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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 721 records · Page 40
All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

Probing baryonic processes and gastrophysics in the formation of the Milky Way dwarf satellites. I. Metallicity distribution properties

The Milky Way (MW) dwarf satellites, as the smallest galaxies discovered in the present-day universe, are potentially powerful probes to various baryonic processes in galaxy formation occurring in the early universe. In this paper, we study the chemical properties of the stars in the dwarf satellites around the MW-like host galaxies, and explore the possible effects of several baryonic processes, including supernova (SN) feedback, the reionization of the universe, and H{sub 2} cooling, and how current and future observations may put some constraints on these processes. We use a semianalytical model to generate MW-like galaxies, for which a fiducial model can reproduce the luminosity function and the stellar metallicity-stellar mass correlation of the MW dwarfs. Using the simulated MW-like galaxies, we focus on investigating three metallicity properties of their dwarfs: the stellar metallicity-stellar mass correlation of the dwarf population, and the metal-poor and metal-rich tails of the stellar metallicity distribution in individual dwarfs. We find that (1) the slope of the stellar metallicity-stellar mass correlation is sensitive to the SN feedback strength and the reionization epoch; (2) the extension of the metal-rich tails is mainly sensitive to the SN feedback strength; (3) the extension of the metal-poor tails is mainly sensitive to the reionization epoch; (4) none of the three chemical properties are sensitive to the H{sub 2} cooling process; and (5) a comparison of our model results with the current observational slope of the stellar metallicity-stellar mass relation suggests that the local universe is reionized earlier than the cosmic average, local sources may have a significant contribution to the reionization in the local region, and an intermediate to strong SN feedback strength is preferred. Future observations of metal-rich and metal-poor tails of stellar metallicity distributions will put further constraints on the SN feedback and the reionization processes.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Data-Efficient Strategies for Probabilistic Voltage Envelopes under Network Contingencies

This work presents an efficient data-driven method to construct probabilistic voltage envelopes (PVE) using power flow learning in grids with network contingencies. First, a network-aware Gaussian process (GP) termed Vertex-Degree Kernel (VDK-GP), developed in prior work, is used to estimate voltage–power functions for a few network configurations. The paper introduces a novel multi-task vertex degree kernel (MT-VDK) that amalgamates the learned VDK-GPs to determine power flows for unseen networks, with a significant reduction in the computational complexity and hyperparameter requirements compared to alternate approaches. Simulations on the IEEE 30-Bus network demonstrate the retention and transfer of power flow knowledge in both N-1 and N-2 contingency scenarios. The MT-VDK-GP approach achieves over 50 % reduction in mean prediction error for novel N-1 contingency network configurations in low training data regimes (50–250 samples) over VDK-GP. Additionally, MT-VDK-GP outperforms a hyper-parameter based transfer learning approach in over 75 % of N-2 contingency network structures, even without historical N-2 outage data. Furthermore, the proposed method demonstrates the ability to achieve PVEs using sixteen times fewer power flow solutions compared to Monte-Carlo sampling-based methods.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2018

Carbide Particle Redistribution in U10Mo Alloy during Hot Rolling Process

The influence of initial carbide particle distribution features on the evolution of particle and stringer distribution within U10Mo alloy during hot rolling was investigated in this study. This work will provide guidance to casting optimization work and identify actionable process changes to eliminate the surface features directly attributed to carbides. Various synthetic microstructure-based finite-element (FE) models were generated with consideration of different parameters (i.e., particle shape, particle volume fraction and particle distribution). Plane-strain compression loading was employed in the FE models to simulate hot rolling to 40% and 80% reductions. Stringer statistics analyses and two-point correlation functions were then performed with the simulated hot-rolling results. The results from stringer analyses show that stringer volume fraction substantially increases with increased rolling reduction for microstructure with particles distributed along grain boundaries, and that microstructures with elliptical particles may have slightly higher stringer volume fractions than those with circular particles. The results also show that the maximum stringer length can increase substantially with increased rolling reduction for microstructures with elliptical particles along grain boundaries, and that the microstructures with higher-aspect-ratio elliptical particles may have higher stringer volume fraction and higher maximum stringer length. Near-surface numbers of particles and particle volume fractions also increase with increased rolling reduction. The results from application of the two-point correlation function show that the particle shape (i.e., circular or elliptical) may not have significant influence on the overall shapes of the correlation curves, and that the correlation curves tend to show higher peaks at short distance and then gradually decrease for microstructures with higher particle volume fractions and particles distributed along grain boundaries.

