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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
NASA NTRS2004

Unified Models of Turbulence and Nonlinear Wave Evolution in the Extended Solar Corona and Solar Wind

The PI (Cranmer) and Co-I (A. van Ballegooijen) made substantial progress toward the goal of producing a unified model of the basic physical processes responsible for solar wind acceleration. The approach outlined in the original proposal comprised two complementary pieces: (1) to further investigate individual physical processes under realistic coronal and solar wind conditions, and (2) to extract the dominant physical effects from simulations and apply them to a 1D model of plasma heating and acceleration. The accomplishments in Year 2 are divided into these two categories: 1a. Focused Study of Kinetic Magnetohydrodynamic (MHD) Turbulence. lb. Focused Study of Non - WKB Alfven Wave Rejection. and 2. The Unified Model Code. We have continued the development of the computational model of a time-study open flux tube in the extended corona. The proton-electron Monte Carlo model is being tested, and collisionless wave-particle interactions are being included. In order to better understand how to easily incorporate various kinds of wave-particle processes into the code, the PI performed a detailed study of the so-called "Ito Calculus", i.e., the mathematical theory of how to update the positions of particles in a probabilistic manner when their motions are governed by diffusion in velocity space.

Cranmer, Steven R.↗
NASA NTRS1986

Theories of mass loss from T Tauri stars

The available database on T Tauri stars is examined in order to develop criteria for modeling the physical processes occurring within and around pre-main sequence stars. Observational data on the temperature structures, mass loss rates, and mass motions in T Tauri envelopes are reviewed to form a basis for discussing the possible mechanisms for mass loss in the T Tauri objects. Analytical models are explored for thermally-driven, wave-driven and rotationally-driven winds. The possible interactions of the T Tauri stellar winds with processes occurring in the nearby FU Dri stars are noted, as is the necessity of momdeling physical processes such as turbulent velocity fields through accurate radiative transfer calculations in order to model the envelopes of the T Tauri stars.

Hartmann, L.↗
NASA NTRS2007

Composition of the Solar Wind

The solar wind reflects the composition of the Sun and physical processes in the corona. Analysis produces information on how the solar system was formed and on physical processes in the corona. The analysis can also produce information on the local interstellar medium, galactic evolution, comets in the solar wind, dust in the heliosphere, and matter escaping from planets.

Suess, S. T.↗
NASA NTRSDate not supplied

Assessing the feasibility of a spaceborne 3D lightning observing concept

The distribution of electrical charge in thunderclouds results from thermodynamic, microphysical, and kinematic processes, which also modulate thunderstorm evolution. It is no surprise that the connection between lightning and these physical processes is so strong that the increase and vertical growth of lightning activity closely follows the vertical growth of the thundercloud, but unraveling these connections is not trivial and requires observations of the three-dimensional (3D) structure of electrical activity in a cloud. Ground-based 3D lightning mapping networks give excellent 3D flash-level detail but are limited to regional coverage. Satellite-based optical lightning mappers give excellent global coverage but are largely limited to 2D summaries of flash rate and radiant intensity, albeit new flash products and stereographic techniques are chipping away this limitation. New observing strategies are needed to expand and diversify the corpus of 3D lightning datasets and motivate studies that unravel connections lightning has with these key physical processes and the surrounding environment. This study examines the feasibility of using a distributed network of orbing satellites with VHF-based lightning detectors to obtain global maps of 3D lightning activity and assess efficacy of this approach for use in a new, small satellite mission concept called CubeSpark. CubeSpark combines new VHF and high-resolution, bispectral optical instruments on a constellation of low-Earth orbiting (LEO) satellites to globally map the 3D electrical structure of thunderstorms and study how it relates to thunderstorm evolution, extreme weather, nitrogen oxide production and distribution, upper atmospheric electrical phenomena, and how 3D flash observations can complement existing satellite-based lightning mappers and improve decision support tools. To locate lightning discharges, CubeSpark seeks to use the VHF time-of-arrival technique, similar to ground-based total lightning mapping networks. The vertical location accuracy of these satellite retrievals will be of poorer quality compared to a ground-based network, which has non-trivial implications for lightning flash reconstruction and lightning-based interpretations of deep convection. We adapt a Lightning Mapping Array (LMA) simulation framework to an orbiting network and use it to address feasibility of 3D lightning detection from space with particular attention to location accuracy of VHF detections of lightning in the vertical. These simulations inform a constellation design study that defines a realistic orbital configuration and depicts the global coverage for CubeSpark. Results indicate that a 3D location accuracy of <1-2 km for each dimension can be achieved across 300-500 km wide swaths, which suggests that CubeSpark can resolve the charge structure of thunderclouds from the tropics to the mid- and high- latitudes.

