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Results for “density estimation”

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 703 records · Page 39
All sourcesNASA NTRSDOE OSTI
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 OSTI2016

On the applicability of surrogate-based Markov chain Monte Carlo-Bayesian inversion to the Community Land Model: Case studies at flux tower sites: SURROGATE-BASED MCMC FOR CLM

The Community Land Model (CLM) has been widely used in climate and Earth system modeling. Accurate estimation of model parameters is needed for reliable model simulations and predictions under current and future conditions, respectively. In our previous work, a subset of hydrological parameters has been identified to have significant impact on surface energy fluxes at selected flux tower sites based on parameter screening and sensitivity analysis, which indicate that the parameters could potentially be estimated from surface flux observations at the towers. To date, such estimates do not exist. In this paper, we assess the feasibility of applying a Bayesian model calibration technique to estimate CLM parameters at selected flux tower sites under various site conditions. The parameters are estimated as a joint probability density function (PDF) that provides estimates of uncertainty of the parameters being inverted, conditional on climatologically-average latent heat fluxes derived from observations. We find that the simulated mean latent heat fluxes from CLM using the calibrated parameters are generally improved at all sites when compared to those obtained with CLM simulations using default parameter sets. Further, our calibration method also results in credibility bounds around the simulated mean fluxes which bracket the measured data. The modes (or maximum a posteriori values) and 95% credibility intervals of the site-specific posterior PDFs are tabulated as suggested parameter values for each site. Analysis of relationships between the posterior PDFs and site conditions suggests that the parameter values are likely correlated with the plant functional type, which needs to be confirmed in future studies by extending the approach to more sites.

Huang, Maoyi↗
DOE OSTI2016

Uncertainty quantification in LES of channel flow

Here, in this paper, we present a Bayesian framework for estimating joint densities for large eddy simulation (LES) sub-grid scale model parameters based on canonical forced isotropic turbulence direct numerical simulation (DNS) data. The framework accounts for noise in the independent variables, and we present alternative formulations for accounting for discrepancies between model and data. To generate probability densities for flow characteristics, posterior densities for sub-grid scale model parameters are propagated forward through LES of channel flow and compared with DNS data. Synthesis of the calibration and prediction results demonstrates that model parameters have an explicit filter width dependence and are highly correlated. Discrepancies between DNS and calibrated LES results point to additional model form inadequacies that need to be accounted for.

97 MATHEMATICS AND COMPUTING↗
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 OSTI2023

Uncovering acoustic signatures of pore formation in laser powder bed fusion

Abstract We present a machine learning workflow to discover signatures in acoustic measurements that can be utilized to create a low-dimensional model to accurately predict the location of keyhole pores formed during additive manufacturing processes. Acoustic measurements were sampled at 100 kHz during single-layer laser powder bed fusion (LPBF) experiments, and spatio-temporal registration of pore locations was obtained from post-build radiography. Power spectral density (PSD) estimates of the acoustic data were then decomposed using non-negative matrix factorization with custom $$\varvec{k}$$ k -means clustering (NMF $$\varvec{k}$$ k ) to learn the underlying spectral patterns associated with pore formation. NMF $$\varvec{k}$$ k returned a library of basis signals and matching coefficients to blindly construct a feature space based on the PSD estimates in an optimized fashion. Moreover, the NMF $$\varvec{k}$$ k decomposition led to the development of computationally inexpensive machine learning models which are capable of quickly and accurately identifying pore formation with classification accuracy of supervised and unsupervised label learning greater than 95% and 90%, respectively. The intrinsic data compression of NMF k , the relatively light computational cost of the machine learning workflow, and the high classification accuracy makes the proposed workflow an attractive candidate for edge computing toward in-situ keyhole pore prediction in LPBF.

36 MATERIALS SCIENCE↗
DOE OSTI2026

A Multi-Region SEIR Model Incorporating Inter-County Mobility and Time-Dependent Transmission Dynamics: Application to COVID-19 Disease Outbreak Data in North Carolina.

