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At least 649 records · Page 36
All sourcesNASA NTRSDOE OSTI
NASA NTRS2012

Forecasting the Solar Drivers of Solar Energetic Particle Events

Large flares and fast CMEs are the drivers of the most severe space weather including Solar Energetic Particle Events (SEP Events). Large flares and their co-produced CMEs are powered by the explosive release of free magnetic energy stored in non-potential magnetic fields of sunspot active regions. The free energy is stored in and released from the low-beta regime of the active region's magnetic field above the photosphere, in the chromosphere and low corona. From our work over the past decade and from similar work of several other groups, it is now well established that (1) a proxy of the free magnetic energy stored above the photosphere can be measured from photospheric magnetograms, maps of the measured field in the photosphere, and (2) an active region's rate of production of major CME/flare eruptions in the coming day or so is strongly correlated with its present measured value of the free-energy proxy. These results have led us to use the large database of SOHO/MDI full-disk magnetograms spanning Solar Cycle 23 to obtain empirical forecasting curves that from an active region's present measured value of the free-energy proxy give the active region's expected rates of production of major flares, CMEs, fast CMEs, and SEP Events in the coming day or so (Falconer et al 2011, Space Weather, 9, S04003). We will present these forecasting curves and demonstrate the accuracy of their forecasts. In addition, we will show that the forecasts for major flares and fast CMEs can be made significantly more accurate by taking into account not only the value of the free energy proxy but also the active region's recent productivity of major flares; specifically, whether the active region has produced a major flare (GOES class M or X) during the past 24 hours before the time of the measured magnetogram.

Falconer, David A.↗
NASA NTRS2012

Forecasting the Solar Drivers of Severe Space Weather from Active-Region Magnetograms

Large flares and fast CMEs are the drivers of the most severe space weather including Solar Energetic Particle Events (SEP Events). Large flares and their co-produced CMEs are powered by the explosive release of free magnetic energy stored in non-potential magnetic fields of sunspot active regions. The free energy is stored in and released from the low-beta regime of the active region s magnetic field above the photosphere, in the chromosphere and low corona. From our work over the past decade and from similar work of several other groups, it is now well established that (1) a proxy of the free magnetic energy stored above the photosphere can be measured from photospheric magnetograms, and (2) an active region s rate of production of major CME/flare eruptions in the coming day or so is strongly correlated with its present measured value of the free-energy proxy. These results have led us to use the large database of SOHO/MDI full-disk magnetograms spanning Solar Cycle 23 to obtain empirical forecasting curves that from an active region s present measured value of the free-energy proxy give the active region s expected rates of production of major flares, CMEs, fast CMEs, and SEP Events in the coming day or so (Falconer et al 2011, Space Weather, 9, S04003). We will present these forecasting curves and demonstrate the accuracy of their forecasts. In addition, we will show that the forecasts for major flares and fast CMEs can be made significantly more accurate by taking into account not only the value of the free energy proxy but also the active region s recent productivity of major flares; specifically, whether the active region has produced a major flare (GOES class M or X) during the past 24 hours before the time of the measured magnetogram. By empirically determining the conversion of the value of free-energy proxy measured from a GONG or HMI magnetogram to that which would be measured from an MDI magnetogram, we have made GONG and HMI magnetograms useable with our MDI-based forecasting curves to forecast event rates.

Falconer, David A.↗
NASA NTRS2012

Forecasting Space Weather from Magnetograms

Large flares and fast CMEs are the drivers of the most severe space weather including Solar Energetic Particle Events (SEP Events). Large flares and their co-produced CMEs are powered by the explosive release of free magnetic energy stored in non-potential magnetic fields of sunspot active regions. The free energy is stored in and released from the low-beta regime of the active region s magnetic field above the photosphere, in the chromosphere and low corona. From our work over the past decade and from similar work of several other groups, it is now well established that (1) a proxy of the free magnetic energy stored above the photosphere can be measured from photospheric magnetograms, maps of the measured field in the photosphere, and (2) an active region s rate of production of major CME/flare eruptions in the coming day or so is strongly correlated with its present measured value of the free-energy proxy. These results have led us to use the large database of SOHO/MDI full-disk magnetograms spanning Solar Cycle 23 to obtain empirical forecasting curves that from an active region s present measured value of the free-energy proxy give the active region s expected rates of production of major flares, CMEs, fast CMEs, and SEP Events in the coming day or so (Falconer et al 2011, Space Weather, 9, S04003). For each type of event, the expected rate is readily converted to the chance that the active region will produce such an event in any given forward time window of a day or so. If the chance is small enough (e.g. <5%), the forecast is All Clear for that type of event. We will present these forecasting curves and demonstrate the accuracy of their forecasts. In addition, we will show that the forecasts for major flares and fast CMEs can be made significantly more accurate by taking into account not only the value of the free energy proxy but also the active region s recent productivity of major flares; specifically, whether the active region has produced a major flare (GOES class M or X) during the past 24 hours before the time of the measured magnetogram.