36 MATERIALS SCIENCE↗
DOE OSTI2018

When managers forage for pests: Implementing the functional response in pest management

In this work, we explore how the functional response framework can be implemented in pest management. Here, managers take the role of predators foraging on pests and facing monetary costs for survey and control in a spatial domain where the pest distribution and control strategy do not have to be random. To investigate this framework quantitatively, we simulated various management processes on different pest spatial distributions using a spatially-explicit individual-based model and Monte-Carlo simulations, and also confirmed some of the results analytically. By graphing the number of pests controlled versus pest density, we obtained management functional response curves. Whether the management functional response was shaped like a type I, type II or type III functional response depended on the management costs and the search area. Yet, the management spatial strategy and the pest spatial distribution had little effect on the functional response. We applied our model to the management of mountain pine beetle epidemic in Cypress Hills, Saskatchewan, Canada, with simulations matching the real number of attacked trees controlled by managers. We showed how to make an analogy between functional responses in predator–prey interactions and in human–pest interactions and thereby, apply insights from the functional response framework to pest management.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Limitations of Bin and Bulk Microphysics in Reproducing the Observed Spatial Structure of Light Precipitation

Abstract Coarse-gridded atmospheric models often account for subgrid-scale variability by specifying probability distribution functions (PDFs) of process rate inputs such as cloud and rainwater mixing ratios ( q c and q r , respectively). PDF parameters can be obtained from numerous sources: in situ observations, ground- or space-based remote sensing, or fine-scale modeling such as large-eddy simulation (LES). LES is appealing to constrain PDFs because it generates large sample sizes, can simulate a variety of cloud regimes/case studies, and is not subject to the ambiguities of observations. However, despite the appeal of using model output for parameterization development, it has not been demonstrated that LES satisfactorily reproduces the observed spatial structure of microphysical fields. In this study, the structure of observed and modeled microphysical fields are compared by applying bifractal analysis, an approach that quantifies variability across spatial scales, to simulations of a drizzling stratocumulus field that span a range of domain sizes, drop concentrations (a proxy for mesoscale organization), and microphysics schemes (bulk and bin). Simulated q c closely matches observed estimates of bifractal parameters that measure smoothness and intermittency. There are major discrepancies between observed and simulated q r properties, though, with bulk simulated q r consistently displaying the bifractal properties of observed clouds (smooth, minimally intermittent) rather than rain while bin simulations produce q r that is appropriately intermittent but too smooth. These results suggest fundamental limitations of bulk and bin schemes to realistically represent higher-order statistics of the observed rain structure.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Multidimensional visualization of the dynamic evolution of Li metal via in situ/operando methods

The growing demands for high-energy density electrical energy storage devices stimulate the coupling of conversion-type cathodes and lithium (Li) metal anodes. While promising, the use of these “Li-free” cathodes brings new challenges to the Li anode interface, as Li needs to be dissolved first during cell operation. In this study, we have achieved a direct visualization and comprehensive analysis of the dynamic evolution of the Li interface. The critical metrics of the interfacial resistance, Li growth, and solid electrolyte interface (SEI) distribution during the initial dissolution/deposition processes were systematically investigated by employing multidimensional analysis methods. They include three-electrode impedance tests, in situ atomic force microscopy, scanning electrochemical microscopy, and cryogenic scanning transmission electron microscopy. The high-resolution imaging and real-time observations show that a loose, diffuse, and unevenly distributed SEI is formed during the initial dissolution process. This leads to the dramatically fast growth of Li during the subsequent deposition, deviating from Fick’s law, which exacerbates the interfacial impedance. The compactness of the interfacial structure and enrichment of electrolyte species at the surface during the initial deposition play critical roles in the long-term stability of Li anodes, as revealed by operando confocal Raman spectroscopic mapping. In conclusion, our observations relate to ion transfer, morphological and structural evolution, and Li (de)solvation at Li interfaces, revealing the underlying pathways influenced by the initial dissolution process, which promotes a reconsideration of anode investigations and effective protection strategies.

