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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 1,585 records · Page 88
All sourcesNASA NTRSDOE OSTI
NASA NTRS2013

Irradiation of an Accretion Disc by a Jet: General Properties and Implications for Spin Measurements of Black Holes

X-ray irradiation of the accretion disc leads to strong reflection features, which are then broadened and distorted by relativistic effects. We present a detailed, general relativistic approach to model this irradiation for different geometries of the primary X-ray source. These geometries include the standard point source on the rotational axis as well as more jet-like sources, which are radially elongated and accelerating. Incorporating this code in the RELLINE model for relativistic line emission, the line shape for any configuration can be predicted. We study how different irradiation geometries affect the determination of the spin of the black hole. Broad emission lines are produced only for compact irradiating sources situated close to the black hole. This is the only case where the black hole spin can be unambiguously determined. In all other cases the line shape is narrower, which could either be explained by a low spin or an elongated source. We conclude that for those cases and independent of the quality of the data, no unique solution for the spin exists and therefore only a lower limit of the spin value can be given

Accretion Disc↗
DOE OSTI2025

Neutrino-Nucleus Scattering Cross Sections at Medium Energies

The weak interactions of neutrinos with other Standard Model particles are well described within the Standard Model of particle physics. However, modern accelerator-based neutrino experiments employ nuclei as targets, where neutrinos interact with bound nucleons, turning a seemingly simple electroweak process into a complex many-body problem in nuclear physics. At the time of writing this Encyclopedia of Particle Physics chapter, neutrino-nucleus interactions remain one of the leading sources of systematic uncertainty in accelerator-based neutrino oscillation measurements. This chapter provides a pedagogical overview of neutrino interactions with nuclei in the medium-energy regime, spanning a few hundred MeV to several GeV. It introduces the fundamental electroweak formalism, outlines the dominant interaction mechanisms - including quasielastic scattering, resonance production, and deep inelastic scattering - and discusses how nuclear effects such as Fermi motion, nucleon-nucleon correlations, meson-exchange currents, and final-state interactions modify observable cross sections. The chapter also presents a brief survey of the foundational and most widely used theoretical models for neutrino-nucleus cross sections, together with an overview of current and upcoming accelerator-based neutrino oscillation experiments that are shaping the field. Rather than targeting experts, this chapter serves as a primer for advanced undergraduates, graduate students, and early-career researchers entering the field. It provides a concise foundation for understanding neutrino-nucleus scattering, its relevance to oscillation experiments, and its broader connections to both particle and nuclear physics.

Pandey, Vishvas [Fermilab] (ORCID:0000000230827987↗
NASA NTRS2009

Updating the Finite Element Model of the Aerostructures Test Wing using Ground Vibration Test Data

Improved and/or accelerated decision making is a crucial step during flutter certification processes. Unfortunately, most finite element structural dynamics models have uncertainties associated with model validity. Tuning the finite element model using measured data to minimize the model uncertainties is a challenging task in the area of structural dynamics. The model tuning process requires not only satisfactory correlations between analytical and experimental results, but also the retention of the mass and stiffness properties of the structures. Minimizing the difference between analytical and experimental results is a type of optimization problem. By utilizing the multidisciplinary design, analysis, and optimization (MDAO) tool in order to optimize the objective function and constraints; the mass properties, the natural frequencies, and the mode shapes can be matched to the target data to retain the mass matrix orthogonality. This approach has been applied to minimize the model uncertainties for the structural dynamics model of the Aerostructures Test Wing (ATW), which was designed and tested at the National Aeronautics and Space Administration (NASA) Dryden Flight Research Center (DFRC) (Edwards, California). This study has shown that natural frequencies and corresponding mode shapes from the updated finite element model have excellent agreement with corresponding measured data.