Lightning↗
NASA NTRS2000

Solar Physics

The areas of emphasis are: (1) develop theoretical models of the transient release of magnetic energy in the solar atmosphere, e.g., in solar flares, eruptive prominences, coronal mass ejections, etc.; (2) investigate the role of the Sun's magnetic field in the structuring of solar corona by the development of three-dimensional numerical models that describe the field configuration at various heights in the solar atmosphere by extrapolating the field at the photospheric level; (3) develop numerical models to investigate the physical parameters obtained by the ULYSSES mission; (4) develop numerical and theoretical models to investigate solar activity effects on the solar wind characteristics for the establishment of the solar-interplanetary transmission line; and (5) develop new instruments to measure solar magnetic fields and other features in the photosphere, chromosphere transition region and corona. We focused our investigation on the fundamental physical processes in solar atmosphere which directly effect our Planet Earth. The overall goal is to establish the physical process for the Sun-Earth connections.

Wu, S. T.↗
DOE OSTI2024

Nanosecond anomaly detection with decision trees and real-time application to exotic Higgs decays

Abstract We present an interpretable implementation of the autoencoding algorithm, used as an anomaly detector, built with a forest of deep decision trees on FPGA, field programmable gate arrays. Scenarios at the Large Hadron Collider at CERN are considered, for which the autoencoder is trained using known physical processes of the Standard Model. The design is then deployed in real-time trigger systems for anomaly detection of unknown physical processes, such as the detection of rare exotic decays of the Higgs boson. The inference is made with a latency value of 30 ns at percent-level resource usage using the Xilinx Virtex UltraScale+ VU9P FPGA. Our method offers anomaly detection at low latency values for edge AI users with resource constraints.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS2015

Construction of Polarimetric Radar-Based Reference Rain Maps for the Iowa Flood Studies Campaign

The Global Precipitation Measurement (GPM) Mission Iowa Flood Studies (IFloodS) campaign was conducted in central and northeastern Iowa during the months of April-June, 2013. Specific science objectives for IFloodS included quantification of uncertainties in satellite and ground-based estimates of precipitation, 4-D characterization of precipitation physical processes and associated parameters (e.g., size distributions, water contents, types, structure etc.), assessment of the impact of precipitation estimation uncertainty and physical processes on hydrologic predictive skill, and refinement of field observations and data analysis approaches as they pertain to future GPM integrated hydrologic validation and related field studies. In addition to field campaign archival of raw and processed satellite data (including precipitation products), key ground-based platforms such as the NASA NPOL S-band and D3R Ka/Ku-band dual-polarimetric radars, University of Iowa X-band dual-polarimetric radars, a large network of paired rain gauge platforms, and a large network of 2D Video and Parsivel disdrometers were deployed. In something of a canonical approach, the radar (NPOL in particular), gauge and disdrometer observational assets were deployed to create a consistent high-quality distributed (time and space sampling) radar-based ground "reference" rainfall dataset, with known uncertainties, that could be used for assessing the satellite-based precipitation products at a range of space/time scales. Subsequently, the impact of uncertainties in the satellite products could be evaluated relative to the ground-benchmark in coupled weather, land-surface and distributed hydrologic modeling frameworks as related to flood prediction. Relative to establishing the ground-based "benchmark", numerous avenues were pursued in the making and verification of IFloodS "reference" dual-polarimetric radar-based rain maps, and this study documents the process and results as they pertain specifically to efforts using the NPOL radar dataset. The initial portions of the "process" involved dual-polarimetric quality control procedures which employed standard phase and correlation-based approaches to removal of clutter and non-meteorological echo. Calculation of a scale-adaptive KDP was accomplished using the method of Wang and Chandrasekar (2009; J. Atmos. Oceanic Tech.). A dual-polarimetric blockage algorithm based on Lang et al. (2009; J. Atmos. Oceanic Tech.) was then implemented to correct radar reflectivity and differential reflectivity at low elevation angles. Next, hydrometeor identification algorithms were run to identify liquid and ice hydrometeors. After the quality control and data preparation steps were completed several different dual-polarimetric rain estimation algorithms were employed to estimate rainfall rates using rainfall scans collected approximately every two to three minutes throughout the campaign. These algorithms included a polarimetrically-tuned Z-R algorithm that adjusts for drop oscillations (via Bringi et al., 2004, J. Atmos. Oceanic Tech.), and several different hybrid polarimetric variable approaches, including one that made use of parameters tuned to IFloodS 2D Video Disdrometer measurements. Finally, a hybrid scan algorithm was designed to merge the rain rate estimates from multiple low level elevation angle scans (where blockages could not be appropriately corrected) in order to create individual low-level rain maps. Individual rain maps at each time step were subsequently accumulated over multiple time scales for comparison to gauge network data. The comparison results and overall error character depended strongly on rain event type, polarimetric estimator applied, and range from the radar. We will present the outcome of these comparisons and their impact on constructing composited "reference" rainfall maps at select time and space scales.

