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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 613 records · Page 34
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Validation on Aggregate Flexibility from Residential Air Conditioning Systems for Building-to-Grid Integration

To facilitate the integration of buildings to the power grid, battery-equivalent models have been proposed to characterize and quantify aggregate flexibility from building loads. An analytical method has been proposed to construct such a flexibility model for thermostatically controlled loads. Since this analytical method is derived from a simplified representation of building thermal dynamics, it is necessary to evaluate the resulting flexibility model in a more realistic context. This paper focuses on the validation of this analytical method for estimating aggregate flexibility from residential air conditioning (ACs) systems. A high-fidelity model is first developed to mimic thermal behaviors of a residential AC system through a co-simulation between Modelica and EnergyPlus. A population of virtual residential AC systems is then generated by randomizing parameters of the high-fidelity model. Finally, an aggregate flexibility model is constructed for the residential AC population using the analytical method and validated using results from simulation of the high-fidelity model. It is found that the flexibility estimated using the analytical method is with reasonable accuracy, but can be improved by explicitly incorporating heat gains into the method.

Huang, Sen↗
DOE OSTI2015

On adiabatic invariant in generalized Galileon theories

We consider background dynamics of generalized Galileon theories in the context of inflation, where gravity and inflaton are non-minimally coupled to each other. In the inflaton oscillation regime, the Hubble parameter and energy density oscillate violently in many cases, in contrast to the Einstein gravity with minimally coupled inflaton. However, we find that there is an adiabatic invariant in the inflaton oscillation regime in any generalized Galileon theory. This adiabatic invariant is useful in estimating the expansion law of the universe and also the particle production rate due to the oscillation of the Hubble parameter.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Real-Time High-Accuracy Digital Wireless Time, Frequency, and Phase Calibration for Coherent Distributed Antenna Arrays

his work presents a fully-digital high-accuracy real-time calibration procedure for frequency and time alignment of open-loop wirelessly coordinated coherent distributed antenna array (CDA) modems, enabling radio frequency (RF) phase coherence of spatially separated commercial off-the-shelf (COTS) software-defined radios (SDRs) without cables or external references such as the global navigation satellite system (GNSS). Building on previous work using high-accuracy spectrally-sparse time of arrival (ToA) waveforms and a multistep ToA refinement process, a high-accuracy two-way time transfer (TWTT)-based time–frequency coordination approach is demonstrated. Due to the two-way nature of the high-accuracy TWTT approach, the time and frequency estimates are Doppler and multipath tolerant, so long as the channel is reciprocal over the synchronization epoch. This technique is experimentally verified using COTS SDRs in a lab environment in static and dynamic scenarios and with significant multipath scatterers. Time, frequency, and phase stability were evaluated by beamforming over coaxial cables to an oscilloscope which achieved time and phase precisions of ~60– 70 ps , with median coherent gains above 99% using optimized coordination parameters, and a beamforming frequency root-mean-square error (RMSE) of 3.73 ppb in a dynamic scenario. Finally, experiments were conducted to compare the performance of this technique with previous works using an analog continuous-wave two-tone (CWTT) frequency reference technique in both static and dynamic settings.

Clock synchronization↗
DOE OSTI2017

Processes of diffusion in a limited ensemble of charged particles in a static magnetic field

The dynamics of a limited ensemble of charged particles in a spatially uniform static magnetic field has been studied analytically and numerically. Calculations have been performed for particles with various masses and charges in a wide range of the parameters of the systems under study. It has been shown that the transverse diffusion coefficient in an ensemble of particles in the magnetic field for weakly nonideal systems is described by the Townsend formula. Analytical estimates have been proposed for the analysis of the effective diffusion radius of the ensemble of particles owing to their thermal motion. The proposed relations have been tested by the numerical simulation of the problem.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2017

The Spectroscopy and H-band Imaging of Virgo Cluster Galaxies (SHIVir) Survey: Scaling Relations and the Stellar-to-total Mass Relation

