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At least 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

A hydrogeophysical framework to assess infiltration during a simulated ecosystem-scale flooding experiment

This study presents a framework to quantify changes in soil saturation in response to flooding caused by extreme hydrologic perturbation on coastal ecosystems at the interfaces and transition between terrestrial and aquatic systems. Subsurface heterogeneity limits the use of in situ measurements to quantify subsurface flow during flooding due to the spatial discontinuity in the measured data. While geophysical methods, including time-lapse electrical resistivity imaging (ERI), are increasingly used to monitor soil hydrological processes, their abilities to parameterize flow models have been underutilized. This study combines background ERI, ground penetrating radar (GPR), time-lapse ERI, soil characterization, and a numerical flow model developed using an Advanced Terrestrial Simulator (ATS) code to quantify the infiltration pathway and describe the hydrological dynamics during a simulated flooding experiment. We assessed the use of two conceptual models developed using [1] ERI and GPR data that described the stratigraphic distribution, and time-lapse ERI that mapped permeability contrast, and [2] information from a national soil database for capturing changes in saturation. Combining the ERI and GPR results with soil core data revealed the stratigraphic heterogeneity at the site with a silty clay layer from 1 to 2 m between an overlying loamy topsoil and an underlying saturated silty sand. This silty clay layer could restrict deep infiltration. The time-lapse ERI showed up to a 35% decrease in resistivity, which correlated with soil moisture data (R 2 value > 0.53) and revealed preferential infiltration zones used to inform the flow model. Numerical simulation results from both the geophysics- and soil database-informed models quantified changes in soil saturation with calculated soil moistures that agreed with field data. The geophysics-informed model captured more of the system’s variability, reflective of shallow subsurface heterogeneities. The framework presented will serve as a precursor for a robust ecohydrological model that can describe the impacts of extreme events induced by climate change on coastal ecosystems.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1992

Nonlinear magnetosonic waves and mirror mode structures in the March 1991 Ulysses interplanetary event

In examining the March 23-25, 1991 Ulysses (2.2 AU) high speed solar wind events, two distinct plasma wave modes are found: steepened magnetosonic waves with whistler precursors and mirror mode structures. These two modes are locally generated by plasma instabilities, presumably associated with anisotropies existing in the energetic shock particles and solar wind plasma, respectively. The magnetosonic waves are generated by a right-hand resonant instability associated with an about 40 keV ion beam. By an extrapolation of the results presented here, assuming microflares and nanoflares at the sun generate shocks in the lower corona and these shocks accelerate energetic ions, it is suggested that the ions, via the right-hand resonant instability, generate magnetosonic waves which steepened to form 'microshocks'. These shocks could, in turn, accelerate more energetic ions, leading to a shock/energetic ion/magnetosonic wave cascade. These newly formed magnetosonic waves and shocks presumably could propagate in a broad range of directions, leading to energy dissipation over a large region of the outer corona.

Tsurutani, Bruce T.↗
DOE OSTI2024

Machine Learning and Data Science to Advance Laboratory Earthquake Prediction and Illuminate the Mechanics of Precursors to Failure

Earthquakes represent one of our greatest natural hazards and in recent years human induced seismicity is adding to the threat. Even a modest improvement in the ability to forecast devastating large earthquakes or smaller shallow events associated with fluid injection could save thousands of lives and billions of dollars. Current efforts to forecast earthquakes are limited by knowledge of earthquake physics and hampered by a lack of reliable lab or field observations. However, recent work has provided a critical opportunity for advancement. We have found: 1) clear and consistent precursors prior to earthquake-like failure in the laboratory and 2) that lab earthquakes can be predicted using machine learning (ML). These works show that stick-slip failure events –the lab equivalent of earthquakes– are preceded by a cascade of micro-failure events that radiate elastic energy in a manner that foretells catastrophic failure. Remarkably, ML predicts the fault zone stress state, the failure time and in some cases the magnitude of lab earthquakes. In addition, the observations include clear precursors to failure in the form of changes in fault zone properties prior to lab earthquakes. Precursors have been observed in previous laboratory studies but their origin is poorly understood and their possible connection to ML based earthquake prediction is unknown. The work conducted under our project has dramatically expanded these efforts. We have developed an integrated data science approach to illuminate the physics of earthquake precursors and lab earthquake prediction. Our work has accelerated the development of ML, artificial intelligence (AI), and related data science approaches by providing massive data sets that are tightly connected to critical scientific problems and by bringing together leading subject matter experts and data scientists. Earthquake physics involves phenomena that are far from equilibrium. Our work has leveraged data science methods to illuminate these phenomena and investigate how they relate to earthquake prediction. In addition to a large database with many types of labeled events that is available to everyone, our work has advanced the fundamental understanding of seismic forecasting, earthquake physics, and fault rheology

