how indoor thermal conditions due to DR depend on the thermal envelope characteristics of the housing stock. To address this gap, this study provides a systematic, location-specific assessment of indoor thermal performance during DR-events across the US housing stock using both typical DR weather data and detailed building metadata. We evaluate how envelope characteristics influence indoor temperatures during realistic simulated summer and winter DR events across 37 US locations, applying both temperature threshold and rate of temperature change criteria to estimate region-level probabilities of discomfort. Additionally, we show the impact of distinct weather patterns that intensify or abate thermal stress on comfort outcomes. Results show a near-universal overheating risk in summer DR events, where comfort outcomes are strongly influenced by rapid risk of comfort violations. In contrast, overall winter DR discomfort risk is lower, risk escalation is more gradual and shows greater sensitivity to event duration. These findings offer a data-driven quantification of comfort risk across diverse climates and building envelopes, demonstrating the need for region-specific DR scheduling and discomfort mitigation strategies tailored to local weather patterns and the performance of existing residential buildings.

Demand response↗
NASA NTRS2005

Flare Emission Onset in the Slow-Rise and Fast-Rise Phases of an Erupting Solar Filament Observed with TRACE

We observe the eruption of an active-region solar filament of 1998 July 11 using high time cadence and high spatial resolution EUV observations from the TRACE sareiii'ce, along with soft X-ray images from the soft X-ray telescope (SXT) on the Yohkoh satellite, hard X-ray fluxes from the BATSE instrument on the (CGRO) satellite and from the hard X-ray telescope (HXT) on Yohkoh, and ground-based magnetograms. We concentrate on the initiation of the eruption in an effort to understand the eruption mechanism. First the filament undergoes slow upward movement in a "slow rise" phase with an approximately constant velocity of approximately 15 km/s that lasts about 10-min, and then it erupts in a "fast-rise" phase, reaching a velocity of about 200 km/s in about 5-min, followed by a period of deceleration. EUV brightenings begin just before the start of the filament's slow rise, and remain immediately beneath the rising filament during the slow rise; initial soft X-ray brightenings occur at about the same time and location. Strong hard X-ray emission begins after the onset of the fast rise, and does not peak until the filament has traveled a substantial altitude (to a height about equal to the initial length of the erupting filament) beyond its initial location. Our observations are consistent with the slow-rise phase of the eruption resulting from the onset of "tether cutting" reconnection between magnetic fields beneath the filament, and the fast rise resulting from an explosive increase in the reconnection rate or by catastrophic destabilization of the overlying filament-carrying fields. About two days prior to the event new flux emerged near the location of the initial brightenings, and this recently- emerged flux could have been a catalyst for initiating the tether-cutting reconnection. With the exception of the initial slow rise, our findings qualitatively agree with the prediction for erupting-flux-rope height as a function of time in a model discussed by Chen & Shibata (2000) based on reconnection between emerging flux and a flux rope.

Sterling, A. C.↗
NASA NTRS2004

Reduced-Order Modeling and Wavelet Analysis of Turbofan Engine Structural Response Due to Foreign Object Damage (FOD) Events

The development of a wavelet-based feature extraction technique specifically targeting FOD-event induced vibration signal changes in gas turbine engines is described. The technique performs wavelet analysis of accelerometer signals from specified locations on the engine and is shown to be robust in the presence of significant process and sensor noise. It is envisioned that the technique will be combined with Kalman filter thermal/health parameter estimation for FOD-event detection via information fusion from these (and perhaps other) sources. Due to the lack of high-frequency FOD-event test data in the open literature, a reduced-order turbofan structural model (ROM) was synthesized from a finite element model modal analysis to support the investigation. In addition to providing test data for algorithm development, the ROM is used to determine the optimal sensor location for FOD-event detection. In the presence of significant noise, precise location of the FOD event in time was obtained using the developed wavelet-based feature.

Turso, James↗
NASA NTRS1972

The impulsive X-ray burst of October 10, 1970.

An impulsive burst of 100-400 keV solar X-rays associated with a small solar flare was observed on October 10, 1970 with a large area scintillator aboard a balloon. The X-ray burst was also observed simultaneously in 10-80 keV range by the OGO-5 satellite and in 8-20 A range by the SOLRAD-9 satellite. The event is attributed to an H-alpha subflare located approximately at S13, E88 on the solar disk. The spectral characteristics of this event are examined in the light of the earlier X-ray observations of small solar flares.

