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At least 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Outer Radiation Belt Flux and Phase Space Density Response to Sheath Regions: Van Allen Probes and GPS Observations

Turbulent and compressed sheath regions preceding interplanetary coronal mass ejections strongly impact electron dynamics in the outer radiation belt. Changes in electron flux can occur on timescales of tens of minutes, which are unlikely to be captured by a two-satellite mission. The recently released Global Positioning System (GPS) data set generally has shorter revisit times (at L ~ 4–8) owing to the large number of satellites in the constellation equipped with energetic particle detectors. Investigating electron fluxes at energies from 140 keV to 4 MeV and sheaths observed in 2012–2018, we show that the flux response to sheaths on a timescale of 6 hr, previously reported from Van Allen Probes (RBSP) data, is reproduced by GPS measurements. Furthermore, GPS data enables derivation of the response on a timescale of 30 min, which further confirms that the energy and L-shell dependent changes in electron flux are associated with the impact of the sheath. Sheath-driven loss is underestimated over longer timescales as the electrons recover during the ejecta. We additionally show the response of electron phase space density (PSD), which is a key quantity in identifying non-adiabatic loss from the system and electron energization through wave-particle interactions. The PSD response is calculated from both RBSP and GPS data for the 6 hr timescale, as well as from GPS data for the 30 min timescale. The response is divided based on the geoeffectiveness of the sheaths revealing that electrons are effectively accelerated only during geoeffective sheaths, while loss commonly occurs during all sheaths.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

Latent space dynamics identification for interface tracking with application to shock-induced pore collapse

Capturing sharp, evolving interfaces remains a central challenge in reduced-order modeling, especially when data is limited and the system exhibits localized nonlinearities or discontinuities. Here, we propose LaSDI-IT (Latent Space Dynamics Identification for Interface Tracking), a data-driven framework that combines low-dimensional latent dynamics learning with explicit interface-aware encoding to enable accurate and efficient modeling of physical systems involving moving material boundaries. At the core of LaSDI-IT is a revised autoencoder architecture that jointly reconstructs the physical field and an indicator function representing material regions or phases, allowing the model to track complex interface evolution without requiring detailed physical models or mesh adaptation. The latent dynamics are learned through linear regression in the encoded space and generalized across parameter regimes using Gaussian process interpolation with greedy sampling. We demonstrate LaSDI-IT on the problem of shock-induced pore collapse in high explosives, a process characterized by sharp temperature gradients and dynamically deforming pore geometries. The method achieves relative prediction errors below 9% across the parameter space, accurately recovers key quantities of interest such as pore area and hot spot formation, and matches the performance of dense training with only half the data. This latent dynamics prediction was 10 6 times faster than the conventional high-fidelity simulation, proving its utility for multi-query applications. These results highlight LaSDI-IT as a general, data-efficient framework for modeling discontinuity-rich systems in computational physics, with potential applications in multiphase flows, fracture mechanics, and phase change problems.

Gaussian process↗
DOE OSTI2024

Unveiling the Electrocatalytic Hydrogen Evolution Reaction Pathway on RuP 2 through Ab Initio Grand Canonical Monte Carlo

In this study, the high catalytic reactivity of ruthenium phosphide (RuP 2 ) has been identified by first-principles density functional theory (DFT) calculations for the electrocatalytic hydrogen evolution reaction (HER). Complex surface reconstructions are considered by applying the ab initio grand canonical Monte Carlo (ai-GCMC) algorithm, efficiently providing a sufficient phase-space exploration of possible surfaces. Combined with surface-phase Pourbaix diagrams, we are able to identify the actual surfaces that obtained under specific experimental environments, thus leading to a more accurate understanding of the nature of the active sites and the binding strength of adsorbates. Specifically, through hundreds of surface reconstructions and hydrogenation states generated with ai-GCMC, we identify the most favorable surface phases of RuP 2 under aqueous acidic conditions. We discover that the HER activity is determined by multiple surfaces with different stoichiometries within a narrow electrode potential window. Low HER overpotential (η) has been found for each of the identified surfaces, as low as 0.04 V. High H-coverage reconstructed surfaces have been discovered under acidic conditions, and the surface Ru sites introduced by additional Ru adatoms or exposed by P-vacancies serve as the active sites for HER based on their nearly reversible H binding. Furthermore, this work provides atomistic insights into the origin of high HER activity on RuP 2 by exploring the dynamic surface phases of electrocatalysts and features a generalizable method to explore the reconstructed/hydrogenated surface space as a function of experimental conditions.