58 GEOSCIENCES↗
DOE OSTI2020

Progress Toward Interpretable Machine Learning–Based Disruption Predictors Across Tokamaks

Here in this paper we lay the groundwork for a robust cross-device comparison of data-driven disruption prediction algorithms on DIII-D and JET tokamaks. In order to consistently carry on a comparative analysis, we define physics-based indicators of disruption precursors based on temperature, density, and radiation profiles that are currently not used in many other machine learning predictors for DIII-D data. These profile-based indicators are shown to well-describe impurity accumulation events in both DIII-D and JET discharges that eventually disrupt. The univariate analysis of the features used as input signals in the data-driven algorithms applied on the data of both tokamaks statistically highlights the differences in the dominant disruption precursors. JET with its ITER-like wall is more prone to impurity accumulation events, while DIII-D is more subject to edge-cooling mechanisms that destabilize dangerous magnetohydrodynamic modes. Even though the analyzed data sets are characterized by such intrinsic differences, we show through a few examples that the inclusion of physics-based disruption markers in data-driven algorithms is a promising path toward the realization of a uniform framework to predict and interpret disruptive scenarios across different tokamaks. As long as the destabilizing precursors are diagnosed in a device-independent way, the knowledge that data-driven algorithms learn on one device can be re-used to explain a disruptive behavior on another device.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS1989

Nature and origin of matrix in the unique type 3 chondrite, Kakangari

The characteristics of the matrix of the Kakangari type-3 chondrite were investigated using high-resolution TEM and AEM. It was found that the textural and mineralogical characteristics of the fine-grained matrix of Kakangari are different from those of the other chondrite groups. Unlike the matrix phases present in the CV3 and CO3 chondrites, the matrix mineralogy of Kakangari contains clear information regarding its possible origin and thermal history. Data obtained are most consistent with an origin of Kakangari by annealing, without melting at high temperature (possibly during a chondrule-forming thermal event), of clusters or aggregates of ultrafine-grained amorphous or crystalline phases. The precursor materials were most likely to have been a mixture of nebula and presolar dust. Chondrules in Kakangari were probably formed from identical precursors to the matrix, but reached temperatures sufficiently high to produce melting.

Brearley, Adrian J.↗
NASA NTRS1992

Shock breakout in SN 1987A

Detailed models for the UV burst from SN 1987A are calculated using a two-temperature radiation hydrodynamics code. The sequence of events which occur during shock breakout is described, including the formation of a radiative precursor, the disappearance of the shock, and the growth of a thin, dense shell above the photosphere which gives rise to a new viscous, isothermal shock. Continuum spectra are calculated under the assumption that the emergent radiation is a dilute blackbody with a color temperature equal to the radiation temperature at the thermalization depth. This color temperature is 2-3 times higher than the effective temperature. Light-travel-time corrections have been included in the light curves and the spectra. Quantities most relevant to accurate modeling of the fluorescing ring around SN 1987A are highlighted.