Lung, Shun-fat↗
NASA NTRS2009

Updating the Finite Element Model of the Aerostructures Test Wing Using Ground Vibration Test Data

Improved and/or accelerated decision making is a crucial step during flutter certification processes. Unfortunately, most finite element structural dynamics models have uncertainties associated with model validity. Tuning the finite element model using measured data to minimize the model uncertainties is a challenging task in the area of structural dynamics. The model tuning process requires not only satisfactory correlations between analytical and experimental results, but also the retention of the mass and stiffness properties of the structures. Minimizing the difference between analytical and experimental results is a type of optimization problem. By utilizing the multidisciplinary design, analysis, and optimization (MDAO) tool in order to optimize the objective function and constraints; the mass properties, the natural frequencies, and the mode shapes can be matched to the target data to retain the mass matrix orthogonality. This approach has been applied to minimize the model uncertainties for the structural dynamics model of the aerostructures test wing (ATW), which was designed and tested at the National Aeronautics and Space Administration Dryden Flight Research Center (Edwards, California). This study has shown that natural frequencies and corresponding mode shapes from the updated finite element model have excellent agreement with corresponding measured data.

Lung, Shun-Fat↗
NASA NTRS1983

Postglacial rebound observed by Lageos and the effective viscosity of the lower mantle

Sixty-four observations of the orbital node made by the Lageos satellite over a five year time interval reveal an acceleration of (-8.1 + or 1.8) x 10 to the -8 power arcseconds day/2 due to a source which is not presently modeled in the GEODYN orbit determination computer program. This acceleration cannot be explained by the ocean tide with 18.6 year period, assuming it to be an equilibrium tide. Instead it seems to be due to postglacial rebound, which changes the J(2) coefficient in the spherical harmonic expansion of the earth's gravitational field at the rate of (-8.2 + or - 18) x 10 to the -19th power/s; this in turn accelerates the node. This rate does not agree with the -32 x 10 to the -19th power/s predicted by Wu and Peltier's (1982) L2 model, which has upper and lower mantle effective viscosities of 10 to the 21st and 22nd powers Pa's, respectively. it does agree well with their L1 model, which gives about 10 x 10 to the 19th power/s. Since the effective viscosity is 10 to the 21st power Pa s throughout the entire mantle in the L1 model, the results support the contentions that the effective viscosity is near 10 to the 21st power Pa s everywhere in the mantle, and this relatively low value for the effective viscosity may have permitted several degrees of polar wander due to glaciation during the Quaternary Ice Age.

Rubincam, D. P.↗
NASA NTRS1984

Postglacial rebound observed by Lageos and the effective viscosity of the lower mantle

Sixty-four observations of the orbital node made by the Lageos satellite over a five year time interval reveal an acceleration of (-8.1 + or - 1.8) x 10 to the -8 power arcseconds day/2 due to a source which is not presently modeled in the GEODYN orbit determination computer program. This acceleration cannot be explained by the ocean tide with 18.6 year period, assuming it to be an equilibrium tide. Instead it seems to be due to postglacial rebound, which changes the J(2) coefficient in the spherical harmonic expansion of the earth's gravitational field at the rate of (-8.2 + or - 18) x 10 to the -19th power/s; this in turn accelerates the node. This rate does not agree with the -32 x 10 to the -19th power/s predicted by Wu and Peltier's (1982) L2 model, which has upper and lower mantle effective viscosities of 10 to the 21st and 22nd powers Pa's, respectively. It does agree well with their L1 model, which gives about 10 x 10 to the 19th power/s. Since the effective viscosity is 10 to the 21st power Pa s throughout the entire mantle in the L1 model, the results support the contentions that the efective viscosity is near 10 to the 21st power Pa s everyhere in the mantle, and this relatively low value for the effective viscosity may have permitted several degrees of polar wander due to glaciation during the Quaternary Ice Age. Previously announced in STAR as N84-13705

Rubincam, D. P.↗
NASA NTRS2007

Self-consistent Non-LTE Model of Infrared Molecular Emissions and Oxygen Dayglows in the Mesosphere and Lower Thermosphere

We present the new version of the ALI-ARMS (for Accelerated Lambda Iterations for Atmospheric Radiation and Molecular Spectra) model. The model allows simultaneous self-consistent calculating the non-LTE populations of the electronic-vibrational levels of the O3 and O2 photolysis products and vibrational level populations of CO2, N2,O2, O3, H2O, CO and other molecules with detailed accounting for the variety of the electronic-vibrational, vibrational-vibrational and vibrational-translational energy exchange processes. The model was used as the reference one for modeling the O2 dayglows and infrared molecular emissions for self-consistent diagnostics of the multi-channel space observations of MLT in the SABER experiment It also allows reevaluating the thermalization efficiency of the absorbed solar ultraviolet energy and infrared radiative cooling/heating of MLT by detailed accounting of the electronic-vibrational relaxation of excited photolysis products via the complex chain of collisional energy conversion processes down to the vibrational energy of optically active trace gas molecules.