Falconer, David A.↗
NASA NTRS2012

Forecasting the Solar Drivers of Severe Space Weather from Active-Region Magnetograms

Large flares and fast CMEs are the drivers of the most severe space weather including Solar Energetic Particle Events (SEP Events). Large flares and their co-produced CMEs are powered by the explosive release of free magnetic energy stored in non-potential magnetic fields of sunspot active regions. The free energy is stored in and released from the low-beta regime of the active region s magnetic field above the photosphere, in the chromosphere and low corona. From our work over the past decade and from similar work of several other groups, it is now well established that (1) a proxy of the free magnetic energy stored above the photosphere can be measured from photospheric magnetograms, and (2) an active region s rate of production of major CME/flare eruptions in the coming day or so is strongly correlated with its present measured value of the free-energy proxy. These results have led us to use the large database of SOHO/MDI full-disk magnetograms spanning Solar Cycle 23 to obtain empirical forecasting curves that from an active region s present measured value of the free-energy proxy give the active region s expected rates of production of major flares, CMEs, fast CMEs, and SEP Events in the coming day or so (Falconer et al 2011, Space Weather, 9, S04003). We will present these forecasting curves and demonstrate the accuracy of their forecasts. In addition, we will show that the forecasts for major flares and fast CMEs can be made significantly more accurate by taking into account not only the value of the free energy proxy but also the active region s recent productivity of major flares; specifically, whether the active region has produced a major flare (GOES class M or X) during the past 24 hours before the time of the measured magnetogram. By empirically determining the conversion of the value of free-energy proxy measured from a GONG or HMI magnetogram to that which would be measured from an MDI magnetogram, we have made GONG and HMI magnetograms useable with our MDI-based forecasting curves to forecast event rates.

Falconer, David A.↗
NASA NTRS2014

Aurora on Ganymede

Jupiter's largest satellite Ganymede is unique because it possesses an internal magnetic field strong enough to create a small magnetosphere around the satellite. The interaction between Ganymede's magentosphere and the Jovian magnetic field and magnetospheric plasma generates classic polar auroral emissions from Ganymede which have been captured in a series of stunning ultraviolet images using the Hubble Space Telescope on six different dates from 1998 to 2012. Analysis of these images (McGrath et al. 2013) has provided a nearly global mapping of the location of Ganymede's auroral ovals, which appear to be remarkably stable in the 14 years spanning the observations. The location of the auroral ovals is compared with several model predictions of the boundary between open and closed magnetic field lines (Koop and Ip 2002; Khurana et al. 2007; Jia et al. 2009), a region where strong field aligned potentials are a likely candidate to accelerate electrons that produce the auroral emissions. The location of the auroral emission is also compared with the polar cap boundary on Ganymede, thought to be produced by charged particle bombardment of the polar region, as delineated by color ratio images acquired by the Galileo mission (Khurana et al. 2007).