25 ENERGY STORAGE↗
DOE OSTI2023

On fast simulation of dynamical system with neural vector enhanced numerical solver

The large-scale simulation of dynamical systems is critical in numerous scientific and engineering disciplines. However, traditional numerical solvers are limited by the choice of step sizes when estimating integration, resulting in a trade-off between accuracy and computational efficiency. To address this challenge, we introduce a deep learning-based corrector called Neural Vector (NeurVec), which can compensate for integration errors and enable larger time step sizes in simulations. Our extensive experiments on a variety of complex dynamical system benchmarks demonstrate that NeurVec exhibits remarkable generalization capability on a continuous phase space, even when trained using limited and discrete data. NeurVec significantly accelerates traditional solvers, achieving speeds tens to hundreds of times faster while maintaining high levels of accuracy and stability. Moreover, NeurVec’s simple-yet-effective design, combined with its ease of implementation, has the potential to establish a new paradigm for fast-solving differential equations based on deep learning.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Path Properties of Atmospheric Transitions: Illustration with a Low-Order Sudden Stratospheric Warming Model

Many rare weather events, including hurricanes, droughts, and floods, dramatically impact human life. To accurately forecast these events and characterize their climatology requires specialized mathematical techniques to fully leverage the limited data that are available. Here we describe transition path theory (TPT), a framework originally developed for molecular simulation, and argue that it is a useful paradigm for developing mechanistic understanding of rare climate events. TPT provides a method to calculate statistical properties of the paths into the event. As an initial demonstration of the utility of TPT, we analyze a low-order model of sudden stratospheric warming (SSW), a dramatic disturbance to the polar vortex that can induce extreme cold spells at the surface in the midlatitudes. SSW events pose a major challenge for seasonal weather prediction because of their rapid, complex onset and development. Climate models struggle to capture the long-term statistics of SSW, owing to their diversity and intermittent nature. We use a stochastically forced Holton–Mass-type model with two stable states, corresponding to radiative equilibrium and a vacillating SSW-like regime. In this stochastic bistable setting, from certain probabilistic forecasts TPT facilitates estimation of dominant transition pathways and return times of transitions. These “dynamical statistics” are obtained by solving partial differential equations in the model’s phase space. With future application to more complex models, TPT and its constituent quantities promise to improve the predictability of extreme weather events through both generation and principled evaluation of forecasts.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1993

Physics of the magnetotail current sheet

The Earth's magnetotail plays an important role in the solar-wind-magnetosphere coupling. At the midplane of the magnetotail is a current sheet where the dominant magnetic field component reverses sign. The charged particle motion in and near the current sheet is collisionless and nonintegrable, exhibiting chaotic scattering. The current understanding of the dynamical properties of the charged particle motion is discussed. In particular, the relationships between particle dynamics and global attributes of the system are elucidated. Geometrical properties of the phase space determine important physical observables on both micro- and macroscales.

Chen, James↗
NASA NTRS1996

Application of Tracking and Data Relay Satellite (TDRS) Differenced One-Way Doppler (DOWD) Tracking Data for Orbit Determination and Station Acquisition Support of User Spacecraft Without TDRS Compatible Transponders

Many spacecraft are launched today with only an omni-directional (omni) antenna and do not have an onboard Tracking and Data Relay Satellite (TDRS) transponder that is capable of coherently returning a carrier signal through TDRS. Therefore, other means of tracking need to be explored and used to adequately acquire the spacecraft. Differenced One-Way Doppler (DOWD) tracking data are very useful in eliminating the problems associated with the instability of the onboard oscillators when using strictly one-way Doppler data. This paper investigates the TDRS DOWD tracking data received by the Goddard Space Flight Center (GSFC) Flight Dynamics Facility (FDF) during the launch and early orbit phases for the the Interplanetary Physics Laboratory (WIND) and the National Oceanographic and Atmospheric Administration (NOAA)-J missions. In particular FDF personnel performed an investigation of the data residuals and made an assessment of the acquisition capabilities of DOWD-based solutions. Comparisons of DOWD solutions with existing data types were performed and analyzed in this study. The evaluation also includes atmospheric editing of the DOWD data and a study of the feasibility of solving for Doppler biases in an attempt to minimize error. Furthermore, by comparing the results from WIND and NOAA-J, an attempt is made to show the limitations involved in using DOWD data for the two different mission profiles. The techniques discussed in this paper benefit the launches of spacecraft that do not have TDRS transponders on board, particularly those launched into a low Earth orbit. The use of DOWD data is a valuable asset to missions which do not have a stable local oscillator to enable high-quality solutions from the one-way/return-link Doppler tracking data.