Feofilov, Artem G.↗
DOE OSTI2022

Development of Accelerated Steady-state Test Capsule Experiments to Replicate EBR-II Fuel Behavior Using BISON Fuel Performance Analysis

Here in this work, BISON fuel performance calculations were performed to predict the fuel behavior of accelerated burnup U-Pu-Zr fuel, with temperature operation conditions of the fuel and the cladding mirroring conditions within EBR-II fuel pins. The temperature operating conditions within the FAST accelerated burnup rods were aimed at replicating EBR-II X447/X447A fuel surface and inner cladding surface temperatures. Due to the FAST capsule design, these temperatures can be replicated with fission rate densities being significantly increased. fuel performance modeling has not been assessed for novel experiments such as accelerated burnup utilizing the FAST capsule within ATR. This is an important step in understanding accelerated irradiation methods as many performance models are empirical models conforming to the results of PIE but do not always include physical models that would represent the changes in irradiation tests.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Thermodynamic Modeling of Complex Solid Solutions in the Lu-H-N System via Graph Neural Network Accelerated Monte Carlo Simulations

Metal hydrides are important across diverse applications, such as hydrogen storage, batteries, gas sensors, nuclear reactions, and high-temperature superconductivity. Previous computational studies of metal hydrides under extreme pressures, e.g., 𝑂⁡(10 2 ) ⁢GPa, usually treat them as stoichiometric compounds without considering interstitial lattice disorder. As pressures become more moderate in the 𝑂⁡(10 0 ) ⁢GPa and below range, hydrogen disorder at interstitial lattice sites becomes prominent, e.g., in the N-doped Lu hydride that was recently claimed superconducting near 1 GPa. Further adding compositional complexity from alloying and/or multielement interstitial occupation makes elucidating pressure- and temperature-dependent observables intractable by first-principles calculations alone. We therefore propose a lattice graph neural-network surrogate modeling approach to predict configuration- and pressure-dependent equation-of-state properties. Their efficiency permits Monte Carlo simulations to calculate Gibbs energies and pressure-dependent phase diagrams, thereby revealing insights into the synthesis conditions required for achieving desired phase equilibria. We demonstrate this concept for the compositionally complex cubic Lu(H,N,Va) 3 system where three constituents (hydrogen, nitrogen and vacancy) have disordered multielement interstitial occupancies and insights into pressure-dependent phase equilibria are critically needed, e.g., N-doping levels can significantly lower dehydrogenation temperatures and provide a new strategy to optimize hydrogen-storage alloys. This work can improve the thermodynamic understanding of the Lu-H-N system and help rational synthesis of N-doped Lu hydrides, but more generally demonstrates an efficient approach to model pressure-dependent thermodynamics of multicomponent solid solutions.

Monte Carlo methods↗
DOE OSTI2020

Deep Learning Emulation of Subgrid-Scale Processes in Turbulent Shear Flows

Deep neural networks (DNNs) are developed from a data set obtained from the dynamic Smagorinsky model to emulate the subgrid-scale (SGS) viscosity (ν sgs ) and diffusivity (κ sgs ) for turbulent stratified shear flows encountered in the oceans and the atmosphere. These DNNs predict ν sgs and κ sgs from velocities, strain rates, and density gradients such that the evolution of the kinetic energy budget and density variance budget terms is similar to the corresponding values obtained from the original dynamic Smagorinsky model. These DNNs also compute ν sgs and κ sgs ~2–4 times quicker than the dynamic Smagorinsky model resulting in a ~2–2.5 times acceleration of the entire simulation. This study demonstrates the feasibility of deep learning in emulating the subgrid-scale (SGS) phenomenon in geophysical flows accurately in a cost-effective manner. In a broader perspective, deep learning-based surrogate models can present a promising alternative to the traditional parameterizations of the subgrid-scale processes in climate models.

