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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 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Coherent Phonon Dynamics in Plasmonic Gold Tetrahedral Nanoparticle Ensembles

Coherent phonon modes supported by plasmonic nanoparticles offer prospective applications in chemical and biological sensing. Whereas characterization of these phonon modes often requires single particle measurements, synthetic routes to narrow size distributions of nanoparticles permit ensemble investigations. Recently, the synthesis of highly monodisperse gold tetrahedral nanoparticles with tunable edge length and corner sharpness has been developed. Herein, we characterize a size series of these nanoparticles in colloidal dispersion via transient absorption spectroscopy to examine their mechanical and plasmonic responses upon photoexcitation. Oscillations of transient absorption signals are observed in the plasmon resonance and correspond to the lowest order radial breathing modes of the nanoparticles, the frequencies of which are affected by edge length and truncation of the corners. Furthermore, quality factor values ranging from 10 to 15 are observed for the oscillations that convey potential utility in mass-sensing and plasmon-exciton coupling photonics schemes. Finite-difference time domain and finite element analysis calculations establish the specific optically-relevant phonon modes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1983

Theoretical quasar emission-line profiles. I - Curve-of-growth effects on observed profiles

Radiative transfer effects are examined in an investigation of the kinematics of quasar and Seyfert emission-line regions with pancake cloud geometries. Consideration is given only to the effects of limb brightening with the aspect angle of pancake clouds, assuming that all lines lie on a single portion of the curve of growth. This effect is coupled with several simple but plausible ensemble geometries and dynamics, and a number of theoretical emission-line profiles have been generated. It is shown that these profiles differ substantially depending on both the ensemble geometry and the portion of the curve of growth considered; for a given ensemble geometry, optically thick line profiles are different from optically thick profiles. It is shown that, for radiatively driven clouds, ensembles of clouds which have maximum velocities approaching the terminal velocity of the acceleration mechanism never produce acceptable profiles unless the cloud luminosity is a strongly decreasing function of radius.

Hubbard, E. N.↗
NASA NTRS1991

Laser velocimetry measurements of oscillating airfoil dynamic stall flow field

Ensemble-averaged two-component velocity measurements over an airfoil experiencing oscillatory dynamic stall under compressibility conditions were obtained. The measurements show the formation of a separation bubble over the airfoil that persists till angles of attack close to when the dynamic stall vortex forms and convects. The fluid attains mean velocities as large as 1.6 times the free stream velocity with instantaneous values of 1.8 times the free stream velocity. The airfoil motion induces these large velocities in regions that are far removed from the surface.

Chandrasekhara, M. S.↗
NASA NTRS2002

Modeling Disturbance Dynamics in Transitional and Turbulent Boundary Layers

The dynamics of an ensemble of linear disturbances in boundary-layer flows at various Reynolds numbers is studied through an analysis of the transport equations for the mean disturbance kinetic energy and energy dissipation rate. Effects of adverse and favorable pressure-gradients on the disturbance dynamics are also included in the analysis. Unlike the fully turbulent regime where nonlinear phase scrambling of the fluctuations affects the flow field even in proximity to the wall, the early stage transition regime fluctuations studied here are influenced across the boundary layer by the solid boundary. In addition, the dominating dynamics in the disturbance kinetic energy equation is governed by the energy production, pressure-transport and viscous diffusion - also in contrast to the fully turbulent regime. For the disturbance dissipation rate, a dynamic balance exists between the destruction and diffusion of dissipation.

Grosch, C. E.↗
NASA NTRS2005

Analysis of Transition-Sensitized Turbulent Transport Equations

The dynamics of an ensemble of linear disturbances in boundary-layer flows at various Reynolds numbers is studied through an analysis of the transport equations for the mean disturbance kinetic energy and energy dissipation rate. Effects of adverse and favorable pressure-gradients on the disturbance dynamics are also included in the analysis Unlike the fully turbulent regime where nonlinear phase scrambling of the fluctuations affects the flow field even in proximity to the wall, the early stage transition regime fluctuations studied here are influenced cross the boundary layer by the solid boundary. The dominating dynamics in the disturbance kinetic energy and dissipation rate equations are described. These results are then used to formulate transition-sensitized turbulent transport equations, which are solved in a two-step process and applied to zero-pressure-gradient flow over a flat plate. Computed results are in good agreement with experimental data.