Classical infectious disease compartmental models typically do not incorporate spatial heterogeneity or mobility. We develop a multi-region susceptible-exposed-infected-recovered (SEIR) model in which disease dynamics are coupled via inter-region mobility and the transmission rate is both region and time dependent. We calibrate the model using rolling averages of daily COVID-19 data in all 100 North Carolina counties. Mobility parameters are prescribed using daily inter-county commuter data. The number of transmission rate parameters is substantially reduced by hypothesizing that the dynamics correlate with county-level population density. Parameter estimation is carried out using several objective functions with error terms at different scales. An additive combination of least squares error at the county-level and the state-level, along with a quadratic transmission rate polynomial, yields the lowest overall error at both spatial scales. The calibrated model is used to simulate regional effects of perturbing disease transmission rates in adjacent counties and to illustrate effects of the state’s mobility infrastructure on disease dynamics and spread for a new disease outbreak.

COVID-19 modeling↗
DOE OSTI2022

Thermal diffusivity recovery and defect annealing kinetics of self-ion implanted tungsten probed by insitu transient grating spectroscopy

Tungsten is a promising candidate material for plasma-facing armour components in future fusion reactors. A key concern is irradiation-induced degradation of its normally excellent thermal transport properties. In this comprehensive study, thermal diffusivity degradation in ion-implanted tungsten and its evolution from room temperature (RT) to 1073 K is considered. Five samples were exposed to 20 MeV self-ions at RT to achieve damage levels ranging from 3.2 x 10 -4 to 3.2 displacements per atom (dpa). Transient grating spectroscopy with in-situ heating was then used to study thermal diffusivity evolution as a function of temperature. Using a kinetic theory model, an equivalent point defect density is estimated from the measured thermal diffusivity. The results showed a prominent recovery of thermal diffusivity between 450 K and 650 K, which coincides with the onset of mono-vacancy mobility. After 1073 K annealing samples with initial damage of 3.2 x 10 -3 dpa or less recover close to the pristine value of thermal diffusivity. For doses of 3.2 x 10 -2 dpa or higher, on the other hand, a residual reduction in thermal diffusivity remains even after 1073 K annealing. Transmission electron microscopy reveals that this is associated with extended, irradiation-induced dislocation structures that are retained after annealing. A sensitivity analysis shows that thermal diffusivity provides an efficient tool for the assessing total defect content in tungsten up to 1000 K.

36 MATERIALS SCIENCE↗
DOE OSTI2024

On the measurement of shape: With applications to lunar regolith

With the renewed commitment from NASA and other commercial entities for a presence on the Moon, the importance of understanding the characteristics of lunar regolith and how to utilize it have become the target of increasing scrutiny. Much of what is known about lunar regolith was collected during and immediately after the Apollo program, however, analytical techniques and instrumentation have advanced in leaps and bounds in the subsequent decades. Specifically, dynamic image analysis systems have advanced to the point that millions of particles can have morphological characteristics automatically determined in relatively short time frames. Particle morphological data was collected on several lunar samples and a pair of widely used regolith simulants to ascertain the accuracy of these simulants and to explore statistical analysis methods of these large datasets. It is found that these morphology datasets can vary widely depending on the particle size of the particles, and simple averaging of the data skews the results heavily towards the numerically abundant size ranges, the fines. Different reporting methods are suggested to ameliorate these problems. When applied to the lunar regolith, the particles are noted to be less morphologically complex than initially suspected. Compared to the lunar material, the simulants are found to contain some more morphological variability and angular grains. Such difference is likely due to the wildly different comminution processes that these different powder systems are subjected to.