Radar↗
NASA NTRS1979

Middle atmosphere electrodynamics: Report of the workshop on the Role of the Electrodynamics of the Middle Atmosphere on Solar Terrestrial Coupling

Significant deficiencies exist in the present understanding of the basic physical processes taking place within the middle atmosphere (the region between the tropopause and the mesopause), and in the knowledge of the variability of many of the primary parameters that regulate Middle Atmosphere Electrodynamics (MAE). Knowledge of the electrical properties, i.e., electric fields, plasma characteristics, conductivity and currents, and the physical processes that govern them is of fundamental importance to the physics of the region. Middle atmosphere electrodynamics may play a critical role in the electrodynamical aspects of solar-terrestrial relations. As a first step, the Workshop on the Role of the Electrodynamics of the Middle Atmosphere on Solar-Terrestrial Coupling was held to review the present status and define recommendations for future MAE research.

Maynard, N. C.↗
NASA NTRS1986

Optical imaging spectroscopy

During the recent solar maximum the combination of imaging and spectroscopy in the visible part of the spectrum became a powerful tool for observational study of flares primarily because of the development of two-dimensional charge-coupled-device (CCD) arrays. In combination with appropriate new operational methods, this has led to the ability to observe, for the first time, the preflare and impulsive-phase physical processes associated with spatially resolved features of flare loops. As a result of concurrent theoretical developments, modeling progressed from an empirical to a physical level. This made it possible to interpret imaging spectra in terms of coronal pressure and heat flux, particle beam heating, chromospheric evaporation, and explosive chromospheric dynamics at the footpoints of flare loops. There is clear potential for further advances in the near future, taking advantage of improvements in digital recording speed (approx. 10-fold), number of photosensitive elements per array (approx. 10-fold), real-time data pre-reduction (potentially 10- to 100-fold), and using multiple CCD arrays. By the time of the next solar maximum imaging spectroscopy is expected to achieve spatial resolution or approx. arc 1 arc s, temporal resolution or approx. 5 s, and simultaneous critically-sampled spectroscopy of several lines and continua. As a result, continued increase in our understanding of the physical processes and configurations of solar flares in the chromosphere, temperature minimum region, and photosphere can be anticipated. Even greater progress toward a more global understanding of flares will obviously come about when simultaneous optical, X-ray, and gamma-ray imaging spectroscopy are possible.

Canfield, R. C.↗
NASA NTRS2007

Understanding Local Structure Globally in Earth Science Remote Sensing Data Sets

Empirical probability distributions derived from the data are the signatures of physical processes generating the data. Distributions defined on different space-time windows can be compared and differences or changes can be attributed to physical processes. This presentation discusses on ways to reduce remote sensing data in a way that preserves information, focusing on the rate-distortion theory and using the entropy-constrained vector quantization algorithm.

massive data sets↗
DOE OSTI2024

Modeling graphene sheet growth and dynamical matrix calculations using molecular dynamics

Molecular dynamics (MD) has been an incredibly useful tool to model physical processes that were synthesized experimentally but not fully understood. MD, through the use of semi-empirical inter-atomic potentials, has allowed understanding of different physical processes in materials science. Yet as well as providing useful insights into materials science, molecular dynamics has a wider range of usability. In this report, I will be detailing how MD can be used to study graphene formation from a carbon liquid which requires high temperatures and pressures. Beyond this, I will describe the usefulness of MD for understanding the physics for phonon transport quantum sensors. To do this, MD was employed to determine the dynamical matrix by treating atoms as coupled oscillators. An accurate understanding of the dynamical matrix of a system is required to calculate the non-equilibrium Green’s function used to describe the phonon transport within phonon wave-guides. I found that, across multiple pressures and temperatures, randomly placed carbon atoms will show evidence of pent-first formation with semi-empirical models. Density functional theory (DFT), on the other hand, was too computationally expensive to use for full scale MD simulations, but we have the possibility of training a machine learned interatomic potential to approximate DFT for carbon in the environments being studied for pent-first graphene sheet formation.

