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NASA NTRS1992

Observational support for the current sheet catastrophe model of substorm current disruption

The principles of the current sheet catastrophe models are briefly reviewed, and observations of some of the signatures predicted by the theory are presented. The data considered here include AMPTE/CCE observations of fifteen current sheet disruption events. According to the model proposed here, the root cause of the current disruption is some process, as yet unknown, that leads to an increase in the k sub A parameter. Possible causes for the increase in k sub A are discussed.

Burkhart, G. R.↗

NASA NTRSDate not supplied

A Predictive GNSS Performance Monitor for Autonomous Air Vehicles in Urban Environments

The emergence and development of advanced technologies and vehicle types has created a growing demand for the introduction of new forms of flight operations. These new and increasingly complex operational paradigms such as Advanced and Urban Air Mobility (AAM/UAM) present regulatory authorities and the aviation community with several design and implementation challenges – particularly for highly autonomous vehicles. An overarching and daunting task is finding methods to integrate these emerging operations without compromising safety or disrupting traditional airspace operations. A shift toward a more predictive risk mitigation capability becomes critical to meet this challenge. This paper focus on the development and testing of a prognostic service aimed at estimating the quality of Global Navigation Satellite System (GNSS) performance for an autonomous aircraft in complex environments. The intent of this function is to proactively reduce a flight operations risk of exposure to states that may induce poor or unacceptable navigation system performance by factoring in estimates of GNSS quality into pre-flight and/or in-flight route planning. Methodologies for producing quality estimates are specified and results are provided for selected simulation and flight test cases.

GNSS↗

NASA NTRS2015

Improved Rainfall Estimates and Predictions for 21st Century Drought Early Warning

As temperatures increase, the onset and severity of droughts is likely to become more intense. Improved tools for understanding, monitoring and predicting droughts will be a key component of 21st century climate adaption. The best drought monitoring systems will bring together accurate precipitation estimates with skillful climate and weather forecasts. Such systems combine the predictive power inherent in the current land surface state with the predictive power inherent in low frequency ocean-atmosphere dynamics. To this end, researchers at the Climate Hazards Group (CHG), in collaboration with partners at the USGS and NASA, have developed i) a long (1981-present) quasi-global (50degS-50degN, 180degW-180degE) high resolution (0.05deg) homogenous precipitation data set designed specifically for drought monitoring, ii) tools for understanding and predicting East African boreal spring droughts, and iii) an integrated land surface modeling (LSM) system that combines rainfall observations and predictions to provide effective drought early warning. This talk briefly describes these three components. Component 1: CHIRPS The Climate Hazards group InfraRed Precipitation with Stations (CHIRPS), blends station data with geostationary satellite observations to provide global near real time daily, pentadal and monthly precipitation estimates. We describe the CHIRPS algorithm and compare CHIRPS and other estimates to validation data. The CHIRPS is shown to have high correlation, low systematic errors (bias) and low mean absolute errors. Component 2: Hybrid statistical-dynamic forecast strategies East African droughts have increased in frequency, but become more predictable as Indo- Pacific SST gradients and Walker circulation disruptions intensify. We describe hybrid statistical-dynamic forecast strategies that are far superior to the raw output of coupled forecast models. These forecasts can be translated into probabilities that can be used to generate bootstrapped ensembles describing future climate conditions. Component 3: Assimilation using LSMs CHIRPS rainfall observations (component 1) and bootstrapped forecast ensembles (component 2) can be combined using LSMs to predict soil moisture deficits. We evaluate the skill such a system in East Africa, and demonstrate results for 2013.