58 GEOSCIENCES↗
NASA NTRS1993

A multidimensional model of the effect of gravity on the spatial orientation of the monkey

A "sensory conflict" model of spatial orientation was developed. This mathematical model was based on concepts derived from observer theory, optimal observer theory, and the mathematical properties of coordinate rotations. The primary hypothesis is that the central nervous system of the squirrel monkey incorporates information about body dynamics and sensory dynamics to develop an internal model. The output of this central model (expected sensory afference) is compared to the actual sensory afference, with the difference defined as "sensory conflict." The sensory conflict information is, in turn, used to drive central estimates of angular velocity ("velocity storage"), gravity ("gravity storage"), and linear acceleration ("acceleration storage") toward more accurate values. The model successfully predicts "velocity storage" during rotation about an earth-vertical axis. The model also successfully predicts that the time constant of the horizontal vestibulo-ocular reflex is reduced and that the axis of eye rotation shifts toward alignment with gravity following postrotatory tilt. Finally, the model predicts the bias, modulation, and decay components that have been observed during off-vertical axis rotations (OVAR).

NASA Discipline Neuroscience↗
DOE OSTI2025

Predicting Si-Anode Calendar Life Using Machine Learning: Correlating Electrolyte Properties and Electrochemical Signals

This study evaluates novel electrolytes tailored for Si-containing anodes to promote calendar-life. Drawing inspiration from advancements in electrolytes for Li-metal cells, the work investigates correlations between predicted electrolyte properties and measured electrochemical performance using several machine-learning models. By leveraging machine learning and advanced modeling techniques, this study aims to establish predictive frameworks that accelerate calendar-aging experiments and inform rational electrolyte design for Si-containing cells. In the present study, fifteen different electrolytes are evaluated in a Si-containing cell using an accelerated calendar-life protocol. For each electrolyte considered, 87 properties (features) from the Advanced Electrolyte Model were produced to identify key property/performance relationships. In this study, the best performing electrolytes were generally those formulations that included non-coordinating fluoroether solvents, and the most predictive features for long-term calendar-life were features related to salt concentration and electrolyte viscosity as well as early capacity, ionic conductivity, and Coulombic efficiency measurements. The framework developed in this study correlating electrolyte properties to measured electrochemical performance is expected to accelerate electrolyte design for Si-containing anodes and ultimately enable high-energy-density, long-life Li-ion batteries.

25 - ENERGY STORAGE↗
DOE OSTI2022

Renewable Energy and Efficiency Technologies in Scenarios of U.S. Decarbonization in Two Types of Models: Comparison of GCAM Modeling and Sector-Specific Modeling

Energy system projections from analytic models inform actions ranging from short-term and local decisions, such as technology and infrastructure deployment, to global and long-term negotiations and targets. Computational limits require the designers of these models to trade off between coverage and resolution. Some models, such as the Global Change Analysis Model (GCAM), represent all energy sources and uses but at a relatively coarse level of resolution. GCAM balances global supply and demand of all energy carriers by endogenously projecting prices for energy sources and costs of greenhouse gas mitigation while capturing interlinkages between the energy system, water, agriculture and land use, the economy, and the climate. This global model was used to frame the Long-Term Strategy released by the White House in 2021 and has been used to inform national and global economy-wide decarbonization discussions and strategy development for decades. Other models instead focus on a portion of the energy sector with greater detail and resolution. The Regional Energy Deployment System (ReEDS) electricity-sector model, for example, projects capacity expansion with an emphasis on integration of variable renewable energy into the grid of the future. The Transportation Energy and Mobility Pathway Options (TEMPO) transportation-sector model enables analysis of household choices in adoption, charging, and use of electric vehicles. The Scout buildings-sector model supports detailed consideration of the policies and markets that can accelerate the adoption of energy conservation measures in buildings. Such sector-specific models are instrumental in informing technology research, sectoral planning strategies, and sector-specific aspects of greenhouse gas (GHG) mitigation strategies in the United States. These global and sector-specific modeling approaches can complement each other. The global approach ensures consistent, endogenous energy pricing and resource allocation, which can substantially diverge from current conditions in transformative scenarios, while the sector-specific approach facilitates representation of granular details across spatial, temporal, technological, and market dimensions that enable exploration of particular interactions and trade-offs. This report presents the results of recent work to explore the differences and tradeoffs between these approaches by comparing GCAM with the sector-specific ReEDS, TEMPO, and Scout models. The report compares both model structures and results, and discusses their potential relevance and applications.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
NASA NTRS2005