McGrath, Melissa A.↗
NASA NTRSDate not supplied

A Data-Driven Reduced Order Model of an Isolated Rotor

There are numerous conceptual design stage rotorcraft analysis tasks which demand a high-fidelity and low cost method for rotor load distribution predictions. Considering Urban Air Mobility (UAM) vehicles aim to operate in close proximity to buildings and with unique rotor configurations, there is a significant challenge in quickly and accurately modeling rotors operating in complex, turbulent flow fields. One potential path for deriving a high-fidelity, low cost rotor model is with data-driven surrogate modeling. In this study, an initial investigation is taken to apply a proper orthogonal decomposition (POD) based reduced order model (ROM) for the purpose of pressure distribution prediction. In this study, a POD ROM was derived to produce distributed pressure predictions on rotor blades subjected to topology change due to variation in twist and taper ratio. Rotor twist was varied between 0◦, 10◦, 20◦, and 30◦ while taper ratio was varied between 1.0, 0.9, 0.8, and 0.7. All rotors consisted of a single blade. The POD ROM was validated for three demonstration cases; a high thrust rotor in hover, a low thrust rotor in hover, and a rotor in forward flight with a flight speed of M = 0.1. Results showed highly accurate distributed load predictions could be achieved at minimal computational cost. Computational cost for hovering blade surface pressure modeling was reduced from 12 hours on 440 cores to 10−5 seconds on a single core. For blade in forward flight cost was reduced from 20 hours on 440 cores to 0.6 seconds on a single core. For cases of high thrust and low thrust rotors, POD ROM was used to undergo a design optimization of the rotor such that figure of merit was maximized. Total optimization time for each case was 1 minute.

Data-Driven↗
NASA NTRSDate not supplied

A Study of the Kinematic and Dynamic Processes associated with Mesoscale Snowbands in a Midwest United States Snowstorm on 5 February 2020

Mesoscale snowbands are frequently responsible for dumping large amounts of snow over a relatively small region and pose a considerable forecasting challenge. The present study focuses on the mesoscale snowbands observed on 5 February 2020 over the Midwest United States. In order to improve the forecasting of mesoscale snowbands, it is important to understand the processes that organize these features. To this end, we are investigating the kinematic and dynamic processes that shape the mesoscale snowbands using a combination of high-altitude airborne radar, in-situ aircraft measurements, surface observations, and model simulations. This presentation will primarily focus on the three-dimensional structure of the mesoscale snowbands in terms of EXRAD reflectivity and horizontal winds. The horizontal winds are retrieved from the EXRAD scanning-beam Doppler velocities using a VAD technique. These winds, in combination with virtual potential temperature taken from the HRRR operational analysis, are used to compute the bulk Richardson number in order to investigate any contributions to banding features that might be tied to Kelvin-Helmholtz instability. Our analysis does not support the presence of Kelvin-Helmholtz instability. That said, low, but not subcritical, Richardson numbers were found near the top of some banding features in this event and it is possible that the model analysis is smoothing out the virtual potential temperature fields. Finally, we present arguments for using a flight module designed to sample the along-band structures with particular emphasis on observing generating cells and low-level microphysics.

Charles N. Helms↗
NASA NTRS2018

Statistical Analysis of Torus and Kink Instabilities in Solar Eruptions

A recent laboratory experiment of ideal magnetohydrodynamic instabilities revealed four distinct eruption regimes readily distinguished by the torus instability (TI) and helical kink instability (KI) parameters. To establish its observational counterpart, we collected 38 solar flares (stronger than GOES-class M5 in general) that took place within 45° of disk center during 2011–2017, 26 of which are associated with a halo or partial halo coronal mass ejection (CME; i.e., ejective events), while the others are CME-less (i.e., confined events). This is a complete sample of solar events satisfying our selection criteria detailed in the paper. For each event, we calculate a decay index n of the potential strapping field above the magnetic flux rope (MFR) in and around the flaring magnetic polarity inversion line (a TI parameter) and the unsigned twist number T(sub w) of the nonlinear force-free field lines forming the same MFR (a KI parameter). We then construct an n–T(sub w) diagram to investigate how the eruptiveness depends on these parameters. We find that (1) T(sub w) appears to play little role in discriminating between confined and ejective events; (2) the events with n ≳ 0.8 are all ejective, and all confined events have n ≲ 0.8. However, n ≳ 0.8 is not a necessary condition for eruption because some events with n ≲ 0.8 also erupted. In addition, we investigate the MFR’s geometrical parameters, apex height, and distance between footpoints, as a possible factors for the eruptiveness. We briefly discuss the difference of the present result for solar eruptions with that of the laboratory result in terms of the role played by magnetic reconnection.