Ensman, Lisa↗
NASA NTRS1994

Asteroid 243 IDA and its satellite

A high-resolution mosaic of Ida shows a highly irregular body (roughly 56 km long), heavily covered with craters, with many interesting geological features, including grooves, blocks, chutes, dark-floored craters, and crater chains. A satellite of Ida, with a preliminary designation of 1993 (243) 1, was discovered in orbit around Ida. It is approximately 1.5 km in diameter, has an albedo and spectral reflectance not grossly different from Ida, and orbits Ida in a prograde direction with a period of roughly 20 hr. No other comparable-sized satellites have been found near Ida. New pictures of the opposite side of Ida reveal an irregular, dog-bone shape, with a prominent gouge that seems to separate Ida into two chief components. A V-shaped valley, well shown in the highest-resolution view of Ida returned in April, may mark a modest expression on the September face of the more dramatic feature on the back side. Ida's dense population of craters shows a wide diversity of morphologies, consistent with the surface having been subjected to saturated bombardment by smaller projectiles. Assuming the same projectile flux applies to Ida was used in deriving Gaspra's cratering age of about 200 m.y., and assuming that Gaspra and Ida both have the same impact strength, then the age of Ida's surface is calculated to be 1-2 b.y. This is considerably older than expected from other evidence concerning the Koronis family. Our favored explanation of Ida's satellite is that it (or a precursor satellite from which the present satellite was derived) formed during the catastrophic disruption event that formed Ida itself and formed the Koronis family of asteroids. Perhaps, instead, the satellite is a block ejected from a cratering impact. In any case, smaller blocks visible on some parts of Ida are more certain to be crater ejecta, whether or not they were ever temporary satellites.

Chapman, C. R.↗
NASA NTRS2006

Robotic Lunar Exploration

This presentation describes current Lunar Exploration plans and objectives. It begins with specific statements from the President s vision for U.S. Space Exploration which pertain to robotic lunar missions. An outline of missions objectives is provided, along with a high-level schedule of events through the year 2025. Focus is then given to the Lunar Robotic and Precursor Program (LPRP) to describe objectives and goals. Recent developments in the Program are explained - specifically, the renaming of the RLEP program to "LPRP" and the movement of the program office to MSFC. A brief summary of the synergy expected between the robotic and crewed missions, with the LSAM descent stage Project is given. The Lunar Reconnaissance Orbiter mission, with its co-manifested Lunar Crater Observation and Sensing Satellite (LCROSS), is then described with an overview of the payloads and mission objectives. Finally, information is given about the expected future of the LPRP program and Exploration and the development of a compressive Lunar Exploration Architecture.

Echols, Raymond↗
NASA NTRS2008

Inductive System Monitors Tasks

The Inductive Monitoring System (IMS) software developed at Ames Research Center uses artificial intelligence and data mining techniques to build system-monitoring knowledge bases from archived or simulated sensor data. This information is then used to detect unusual or anomalous behavior that may indicate an impending system failure. Currently helping analyze data from systems that help fly and maintain the space shuttle and the International Space Station (ISS), the IMS has also been employed by data classes are then used to build a monitoring knowledge base. In real time, IMS performs monitoring functions: determining and displaying the degree of deviation from nominal performance. IMS trend analyses can detect conditions that may indicate a failure or required system maintenance. The development of IMS was motivated by the difficulty of producing detailed diagnostic models of some system components due to complexity or unavailability of design information. Successful applications have ranged from real-time monitoring of aircraft engine and control systems to anomaly detection in space shuttle and ISS data. IMS was used on shuttle missions STS-121, STS-115, and STS-116 to search the Wing Leading Edge Impact Detection System (WLEIDS) data for signs of possible damaging impacts during launch. It independently verified findings of the WLEIDS Mission Evaluation Room (MER) analysts and indicated additional points of interest that were subsequently investigated by the MER team. In support of the Exploration Systems Mission Directorate, IMS is being deployed as an anomaly detection tool on ISS mission control consoles in the Johnson Space Center Mission Operations Directorate. IMS has been trained to detect faults in the ISS Control Moment Gyroscope (CMG) systems. In laboratory tests, it has already detected several minor anomalies in real-time CMG data. When tested on archived data, IMS was able to detect precursors of the CMG1 failure nearly 15 hours in advance of the actual failure event. In the Aeronautics Research Mission Directorate, IMS successfully performed real-time engine health analysis. IMS was able to detect simulated failures and actual engine anomalies in an F/A-18 aircraft during the course of 25 test flights. IMS is also being used in colla