Funk, Chris↗

NASA NTRS2015

Improved Rainfall Estimates and Predictions for 21st Century Drought Early Warning

Funk, Chris↗

DOE OSTI2021

Machine learning methods for probabilistic locked-mode predictors in tokamak plasmas

A rotating tokamak plasma can interact resonantly with the external helical magnetic perturbations, also known as error fields. This can lead to locking and then to disruptions. We leverage machine learning (ML) methods to predict the locking events. We use a coupled third-order nonlinear ordinary differential equation model to represent the interaction of the magnetic perturbation and the plasma rotation with the error field. This model is sufficient to describe qualitatively the locking and unlocking bifurcations. Here, we explore using ML algorithms with the simulation data and experimental data, focusing on the methods that can be used with sparse datasets. These methods lead to the possibility of the avoidance of locking in real-time operations. We describe the operational space in terms of two control parameters: the magnitude of the error field and the rotation frequency associated with the momentum source that maintains the plasma rotation. The outcomes are quan- tified by order parameters that completely characterize the state, whether locked or unlocked. We use unsupervised ML methods to classify locked/unlocked states and note the usefulness of a certain normalization of the order parameters. Three supervised ML classifiers are used in suite to estimate the probability of locking in the region of control parameter space with hysteresis, i.e., the set of control parameters for which both locked and unlocked states can exist. The results show that a neural network gives the best estimate of the locking probability. An analogy of the present locking model with the van der Waals equation of state is also provided.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2024

Wall heating by subcritical energetic electrons generated by the runaway electron avalanche source *

Abstract Subcritical energetic electrons (SEEs) produced by the runaway electron (RE) avalanche source at energies below the runaway threshold are found to be the primary contributor to surface heating of plasma-facing components (PFCs) during final loss events. This finding is supported by theoretical analysis, computational modeling with the Kinetic Orbit Runaway electrons Code (KORC), and qualitative agreement with DIII-D experimental observations. The avalanche source generates significantly more secondary electrons below the runaway threshold, which thermalize rapidly when well-confined. However, during a final loss event, the RE beam impacts the first wall, and SEEs are deconfined before they can thermalize. Additionally, because the energy deposition length decreases faster than energy, the deposited energy density, and thus the maximum PFC surface temperature change, is larger for SEEs than REs. KORC simulations employ an analytic first wall to model particle deconfinement onto a non-axisymmetric wall composed of individual tiles. PFC surface heating is calculated using a 1D model extended to include an energy-dependent deposition length scale. Simulations of DIII-D qualitatively agree with infrared (IR) imaging only when SEEs from the avalanche source are included. These results demonstrate that SEEs are the dominant contributor to PFC surface heating and indicate that the avalanche source plays a critical role in the PFC damage caused during final loss events. The prominence of SEEs also has important implications for interpreting IR imaging, one of the primary diagnostics for RE-wall interaction diagnosis, despite REs dominating the energy and current density. This result improves predictions of wall damage due to post-disruption REs to estimate material lifetime and design RE mitigation systems for ITER and future reactors.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

NASA NTRS1984

Operational numerical weather prediction on the CYBER 205 at the National Meteorological Center

The Development Division of the National Meteorological Center (NMC), having the responsibility of maintaining and developing the numerical weather forecasting systems of the center, is discussed. Because of the mission of NMC data products must be produced reliably and on time twice daily free of surprises for forecasters. Personnel of Development Division are in a rather unique situation. They must develop new advanced techniques for numerical analysis and prediction utilizing current state-of-the-art techniques, and implement them in an operational fashion without damaging the operations of the center. With the computational speeds and resources now available from the CYBER 205, Development Division Personnel will be able to introduce advanced analysis and prediction techniques into the operational job suite without disrupting the daily schedule. The capabilities of the CYBER 205 are discussed.

Deaven, D.↗

NASA NTRS1995

An extended galactic population of low-luminosity x-ray sources (CVs?) and the diffuse x-ray background