Kane, S. R.↗
NASA NTRS2001

First Flight of the Advanced Thin Ionization Calorimeter (ATIC) Balloon Experiment

The ATILT instrument is designed to measure the composition and energy spectra of Z = 1 to 28 cosmic rays over the energy range -10 GeV - 100 TeV. ATIC was launched as a long duration test balloon flight on 12/28/00 local time from McMurdo, Antarctica. The operations preceding and during launch went very smoothly. During the first -20 hr while the instrument remained within line of sight (LOS), a full system check out was conducted, the experiment was operated in several test configurations, and all major tuning was completed. Preliminary analysis of the science data indicates that the overall detector system is functioning as expected. With our fully functioning analysis software we were able to monitor the data in nearly real time. Each event was reconstructed event-by-event to confirm the detector performance. The shower profiles indicate that the shower maximum location is deeper in the calorimeter for higher energy events, as expected. The energy spectra of protons, Helium nuclei, and "all particles" appear to follow power laws. Both the Si matrix and top scintillator layer of the charge module show clear charge separation for p and He. As the statistics increase, heavy nuclei charge separation will be evaluated. We will present preliminary results of the LOS data, as well as other data that will be available from the flight-data hard disk,

Case, G.↗
NASA NTRS2007

Reduced-Order Modeling and Wavelet Analysis of Turbofan Engine Structural Response Due to Foreign Object Damage "FOD" Events

The development of a wavelet-based feature extraction technique specifically targeting FOD-event induced vibration signal changes in gas turbine engines is described. The technique performs wavelet analysis of accelerometer signals from specified locations on the engine and is shown to be robust in the presence of significant process and sensor noise. It is envisioned that the technique will be combined with Kalman filter thermal/ health parameter estimation for FOD-event detection via information fusion from these (and perhaps other) sources. Due to the lack of high-frequency FOD-event test data in the open literature, a reduced-order turbofan structural model (ROM) was synthesized from a finite-element model modal analysis to support the investigation. In addition to providing test data for algorithm development, the ROM is used to determine the optimal sensor location for FOD-event detection. In the presence of significant noise, precise location of the FOD event in time was obtained using the developed wavelet-based feature.

Turso, James A.↗
NASA NTRS1994

Automatic generation of efficient orderings of events for scheduling applications

In scheduling a set of tasks, it is often not known with certainty how long a given event will take. We call this duration uncertainty. Duration uncertainty is a primary obstacle to the successful completion of a schedule. If a duration of one task is longer than expected, the remaining tasks are delayed. The delay may result in the abandonment of the schedule itself, a phenomenon known as schedule breakage. One response to schedule breakage is on-line, dynamic rescheduling. A more recent alternative is called proactive rescheduling. This method uses statistical data about the durations of events in order to anticipate the locations in the schedule where breakage is likely prior to the execution of the schedule. It generates alternative schedules at such sensitive points, which can be then applied by the scheduler at execution time, without the delay incurred by dynamic rescheduling. This paper proposes a technique for making proactive error management more effective. The technique is based on applying a similarity-based method of clustering to the problem of identifying similar events in a set of events.

Morris, Robert A.↗
DOE OSTI2020

Enhanced Dynamic Equivalent Identification Method of Large-Scale Power Systems Using Multiple Event

The increasing complexity of the interconnected power system makes high-fidelity dynamic simulation models computationally more intensive. To improve computation efficiency, model reduction techniques have been investigated to only preserve the dynamics in a limited area of interest (study area), while deriving equivalent representation for the external area. For this purpose, a measurement-based reduction approach using system identification techniques has been previously proposed. In that case, external areas are represented by dynamic equivalent loads using transfer function estimation. In this paper, in order to enhance the accuracy of the reduced model in preserving dynamics of the study area, multiple “grid” events of different types and at different locations are considered for identifying the parameters of the equivalent loads. Case studies are carried out in the NPCC 140-bus system. Comparison are made between multiple events training and single event training, highlighting the advantages of the proposed method in providing a better representation of the grid dynamics under different operating conditions.

Xue, Yaosuo↗