We present parameter distributions and fundamental scaling relations for 190 Virgo cluster galaxies in the SHIVir survey. The distribution of galaxy velocities is bimodal about V {sub circ} ∼ 125 km s{sup −1}, hinting at the existence of dynamically unstable modes in the inner regions of galaxies. An analysis of the Tully-Fisher relation (TFR) of late-type galaxies (LTGs) and the fundamental plane (FP) of early-type galaxies (ETGs) is presented, yielding a compendium of galaxy scaling relations. The slope and zero-point of the Virgo TFR match those of field galaxies, while scatter differences likely reflect distinct evolutionary histories. The velocities minimizing scatter for the TFR and FP are measured at large apertures where the baryonic fraction becomes subdominant. While TFR residuals remain independent of any galaxy parameters, FP residuals (i.e., the FP “tilt”) correlate strongly with the dynamical-to-stellar mass ratio, yielding stringent galaxy formation constraints. We construct a stellar-to-total mass relation (STMR) for ETGs and LTGs and find linear but distinct trends over the range M {sub *} = 10{sup 8–11} M {sub ⊙}. Stellar-to-halo mass relations (SHMRs), which probe the extended dark matter halo, can be scaled down to masses estimated within the optical radius, showing a tight match with the Virgo STMR at low masses; possibly inadequate halo abundance matching prescriptions and broad radial scalings complicate this comparison at all masses. While ETGs appear to be more compact than LTGs of the same stellar mass in projected space, their mass-size relations in physical space are identical. The trends reported here may soon be validated through well-resolved numerical simulations.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2018

An exploration of pressure dynamics using differential equations defined on a fractal geometry

Pressure tests have been used to understand the behavior of naturally fractured reservoirs (NFRs) by establishing parameters such as permeability, connectivity of fractures, system compressibility, fracture network parameters, and others associated with the physical properties of the reservoir. The complex fracture network of a NFR produces anomalous fluid flow, which is shown by the pressure behavior at the well. A plausible model to explain this behavior is to assume that it arises from a fractal fracture system. However, to estimate the parameters that define this fractal fracture system, fluid flow models based on the modification of Darcy’s law are used. On the other hand, in this work, a fractal structure with known fractal dimension: Sierpinski gasket (SG) is proposed. The objective of this work is to solve numerically the diffusion equation on SG, and establish a comparison with flow models used in the oil industry to investigate the fractality assumption. This study is focused on the qualitative behavior of the solution of the diffusion equation defined on a SG supported by the Kigami’s theory of differential equations on fractals.

42 ENGINEERING↗
DOE OSTI2017

Determination of Dark Matter Halo Mass from Dynamics of Satellite Galaxies

We propose that the mass of a dark matter halo can be inferred from the dynamical status of its satellite galaxies. Using nine dark matter simulations of halos like the Milky Way (MW), we find that the present-day substructures in each halo follow a characteristic distribution in the phase space of orbital binding energy and angular momentum, and that this distribution is similar from halo to halo, but has an intrinsic dependence on the halo formation history. We build this distribution directly from the simulations for a specific halo and extend the result to halos of similar formation history but different masses by scaling. The mass of an observed halo can then be estimated by maximizing the likelihood in comparing the measured kinematic parameters of its satellite galaxies with these distributions. We test the validity and accuracy of this method with mock samples taken from the simulations. Using the positions, radial velocities, and proper motions of nine tracers and assuming observational uncertainties comparable to those of MW satellite galaxies, we find that the halo mass can be recovered to within $\sim 40 \% $. The accuracy can be improved to within ~25% if 30 tracers are used. Yet, the dependence of the phase-space distribution on the halo formation history sets a minimum uncertainty of $\sim 20 \% $ that cannot be reduced by using more tracers. We believe that this minimum uncertainty also applies to any mass determination for a halo when the phase-space information of other kinematic tracers is used.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Accelerating uncertainty quantification in incremental dynamic analysis using dimension reduction-based surrogate modeling

We propose a surrogate modeling framework based on dimension reduction to facilitate the quantification of seismic risk of structural systems in performance-based earthquake engineering. The framework adopts incremental dynamic analysis (IDA) for addressing hazard variability, and promotes significant computational efficiency improvement for propagating epistemic uncertainties associated with the structural models. It utilizes both linear and nonlinear dimension reduction approaches, equipped with inverse mappings, to learn a functional between the input parameter space (e.g., the epistemic uncertainties of the structure) to the high-dimensional output space created through the IDA implementation across different ground motions and seismic intensity levels. Polynomial chaos expansion is adopted as the surrogate model to learn this functional in the reduced space. A nine-story steel moment-resisting frame with uncertain structural properties is used as a testbed. Furthermore, we select the seismic fragility curves as a measure of the structure’s seismic performance, since it provides an estimate of the probability of entering specified damage states for given levels of ground shaking.