The incompatibility of the properties of the X-ray background (XRB) with active galactic nuclei (AGNs) contributing approximately greater than 60% at energies of a few keV has often been interpreted as being due to a substantial contribution of a new population of yet unrecognized X-ray sources. The existence of such population has been recently suggested also by an analysis of very deep ROSAT observations which revealed a considerable excess of faint X-ray sources over that expected from QSO evolution models, and that the average spectrum of the resolved sources becomes harder with decreasing flux limit. These sources could be extragalactic in origin, but if they make a substantial contribution to the XRB then they must exhibit much weaker clustering than galaxies or QSOs in order to be consistent with the stringent constraints on source clustering imposed by autocorrelation analyses of the unresolved XRB. We investigate the possibility that the indicated new population of X-ray sources is Galactic in origin. Examining spherical halo and thick disk distributions, we derive the allowed properties of such populations which would resolve the discrepancy found in the number counts of faint sources and be consistent with observational constraints on the total background intensity, the XRB anisotropy, the number of unidentified bright sources, the Galaxy's total X-ray luminosity, and with the results of fluctuation analyses of the unresolved XRB. We find that a flattened Galactic halo (or a thick disk) distribution with a scale height of a few kpc is consistent with all the above requirements. The typical X-ray luminosity of the sources is approximately equal to 10(exp 30-31)ergs/s in the 0.5-2 keV band, the number density of sources in the solar vicinity is approximately 10(exp -4.5)pc(exp -3), their total number in the Galaxy is approximately 10(exp 8.5), and their total contribution to the Galaxy's X-ray luminosity is approximately 10(exp 39) ergs/s. We discuss the possible nature of these soures, including their being subdwarfs, low mass x-ray binaries (LMXBs), massive black holes, and old neutron stars. We argue that the inferred X-ray and optical luminosities of these sources, the slope of their energy spectrum, and the derived local number density and spatial distribution are all consistent with their being intrinsically faint cataclysmic variables with low accretion rates. We suggest a few possibilities for the origin of such population, including an origin from disrupted globular clusters or dark clusters. We make predictions and suggest tests that could either confirm or rule out our proposal in the near future.

Maoz, Eyal↗

NASA NTRS2011

First Observations of a Foreshock Bubble at Earth: Implications for Magnetospheric Activity and Energetic Particle Acceleration

Earth?s foreshock, which is the quasi-parallel region upstream of the bow shock, is a unique plasma region capable of generating several kinds of large-scale phenomena, each of which can impact the magnetosphere resulting in global effects. Interestingly, such phenomena have also been observed at planetary foreshocks throughout our solar system. Recently, a new type of foreshock phenomena has been predicted: foreshock bubbles, which are large-scale disruptions of both the foreshock and incident solar wind plasmas that can result in global magnetospheric disturbances. Here we present unprecedented, multi-point observations of foreshock bubbles at Earth using a combination of spacecraft and ground observations primarily from the Time History of Events and Macroscale Interactions during Substorms (THEMIS) mission, and we include detailed analysis of the events? global effects on the magnetosphere and the energetic ions and electrons accelerated by them, potentially by a combination of first and second order Fermi and shock drift acceleration processes. This new phenomena should play a role in energetic particle acceleration at collisionless, quasi-parallel shocks throughout the Universe.

Turner, D. L.↗

NASA NTRS2022

Evolution of a Dark Vortex on Neptune with Transient Secondary Features

Dark spots on Neptune observed by Voyager and the Hubble Space Telescope are thought to be anticyclones with lifetimes of a few years, in contrast with very long-lived anticyclones in Jupiter and Saturn. The full life cycle of any Neptune dark spot has not been captured due to limited temporal coverage, but our Hubble observations of a recent feature, NDS-2018, provide the most complete long-term observational history of any dark vortex on Neptune. Past observations suggest some dark spots meet their demise by fading and dissipating without migrating meridionally. On the other hand, simulations predict a second pathway with equatorward migration and disruption. Our HST observations suggest NDS-2018 is following the second pathway.

Michael H Wong↗

DOE OSTI2026

Leveraging ARM Data to Improve Models for Predictive Understanding of Energy and Security Challenges