Olszewski, A. D., Jr.↗
NASA NTRS2009

The Anomalous Low State of LMC X-3

Archival RXTE ASM and PCA observations of the black hole binary LMC X-3 reveal a dramatic and extended low state lasting from December 8, 2003 until March 18, 2004, unprecedented both in its Low luminosity (Lx(2-10keV)=4.2x 1035 ergs s-1, approximately 4 times fainter than ever before seen from LMC X-3 in its low/hard state, and representing 0.15% of its X-ray luminosity during the high/soft state); and Long duration (approximately equal to 100 days, as compared with 5-20 days for 'normal' low/hard state excursions). During this anomalous low state no significant variability is observed on timescales of days-weeks, and the spectrum is well described by a simple power law with index 1.7 plus or minus 0.2. We examine the variability characteristics of LMC X-3 before and after this event using conventional and topological methods, and show that with the exception of the anomalous low state itself the long-term behavior of the source in topological phase space can be completely described in terms of a well-understood nonlinear dynamics system known as the Duffing oscillator, implying that the accretion disk in LMC X-3 is a driven, dissipative system with two solutions competing for control of its time evolution. This work shows that dynamical information and constraints revealed by topological analysis methods can provide a valuable addition to traditional studies of accretion disk behavior.

Smale, A. P.↗
NASA NTRS1988

Containerless science for materials processing

Containerless materials processing in space to restrict specimen deformation from hydrostatic pressure of contact with the container is discussed. Several containerless science studies are reviewed, including the study of drop dynamics, nucleation studies, metastable solid phases experiments, glass research, biological materials research, and protein crystal growth. The development of technologies for materials research in space are examined, including acoustic containerless systems, and electrostatic and electromagnetic containerless processing.

Wang, T. G.↗
NASA NTRS1987

General purpose algorithms for characterization of slow and fast phase nystagmus

In the overall aim for a better understanding of the vestibular and optokinetic systems and their roles in space motion sickness, the eye movement responses to various dynamic stimuli are measured. The vestibulo-ocular reflex (VOR) and the optokinetic response, as the eye movement responses are known, consist of slow phase and fast phase nystagmus. The specific objective is to develop software programs necessary to characterize the vestibulo-ocular and optokinetic responses by distinguishing between the two phases of nystagmus. The overall program is to handle large volumes of highly variable data with minimum operator interaction. The programs include digital filters, differentiation, identification of fast phases, and reconstruction of the slow phase with a least squares fit such that sinusoidal or psuedorandom data may be processed with accurate results. The resultant waveform, slow phase velocity eye movements, serves as input data to the spectral analysis programs previously developed for NASA to analyze nystagmus responses to pseudorandom angular velocity inputs.

Lessard, Charles S.↗
NASA NTRS1993

The uncertainty principle and quantum chaos

The conception of quantum chaos is described in some detail. The most striking feature of this novel phenomenon is that all the properties of classical dynamical chaos persist here but, typically, on the finite and different time scales only. The ultimate origin of such a universal quantum stability is in the fundamental uncertainty principle which makes discrete the phase space and, hence, the spectrum of bounded quantum motion. Reformulation of the ergodic theory, as a part of the general theory of dynamical systems, is briefly discussed.