Source record↗
NASA NTRS2023

Great Salt Lake Health and Air Quality: Monitoring Lakebed Exposure and its Impact on Air Quality and Environmental Hazards in the Great Salt Lake Watershed

Water flow into the Great Salt Lake has declined rapidly over the last forty years due to human withdrawals and climate change. As a result of declining lake levels, over 50% of the lakebed is now exposed. Dust storms may grow in frequency and intensity across Northern Utah as lakebed dust becomes airborne under specific meteorological conditions. In our research project, we utilized satellite imagery from Terra and Aqua, Sentinel-5P, CALIPSO, Landsat 5 TM, Landsat 7 ETM+, Landsat 8 OLI-2, Suomi NPP, ground sensor environmental data, and demographic data to understand the relationship between lake desiccation and dust, and the impact of pollution upon the communities surrounding the Great Salt Lake. By plotting changes in Lake Surface Area against Aerosol Optical Depth (AOD) over our study period (2010-2022), we found an inverse relationship (R2=0.3423) between lake surface area and dust levels within our study area. We conducted a Vertical Feature Mask (VFM) and Extinction Coefficient Plot, from which we identified that during dust events, the aerosol type is mainly polluted dust and the aerosol height is 200 meters from the surface. Lastly, we created bivariate choropleth maps, which demonstrate which census tracts within our study area are most vulnerable to AOD (a proxy for PM2.5 from dust), NO2 and HCHO (precursors to ozone). In summary, our findings revealed that declining lake levels are associated with an increase in intensity of dust events, and these dust events will particularly impact residents of Tooele County and the west side of Salt Lake City. Project resources support partner needs by informing targeted air monitoring efforts, lakebed management practices, and advocacy efforts for GSL stewardship.

Terminal Saline Lake↗
DOE OSTI2025

Building Datasets and Training Methods for ML Based Magnet Quench Detection

Detecting quenches in superconducting (SC) magnets during training is a challenging process that involves capturing physical events that occur at different frequencies and appear as various signal features. These events may be correlated across instrumentation type, thermal cycle, and ramp. These events together build a more complete picture of continuous processes occurring in the magnet, and may allow us to flag potential precursors for quench detection. We present our work on building an automatic machine learning (ML) based quench detection system. We build upon our existing work on unsupervised auto-encoders for acoustic sensors and quench antenna (QA) by first establishing a supervised ML training pipeline. We show the results of an event tagging, analysis, and simulation framework on our QA and acoustic data which are used concurrently to build a training dataset for a supervised implementation. We then show how this supervised training can be used as a prior in a semi-supervised framework and compare this to the unsupervised neural network auto-encoder performance.This allows us to have a more concrete understanding of the performance of our algorithms relative to physical events occurring in the magnet, and also provides a baseline software tool to generically evaluate our quench prediction autoencoders under completely unsupervised, supervised, and semi-supervised training conditions.

Khan, Maira [Fermilab]↗
DOE OSTI2023

Vertical distribution of boundary layer new particle formation and implications for nanoparticle growth mechanisms (Final Report)