Rumsey, Christopher L.↗
NASA NTRS2001

Disturbance Dynamics in Transitional and Turbulent Flows

The dynamics of an ensemble of linear disturbances with a known probability distribution associated with the initial mode amplitudes are studied in boundary-layer flows through an analysis of the transport equations for the mean disturbance kinetic energy and disturbance energy dissipation rate. Effects of adverse and favorable pressure-gradients on the disturbance dynamics are also included in the analysis. Unlike the fully turbulent regime where nonlinear phase scrambling of the fluctuations affects the flow field in proximity to the wall, the laminar regime fluctuations studied here are influenced across the boundary layer by the solid boundary. In addition to the low Reynolds number, early stage transition regime, the dynamics of these disturbance fields can be related in some respects to the near-wall dynamics of the fully turbulent regime.

Grosch, C. E.↗
NASA NTRS2016

A New Tropical Cyclone Dynamic Initialization Technique Using High Temporal and Spatial Density Atmospheric Motion Vectors and Airborne Field Campaign Data

Background: Initialization of tropical cyclones in numerical weather prediction (NWP) systems is a great challenge: Mass-wind field balance; Secondary circulation and heating; Asymmetries. There can be large adjustments in structure and intensity in the first 24 hours if the initial vortex is not in balance: Spurious gravity waves; Spin-up (model and physics). Existing mesoscale NWP model TC (Tropical Cyclone) initialization strategies: Bogus vortex, cold start from global analyses; 3DVAR or 4DVAR, possibly with synthetic observations; EnKF (Ensemble Kalman Filter); Dynamic initialization. Dynamic initialization allows vortex to have improved balance and physics spin-up at the initial time (e.g., Hendricks et al. 2013, 2011; Nguyen and Chen 2011; Fiorino and Warner 1981; Hoke and Anthes 1976). Himawari-8 geostationary satellite has capability of continuous imagery (10-minutes) over the full disk: New GOES-R satellites will have same capability. This will allow for unprecedented observations of tropical cyclones. However, current data assimila1on systems are not capable of ingesting such high temporal observations (Atmospheric Mo1on Vectors - AMVs). Hourly AMVs are produced, and thinned to 100-kilometer spacing in the horizontal. An entirely new data assimilation concept is required to utilize these observations.

remote sensing↗
NASA NTRS2015

Interactive Vegetation Phenology, Soil Moisture, and Monthly Temperature Forecasts

The time scales that characterize the variations of vegetation phenology are generally much longer than those that characterize atmospheric processes. The explicit modeling of phenological processes in an atmospheric forecast system thus has the potential to provide skill to subseasonal or seasonal forecasts. We examine this possibility here using a forecast system fitted with a dynamic vegetation phenology model. We perform three experiments, each consisting of 128 independent warm-season monthly forecasts: 1) an experiment in which both soil moisture states and carbon states (e.g., those determining leaf area index) are initialized realistically, 2) an experiment in which the carbon states are prescribed to climatology throughout the forecasts, and 3) an experiment in which both the carbon and soil moisture states are prescribed to climatology throughout the forecasts. Evaluating the monthly forecasts of air temperature in each ensemble against observations, as well as quantifying the inherent predictability of temperature within each ensemble, shows that dynamic phenology can indeed contribute positively to subseasonal forecasts, though only to a small extent, with an impact dwarfed by that of soil moisture.

Seasonal Forecasting↗
NASA NTRS2023

Unraveling the Mechanisms and Implications of a Stronger Mid-Pliocene Atlantic Meridional Overturning Circulation (AMOC) in PlioMIP2

