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At least 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Relationships between the Stellar, Gaseous, and Star Formation Disks in LITTLE THINGS Dwarf Irregular Galaxies: Indirect Evidence for Substantial Fractions of Dark Molecular Gas

The stellar, gaseous and young stellar disks in the LITTLE THINGS sample of nearby dwarf irregular galaxies are fitted with functions to search for correlations between the parameters. We find that the H i radial profiles are generally flatter in the center and fall faster in the outer regions than the V-band profiles, while young stars are more centrally concentrated, especially if the H i is more centrally flat. This pattern suggests that the H i is turning into molecules in the center, and the molecular clouds are forming stars and FUV. A model that assumes the molecular surface density is proportional to the total gas surface density to a power of 1.5 or 2, in analogy with the Kennicutt–Schmidt relation, reproduces the relationship between the ratio of the visible to the H i scale length and the H i Sérsic index. The molecular fraction is estimated as a function of radius for each galaxy by converting the FUV to a molecular surface density using conventional calibrations. The average molecular fraction inside 3R {sub D} is 23% ± 17%. However, the break in the stellar surface brightness profile has no unified tracer related to star formation.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2014

Anomalous photoelectric emission from Ag on zinc-phthalocyanine film

Photoelectric emission from organic and metal thin films is generally observed with irradiation of photon energy larger than 4 eV. In this paper, however, we report photoelectric emission from Ag on a zinc-phthalocyanine (ZnPc) layer at a photon energy of 3.4 eV. The threshold energy for this photoelectric emission is much smaller than the work function of Ag estimated by conventional photoelectron spectroscopy. The photoelectric emission by low-energy photons is significant for Ag thicknesses of less than 1 nm. Photoelectron spectroscopy and morphological study of the Ag/ZnPc suggest that the anomalous photoelectric emission from the Ag surface is caused by a vacuum level shift at the Ag/ZnPc interface and by surface plasmons of the Ag nanoparticles.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2013

Improved statistical models for limited datasets in uncertainty quantification using stochastic collocation

This paper presents a data-driven framework for performing uncertainty quantification (UQ) by choosing a stochastic model that accurately describes the sources of uncertainty in a system. This model is propagated through an appropriate response surface function that approximates the behavior of this system using stochastic collocation. Given a sample of data describing the uncertainty in the inputs, our goal is to estimate a probability density function (PDF) using the kernel moment matching (KMM) method so that this PDF can be used to accurately reproduce statistics like mean and variance of the response surface function. Instead of constraining the PDF to be optimal for a particular response function, we show that we can use the properties of stochastic collocation to make the estimated PDF optimal for a wide variety of response functions. We contrast this method with other traditional procedures that rely on the Maximum Likelihood approach, like kernel density estimation (KDE) and its adaptive modification (AKDE). We argue that this modified KMM method tries to preserve what is known from the given data and is the better approach when the available data is limited in quantity. We test the performance of these methods for both univariate and multivariate density estimation by sampling random datasets from known PDFs and then measuring the accuracy of the estimated PDFs, using the known PDF as a reference. Comparing the output mean and variance estimated with the empirical moments using the raw data sample as well as the actual moments using the known PDF, we show that the KMM method performs better than KDE and AKDE in predicting these moments with greater accuracy. This improvement in accuracy is also demonstrated for the case of UQ in electrostatic and electrothermomechanical microactuators. We show how our framework results in the accurate computation of statistics in micromechanical systems.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Spread Spectrum Time Domain Reflectometry and Steepest Descent Inversion to Measure Complex Impedance

In this paper, we present a method for estimating complex impedances using reflectometry and a modified steepest descent inversion algorithm. We simulate spread spectrum time domain reflectometry (SSTDR), which can measure complex impedances on energized systems for an experimental setup with resistive and capacitive loads. A parametric function, which includes both a misfit function and stabilizer function, is created. The misfit function is a least squares estimate of how close the model data matches observed data. The stabilizer function prevents the steepest descent algorithm from becoming unstable and diverging. Steepest descent iteratively identifies the model parameters that minimize the parametric function. We validate the algorithm by correctly identifying the model parameters (capacitance and resistance) associated with simulated SSTDR data, with added 3 dB white Gaussian noise. With the stabilizer function, the steepest descent algorithm estimates of the model parameters are bounded within a specified range. Furthermore, the errors for capacitance (220pF to 820pF) and resistance (50 Ω to 270 Ω) are < 10%, corresponding to a complex impedance magnitude |R +1/jωC| of 53 Ω to 510 Ω.