Chirikov, Boris V.↗
NASA NTRS1982

Approximate constants of motion for classically chaotic vibrational dynamics - Vague tori, semiclassical quantization, and classical intramolecular energy flow

Substantial short time regularity, even in the chaotic regions of phase space, is found for what is seen as a large class of systems. This regularity manifests itself through the behavior of approximate constants of motion calculated by Pade summation of the Birkhoff-Gustavson normal form expansion; it is attributed to remnants of destroyed invariant tori in phase space. The remnant torus-like manifold structures are used to justify Einstein-Brillouin-Keller semiclassical quantization procedures for obtaining quantum energy levels, even in the absence of complete tori. They also provide a theoretical basis for the calculation of rate constants for intramolecular mode-mode energy transfer. These results are illustrated by means of a thorough analysis of the Henon-Heiles oscillator problem. Possible generality of the analysis is demonstrated by brief consideration of classical dynamics for the Barbanis Hamiltonian, Zeeman effect in hydrogen and recent results of Wolf and Hase (1980) for the H-C-C fragment.

Shirts, R. B.↗
DOE OSTI2024

Regulation of Solar Wind Electron Temperature Anisotropy by Collisions and Instabilities

Abstract Typical solar wind electrons are modeled as being composed of a dense but less energetic thermal “core” population plus a tenuous but energetic “halo” population with varying degrees of temperature anisotropies for both species. In this paper, we seek a fundamental explanation of how these solar wind core and halo electron temperature anisotropies are regulated by combined effects of collisions and instability excitations. The observed solar wind core/halo electron data in ( β ∥ , T ⊥ / T ∥ ) phase space show that their respective occurrence distributions are confined within an area enclosed by outer boundaries. Here, T ⊥ / T ∥ is the ratio of perpendicular and parallel temperatures and β ∥ is the ratio of parallel thermal energy to background magnetic field energy. While it is known that the boundary on the high- β ∥ side is constrained by the temperature anisotropy-driven plasma instability threshold conditions, the low- β ∥ boundary remains largely unexplained. The present paper provides a baseline explanation for the low- β ∥ boundary based upon the collisional relaxation process. By combining the instability and collisional dynamics it is shown that the observed distribution of the solar wind electrons in the ( β ∥ , T ⊥ / T ∥ ) phase space is adequately explained, both for the “core” and “halo” components.

Yoon, Peter H. (ORCID:0000000181343790)↗
DOE OSTI2024

Emergent symmetry in TbTe 3 revealed by ultrafast reflectivity under anisotropic strain

Here, we report ultrafast reflectivity measurements of the dynamics of the order parameter of the charge density wave (CDW) in TbTe 3 under anisotropic strain. We observe an increase in the frequency of the amplitude mode with increasing tensile strain along the a-axis (which drives the lattice into a > c, with a and c the lattice constants), and similar behavior for tensile strain along c (c > a). This suggests that both strains stabilize the corresponding CDW order and further support the near equivalence of the CDW phases oriented in a- and c-axis, in spite of the orthorhombic space group. The results were analyzed within the time-dependent Ginzburg–Landau framework, which agrees well with the reflectivity dynamics. Our study presents an ultrafast approach to assess the stability of phases and order parameter dynamics in strained systems.

Kim, Soyeun↗
NASA NTRSDate not supplied

Improving Regional Air Quality Forecasting Through Chemical Data Assimilation and Dynamic Emissions Adjustment

Poor air quality (AQ) is one of the most important human-health and environmental problems facing the United States (US). In addition to the detrimental impacts on human- and environmental-health, poor AQ has an economic cost of ~5% of the US gross domestic product (~$790 billion). AQ managers use AQ analyses and modeling to better understand, anticipate, and avoid poor AQ events. Our research focuses on improving AQ analysis/forecast skill, predictability, and emission estimates through improved and more efficient: (i) modeling and data assimilation strategies; (ii) dynamic emissions adjustment strategies; and (iii) use of satellite remote-sensing Earth observations (e.g., MOPITT, IASI, MODIS, OMI, TROPOMI, TEMPO, etc.). This seminar will review: (i) regional chemical weather forecasting/data assimilation with dynamic emissions adjustment with WRF-Chem/DART; (ii) strategies for efficiently assimilating satellite retrieval profiles with ‘compact phase space retrievals’ (CPSRs); (iii) results from joint assimilation of multiple satellite retrievals at medium (12 km × 12 km) and high (4 km × 4 km) spatial resolutions; and (iv) results from observing system simulation experiments (OSSEs) to investigate whether we can recover COVID-period anthropogenic emissions by assimilating synthetic TEMPO NO2 tropospheric column retrievals with dynamic emissions adjustment. Biographical Sketch: Dr. Mizzi is a Senior Research Fellow working and Dr. Johnson at the NASA Ames Research Center. He holds BA and MS degrees in Environmental Science from the University of Virginia, MS and PhD degrees in Applied Mathematics from the University of Colorado at Boulder (CUB), and a JD degree (with an emphasis in Environmental Law) from the University of Colorado School of Law. He worked at the National Center for Atmospheric Research for nearly 25 years on global atmospheric modeling, dynamic and physical initialization, regional hybrid data assimilation, and most recently on regional chemical data assimilation. He also worked as an environmental attorney and consultant for nearly 15 years. He is an expert in numerical modeling and is recognized internationally as a leading expert in regional, chemical data assimilation with dynamic emissions adjustment. Dr. Mizzi became affiliated with NASA Ames in March 2020 to work on improving AQ analysis/forecast skill, predictability, and ‘top-down’ emissions adjustment though the assimilation of Earth observations. An emphasis of his current work is developing methods for assimilating synthetic TEMPO retrievals to quantify the expected benefits of TEMPO relative to existing AQ observations.