25 ENERGY STORAGE↗
DOE OSTI2013

AZIMUTHAL STRUCTURE OF THE Cyg X-2 X-RAY DUST HALO

There is little information concerning the azimuthal distribution of X-rays in dust-scattering halos. This paper describes a Chandra observation of the bright source Cyg X-2 designed specifically for this purpose. After measuring and subtracting Almost-Equal-To 10% instrument effects, we find the scattering halo to be rather uniform with possible fluctuations in the surface brightness of only 2%. Observations and data processing are discussed in detail. Some information about the dust distribution is derived.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2014

A stepped leader model for lightning including charge distribution in branched channels

The stepped leader process in negative cloud-to-ground lightning plays a vital role in lightning protection analysis. As lightning discharge usually presents significant branched or tortuous channels, the charge distribution along the branched channels and the stochastic feature of stepped leader propagation were investigated in this paper. The charge density along the leader channel and the charge in the leader tip for each lightning branch were approximated by introducing branch correlation coefficients. In combination with geometric characteristics of natural lightning discharge, a stochastic stepped leader propagation model was presented based on the fractal theory. By comparing simulation results with the statistics of natural lightning discharges, it was found that the fractal dimension of lightning trajectory in simulation was in the range of that observed in nature and the calculation results of electric field at ground level were in good agreement with the measurements of a negative flash, which shows the validity of this proposed model. Furthermore, a new equation to estimate the lightning striking distance to flat ground was suggested based on the present model. The striking distance obtained by this new equation is smaller than the value estimated by previous equations, which indicates that the traditional equations may somewhat overestimate the attractive effect of the ground.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2010

kt-factorization for Hard Processes in Nuclei

Two widely proposed kt-dependent gluon distributions in the small-x saturation regime are investigated using two particle back-to-back correlations in high energy scattering processes. The Weizsacker-Williams gluon distribution, interpreted as the number density of gluon inside the nucleus, is studied in the quark-antiquark jet correlation in deep inelastic scattering. On the other hand, the unintegrated gluon distribution, defined as the Fourier transform of the color-dipole cross section, is probed in the direct photon-jet correlation in pA collisions. Dijet-correlation in pA collisions depends on both gluon distributions through combination and convolution in the large Nc limit. We calculate these processes in two approaches: the transverse momentum dependent factorization approach and the color-dipole/color glass condensate formalism, and they agree with each other completely.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2015

A variance-based decomposition and global sensitivity index method for uncertainty quantification: Application to retrieved ice cloud properties

This study develops a novel uncertainty quantification (UQ) method for cloud microphysical property retrievals using variance-based decomposition and global sensitivity index. In this UQ framework, empirical orthogonal function (EOF) analysis is applied to the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) ground-based observations, which are the inputs for the cloud retrieval studied here. The principal components (PCs) in the EOF expansion are parameterized as random input variables, and hence, the input dimension is greatly reduced (up to a factor of 50), allowing large ensemble of random samplings. The EOF expansion improves the accuracy of the uncertainty estimation by taking into account the cross correlations in the input data profiles. Here, this method enables a probabilistic representation of a retrieval process by adding normally distributed perturbations into PCs of sample means of input data profiles within a time window. Therefore, it effectively facilitates objective validation of climate models against cloud retrievals under a probabilistic framework for rigorous statistical inferences. Moreover, the variance-based global sensitivity index analysis, part of this method, attributes the output uncertainties to each individual source, thus providing directions for improving retrieval algorithms and observation strategies. For demonstration, we apply this method to quantify the uncertainties of the ARM program's baseline cloud retrieval algorithm for an ice cloud case observed at the Southern Great Plains site on 9 March 2000.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Hierarchical Bayesian method for mapping biogeochemical hot spots using induced polarization imaging