The mid-Pliocene warm period (3.264–3.025 Ma) is the most recent geological period in which the atmospheric CO2 concentration was approximately equal to the concentration we measure today (ca. 400 ppm). Sea surface temperature (SST) proxies indicate above-average warming over the North Atlantic in the mid-Pliocene with respect to the pre-industrial period, which may be linked to an intensified Atlantic Meridional Overturning Circulation (AMOC). Earlier results from the Pliocene Model Intercomparison Project Phase 2 (PlioMIP2) show that the ensemble simulates a stronger AMOC in the mid-Pliocene than in the pre-industrial. However, no consistent relationship between the stronger mid-Pliocene AMOC and either the Atlantic northward ocean heat transport (OHT) or average North Atlantic SSTs has been found. In this study, we look further into the drivers and consequences of a stronger AMOC in mid-Pliocene compared to pre-industrial simulations in PlioMIP2. We find that all model simulations with a closed Bering Strait and Canadian Archipelago show reduced freshwater transport from the Arctic Ocean into the North Atlantic. This contributes to an increase in salinity in the subpolar North Atlantic and Labrador Sea that can be linked to the stronger AMOC in the mid-Pliocene. To investigate the dynamics behind the ensemble's variable response of the total Atlantic OHT to the stronger AMOC, we separate the Atlantic OHT into two components associated with either the overturning circulation or the wind-driven gyre circulation. While the ensemble mean of the overturning component is increased significantly in magnitude in the mid-Pliocene, it is partly compensated by a reduction in the gyre component in the northern subtropical gyre region. This indicates that the lack of relationship between the total OHT and AMOC is due to changes in OHT by the subtropical gyre. The overturning and gyre components should therefore be considered separately to gain a more complete understanding of the OHT response to a stronger mid-Pliocene AMOC. In addition, we show that the AMOC exerts a stronger influence on North Atlantic SSTs in the mid-Pliocene than in the pre-industrial, providing a possible explanation for the improved agreement of the PlioMIP2 ensemble mean SSTs with reconstructions in the North Atlantic.

AMOC↗
DOE OSTI2024

Evolution of highly multimodal Rayleigh–Taylor instabilities

Rayleigh–Taylor (RT) instabilities are important fluid instabilities that arise in inertial confinement fusion (ICF) capsule implosions, and many other contexts. Multi-mode coupling is observed in experiments and plays a substantial role in material mix from RT instabilities. In this work, we study the evolution of highly multimodal perturbations (power law distribution) that approximate those found at manufactured material interfaces. We use simulations of over 2000 different perturbations in the LANL code xRAGE to identify distinct phases in the processes of bubble growth and bubble merger which can be visualized in a 2D phase portrait with clear regimes of mode growth and decay. Our results show that the dynamic evolution of the instability strongly depends on the mode of the perturbations and mode interactions. The merger process accelerates bubble growth. A non-Markovian region and a transition of the instability from: (1) initial exponential growth to (2) linear growth and to (3) quadratic growth and asymptotic behavior, are clearly captured in the phase space. We have developed a quantitative model of bubble growth that reproduces the dynamic behavior of ensembles of perturbations. Implications for ICF capsules designed for robustness against instabilities are discussed.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Scenario Storyline Discovery for Planning in Multi‐Actor Human‐Natural Systems Confronting Change

Scenarios have emerged as valuable tools in managing complex human-natural systems, but the traditional approach of limiting focus on a small number of predetermined scenarios can inadvertently miss consequential dynamics, extremes, and diverse stakeholder impacts. Exploratory modeling approaches have been developed to address these issues by exploring a wide range of possible futures and identifying those that yield consequential vulnerabilities. However, vulnerabilities are typically identified based on aggregate robustness measures that do not take full advantage of the richness of the underlying dynamics in the large ensembles of model simulations and can make it hard to identify key dynamics and/or storylines that can guide planning or further analyses. This study introduces the FRamework for Narrative Storylines and Impact Classification (FRNSIC; pronounced “forensic”): a scenario discovery framework that addresses these challenges by organizing and investigating consequential scenarios using hierarchical classification of diverse outcomes across actors, sectors, and scales, while also aiding in the selection of scenario storylines, based on system dynamics that drive consequential outcomes. We present an application of this framework to the Upper Colorado River Basin, focusing on decadal droughts and their water scarcity implications for the basin's diverse users and its obligations to downstream states through Lake Powell. We show how FRNSIC can explore alternative sets of impact metrics and drought dynamics and use them to identify drought scenario storylines, that can be used to inform future adaptation planning.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Quantum turbulence, superfluidity, non-Markovian dynamics, and wave function thermalization