42 ENGINEERING↗
DOE OSTI2023

Weak trimerization in the frustrated two-dimensional triangular Heisenberg antiferromagnet Lu y Y 1-y MnO 3

To understand the 2D triangular Heisenberg antiferromagnetic system, we investigated the magnetic structures and the dynamics of Lu y Y 1-y MnO 3 in detail. The substitutions are adjusted to the Mn atomic position close to x Mn =$\frac{1}{3}$. The neutron powder diffraction data claims that the magnetic structure of Lu y Y 1-y MnO 3 is described as a mixture of Γ 3 (P6' 3 cm') and Γ 4 (P6' 3 c'm) at the x Mn position for y=0.15, 0.30, and 0.45. The ratio of Γ 3 and Γ 4 depends on temperature and composition and the fraction of Γ 3 increases upon cooling, while no clear trimerization was observed at the xMn position. We estimated exchange parameters from the analysis of the low-energy part of the spin waves. The results showed a weak trimerization effect on cooling because the nearest-neighbor exchange interaction is slightly enhanced. The temperature dependence of the spin-wave dispersion around the Γ point shows that the spin gap closes with increasing temperature because the exchange interactions in the nearest Mn-Mn neighbor become smaller. Gapless diffusive magnetic excitation from a Mn triangular lattice has been observed in a wide range in Q and E space of Lu y Y 1-y MnO 3 . We found that Lu 0.3 Y 0.7 MnO 3 could be an ideal case to investigate the trimerization, frustrated magnetism, and magnetoelastic coupling often observed in two-dimensional triangular lattice Heisenberg antiferromagnet systems.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2015

Distributed database kriging for adaptive sampling (D²KAS)

We present an adaptive sampling method supplemented by a distributed database and a prediction method for multiscale simulations using the Heterogeneous Multiscale Method. A finite-volume scheme integrates the macro-scale conservation laws for elastodynamics, which are closed by momentum and energy fluxes evaluated at the micro-scale. In the original approach, molecular dynamics (MD) simulations are launched for every macro-scale volume element. Our adaptive sampling scheme replaces a large fraction of costly micro-scale MD simulations with fast table lookup and prediction. The cloud database Redis provides the plain table lookup, and with locality aware hashing we gather input data for our prediction scheme. For the latter we use kriging, which estimates an unknown value and its uncertainty (error) at a specific location in parameter space by using weighted averages of the neighboring points. We find that our adaptive scheme significantly improves simulation performance by a factor of 2.5 to 25, while retaining high accuracy for various choices of the algorithm parameters.

36 MATERIALS SCIENCE↗
DOE OSTI2016

DOUBLE DYNAMO SIGNATURES IN A GLOBAL MHD SIMULATION AND MEAN-FIELD DYNAMOS

The 11 year solar activity cycle is the most prominent periodic manifestation of the magnetohydrodynamical (MHD) large-scale dynamo operating in the solar interior, yet longer and shorter (quasi-) periodicities are also present. The so-called “quasi-biennial” signal appearing in many proxies of solar activity has been gaining increasing attention since its detection in p -mode frequency shifts, which suggests a subphotospheric origin. A number of candidate mechanisms have been proposed, including beating between co-existing global dynamo modes, dual dynamos operating in spatially separated regions of the solar interior, and Rossby waves driving short-period oscillations in the large-scale solar magnetic field produced by the 11 year activity cycle. In this article, we analyze a global MHD simulation of solar convection producing regular large-scale magnetic cycles, and detect and characterize shorter periodicities developing therein. By constructing kinematic mean-field α {sup 2}Ω dynamo models incorporating the turbulent electromotive force (emf) extracted from that same simulation, we find that dual-dynamo behavior materializes in fairly wide regions of the model’s parameters space. This suggests that the origin of the similar behavior detected in the MHD simulation lies with the joint complexity of the turbulent emf and differential rotation profile, rather that with dynamical interactions such as those mediated by Rossby waves. Analysis of the simulation also reveals that the dual dynamo operating therein leaves a double-period signature in the temperature field, consistent with a dual-period helioseismic signature. Order-of-magnitude estimates for the magnitude of the expected frequency shifts are commensurate with helioseismic measurements. Taken together, our results support the hypothesis that the solar quasi-biennial oscillations are associated with a secondary dynamo process operating in the outer reaches of the solar convection zone.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