Extreme weather and natural hazards can disrupt the energy sector, affecting demand, generation, transmission, distribution, consumption and operational planning at regional and national scales. These disruptions stem from a broad range of atmospheric phenomena, including winter storms, freezing rain, wet snow loading, severe convection, flooding and landslides, wildfires, prolonged heat, and drought. Many of these same phenomena can also affect national security through impacts to transportation and infrastructure. To support the U.S. Department of Energy (DOE) focus on energy resilience and national security, the Atmospheric Radiation Measurement (ARM) User Facility is uniquely positioned to contribute measurement data, analyses, and modeling frameworks that can significantly improve predictive understanding of these hazards to mitigate their effects. To explore this opportunity, ARM convened a two-part virtual workshop in November 2025. The workshop engaged interdisciplinary experts in atmospheric science, energy systems, modeling, and operations. The goal of the meeting was to engage with these interdisciplinary experts to address three questions: • What are examples of atmospheric processes that represent significant risks to energy security or national security and where are those risks greatest? • What measurements or measurement strategies would improve ARM’s capacity to address these issues? • How can ARM and users of the ARM facility better work with the Energy Exascale Earth System Model (E3SM) and multi-sector modeling communities to apply ARM data to improving E3SM simulations of these phenomena? Participants were asked to submit white papers ahead of the meeting to initiate thinking on these themes and to help organize discussions. Workshop sessions were then organized around themes identified in the white papers. First from the white papers and then through subsequent discussions, workshop participants identified many examples that address the three questions listed above. Participants called out energy system vulnerabilities to weather phenomena such as the impact of freezing rain, strong winds, and excessive heat on power grids. They also noted the effects that weather phenomena could have on energy demand or supply (e.g., through effects of extreme temperatures). They called out security vulnerabilities such as impacts to crops from aerosol-borne pathogens and risks to industry due to melting permafrost in the Arctic. In all, over a dozen meteorological phenomena were linked to energy or security vulnerabilities. For many of the identified phenomena, participants pointed out where ARM was well poised to address issues (e.g., through measurements of cloud microphysics to inform studies of freezing rain) but also noted needs for additional measurements or modified measurement strategies. For example, adaptive scanning of severe weather would be valuable for probing winter storms or severe convection. Participants pointed out the value in integrating external observations with ARM measurements and with applying artificial intelligence (AI) to ARM observation analysis and they advocated for using model simulations to help optimize measurement strategies through Observing System Simulation Experiments (OSSEs). It was clear from the workshop that there are many ways that ARM observations can be used to mitigate energy and security concerns, but meeting participants were also asked to identify what they considered to be the greatest opportunities by ranking issues pertaining to the three workshop questions. This was accomplished through a survey administered to participants between the two virtual sessions. The highest-priority phenomena identified were winter storms, severe convection, and arctic processes. Discussion in the second session, therefore, focused primarily on these three areas, which were most fully developed in exploring ARM opportunities. Nevertheless, it was also clear that ARM has opportunities to contribute to all the identified topics. This report describes the workshop, including input from discussion and white papers (Sections 2 and 3) and a list of priority recommendations (section 4). Many other ideas for ARM contributions are discussed in individual white papers (Appendix D).

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2020

Impedance-Based Prediction of SSR-Generated Harmonics in Doubly-Fed Induction Generators

Doubly-fed induction generators (DFIGs) are prone to subsynchronous resonance (SSR) with series-compensated transmission lines and experiencing SSR-generated harmonics of wide-ranging magnitudes. This paper presents a large-signal impedance-based approach for the prediction of the magnitude of SSR-generated harmonics in DFIGs. Note that the large-signal impedance of a network shows variation in its impedance response with the magnitude of perturbation at its terminals. It is discovered in this paper that the impedance of a series-compen- sated transmission line starts changing with the magnitude of SSR because of the metal-oxide varistor-based protection of series capacitors in the line. The changing line impedance halts the growth of the SSR beyond a certain point, where the DFIG forms a limit-cycle mode and emits harmonics at the SSR frequency. The discovered role of the protection of series capacitors in SSR not only enables the prediction of SSR-generated harmonics but also can be used for the timely detection of an SSR event to avoid system disruption and sudden loss of bulk generation. The large- signal impedance-based prediction of SSR-generated harmonics in DFIG-based wind and hydro generators is demonstrated using numerical simulations of a 2.5-MVA, 690-V DFIG supplying to a series-compensated transmission line.