14 SOLAR ENERGY↗
DOE OSTI2021

Atom Equivalent Energies for the Rapid Estimation of the Heat of Formation of Explosive Molecules from Density Functional Tight Binding Theory

Atom equivalent energies have been derived from which the gas-phase heat of formation of explosive molecules can be estimated from fast, semiempirical density functional tight binding total energy calculations. The root-mean-square deviation and maximum deviation of the heats of formation from the experimental values for the set of 45 energetic molecules compiled by Byrd and Rice [ J. Phys. Chem. A, 2006, 110, 1005–1013] are 10.4 and 25.5 kcal/mol, respectively, using 4 atom equivalent energies and 7.4 and 15.0 kcal/mol, respectively, using 7 atom equivalent energies. These errors are around a factor of 2–3 larger than those obtained from density functional theory calculations but are smaller than those obtained from other semiempirical electronic structure methods. Heats of formation calculated with density functional tight binding theory using the 4 and 7 atom equivalent energies, the Byrd and Rice scheme, and the atom pair contribution method for a new set of 531 energetic molecules that contain only carbon, hydrogen, nitrogen, and oxygen are provided.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

The climatological distribution of extreme Arctic winds and implications for ocean and sea ice processes

Abstract Some of the strongest near‐surface winds on Earth form in the Arctic and sub‐Arctic due to intense midlatitude cyclones and mesoscale processes, and these strong surface winds have important impacts on ocean and sea ice processes. We examine the climatological distribution of over‐ocean, near‐surface wind speeds within a Pan‐Arctic domain for 18 years (1990–2007) in four gridded data sets: the European Centre for Medium‐Range Weather Forecasts Interim reanalysis (ERA‐I), the Climate Forecast System Reanalysis, version 2 of the Common Ocean‐Ice Reference Experiment data set, and a regional climate simulation generated using the Weather Research and Forecasting (WRF) model run at 50 km (WRF50) horizontal resolution with ERA Interim as lateral boundary conditions. We estimate probability density functions, the annual cycle, and map the 50th and 99th percentile winds. We then perform the same statistical analysis of winds for 2 years when 10 km WRF data are available (June 2005 to May 2007); despite the much shorter time period, the Pan‐Arctic statistics are very similar to those from the 18 year analysis. We repeat the wind speed statistical analysis within a subdomain surrounding Greenland and find that WRF10 has consistently larger maximum wind speeds, but this difference only appears at wind speed percentiles higher than 99%. Differences in the 99th percentile wind speeds are spatially heterogeneous. An investigation of surface fluxes within WRF50 and WRF10 reveals unrealistically large sensible heat fluxes along the sea ice edge, and the geographic distribution and magnitude of these fluxes is shown to be sensitive to sea ice representation in WRF.

Hughes, Mimi↗
DOE OSTI2015

Scaling nitrogen and carbon interactions: what are the consequences of biological buffering?

Abstract Understanding the consequences of elevated CO 2 ( eCO 2 ; 800 ppm) on terrestrial ecosystems is a central theme in global change biology, but relatively little is known about how altered plant C and N metabolism influences higher levels of biological organization. Here, we investigate the consequences of C and N interactions by genetically modifying the N‐assimilation pathway in A rabidopsis and initiating growth chamber and mesocosm competition studies at current CO 2 ( cCO 2 ; 400 ppm) and eCO 2 over multiple generations. Using a suite of ecological, physiological, and molecular genomic tools, we show that a single‐gene mutant of a key enzyme ( nia2 ) elicited a highly orchestrated buffering response starting with a fivefold increase in the expression of a gene paralog ( nia1 ) and a 63% increase in the expression of gene network module enriched for N‐assimilation genes. The genetic perturbation reduced amino acids, protein, and TCA ‐cycle intermediate concentrations in the nia2 mutant compared to the wild‐type, while eCO 2 mainly increased carbohydrate concentrations. The mutant had reduced net photosynthetic rates due to a 27% decrease in carboxylation capacity and an 18% decrease in electron transport rates. The expression of these buffering mechanisms resulted in a penalty that negatively correlated with fitness and population dynamics yet showed only minor alterations in our estimates of population function, including total per unit area biomass, ground cover, and leaf area index. This study provides insight into the consequences of buffering mechanisms that occur post‐genetic perturbations in the N pathway and the associated outcomes these buffering systems have on plant populations relative to eCO 2 .

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Probabilistic learning and updating of a digital twin for composite material systems

This paper presents an approach for characterizing and estimating statistical dependence between a large number of observables in a composite material system. Conditional regression is carried out using the estimated joint density function, permitting a systematic exploration of interdependence between fine scale and coarse observables that can be used for both prognosis and design of complex material systems. An example demonstrates the integration of experimental data with a computational database. The statistical approach is based on the probabilistic learning on manifolds recently developed by the authors. This approach leverages intrinsic structure detected through diffusion on graphs with projected stochastic differential equations to generate samples constrained to that structure.