In floodplain environments, a naturally reduced zone (NRZ) is considered to be a common biogeochemical hot spot, having distinct microbial and geochemical characteristics. Although important for understanding their role in mediating floodplain biogeochemical processes, mapping the subsurface distribution of NRZs over the dimensions of a floodplain is challenging, as conventional wellbore data are typically spatially limited and the distribution of NRZs is heterogeneous. In this work, we present an innovative methodology for the probabilistic mapping of NRZs within a three-dimensional (3-D) subsurface domain using induced polarization imaging, which is a noninvasive geophysical technique. Measurements consist of surface geophysical surveys and drilling-recovered sediments at the U.S. Department of Energy field site near Rifle, CO (USA). Inversion of surface time domain-induced polarization (TDIP) data yielded 3-D images of the complex electrical resistivity, in terms of magnitude and phase, which are associated with mineral precipitation and other lithological properties. By extracting the TDIP data values colocated with wellbore lithological logs, we found that the NRZs have a different distribution of resistivity and polarization from the other aquifer sediments. To estimate the spatial distribution of NRZs, we developed a Bayesian hierarchical model to integrate the geophysical and wellbore data. In addition, the resistivity images were used to estimate hydrostratigraphic interfaces under the floodplain. Validation results showed that the integration of electrical imaging and wellbore data using a Bayesian hierarchical model was capable of mapping spatially heterogeneous interfaces and NRZ distributions thereby providing a minimally invasive means to parameterize a hydrobiogeochemical model of the floodplain.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

The dynamic and thermodynamic structure of the monsoon over southern India: New observations from the INCOMPASS IOP

Some of the highest summer monsoon rainfall in South Asia falls on the windward slopes of the Western Ghats mountains on India's west coast and offshore over the eastern Arabian Sea. Understanding of the processes determining the spatial distribution and temporal variability of this region remains incomplete. In this paper, new Interaction of Convective Organization and Monsoon Precipitation, Atmosphere, Surface and Sea (INCOMPASS) aircraft and ground‐based measurements of the summer monsoon over the Western Ghats and upstream of them are presented and placed within the context of remote‐sensing observations and reanalysis. The transition from widespread rainfall over the eastern Arabian Sea to rainfall over the Western Ghats is documented in high spatial and temporal resolution. Heavy rainfall offshore during the campaign was associated primarily with mid‐tropospheric humidity, secondarily with sea surface temperature, and only weakly with orographic blocking. A mid‐tropospheric dry intrusion suppressed deep convection offshore in the latter half of the campaign, allowing the build‐up of low‐level humidity in the onshore flow and enhancing rainfall over the mountains. Rainfall on the lee side of the Western Ghats occurred during the latter half of the campaign in association with enhanced mesoscale easterly upslope flow. Diurnal cycles in rainfall offshore (maximum in the morning) and on the mountains (maximum in the afternoon) were observed. Considerable zonal and temporal variability was seen in the offshore boundary layer, suggesting the presence of convective downdraughts and cold pools. Persistent drying of the subcloud mixed layer several hundred kilometres off the coast was observed, suggesting strong mixing between the boundary layer and the free troposphere. These observations provide quantitative targets to test models and suggest hypotheses on the physical mechanisms determining the distribution and variability in rainfall in the Western Ghats region.

Fletcher, Jennifer K.↗
DOE OSTI2021

The ezSpectra suite: An easy‐to‐use toolkit for spectroscopy modeling

Abstract A molecule's spectrum encodes information about its structure and electronic properties. It is a unique fingerprint that can serve as a molecular ID. Quantum chemistry calculations provide key ingredients for interpreting spectra, but modeling the spectra rarely ends there; it requires additional steps that entail combined treatments of electronic and nuclear degrees of freedom and account for specifics of the experimental setup (light energy, polarization, averaging over molecular orientations, temperature, etc.). This Software Focus article describes the ezSpectra suite, which currently comprises two stand‐alone open‐source codes: ezFCF and ezDyson . ezFCF calculates Franck–Condon factors, which yield vibrational progressions for polyatomic molecules, within the double‐harmonic approximation. ezDyson calculates absolute cross‐sections for photodetachment/photoionization processes and photoelectron angular distributions using Dyson orbitals computed by a quantum chemistry program. This article is categorized under: Electronic Structure Theory > Ab Initio Electronic Structure Methods Theoretical and Physical Chemistry > Spectroscopy Software > Simulation Methods