Arthur P. Mizzi↗
DOE OSTI2023

Supercritical fluids behave as complex networks

Abstract Supercritical fluids play a key role in environmental, geological, and celestial processes, and are of great importance to many scientific and engineering applications. They exhibit strong variations in thermodynamic response functions, which has been hypothesized to stem from the microstructural behavior. However, a direct connection between thermodynamic conditions and the microstructural behavior, as described by molecular clusters, remains an outstanding issue. By utilizing a first-principles-based criterion and self-similarity analysis, we identify energetically localized molecular clusters whose size distribution and connectivity exhibit self-similarity in the extended supercritical phase space. We show that the structural response of these clusters follows a complex network behavior whose dynamics arises from the energetics of isotropic molecular interactions. Furthermore, we demonstrate that a hidden variable network model can accurately describe the structural and dynamical response of supercritical fluids. These results highlight the need for constitutive models and provide a basis to relate the fluid microstructure to thermodynamic response functions.

42 ENGINEERING↗
NASA NTRS1994

Energy transport and dynamics

We report findings concerning energy transport and dynamics in flares during the impulsive and gradual phases based on new ground-based and space observations (notably from Yohkoh). A preheating sometimes occurs during the impulsive phase. Ca XIX line shifts are confirmed to be good tracers of bulk plasma motions, although strong blue shifts are not as frequent as previously claimed. They often appear correlated with hard X-rays but, for some events, the concept that electron beams provide the whole energy input to the thermal component seems not to apply. Theory now yields: new diagnostics of low-energy proton and electric beams; accurate hydrodynamical modeling of pulse beam heating of the atmosphere; possible diagnostics of microflares (based on X-ray line ratio or on loop variability); and simulated images of chromospheric evaporation fronts. For the gradual phase, the continual reorganization of magnetic field lines over active regions determines where and when magnetic reconnection, the mechanism favored for energy release, will occur. Spatial and temporal fragmentation of the energy release, observed at different wavelengths, is considered to be a factor as well in energy transport and plasma dynamics.

Schmieder, Brigitte↗
DOE OSTI2024

Machine-assisted discovery of integrable symplectic mappings

Integrable systems possess a hidden symmetry associated with the existence of conserved quantities known as integrals of motion. These systems play an important role in understanding general dynamics in accelerators and have potential for future designs. This work will cover two automated methods for finding integrable symplectic maps of the plane. The first algorithm is based on the observation that the evolution of an integrable system in phase space is confined to a lower-dimensional submanifold of a specific type. The second algorithm relies on an analysis of dynamical variables. Both methods rediscover some of the famous McMillan-Suris integrable mappings and ultra-discrete Painlev\'e equations. Over 100 new integrable families are presented and analyzed, some of which are isolated in the space of parameters, while others are families with one parameter (or the ratio of parameters) being either continuous or discrete. In addition, the newly discovered maps are related to a general 2D symplectic map through the use of discrete perturbation theory. A method is proposed for constructing smooth near-integrable dynamical systems based on mappings with polygon invariants.

43 PARTICLE ACCELERATORS↗