Studies of Particle Acceleration, Transport and Radiation in Impulsive Phase of Solar Flares

Solar activity and its most prominent aspect, the solar flares, have considerable influence on terrestrial and space weather. Solar flares also provide a suitable laboratory for the investigation of many plasma and high energy processes important in the magnetosphere of the Earth and many other space and astrophysical situations. Hence, progress in understanding of flares will have considerable scientific and societal impact. The primary goal of this grant is the understanding of two of the most important problems of solar flare physics, namely the determination of the energy release mechanism and how this energy accelerates particles. This is done through comparison of the observations with theoretical models, starting from observations and gradually proceeding to theoretically more complex situations as the lower foundations of our understanding are secured. It is generally agreed that the source of the flare energy is the annihilation of magnetic fields by the reconnection process. Exactly how this energy is released or how it is dissipated remains controversial. Moreover, the exact mechanism of the acceleration of the particles is still a matter of debate. Data from many spacecrafts and ground based instruments obtained over the past decades have given us some clues. Theoretical analyses of these data have led to the standard thick target model (STT) where most of the released energy goes into an (assumed) power law spectrum of accelerated particles, and where all the observed radiations are the consequence of the interaction of these particles with the flare plasma. However, some theoretical arguments, and more importantly some new observations, have led us to believe that the above picture is not complete. It appears that plasma turbulence plays a more prominent role than suspected previously, and that it is the most likely agent for accelerating particles. The model we have developed is based on production of a high level of plasma waves and turbulence in the reconnection region above a flare loop. This turbulence accelerates particles stochastically which radiate some of their energy in this region but carry most of their energy to the footpoints of the loop, where they lose all their energy and radiate bulk of the observed radiation as in the traditional thick target model. In the past we have worked on various aspects of this model. We have evaluated the interaction rates of the plasma waves with electrons and ions, developed theoretical frameworks for the acceleration, transport and radiative processes, and produced numerical codes for the investigation of these processes. The goal of this grant has been further development and testing of this new paradigm, with emphases on the relative acceleration of electrons and ions and on a comprehensive investigation of the turbulence generation, cascade, and damping processes. We review several pieces of important evidence that we have uncovered indicating the crucial roles of turbulence, in and we describe accomplishments during the past two years of this grant.

Petrosian, Vahe↗
DOE OSTI2020

Highly selective Si 3 N 4 /SiO 2 etching using an NF 3 /N 2 /O 2 /H 2 remote plasma. II. Surface reaction mechanism

Developing processes for highly selective etching of silicon nitride (Si 3 N 4 ) with respect to silicon dioxide (SiO 2 ) is a major priority for semiconductor fabrication processing. In this paper and in Paper I [Volynets et al., J. Vac. Sci. Technol. A 38, 023007 (2020)], mechanisms are discussed for highly selective Si3N4 etching in a remote plasma based on experimental and theoretical investigations. The Si 3 N 4 /SiO 2 etch selectivity of up to 380 was experimentally produced using a remote plasma sustained in NF 3 /N 2 /O 2 /H 2 mixtures. A selectivity strongly depends on the flow rate of H 2 , an effect attributed to the formation of HF molecules in vibrationally excited states that accelerate etching reactions. Based on experimental measurements and zero-dimensional plasma simulations, an analytical etching model was developed for etch rates as a function of process parameters. Reaction rates and sticking coefficients were provided by quantum chemistry models and also fitted to the experimental results. Etch rates from the analytical model show good agreement with the experimental results and demonstrate why certain etchants accelerate or inhibit the etch process. In particular, the modeling shows the important role of HF molecules in the first vibrationally excited state [HF( v = 1)] in achieving high Si 3 N 4 /SiO 2 selectivity.