System and method for modeling and forecasting cyclical demand systems with dynamic controls and dynamic incentives

Systems and methods for modeling and forecasting cyclical demand systems in the presence of dynamic control or dynamic incentives. A method for modeling a cyclical demand system comprises obtaining historical data on one or more demand measurements over a plurality of demand cycles, obtaining historical data on incentive signals over the plurality of demand cycles, constructing a model using the obtained historical data on the one or more demand measurements and the incentive signals, wherein constructing the model comprises specifying a state-space model, specifying variance parameters in the model, and estimating unknown variance parameters.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Mapping Glacier Basal Sliding Applying Machine Learning

During the RESOLVE project (“High-resolution imaging in subsurface geophysics: development of a multi-instrument platform for interdisciplinary research”), continuous surface displacement and seismic array observations were obtained on Glacier d’Argentière in the French Alps for 35 days in May 2018. The data set is used to perform a detailed study of targeted processes within the highly dynamic cryospheric environment. In particular, the physical processes controlling glacial basal motion are poorly understood and remain challenging to observe directly. Especially in the Alpine region for temperate based glaciers where the ice rapidly responds to changing climatic conditions and thus, processes are strongly intermittent in time and heterogeneous in space. Spatially dense seismic and Global Positioning System (GPS) measurements are analyzed applying machine learning to gain insight into the processes controlling glacial motions of Glacier d’Argentière. Using multiple bandpass-filtered copies of the continuous seismic waveforms, we compute energy-based features, develop a matched field beamforming catalog and include meteorological observations. Features describing the data are analyzed with a gradient boosting decision tree model to directly estimate the GPS displacements from the seismic noise. We posit that features of the seismic noise provide direct access to the dominant parameters that drive displacement on the highly variable and unsteady surface of the glacier. The machine learning model infers daily fluctuations and longer term trends. The results show on-ice displacement rates are strongly modulated by activity at the base of the glacier. The techniques presented provide a new approach to study glacial basal sliding and discover its full complexity.

58 GEOSCIENCES↗
DOE OSTI2013

Dynamics of the order parameter and the potential of the hydrogen bond in a ferroelectric DKDP crystal

Within a pseudospin model of a KD{sub 2}PO{sub 4} crystal, the relaxation time of the average pseudospin (the order parameter) in the mean-field approximation depends on the activation energy of the jump of a deuteron between the minima of the hydrogen bond potential, the average equilibrium value of the pseudospin, and the dielectric susceptibility. Calculating the average equilibrium spin and the susceptibility within the four-particle cluster approximation and fitting the data for the width of the central peak from a Raman scattering experiment, we numerically estimate the activation energy. For the same values of the parameters of the cluster method, the calculated inverse relaxation time is in good agreement with the data of ultrasonic measurements.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

Computationally efficient CFD prediction of bubbly flow using physics-guided deep learning

To realize efficient computational fluid dynamics (CFD) prediction of two-phase flow, a multi-scale framework was proposed in this paper by applying a physics-guided data-driven approach. Instrumental to this framework, Feature Similarity Measurement (FSM) technique was developed for error estimation in two-phase flow simulation using coarse-mesh CFD, to achieve a comparable accuracy as fine-mesh simulations with fast-running feature. In this work, by defining physics-guided parameters and variable gradients as physical features, FSM has the capability to capture the underlying local patterns in the coarse-mesh CFD simulation. Massive low-fidelity data and respective high-fidelity data are used to explore the underlying information relevant to the main simulation errors and the effects of phenomenological scaling. By learning from previous simulation data, a surrogate model using deep feedforward neural network (DFNN) can be developed and trained to estimate the simulation error of coarse-mesh CFD. In a demonstration case of two-phase bubbly flow, the DFNN model well captured and corrected the unphysical “peaks” in the velocity and void fraction profiles near the wall in the coarse-mesh configuration, even for extrapolative predictions. The research documented supports the feasibility of the physics-guided deep learning methods for coarse mesh CFD simulations which has a potential for the efficient industrial design.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2012