36 MATERIALS SCIENCE↗
NASA NTRS2016

Contributions of the ARM Program to Radiative Transfer Modeling for Climate and Weather Applications

Accurate climate and weather simulations must account for all relevant physical processes and their complex interactions. Each of these atmospheric, ocean, and land processes must be considered on an appropriate spatial and temporal scale, which leads these simulations to require a substantial computational burden. One especially critical physical process is the flow of solar and thermal radiant energy through the atmosphere, which controls planetary heating and cooling and drives the large-scale dynamics that moves energy from the tropics toward the poles. Radiation calculations are therefore essential for climate and weather simulations, but are themselves quite complex even without considering the effects of variable and inhomogeneous clouds. Clear-sky radiative transfer calculations have to account for thousands of absorption lines due to water vapor, carbon dioxide, and other gases, which are irregularly distributed across the spectrum and have shapes dependent on pressure and temperature. The line-by-line (LBL) codes that treat these details have a far greater computational cost than can be afforded by global models. Therefore, the crucial requirement for accurate radiation calculations in climate and weather prediction models must be satisfied by fast solar and thermal radiation parameterizations with a high level of accuracy that has been demonstrated through extensive comparisons with LBL codes. See attachment for continuation.

climatology↗
NASA NTRS2020

Advances in Understanding High-Mass X-ray Binaries with INTEGRAL and Future Directions

High mass X-ray binaries are among the brightest X-ray sources in the Milky Way, as well as in nearby Galaxies. Thanks to their highly variable emissions and complex phenomenology, they have attracted the interest of the high energy astrophysical community since the dawn of X-ray Astronomy. In more recent years, they have challenged our comprehension of physical processes in many more energy bands, ranging from the infrared to very high energies. In this review, we provide a broad but concise summary of the physical processes dominating the emission from high mass X-ray binaries across virtually the whole electromagnetic spectrum. These comprise the interaction of stellar winds with the high gravitational and magnetic fields of compact objects, the behaviour of matter under extreme magnetic and gravity conditions, and the perturbation of the massive star evolutionary processes. We highlight the role of the INTEGRAL mission in the discovery of many of the most interesting objects in the high mass X-ray binary class and its contribution in reviving the interest for these sources over the past two decades. We show how the INTEGRAL discoveries have not only contributed to significantly increase the number of high mass X-ray binaries known, thus advancing our understanding of the population as a whole, but also have opened new windows of investigation that stimulated the multi-wavelength approach nowadays common in most astrophysical research fields. We conclude the review by providing an overview of future facilities being planned from the X-ray to the very high energy domain that will hopefully help us in finding an answer to the many questions left open after more than 18 years of INTEGRAL scientific observations.

Peter Kretschmar↗
DOE OSTI2024

Generalization error guaranteed auto-encoder-based nonlinear model reduction for operator learning

Many physical processes in science and engineering are naturally represented by operators between infinite-dimensional function spaces. The problem of operator learning, in this context, seeks to extract these physical processes from empirical data, which is challenging due to the infinite or high dimensionality of data. An integral component in addressing this challenge is model reduction, which reduces both the data dimensionality and problem size. In this paper, we utilize low-dimensional nonlinear structures in model reduction by investigating Auto-Encoder-based Neural Network (AENet). AENet first learns the latent variables of the input data and then learns the transformation from these latent variables to corresponding output data. Our numerical experiments validate the ability of AENet to accurately learn the solution operator of nonlinear partial differential equations. Furthermore, we establish a mathematical and statistical estimation theory that analyzes the generalization error of AENet. Finally, our theoretical framework shows that the sample complexity of training AENet is intricately tied to the intrinsic dimension of the modeled process, while also demonstrating the robustness of AENet to noise.