42 ENGINEERING↗
DOE OSTI2020

Error-mitigated data-driven circuit learning on noisy quantum hardware

Application-level benchmarks measure how well a quantum device performs meaningful calculations. In the case of parameterized circuit training, the computational task is the preparation of a target quantum state via optimization over a loss landscape. This is complicated by various sources of noise, fixed hardware connectivity, and generative modeling, the choice of target distribution. Gradient-based training has become a useful benchmarking task for noisy intermediate-scale quantum computers because of the additional requirement that the optimization step uses the quantum device to estimate the loss function gradient. In this work, we use gradient-based data-driven circuit learning to qualitatively evaluate the performance of several superconducting platform devices and present results that show how error mitigation can improve the training of quantum circuit Born machines with 28 tunable parameters.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Elucidating the temperature dependence of TRIP in Q&P steels using synchrotron X-Ray diffraction, constituent phase properties, and strain-based kinetics models

Understanding the deformation-induced martensitic transformation (DIMT) is critical for interpreting the structure-property relationships that govern the performance of transformation-induced plasticity (TRIP) assisted steels. However, modern TRIP-assisted steels often exhibit DIMT kinetics that are not easily captured by existing empirical models based on bulk tensile strain. We address this challenge by combined bulk uniaxial tensile tests and in-situ high energy synchrotron X-ray diffraction, which resolved the phase volume fractions, stress-strain response, and microstructure evolution of each constituent phase. A modification of the Olson-Cohen model is implemented, which describes the martensitic transformation kinetics as a function of the estimated partitioned strain in austenite, rather than the bulk tensile strain. This DIMT kinetic model is used as a framework to clarify the root cause of an insufficiently understood toughness trough reported for TRIP-assisted steels during deformation at elevated temperatures. Here, the importance of the temperature-dependent toughness is discussed, based on the opportunity to modify deformation processes to tailor the DIMT kinetics and mechanical properties during forming and in service.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Passive NO x adsorption on Pd/H-ZSM-5: Experiments and modeling

A combined experimental and modeling study of the passive NO x adsorber (PNA) is presented that advances the understanding and prediction of the effects of various operating parameters and material properties of H-ZSM-5 and Pd/H-ZSM-5. Experiments reveal the NO x uptake process to be kinetically limited. Two microkinetic schemes are developed to explain the NO x uptake and release and NO 2 generation data. Both schemes are incorporated into a 1+1 D monolith model to predict and validate NO x uptake and temperature programmed desorption (TPD) data. Scheme I involves Z – [PdOH] + , Z – Pd 2+ Z – and Z – Pd + with Z – Pd + as the strongest NO binding site. Scheme II involves reduction of PdO 2 to PdO and nitrate formation. Model tuning utilizes a combination of infrared spectroscopy measurements and density functional theory (DFT) estimates of energy barriers. Lastly, the model is validated at different conditions including feed parameters and Pd loading.

42 ENGINEERING↗
DOE OSTI2019

Flow regimes and storage efficiency of CO 2 injected into depleted shale reservoirs

Depleted shale reservoirs are potentially attractive targets to store carbon dioxide (CO 2 ) as free and adsorbed phases. The time-dependent efficiency factors that depict dynamic storage performance in shale are estimated as a function of key reservoir parameters, shapes of stimulated reservoir volume, and injection scenarios. Efficiency of CO 2 storage and flow regimes are determined dynamically as CO 2 is injected in a depleted shale formation for a time period of 60 years. The most effective reservoir utilization for carbon storage was achieved during the transition from predominant flow in the stimulated reservoir volume to flow into unfractured zones. That transition occurs within first 15–30 years of injection depending on cases considered. The importance of adsorption as a mechanism of storage is determined based on sensitivity, which indicates that the amount of CO 2 stored by adsorption would be on average ~26% of the CO 2 stored as a free phase.