Gozem, Samer↗
DOE OSTI2024

Dark Radiation Constraints on Heavy QCD Axions

The naturalness problem of PQ symmetry motivates study of the heavy QCD axion, with masses m a > 1 MeV generated at scales above the QCD scale, and low values of the PQ symmetry breaking scale, ƒ a . We compute the abundance of such axions in a model-independent way, assuming only that they freeze-out after reheating from inflation, and are not subsequently diluted by new physics. If these axions decay between neutrino decoupling and the last scatter era of the Cosmic Microwave Background (CMB), they dilute the neutrinos and their abundance is constrained by CMB measurements of the energy density in dark radiation, N eff . We accurately compute this bound using a numerical code to evolve the axion momentum distribution, including many key processes and effects previously ignored. We assume that the only relevant axion decays are to final states involving Standard Model particles. We determine regions of (m a , ƒ a ) that will give a signal in N eff at CMB Stage 4 experiments. We similarly compute the N eff bound and CMB Stage 4 signal for heavy axions that can decay to light mirror photons. Finally, we compute the bounds on heavy axions with mass below 1 MeV that decay after the era of CMB last scatter, from their contribution to cold or hot dark matter or N eff at this era.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

Zonal-Based Emission Source Term Model for Predicting Particulate Emission Factors in Wildfire Simulations

A physics/chemistry-based numerical model for predicting the emission of fine particles from wildfires is proposed. This model implements the fundamental mechanisms of soot formation in a combustion environment: soot nucleation, surface growth, agglomeration, oxidation, and particle fragmentation. These mechanisms occur on a scale too fine for the discretization of most wildfire models, which need to simulate landscape-scale dynamics. As a result this model implements a zonal approach, where the computed soot particle distribution is partitioned into process zones within a single resolved grid cell. These process zones include: an inception zone (for nucleation), a heating zone (for coagulation, surface growth, and fragmentation), a reaction zone (for oxidation), and a quenched zone (for atmospheric processes). Governing mechanisms are applied to the appropriate zones to predict total particle growth and emission. Additionally, the proposed model is implemented into HIGRAD/FIRETEC, a physics-based wildfire simulation code which couples interactions between fire, fuels, atmosphere, and topography on a landscape scale. Fire simulations among grasslands and conifer forests are performed and compared against experimental data for emission factors.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Current-Induced Spin Polarization in Nonmagnetic Semiconductors

The use of spontaneous electron spin polarization in nonmagnetic semiconductors avoids the transport challenges of electron spin injection from magnetic materials as well as packing constraints of small magnets in a dense array. Although the focus of rearch on the spontaneous spin polarization of electrical current has been on spin-orbit fields and their effects, in principle a moving electron gas can be unstable to forming spin-polarized distributions via carrier scattering processes that are independent of the carrier spin. The two required elements for such current-induced spin polarization without spin-orbit interactions are (1) the presence of built-in spatially-varying electric fields, either naturally forming (as in the Gunn effect) or extrinsic (as in a junction with spatially dependent doping) and (2) energy-dependent carrier scattering processes. As spin-orbit interactions are not required for this effect, it should occur in inversion-symmetric materials like silicon that lack zero-field spin splittings and materials like zinc oxide and gallium nitride that lack significant spin-orbit interactions.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2019

Stationary Distribution and Perturbation Bounds for a Stochastic Inventory Model

In this paper, we use the theory of generalized inverses to compute the stationary distribution of the (s, S) inventory model directly from the transition matrix of the underlying Markov chain and to provide perturbation bounds. Indeed, approximations are employed to build a tractable model, and statistical methods are used to estimate the unknown parameters and distributions. Hence, the system is subject to perturbations that may cause deviation in the characteristics. The proposed perturbation bound provides a means to estimate the impact of the perturbations on the performance measures of the considered inventory system.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Capturing Hidden Geochemical Anomalies in Scarce Data by Fractal Analysis and Stochastic Modeling

Fractal/multifractal modeling is a widely used geomathematical approach to capturing different populations in geochemical mapping. The rationale of this methodology is based on empirical frequency density functions attained from global or local distributions. This approach is quite popular because of its simplicity and versatility; it accounts for the frequency and spatial distribution of geochemical data considering self-similarity across a range of scales. Using this technique for detection of geochemical anomalies in scarce data, however, is problematic and can lead to systematic bias in the characterization of the underlying populations. In this paper, an innovative technique is presented that provides good results without a priori assumptions. A simulation approach is adopted for fractal analysis by generating different possible distribution scenarios for the variable under study to reveal the underlying populations that are frequently hidden due to lack of data. The proposed technique is called the global simulated size–number method, and it is validated in a case study with two synthetic datasets and another case study with real dataset from the Ushtagan gold deposit in northeast Kazakhstan.

58 GEOSCIENCES↗