24 POWER TRANSMISSION AND DISTRIBUTION↗

NASA NTRS2020

Tidal Disruptions of Main Sequence Stars - II. Simulation Methodology and Stellar Mass Dependence of the Character of Full Tidal Disruptions

This paper introduces a series of papers presenting a quantitative theory for the tidal disruption of main-sequence stars by supermassive black holes. Using fully general relativistic hydrodynamics simulations and MESA-model initial conditions, we explore the pericenter-dependence of tidal disruption properties for eight stellar masses (0.15 < M_/M<10)and six black hole masses( ́10<MM105 105BH7). We present here the results most relevant to observations. The effects of internal stellar structure and relativity decouple for both the disruption cross section and the characteristic energy width of the debris. Moreover, the full disruption cross section is almost independent of Må for Må/Me3. Independent of Må, relativistic effects increase the critical pericenter distance for full disruption events by up to a factor of ∼3 relative to the Newtonian prediction. The probability of a direct capture is also independent of Må; at MBH/Me5×106this probability is equal to the probability of a complete disruption. The breadth of the debris energy distribution ΔE can differ from the standard estimate by factors of 0.35−2, depending on Må and MBH, implying a corresponding change(∝(ΔE)−3/2)in the characteristic mass-return timescale. We provide analytic forms, suitable for use in both event rate estimates and parameter inference, to describe all these trends. For partial disruptions, we find a nearly universal relation between the star’s angular momentum and the fraction of Må remaining. Within the “empty loss-cone” regime, partial disruptions must precede full disruptions. These partial disruptions can drastically affect the rate and appearance of subsequent total disruptions

Taeho Ryu↗

NASA NTRS1991

Tessera terrain, Venus - Characterization and models for origin and evolution

Tessera terrain is the dominant tectonic landform in the northern high latitudes of Venus mapped by the Venera 15 and 16 orbiters and is concentrated in the region between the mountain ranges of western Ishtar Terra and Aphrodite Terra. Tesserae are characterized by regionally high topography, a high-degree of small scale surface roughness, and sets of intersecting tectonic features. Available Pioneer Venus line of sight gravity data suggest that tessera terain is compensated at shallow depths relative to many topographic highs on Venus and may be supported by crustal thickness variations. Three types of tessera terrain can be defined on the basis of structural patterns: subparallel ridged terrain (Tsr), trough and ridge terrain (Ttr), and disrupted terrain (Tds). Observed characteristics of tessera terrain are compared to predictions of formational and modificational models in order to begin to address the question of its origin and evolution. It is found that horizontal convergence and late stage gravitational relaxation are basic observations for subparallel ridged terrain and disrupted terrain.

Bindschadler, Duane L.↗

NASA NTRS2020

Tidal Disruptions of Main Sequence Stars - I. Observable Quantities and their Dependence on Stellar and Black Hole Mass

This paper introduces a series of papers presenting a quantitative theory for the tidal disruption of main-sequence stars by supermassive black holes. Using fully general relativistic hydrodynamics simulations and MESA-model initial conditions, we explore the pericenter-dependence of tidal disruption properties for eight stellar masses(MM0.1510)and six black hole masses( MM105 105BH7). We present here the results most relevant to observations. The effects of internal stellar structure and relativity decouple for both the disruption cross section and the characteristic energy width of the debris. Moreover, the full disruption cross section is almost independent of Må for Må/Me3. Independent of Må, relativistic effects increase the critical pericenter distance for full disruption events by up to a factor of∼3 relative to the Newtonian prediction. The probability of a direct capture is also independent of Må; at MBH/Me;5×106 this probability is equal to the probability of a complete disruption. The breadth of the debris energy distribution ΔE can differ from the standard estimate by factors of0.35−2, depending on Må and MBH, implying a corresponding change(∝(ΔE)−3/2)in the characteristic mass-return timescale. We provide analytic forms, suitable for use in both event rate estimates and parameter inference, to describe all these trends. For partial disruptions, we find a nearly universal relation between the star’s angular momentum and the fraction of Må remaining. Within the “empty loss-cone” regime, partial disruptions must precede full disruptions. These partial disruptions can drastically affect the rate and appearance of subsequent total disruptions.