03 NATURAL GAS↗
DOE OSTI2020

Estimation of distributions via multilevel Monte Carlo with stratified sampling

We design and implement a novel algorithm for computing a multilevel Monte Carlo (MLMC) estimator of the joint cumulative distribution function (CDF) of a vector-valued quantity of interest in problems with random input parameters and initial conditions. Our approach combines MLMC with stratified sampling of the input sample space by replacing standard Monte Carlo at each level with stratified Monte Carlo initialized with proportionally allocated samples. We show that the resulting stratified MLMC (sMLMC) algorithm is more efficient than its standard MLMC counterpart due to the additional variance reduction provided by the stratification of the random parameter's domain, especially at the coarsest levels. Additional computational cost savings are obtained by smoothing the indicator function with a Gaussian kernel, which proves to be an efficient and robust alternative to recently developed polynomial-based techniques.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2019

Extending the dynamic range of electronics in a Time Projection Chamber

When Time Projection Chambers (TPCs) are used in low to intermediate heavy ion collisions, the mass and momentum range of the emitted particles cover a wide range in energy losses. Many TPC readout electronics currently only have a single gain output with a fixed dynamic range. In a recent set of experiments using the SAMURAI Pion-Reconstruction and Ion-Tracker (StrRIT) TPC, it was important to simultaneously measure relativistic pions and heavy ion tracks from the same collisions. As the ionization from a track's energy loss is collected and multiplied by the anode wires, a distribution of image charges is induced on the TPC read-out pads. If the avalanche on a wire is large enough, the charge collected by pads directly underneath will saturate the readout electronics; pads farther away in the distribution will not be saturated. Using these unsaturated pads and the known pad distribution function, we can estimate the charge on saturated pads, increasing the dynamic range by a factor of 5.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
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 OSTI2020

The many-body expansion for aqueous systems revisited: 1. Water-water interactions

We revisit the Many-Body Expansion (MBE) for water-water interactions by examining the effects of the basis set, including those resulting from the Basis Set Superposition Error (BSSE) correction, on the various terms for selected sizes of water clusters up to n = 21. The analysis is performed at the second order Møller-Plesset (MP2) perturbation theory with the family of augmented correlation consistent basis sets up to five zeta quality for the (H2O)n, n = 7, 10, 13, 16 and 21 clusters, for which we report either the complete MBE (n = 7, 10) or the one through the 6-body (n = 13) and the 5-body terms (n = 16, 21). Our results suggest that any sizeable contributions to the total cluster binding energy arising from the 5-body and larger terms are solely an artifact of the size of the basis set. Indeed, all terms above the 4-body converge monotonically to practically zero at the Complete Basis Set (CBS) limit. The magnitudes of the 5-body and above terms are accurately reproduced even with the smaller basis set of the series (aug-cc-pVDZ) once the BSSE correction is taken into account. The same level of theory (MP2/aug-cc-pVDZ, BSSEcorrected) also accurately reproduces the MP2/CBS values of the 3- and 4-body terms. The contribution of electron correlation to the 3- and 4-body terms is quite small, so that neglecting the correlation contribution in all terms above the 3-body results in an error of ??(0.1%). The BSSE correction to the largest 2-body term in the MBE was accurately estimated from the function ?? [1 + erf(-?? ??)], which is proportional to the common (overlapping) area between two Gaussian distributions whose centers are separated by R, with the constants ??, ?? fitted to the calculated BSSE corrections for the individual 2-body terms of the clusters with each basis set. Our results unquestionably demonstrate that the MBE for water-water interactions converges to the 4-body term, since any finite terms above the 4-body are artifacts of the size of the basis set and can be safely truncated at the 4-body term when either a very large basis set is used or BSSE corrections are taken into account even with the aug-cc-pVDZ basis set. We expect these findings to have important consequences in the pursuit of accurate many-body molecular dynamics simulations for aqueous systems.

Heindel, Joseph↗
DOE OSTI2015

The melting temperature of liquid water with the effective fragment potential

Direct simulation of the solid-liquid water interface with the effective fragment potential (EFP) via the constant enthalpy and pressure (NPH) ensemble was used to estimate the melting temperature (Tm) of ice-Ih. Initial configurations and velocities, taken from equilibrated constant pressure and temperature (NPT) simulations at T = 300 K, 350 K and 400 K, respectively, yielded corresponding Tm values of 378±16 K, 382±14 K and 384±15 K. These estimates are consistently higher than experiment, albeit to the same degree with previously reported estimates using density functional theory (DFT)-based Born-Oppenheimer simulations with the Becke-Lee-Yang-Parr functional plus dispersion corrections (BLYP-D). KRB was supported by a Computational Science Graduate Fellowship from the Department of Energy. MSG was supported by a U.S. National Science Foundation Software Infrastructure (SI2) grant (ACI – 1047772). SSX acknowledges support from the US Department of Energy, Office of Science, Office of Basic Energy Sciences, Division of Chemical Sciences, Geosciences and Biosciences. Pacific Northwest National Laboratory (PNNL) is a multiprogram national laboratory operated for DOE by Battelle.

Brorsen, Kurt R.↗