New particles can form high above ground in the atmosphere before such formation events are observed by ground-based instruments. Once formed, these particles can take up significant amounts of water vapor, which has implications on the mechanisms by which nanoparticles grow and, ultimately, impact cloud formation processes. These observations motivated the research performed in this project using a combination of modeling, laboratory experiments, and the analysis of field observations. We hypothesized is that ground-based measurements do not always accurately represent the location and timing of new particle formation events, nor do they adequately characterize the dominant physical and chemical processes that are responsible for the subsequent growth of newly formed particles. Essentially, we wanted to study the new particle formation process under conditions that we expect may be more relevant to the actual location in the atmosphere where such events take place, which are often characterized by higher relative humidities, lower temperatures, and a broader range of precursors and oxidants compared to those observed at ground level. This project had two main objectives, each of which directly addressed our hypothesis. Our first is to investigate the timing, distribution, meteorological conditions, and nanoparticle properties associated with boundary layer new particle formation through the analysis of ARM field campaigns such as HI-SCALE and long-term observations and observations performed in other locales such as in China and India where atmospheric conditions could play a crucial role in determining the mechanisms of new particle formation. This activity provided a comprehensive description, both in time and in space, of the gases and nanoparticle properties that are responsible for these events. We also performed modeling studies to explore the vertical profile and timing of new particle formation events from these campaigns. Our second objective was to perform laboratory and process-level modeling studies to investigate the role that conditions such as low ambient temperature, high relative humidity, and different oxidants such as nitrate radical play in determining unique chemical pathways for nanoparticle growth. In doing so, we revisited the representation of nanoparticle growth in global models and updated assumptions of formation and growth based on the findings of the field, laboratory, and process-level-model work. Our research provides crucial insights into the most important regions of the atmospheric boundary layer for future observational and modeling studies. It also identifies the most relevant environmental conditions, precursors, and oxidants that are responsible for nanoparticle growth, which will aid in the design of laboratory studies and process-level model experiments. The unique pathways that we discovered can be incorporated into regional and global models, thereby improving predictions and attribution of the role of new particle formation in, e.g., air pollution formation and cloud properties.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2001

Source Determination for Substorm-Related Ion Injections

The grant supported an effort to restore and analyze data from the Spacecraft Charging at High Altitude (SCATHA) spacecraft. This spacecraft, which was originally an Air Force mission, was launched into a near geo-synchronous orbit in early 1979 to, investigate the inner magnetosphere at altitudes where it was known that spacecraft can undergo significant charging events. SCATHA included an ion composition experiment (designated SC8) and in many ways was a precursor to other missions, such as the AMPTE Charge Composition Explorer.

Strangeway, Robert J.↗
NASA NTRS1999

Seasonal and Interannual Variabilities in Tropical Tropospheric Ozone

This paper presents a detailed characterization of seasonal and interannual variability in tropical tropospheric column ozone (TCO). TCO time series are derived from 20 years (1979-1998) of total ozone mapping spectrometer (TOMS) data using the convective cloud differential (CCD) method. Our study identifies three regions in the tropics with distinctly different zonal characteristics related to seasonal and interannual variability. These three regions are the eastern Pacific, Atlantic, and western Pacific. Results show that in both the eastern and western Pacific seasonal-cycle variability of northern hemisphere (NH) TCO exhibits maximum amount during NH spring whereas largest amount in southern hemisphere (SH) TCO occurs during SH spring. In the Atlantic, maximum TCO in both hemispheres occurs in SH spring. These seasonal cycles are shown to be comparable to seasonal cycles present in ground-based ozonesonde measurements. Interannual variability in the Atlantic region indicates a quasi-biennial oscillation (QBO) signal that is out of phase with the QBO present in stratospheric column ozone (SCO). This is consistent with high pollution and high concentrations of mid-to-upper tropospheric O3-producing precursors in this region. The out of phase relation suggests a UV modulation of tropospheric photochemistry caused by the QBO in stratospheric O3. During El Nino events there is anomalously low TCO in the eastern Pacific and high values in the western Pacific, indicating the effects of convectively-driven transport of low-value boundary layer O3 (reducing TCO) and O3 precursors including H2O and OH. A simplified technique is proposed to derive high-resolution maps of TCO in the tropics even in the absence of tropopause-level clouds. This promising approach requires only total ozone gridded measurements and utilizes the small variability observed in TCO near the dateline. This technique has an advantage compared to the CCD method because the latter requires high-resolution footprint measurements of both reflectivity and total ozone in the presence of tropopause-level cloud tops.