Solar activity↗
NASA NTRSDate not supplied

Enhancing Air Traffic Control Planning with Automatic Speech Recognition

The decisions made during the Federal Aviation Administration Air Traffic Control System Command Center's planning teleconferences hold significant sway over the National Airspace System. Held every two hours, these teleconferences convene air traffic managers and stakeholders from across the nation to discuss airspace conditions, weather, and constraints, leading to the formulation and adjustment of traffic management initiatives. Given the critical nature of these decisions, the need for accurate and efficient record-keeping is paramount. In recent years, the application of automatic speech recognition has gained popularity across diverse industries, including aviation. While traditional applications focus on transcribing air traffic control communication, this paper explores a unique application of automatic speech recognition by converting the audio from planning teleconferences into text transcriptions. This innovative approach addresses key challenges in the field, presenting potential benefits for quality assurance, real-time participation, and downstream natural language processing tasks. A notable breakthrough in the machine learning community, namely the transformer neural network architecture, forms the backbone of the proposed solution in this paper. The transformer architecture's role in this research represents a paradigm shift in the efficiency of automatic speech recognition models. By reducing the amount of in-domain training data required, this architecture allows for the fine-tuning of such models like Whisper, originally pretrained on vast English speech datasets. The adaptability of the transformer architecture proves invaluable in capturing the nuances of aviation terminology and specific language used in planning teleconferences. Leveraging the Whisper model as a baseline, our research details the fine-tuning and validation using a dataset comprising 20 hours of meticulously transcribed planning teleconferences. Notably, the baseline pretrained Whisper model exhibited a word error rate of 18.77%. Through the fine-tuning process, the model achieved a substantial improvement, demonstrating an impressive performance with a reduced word error rate of 6.82%. This substantial decrease in WER not only highlights the effectiveness of the transformer architecture but also emphasizes the practical advancements achieved through the application of automatic speech recognition in this specific domain. The utilization of automatic speech recognition in planning teleconferences in this work introduces several novelties. Firstly, the creation of text transcriptions offers a valuable tool for quality assurance and facilitates the efficient review of teleconferences. This is an important aspect of the proposed solution, given the time-sensitive and high-stakes nature of decisions made during these meetings. Furthermore, text-searchable transcriptions provide a streamlined approach for locating and validating critical information, potentially saving hours of manual effort in searching through audio recordings. Moreover, our research identifies a key use case for external facilities and stakeholders. In situations where attendance at the planning teleconference is not feasible, having access to text transcriptions in real-time or shortly after the teleconference ends, proves to be a time-saving and informative resource. This feature enhances collaboration and ensures that stakeholders can stay abreast of important discussions and decisions even in their absence. Despite the efficiency gains facilitated by the transformer architecture in automatic speech recognition technology, it is essential to acknowledge the human factors in data creation. Subject matter experts play a crucial role in accurately transcribing planning teleconferences due to the specificity and complexity of the information discussed. The research dataset, consisting of 20 hours of transcribed planning teleconferences, forms the foundation for fine-tuning and validating the Whisper model. The achieved word error rate of 6.82% demonstrates promising advancements, particularly in recognizing essential aviation terminology within the teleconferences. In conclusion, this paper presents a comprehensive exploration of the application of automatic speech recognition in Air Traffic Control System Command Center planning teleconferences, leveraging the transformer architecture for enhanced efficiency. The novel contributions lie in the improved accessibility of decision-making records, real-time participation opportunities for external stakeholders, and the potential for downstream natural language processing advancements. As the aviation industry continues to evolve, the integration of automatic speech recognition technologies holds the promise of revolutionizing decision-making processes and contributing to the overall safety and efficiency of air traffic management.