Taeho Ryu↗

DOE OSTI2021

Sulfur Metabolites Play Key System-Level Roles in Modulating Denitrification

Competition between nitrate-reducing bacteria (NRB) and sulfate-reducing bacteria (SRB) for resources in anoxic environments is generally thought to be governed largely by thermodynamics. It is now recognized that intermediates of nitrogen and sulfur cycling (e.g., hydrogen sulfide, nitrite, etc.) can also directly impact NRB and SRB activities in freshwater, wastewater, and sediment and therefore may play important roles in competitive interactions. Here, through comparative transcriptomic and metabolomic analyses, we have uncovered mechanisms of hydrogen sulfide- and cysteine-mediated inhibition of nitrate respiratory growth for the NRB Intrasporangium calvum C5. Specifically, the systems analysis predicted that cysteine and hydrogen sulfide inhibit growth of I. calvum C5 by disrupting distinct steps across multiple pathways, including branched-chain amino acid (BCAA) biosynthesis, utilization of specific carbon sources, and cofactor metabolism. Here, we have validated these predictions by demonstrating that complementation with BCAAs and specific carbon sources relieves the growth inhibitory effects of cysteine and hydrogen sulfide. We discuss how these mechanistic insights give new context to the interplay and stratification of NRB and SRB in diverse environments.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2026

Expanding the genetic toolkit: adenine and cytosine base editors for gene disruption in Aspergillus niger

Despite revolutionizing fungal genetic engineering, conventional CRISPR/Cas9-mediated knockouts rely on DNA double-strand breaks (DSBs), which can cause unwanted insertions and deletions, chromosomal abnormalities, and cytotoxicity. Base editors such as adenine base editors (ABEs), which convert A‧T to G‧C, and cytosine base editors (CBEs), which convert C‧G to T‧A, offer a safer alternative by enabling predictable, target-specific single-nucleotide changes without introducing DSBs. To overcome the limitations of traditional genome editing in filamentous fungi, we developed efficient base-editing systems in Aspergillus niger . For the first time, we constructed an ABE in A. niger , achieving up to 80% editing efficiency and inducing predictable A-to-G mutations at the intended intron sites, disrupting gene function through mRNA mis-splicing. We also developed a highly efficient CBE system, capable of introducing premature stop codons with 50–100% efficiency. To broaden the editing scope, we implemented a Cas9-NG variant recognizing a relaxed PAM sequence requiring only a single guanine (G), enabling editing at start codons and splice sites. Leveraging this expanded scope, we established gene disruption approaches by targeting start codons via ABE-mediated A-to-G conversions (ATG-to-GTG and ATG-to-ACG) and CBE-mediated C-to-T conversion (ATG-to-ATA). Additionally, our base-editing systems enable multiplex gRNA delivery and marker-free editing of multiple genes. Collectively, the scope-expanding strategies increase the number of genes targetable for disruption by base-editing in A. niger by 26.3% and enable near-complete coverage of 96% of the coding genes. Overall, this work demonstrates the potential of ABE and CBE systems as versatile, efficient, and safer alternatives to DSBs-based gene disruption in filamentous fungi.

Aspergillus↗

NASA NTRS2021

Prospect of Increased Disruption to the QBO in a Changing Climate

The quasi-biennial oscillation (QBO) of tropical stratospheric winds was disrupted during the 2019/20 Northern Hemisphere winter. We show that this latest disruption to the regular QBO cycling was similar in many respects to that seen in 2016, but initiated by horizontal momentum transport from the Southern Hemisphere. The predictable signal associated with the QBO’s quasi-regular phase progression is lost during disruptions and the oscillation reemerges after a few months significantly shifted in phase from what would be expected if it has progressed uninterrupted. We infer from an increased wave-momentum flux into equatorial latitudes seen in climate model projections that disruptions to the QBO are likely to become more common in future. Consequently it is possible that in the future the QBO could be a less reliable source of predictability on lead times extending out to several years than it currently is.

James A Anstey↗