Ziemke, J. R.↗
NASA NTRS2012

Observations of Electromagnetic Whistler Precursors at Supercritical Interplanetary Shocks

We present observations of electromagnetic precursor waves, identified as whistler mode waves, at supercritical interplanetary shocks using the Wind search coil magnetometer. The precursors propagate obliquely with respect to the local magnetic field, shock normal vector, solar wind velocity, and they are not phase standing structures. All are right-hand polarized with respect to the magnetic field (spacecraft frame), and all but one are right-hand polarized with respect to the shock normal vector in the normal incidence frame. They have rest frame frequencies f(sub ci) < f much < f(sub ce) and wave numbers 0.02 approx < k rho (sub ce) approx <. 5.0. Particle distributions show signatures of specularly reflected gyrating ions, which may be a source of free energy for the observed modes. In one event, we simultaneously observe perpendicular ion heating and parallel electron acceleration, consistent with wave heating/acceleration due to these waves. Al though the precursors can have delta B/B(sub o) as large as 2, fluxgate magnetometer measurements show relatively laminar shock transitions in three of the four events.

Wilson, L. B., III↗
NASA NTRS2012

Persistent, Widespread Pulsating Aurora: A Case Study

Observations of a pulsating aurora event occurring on February 11, 2008, using the THEMIS all-sky imager array, indicate a spatially and temporally continuous event with a duration of greater than 15 hours and covering a region with a maximum size of greater than 9 hours MLT. The optical pulsations are at times locally interrupted or drowned out by auroral substorm activity, but are observed in the same location once the discrete aurora recedes. The pulsations following the auroral breakup appear to be brighter and have a larger patch size than pre-substorm. This suggests that, while the onset of pulsating aurora is not necessarily dependent upon a substorm precursor, the pulsations are affected and possibly enhanced by the substorm process. The long duration of such pulsating aurora events, enduring for several hours without interruption, is far longer than the expected recovery phase of a substorm, suggesting that pulsating aurora is not strictly a recovery phase phenomenon.

Jones, S. L.↗
NASA NTRS2023

A Recent Impact Origin of Saturn’s Rings and Mid-Sized Moons

We simulate the collision of precursor icy moons analogous to Dione and Rhea as a possible origin forSaturn’s remarkably young rings. Such an event could have been triggered a few hundred million years ago by resonant instabilities in a previous satellite system. Using high-resolution SPH simulations, we find that this kind of impact can produce a wide distribution of massive objects and scatter material throughout the system. This includes the direct placement of pure-ice ejecta onto orbits that enterSaturn’s Roche limit, which could form or rejuvenate rings. In addition, fragments and debris of rock and ice totalling more than the mass of Enceladus can be placed onto highly eccentric orbits that would intersect with any precursor moons orbiting in the vicinity of Mimas, Enceladus, or Tethys. This could prompt further disruption and facilitate a collisional cascade to distribute more debris for potential ring formation, the re-formation of the present-day moons, and to evolve into an eventual cratering population of planeto-centric impactors.

Saturnian satellites↗
NASA NTRS2022

Source and Chemistry of Hydroxymethanesulfonate (HMS) in Fairbanks, Alaska

Fairbanks, Alaska is a subarctic city with fine-particle (PM 2.5 ) concentrations that exceed air quality regulations in winter due to weak dispersion caused by strong atmospheric inversions, local emissions, and the unique chemistry occurring under the cold and dark conditions. Here we report on observations from the winters of 2020 and 2021, motivated by our pilot study which showed exceptionally high concentrations of fine particle hydroxy methane sulfonate (HMS) or related sulfur (IV) species (e.g., sulfite and bisulfite). We deployed an online Particle-Into-Liquid Sampler-Ion Chromatography (PILS-IC) in conjunction with a suite of instruments to determine HMS precursors (HCHO, SO 2 ) and aerosol composition in general, with the goal to characterize the sources and sinks of HMS in wintertime Fairbanks. PM 2.5 HMS comprised a significant fraction of PM 2.5 sulfur (26-41%) and overall PM 2.5 mass concentration (2.8-6.8%) during pollution episodes, substantially higher than what has been observed in other regions, likely due to the exceptionally low temperatures. HMS peaked in January, with lower concentrations in December and February, resulting from changes in precursors as well as meteorological conditions. Strong correlations with inorganic sulfate and organic mass during pollution events suggest HMS is linked to processes responsible for poor air quality episodes. These findings demonstrate unique aspects of air pollution formation in cold and humid atmospheres.

Fine-particle↗