While quantum turbulence has been addressed both experimentally (predominantly for superfluid He 4 and He 3 ) and theoretically, the dynamics of various ensembles of quantized vortices has been followed in time only until the vortices have decayed into phonons. How this “thermalization” is achieved is still an unaddressed and thus an unelucidated question. The unitary Fermi gas (UFG) is a unique quantum system, which has no classical counterpart and is of relevance to neutron stars, cold atoms, condensed-matter and nuclear many-body systems. The non-Markovian evolution of an isolated UFG is put in evidence and its entire nonequilibrium evolution can be studied theoretically within a unified theoretical framework. The initial lattice of quantum vortices and antivortices evolves through a couple of vortex tangles and excitation of Kelvin waves, where vortices cross and reconnect, until very slowly thermalization sets in. Published by the American Physical Society 2024

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS1972

Analysis of instrumentation error effects on the identification accuracy of aircraft parameters

An analytical investigation is presented of the effect of unmodeled measurement system errors on the accuracy of aircraft stability and control derivatives identified from flight test data. Such error sources include biases, scale factor errors, instrument position errors, misalignments, and instrument dynamics. Two techniques (ensemble analysis and simulated data analysis) are formulated to determine the quantitative variations to the identified parameters resulting from the unmodeled instrumentation errors. The parameter accuracy that would result from flight tests of the F-4C aircraft with typical quality instrumentation is determined using these techniques. It is shown that unmodeled instrument errors can greatly increase the uncertainty in the value of the identified parameters. General recommendations are made of procedures to be followed to insure that the measurement system associated with identifying stability and control derivatives from flight test provides sufficient accuracy.

Sorensen, J. A.↗
NASA NTRS1997

Mathematical and Computational Challenges in Population Biology and Ecosystems Science

Mathematical and computational approaches provide powerful tools in the study of problems in population biology and ecosystems science. The subject has a rich history intertwined with the development of statistics and dynamical systems theory, but recent analytical advances, coupled with the enhanced potential of high-speed computation, have opened up new vistas and presented new challenges. Key challenges involve ways to deal with the collective dynamics of heterogeneous ensembles of individuals, and to scale from small spatial regions to large ones. The central issues-understanding how detail at one scale makes its signature felt at other scales, and how to relate phenomena across scales-cut across scientific disciplines and go to the heart of algorithmic development of approaches to high-speed computation. Examples are given from ecology, genetics, epidemiology, and immunology.

Levin, Simon A.↗
NASA NTRS2005

Electronic Transport through Self Assembled Thiol Molecules: Effect of Monolayer Order, Dynamics and Temperature

We present the charge transport and tunneling conductance of self assembled organic thiol molecules and discuss the influence of order and dynamics in the monolayer on the transport behavior and the effect of temperature. Conjugated thiol molecular wires and organometals such as terpyridine metal complexes provide a new platform for molecular electronic devices and we study their self assembly on Au(111) substrates by the scanning tunneling microscope. Determining the organization of the molecule and the ability to control the nature of its interface with the substrate is important for reliable performance of the molecular electronic devices. By concurrent scanning tunneling microscopy and spectroscopy studies on SAMs formed from oligo (phenelyne ethynelyne) monolayers with and without molecular order, we show that packing and order determine the response of a self assembled monolayer (SAM) to competing interactions. Molecular resolution STM imaging in vacuum shows that the OPES adopt an imcommensurate SAM structure on Au(111) with a rectangular unit cell. Tunneling spectroscopic measurements were performed on the SAM as a function of junction resistance. STS results show that the I-Vs are non linear and asymmetric due to the inherent asymmetry in the molecular structure, with larger currents at negative sample biases. The asymmetry increases with increasing junction resistance due to the asymmetry in the coupling to the leads. This is brought out clearly in the differential conductance, which also shows a gap at the Fermi level. We also studied the effect of order and dynamics in the monolayer on the charge transport and found that competing forces between the electric field, intermolecular interactions, tip-molecule physisorption and substrate-molecule chemisorption impact the transport measurements and its reliability and that the presence of molecular order is very important for reproducible transport measurements. Thus while developing new electronic platforms based on molecules, it is important to have a good control of the molecule-substrate interface, for the devices to perform reliably. While such a control would minimize fluctuations and dynamics in the ensemble, the real challenge is to develop device architectures that are tolerant to fluctuations, since they cannot be totally eliminated in these low dimensional soft systems. Results of temperature dependent STS measurements will also be discussed.