ATM↗
NASA NTRSDate not supplied

Video Analysis for Surveillance of Spacecraft Parachute Systems

The Commercial Crew Program (CCP) has established a surveillance methodology to ensure the reliability of spacecraft parachute systems. The implemented methodology relies on an interconnected framework consisting of imagery analysis, hardware inspections, and vehicle data analysis. Imagery analysis serves as a foundation for these core activities which provide a robust approach to the surveillance of spacecraft parachute systems. As the surveillance framework has been developed, the role of imagery has become more prominent, and therefore imagery requirements have changed. To complete photogrammetric analysis, careful consideration must be made to the role of imagery, required data, imagery requirements, the analysis process, and mission planning. The role of imagery will drive the required data, which will in turn drive imagery requirements. Imagery requirements are likely to drive mission planning through consideration to camera selection and placement. If onboard imagery is required, the camera and data system must be implemented prior to launch. If external imagery is required, the photography package must be implemented such that it can be positioned for a return and free of potential debris fields. For these reasons, an integrated approach must be used to build an imagery package around the required analysis with careful coordination with mission planners.

parachutes↗
NASA NTRSDate not supplied

Video Analysis for Surveillance of Spacecraft Parachute Systems

The Commercial Crew Program (CCP) has established a surveillance methodology to ensure the reliability of spacecraft parachute systems. The implemented methodology relies on an interconnected framework consisting of imagery analysis, hardware inspections, and vehicle data analysis. Imagery analysis serves as a foundation for these core activities which provide a robust approach to the surveillance of spacecraft parachute systems. As the surveillance framework has been developed, the role of imagery has become more prominent, and therefore imagery requirements have changed. To complete photogrammetric analysis, careful consideration must be made to the role of imagery, required data, imagery requirements, the analysis process, and mission planning. The role of imagery will drive the required data, which will in turn drive imagery requirements. Imagery requirements are likely to drive mission planning through consideration to camera selection and placement. If onboard imagery is required, the camera and data system must be implemented prior to launch. If external imagery is required, the photography package must be implemented such that it can be positioned for a return and free of potential debris fields. For these reasons, an integrated approach must be used to build an imagery package around the required analysis with careful coordination with mission planners.

parachutes↗
DOE OSTI2025

Machine-Learned Force Field for Molecular Dynamics Simulations of Nonequilibrium Ammonia Synthesis on Iron Catalysts

Ammonia (NH 3 ) is one of the most important industrial chemicals. The conventional NH 3 synthesis method-the Haber–Bosch process-converts atmospheric nitrogen (N 2 ) into NH 3 using H 2 with an iron (Fe) catalyst. However, this process requires high pressures (100–200 atm) and temperatures (700–800 K) near thermal equilibrium. Recently, Fe-based nanocatalysts have been reported to produce promising NH 3 yields under atmospheric pressures and temperature-modulated nonequilibrium conditions. Understanding the mechanism of nonequilibrium catalysis with programmed temperature variation could help to optimize this fully electrified and less energy-intensive process. Although reactive molecular dynamics (RMD) simulations can be a useful tool to model nonequilibrium catalytic processes, they require the development of accurate force fields (i.e., interatomic potentials). Here, we present a machine-learned (ML) force field within the Deep Potential MD (DPMD) framework, trained using periodic density functional theory (DFT) calculations, to model NH 3 synthesis on Fe catalysts with various surface adsorbates such as *N, *H, *N 2 , *H 2 , *NH, *NH 2 , and *NH 3 . Here, we generated the DFT data from static models of elementary reactions on the most stable (110) surface of body-centered cubic Fe, which then were augmented by data from constant number of particles–volume–temperature (NVT) DFT-MD trajectories at various temperatures. Finally, we utilized the fully optimized ML force field to investigate reaction dynamics at an Fe(110) surface at linearly increasing temperatures using NVT-DPMD simulations. Our simulations indicate that pulsed temperature ramping could prove favorable for NH3 synthesis. For example, we conducted ramping under multiple sets of conditions: (i) from 900 to 1200 K over periods of 0.1–0.3 ns for Fe surfaces precovered with N or NH along with H; and (ii) from 300 to 600 K over 0.1–0.3 ns for Fe surfaces precovered with NH 3 . While our simulations so far are limited to short time scales (very rapid heating), these observations shed light on the mechanism of the high NH 3 synthesis rate achieved in a novel temperature-modulated nonequilibrium catalytic reactor using pulsed heating and cooling.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1981

Spherical-earth gravity and magnetic anomaly modeling by Gauss-Legendre quadrature integration

Gauss-Legendre quadrature integration is used to calculate the anomalous potential of gravity and magnetic fields and their spatial derivatives on a spherical earth. The procedure involves representation of the anomalous source as a distribution of equivalent point gravity poles or point magnetic dipoles. The distribution of equivalent point sources is determined directly from the volume limits of the anomalous body. The variable limits of integration for an arbitrarily shaped body are obtained from interpolations performed on a set of body points which approximate the body's surface envelope. The versatility of the method is shown by its ability to treat physical property variations within the source volume as well as variable magnetic fields over the source and observation surface. Examples are provided which illustrate the capabilities of the technique, including a preliminary modeling of potential field signatures for the Mississippi embayment crustal structure at 450 km.