42 ENGINEERING↗
NASA NTRS2011

Accelerating Climate and Weather Simulations through Hybrid Computing

Unconventional multi- and many-core processors (e.g. IBM (R) Cell B.E.(TM) and NVIDIA (R) GPU) have emerged as effective accelerators in trial climate and weather simulations. Yet these climate and weather models typically run on parallel computers with conventional processors (e.g. Intel, AMD, and IBM) using Message Passing Interface. To address challenges involved in efficiently and easily connecting accelerators to parallel computers, we investigated using IBM's Dynamic Application Virtualization (TM) (IBM DAV) software in a prototype hybrid computing system with representative climate and weather model components. The hybrid system comprises two Intel blades and two IBM QS22 Cell B.E. blades, connected with both InfiniBand(R) (IB) and 1-Gigabit Ethernet. The system significantly accelerates a solar radiation model component by offloading compute-intensive calculations to the Cell blades. Systematic tests show that IBM DAV can seamlessly offload compute-intensive calculations from Intel blades to Cell B.E. blades in a scalable, load-balanced manner. However, noticeable communication overhead was observed, mainly due to IP over the IB protocol. Full utilization of IB Sockets Direct Protocol and the lower latency production version of IBM DAV will reduce this overhead.

hybrid computing↗
NASA NTRS1973

Magnetic field reconnection and particle acceleration

After a brief review of steady state reconnection models, the processes are discussed which place an upper limit on the reconnection rate. In many applications the requirement that the width of the diffusion region exceed the ion gyroradius leads to a severe restriction on this limit. Unless the conductivity is much less than the value given by Spitzer's formula, solar flare times may result which are too long by a factor of 1000 or more. Turbulent and gyro effects which may lead to a reduced conductivity are shown to be operative, but only for sufficiently small ratios of plasma to magnetic pressure in the inflow. Particle energization processes associated with magnetic field reconnection and particle reflection by fast shocks are considered. These processes are effective as a first stage in the acceleration of charged particles, but additional multistep processes are needed to reach proton energies above a few MeV.

Sonnerup, B. U. O.↗
DOE OSTI2021

Development of an optimized and scalable method for isolation of umbilical cord blood-derived small extracellular vesicles for future clinical use

Abstract Extracellular vesicles (EV) are a promising therapeutic tool in regenerative medicine. These particles were shown to accelerate wound healing, through delivery of regenerative mediators, such as microRNAs. Herein we describe an optimized and upscalable process for the isolation of EV smaller than 200 nm (sEV), secreted by umbilical cord blood mononuclear cells (UCB-MNC) under ischemic conditions and propose quality control thresholds for the isolated vesicles, based on the thorough characterization of their protein, lipid and RNA content. Ultrafiltration and size exclusion chromatography (UF/SEC) optimized methodology proved superior to traditional ultracentrifugation (UC), regarding production time, standardization, scalability, and vesicle yield. Using UF/SEC, we were able to recover approximately 400 times more sEV per mL of media than with UC, and upscaling this process further increases EV yield by about 3-fold. UF/SEC-isolated sEV display many of the sEV/exosomes classical markers and are enriched in molecules with anti-inflammatory and regenerative capacity, such as hemopexin and miR-150. Accordingly, treatment with sEV promotes angiogenesis and extracellular matrix remodeling, in vitro. In vivo, UCB-MNC-sEV significantly accelerate skin regeneration in a mouse model of delayed wound healing. The proposed isolation protocol constitutes a significant improvement compared to UC, the gold-standard in the field. Isolated sEV maintain their regenerative properties, whereas downstream contaminants are minimized. The use of UF/SEC allows for the standardization and upscalability required for mass production of sEV to be used in a clinical setting.

Cardoso, Renato M. S.↗