Dholakia, Geetha↗
NASA NTRS2001

Ensemble Canonical Correlation Prediction of Seasonal Precipitation Over the United States: Raising the Bar for Dynamical Model Forecasts

This paper presents preliminary results of an ensemble canonical correlation (ECC) prediction scheme developed at the Climate and Radiation Branch, NASA/Goddard Space Flight Center for determining the potential predictability of regional precipitation, and for climate downscaling studies. The scheme is tested on seasonal hindcasts of anomalous precipitation over the continental United States using global sea surface temperature (SST) for 1951-2000. To maximize the forecast skill derived from SST, the world ocean is divided into non-overlapping sectors. The canonical SST modes for each sector are used as the predictor for the ensemble hindcasts. Results show that the ECC yields a substantial (10-25%) increase in prediction skills for all the regions of the US in every season compared to traditional CCA prediction schemes. For the boreal winter, the tropical Pacific contributes the largest potential predictability to precipitation in the southwestern and southeastern regions, while the North Pacific and the North Atlantic are responsible to the enhanced forecast skills in the Pacific Northwest, the northern Great Plains and Ohio Valley. Most importantly, the ECC increases skill for summertime precipitation prediction and substantially reduces the spring predictability barrier over all the regions of the US continent. Besides SST, the ECC is designed with the flexibility to include any number of predictor fields, such as soil moisture, snow cover and additional local observations. The enhanced ECC forecast skill provides a new benchmark for evaluating dynamical model forecasts.

Lau, William K. M.↗
DOE OSTI2026

Enhanced accuracy through ensembling of randomly initialized auto-regressive models for dynamical systems

Computational mechanics simulations using traditional finite element methods (FEM) require prohibitively expensive computational resources for real-time engineering applications, design optimization, and digital twin implementations. While machine learning (ML) surrogate models offer significant computational speedups, autoregressive ML models for time-dependent mechanical systems suffer from error accumulation that compromises long-term prediction reliability - a critical concern for engineering applications where accuracy over extended time horizons is essential for safety and performance assessments. Here, we propose a deep ensemble framework specifically designed to address this challenge in computational mechanics applications, where multiple ML surrogate models with random weight initializations are trained in parallel and their predictions aggregated during inference. This approach leverages statistical diversity to maximize information gain from a fixed set of training data and to mitigate error propagation, while maintaining the computational efficiency that makes ML surrogates attractive for engineering practice. We validate the framework on three representative problems spanning critical areas of computational mechanics: stress field evolution in heterogeneous microstructures under complex loading (relevant to advanced materials design and composite analysis), planetary-scale shallow water dynamics (applicable to environmental and geotechnical engineering), and Gray-Scott reaction-diffusion systems (relevant to mass transport and chemical process engineering). Across all test cases, the ensemble approach demonstrates consistent error reduction of 15-33% compared to individual models. The codes for this work are available on GitHub (https://github.com/Graham-Brady-Research-Group/AutoregressiveEnsemble_SpatioTemporal_Evolution).

autoregressive prediction↗
DOE OSTI2025

Nonlinear Ensemble Filtering with Diffusion Models: Application to the Surface Quasigeostrophic Dynamics

The intersection between classical data assimilation methods and novel machine learning techniques has attracted significant interest in recent years. Here, we explore another promising solution in which diffusion models are used to formulate a robust nonlinear ensemble filter for sequential data assimilation. Unlike standard machine learning methods, the proposed ensemble score filter (EnSF) is completely training free and can efficiently generate a set of analysis ensemble members. Here, in this study, we apply the EnSF to a surface quasigeostrophic model and compare its performance against the popular local ensemble transform Kalman filter (LETKF), which makes Gaussian assumptions in the analysis step. Numerical tests demonstrate that EnSF maintains stable performance in the absence of localization and for a variety of experimental settings. We find that while LETKF maintains optimal performance in the case of linear observations of the entire state and a perfect model, EnSF shows improvements over LETKF when nonlinear observations are assimilated and the system is subject to unexpected model errors. A spectral decomposition of the analysis results in this nonlinear observation regime shows that the largest improvements over LETKF occur at large scales (small wavenumbers), where LETKF lacks sufficient ensemble spread. Overall, this initial application of EnSF to a geophysical model of intermediate complexity motivates further development of the algorithm for more realistic problems.

Artificial intelligence↗