Molecular beam epitaxial growth and characterization of InSb{sub 1-x}N{sub x} on GaAs for long wavelength infrared applications

Recent research progress and findings in InSbN have attracted great attention due to its use in long wavelength infrared applications. A large bandgap reduction in InSb resulting from high N incorporation with minimal crystal defects is challenging due to relatively small atomic size of N. Hence optimization of growth conditions plays an important role in the growth of high-quality InSbN epilayers for device purposes. In this paper, we report on the correlation of structural, vibrational, electrical, and optical properties of molecular beam epitaxially grown InSbN epilayers grown on GaAs substrates, as a function of varying growth temperatures. Two dimensional growths of InSb and InSbN were confirmed from dynamic reflection high energy electron diffraction patterns and growth parameters were optimized. High crystalline quality of the epilayers is attested to by a low full width at half maximum of 200 arcsec from high resolution x-ray diffraction (HRXRD) scans and by the high intensity and well-resolved InSb longitudinal optical (LO) and 2{sup nd} order InSb LO mode observed from micro-Raman spectroscopy. The N incorporation in these InSbN epilayers is estimated to be 1.4% based on HRXRD simulation. X-ray photoelectron spectroscopy (XPS) studies reveal that most of the N present in the layers are in the form of In-N bonding. Variation of the lattice disorder with growth temperature is correlated with the types of N bonding present, the carrier concentration and mobility, observed in the corresponding XPS spectra and Hall measurements, respectively. XPS analysis, HRXRD scans, and Raman spectral analysis indicate that lower growth temperature favors In-N bonding which dictates N incorporation in the substitutional sites and lattice disorder, whereas, high growth temperature promotes the formation of In-N-Sb bonding. The best room temperature and 77 K electrical transport parameters and maximum redshift in the absorption edge have been achieved in the InSbN epilayer grown in the 290 deg. C {approx} 330 deg. C temperature range.

36 MATERIALS SCIENCE↗
DOE OSTI2014

THE LOW-SPIN BLACK HOLE IN LMC X-3

Building upon a new dynamical model for the X-ray binary LMC X-3, we measure the spin of its black hole (BH) primary via the continuum-fitting method. We consider over one thousand thermal-state Rossi X-ray Timing Explorer X-ray spectra of LMC X-3. Using a large subset of these spectra, we constrain the spin parameter of the BH to be a{sub ∗}=0.25{sub −0.29}{sup +0.20} (90% confidence). Our estimate of the uncertainty in a {sub *} takes into account a wide range of systematic errors. We discuss evidence for a correlation between a BH's spin and the complexity of its X-ray spectrum.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Static and dynamic magnetic properties of honeycomb lattice antiferromagnets Na 2 M 2 TeO 6 , M = Co and Ni

The magnetic structures and spin dynamics of Na 2 CO 2 TeO 6 and Na 2 Ni 2 TeO 6 are investigated by means of elastic and inelastic neutron scattering measurements and the results are discussed in the context of a generalized Kitaev-Heisenberg model on a honeycomb lattice with strong spin-orbit coupling. The large number of parameters involved in the Hamiltonian model is evaluated by using an iterative optimization algorithm capable of extracting model solutions and simultaneously estimating their uncertainty. The analyses indicate that both Co 2+ (d 7 ) and Ni 2+ (d 8 ) antiferromagnets realize bond-dependent anisotropic nearest-neighbor interactions and support the theoretical predictions for the realization of Kitaev physics in 3 d electron systems with effective spins S = 1/2 and 1. By studying the Na-doped system Na 2.4 Ni 2 TeO 6 , we show that the control of Na content can provide an effective route for fine-tuning the magnetic lattice dimensionality, as well as to controlling the bond-dependent anisotropic interactions.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