Von Frese, R. R. B.↗
NASA NTRS1985

Acoustic radiation potential on a sphere in plane, cylindrical, and spherical standing wave fields

The method of Gor'kov is applied for deriving the acoustic radiation potential on a sphere in an arbitrary sound field. Generalized potential and force expressions are derived for arbitrary standing wave modes in rectangular, cylindrical, and spherical geometries for the case where the sphere radius is much smaller than the wavelength. Criteria for determining radiation-potential minima are derived and examples of characteristic spatial radiation-potential profiles are presented. Single modes that can sustain stable positioning are discussed for each geometry. The localizing force strengths for representative standing wave modes in the three geometries are also compared. The positioning of samples due to acoustic forces only are considered. However, the method developed is general and is extended to include gravity or other external forces.

Barmatz, M.↗
NASA NTRS2015

Synthetic Astrobiology

Synthetic biology - the design and construction of new biological parts and systems and the redesign of existing ones for useful purposes - has the potential to transform fields from pharmaceuticals to fuels. Our lab has focused on the potential of synthetic biology to revolutionize all three major parts of astrobiology: Where do we come from? Where are we going? and Are we alone? For the first and third, synthetic biology is allowing us to answer whether the evolutionary narrative that has played out on planet earth is likely to have been unique or universal. For example, in our lab we are re-evolving the biosynthetic pathways of amino acids in order to understand potential capabilities of an early organism with a limited repertoire of amino acids and developing techniques for the recovery of metals from spent electronics on other planetary bodies. In the future synthetic biology will play an increasing role in human activities both on earth, in fields as diverse as human health and the industrial production of novel bio-composites. Beyond earth, we will rely increasingly on biologically-provided life support, as we have throughout our evolutionary history. In order to do this, the field will build on two of the great contributions of astrobiology: studies of the origin of life and life in extreme environments.

Potential Fields↗
NASA NTRS1976

A submerged singularity method for calculating potential flow velocities at arbitrary near-field points

A discrete singularity method has been developed for calculating the potential flow around two-dimensional airfoils. The objective was to calculate velocities at any arbitrary point in the flow field, including points that approach the airfoil surface. That objective was achieved and is demonstrated here on a Joukowski airfoil. The method used combined vortices and sources ''submerged'' a small distance below the airfoil surface and incorporated a near-field subvortex technique developed earlier. When a velocity calculation point approached the airfoil surface, the number of discrete singularities effectively increased (but only locally) to keep the point just outside the error region of the submerged singularity discretization. The method could be extended to three dimensions, and should improve nonlinear methods, which calculate interference effects between multiple wings, and which include the effects of force-free trailing vortex sheets. The capability demonstrated here would extend the scope of such calculations to allow the close approach of wings and vortex sheets (or vortices).

Maskew, B.↗
DOE OSTI2019

Influences of the impurity and magnetic field on the probability density and the period of the asymmetric Gaussian potential qubit

The eigenenergies and eigenfunctions of the ground and first-excited states of an electron, which is coupled to an LO-phonon in a quantum dot with an asymmetric Gaussian (AG) potential, Coulomb bound potential and the magnetic field was studied by using Lee-Low-Pines transformation and Pekar variation method. A single qubit can be realized in this two-level quantum system. Numerical results show that the probability density of electrons in the qubit oscillates with changing the time, the well width and the well depth the AG potential. The probability density obviously fluctuates with changes in the magnetic-field cyclotron (MFC) frequency, the dielectric constant (DC) ratio and the electron–phonon coupling (EPC) strength, respectively, which is not conducive to constructing a suitable qubit. The oscillation period of the qubit decreases with increasing the DC ratio, EPC strength and the MFC frequency, respectively, which has an adverse effect on the survival time of qubit.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