Auto-encoder↗
NASA NTRS1977

Microphysical processes affecting stratospheric aerosol particles

Physical processes which affect stratospheric aerosol particles include nucleation, condensation, evaporation, coagulation and sedimentation. Quantitative studies of these mechanisms to determine if they can account for some of the observed properties of the aerosol are carried out. It is shown that the altitude range in which nucleation of sulfuric acid-water solution droplets can take place corresponds to that region of the stratosphere where the aerosol is generally found. Since heterogeneous nucleation is the dominant nucleation mechanism, the stratospheric solution droplets are mainly formed on particles which have been mixed up from the troposphere or injected into the stratosphere by volcanoes or meteorites. Particle growth by heteromolecular condensation can account for the observed increase in mixing ratio of large particles in the stratosphere. Coagulation is important in reducing the number of particles smaller than 0.05 micron radius. Growth by condensation, applied to the mixed nature of the particles, shows that available information is consistent with ammonium sulfate being formed by liquid phase chemical reactions in the aerosol particles. The upper altitude limit of the aerosol layer is probably due to the evaporation of sulfuric acid aerosol particles, while the lower limit is due to mixing across the tropopause.

Hamill, P.↗
NASA NTRS1996

Enhanced Water Vapor Absorption within Tropospheric Clouds: A Partial Explanation for Anomalous Absorption

Comparisons between solar flux measurements and predictions obtained from theoretical radiative transfer models indicate that most of these models underestimate the globally averaged solar energy absorbed by cloudy atmospheres by up to 25Wm&sup-2;.The origin of this anomalous absorption has not yet been established, but it has been attributed to a variety of sources including oversimplified or missing physical processes in the existing models, uncertainties in the input data, and even measurement errors. We used a sophisticated atmospheric radiative transfer model to provide improved constraints on the physical processes that contribute to the absorption of solar radiation by Earth's atmosphere. The results are described herein.

solar flux measurement water vapor absorption atmo↗
DOE OSTI2025

Sensitivity analysis of a parameterization of coagulation in an aqueous transport model

A three-dimensional aqueous transport model, ALGE, was developed at the Savannah River National Laboratory (SRNL) as a tool for emergency response. Recently, coagulation and break-up of sediment and particulate (contaminant adhered to sediment) matter has been added as a new model capability, representing both processes as functions of salinity and turbulence. A sensitivity analysis was performed by comparing time series of sediment and particulate concentrations at various locations when the model’s parameters (particle size and density) are altered. The results show significant differences between experiments in both freshwater and saltwater systems parameters vary (P-values < 0.05). From this sensitivity study, we have concluded the importance of incorporating both salinity and turbulent effects, as they have a large role in the physical process of coagulation and breakup of sediment. By accounting for these physical processes, we have made the ALGE model a more robust tool for emergency response.

Aqueous fate and transport↗
DOE OSTI2025

Using Boosted Decision Trees to Select High Quality Measurements in the Mu2e Experiment at Fermilab

This thesis presents the implementation and evaluation of a Boosted Decision Tree (BDT) model to improve the selection of high-quality track measurements in the Mu2e experiment at Fermilab. The Mu2e experiment is a high-energy physics experiments seeking to observe a rare theoretical physics process known as Charged Lepton Flavor Violation. A significant challenge faced by the Mu2e experiment are so-called background events, which are events whose data mimics that of the rare physics process the experiment seeks to observe. Without a mechanism to reduce background, it would be impossible to know whether Charged Lepton Flavor Violation occurred or not. To this end, high-quality track measurements must be distinguished from low-quality track measurements. A track can be conceived of as the reconstructed path of a particle that traveled through the Mu2e detector. In addition to other data, data about such tracks is stored using a C++-based framework, specific to the domain of high-energy physics, known as ROOT. A boosted decision tree model was trained using ROOT’s Toolkit For Multivariate Analysis by leveraging variables ancillary to track quality. In evaluation, the BDT achieves a ROC-AUC of 0.927 in discriminating good-quality tracks from poor-quality tracks. Such a score is indicative of both strong discrimination and strong generalization. Subsequently, it is shown that applying a BDT-based quality cut to the distribution of particle momenta significantly enhances the signal-to-background distinction for signal electrons, paving the way for improved sensitivity to Charged Lepton Flavor Violation.

Mullany, Brendan T. [Drew U.] (ORCID:0009000818888↗