2D shape↗
DOE OSTI2025

Electrochemical recovery of Gd into liquid Bi in molten LiCl-KCl-GdCl 3

The electrochemical recovery of Gd into liquid Bi electrodes was investigated in molten LiCl-KCl-GdCl 3 electrolyte at 773–973 K using constant currents of 10–150 mA cm −2 . High round-trip coulombic efficiency (>97 %) was demonstrated for deposition and removal of Gd into and from liquid Bi at all temperatures, confirming chemically reversible electrode reactions towards high recovery yield of Gd using liquid Bi. Furthermore, the overpotential associated with deposition of Gd into the liquid Bi electrode gradually increased with current density and decreased with temperature. At the lowest temperature of 773 K, a steep increase in overpotential was evident at high current densities due to slower mass transport and low solubility of Gd in liquid Bi (0.5 at.% Gd). Based on the impedance spectra of Bi electrodes at 773–973 K, the exchange current density was estimated to be 110–220 mA cm −2 , indicating facile charge transfer at the liquid electrode-electrolyte interface. Post-mortem characterization of Bi cathodes after electrolysis at 873 K indicated the formation of a solid GdBi(s) compound layer at the Bi electrode surface. Chemical analysis of Bi cathodes at various deposited Gd compositions resulted in Faradaic efficiencies of ∼75–84 %, promising a high recovery yield of Gd from molten salts using a strongly-interacting liquid Bi electrode.

36 - MATERIALS SCIENCE↗
DOE OSTI2018

Evaluation system and web infrastructure for the second cryo-EM model challenge

An evaluation system and a web infrastructure were developed for the second cryo-EM model challenge. The evaluation system includes tools to validate stereo-chemical plausibility of submitted models, check their fit to the corresponding density maps, estimate their overall and per-residue accuracy, and assess their similarity to reference cryo-EM or X-ray structures as well as other models submitted in this challenge. The web infrastructure provides a convenient interface for analyzing models at different levels of detail. As a result, it includes interactively sortable tables of evaluation scores for different subsets of models and different sublevels of structure organization, and a suite of visualization tools facilitating model analysis.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2018

In situ neutron diffraction in quantifying deformation behaviors of nano-sized carbide strengthened UFG ferritic steel

Here, the microstructures and mechanical properties of a low-alloy medium-carbon steel with a duplex microstructure composed of nanoscale spheroidized carbides in ultrafine-grained (UFG) ferritic steel are examined. The average grain size of the studied steel is ~ 430 nm, and these grains coexist with numerous carbides. Neutron diffraction reveals that the intensity of (011) and (022) peaks for the UFG sample is significantly enhanced, suggesting that the (011)//RD texture is a result of the warm rolling process. The lattice parameter of UFG steel is smaller than that of a martensitic steel (M steel) counterpart, indicating a lower carbon concentration in the lattice. The estimated dislocation densities for M steel and UFG steel are 2.59 × 10 14 cm –2 and 1.76 × 10 12 cm –2 , respectively. The UFG steel reveals a nearly isotropic lattice strain response under initial tension from 0 to 450 MPa, where the lattice strains of the (110), (002), and (112) planes are identical. The increase of lattice strain of the (110) plane becomes smaller than that of the (002) and (112) planes as the stress exceeds 450 MPa, suggesting that the nanosized carbides contribute to the hardening ability by promoting the accumulation of geometrically necessary dislocations around the particles, and the (110) lattice becomes harder compared to the other two planes.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Methodology and performance comparison of statistical learning pulse shape classifiers as demonstrated with organic liquid scintillator [Performance comparison of statistical learning pulse shape classifiers]

In this study, we present novel methods for automated pulse shape discrimination. The classifiers are trained using simple radionuclide sources and do not require ground truth labeling. We test their performance using labels derived from time of flight experiments and present the results in terms of energy-dependent Receiver Operating Characteristic (ROC) curves. In addition, we also train and test standard pulse shape discrimination methods on the same data for comparison. We find multiple methods that can yield similar false neutron and true neutron rates at 24 keVee as tail-to-total or Gatti’s optimal linear filter yield at 54 keVee.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

Configuration and impurity quantification of AmLi sources using radiography and gamma spectroscopy

This paper presents the non-destructive assay of two AmLi sources used for detector characterization and active interrogation at PNNL, identified as MRC-101 and MRC-103. First, a detailed description of the internal configuration of 2724-BT encapsulated MRC sources is established. X-ray radiographs of the AmLi sources are reported for the first time to verify the dimensions and orientation of the encapsulation. Notably, a density variation was observed as a contrast change across the height of the source cavities. Contrary to commonly made assumptions in literature, it is indirectly observed that the AmLi source/target material only occupies a portion of the source cavity. The intensity of the prompt gamma-rays resulting from the inelastic scatter of alpha particles on 7Li was used to calculate the mass ratios of LiH:AmO2. The gamma-ray spectra revealed the presence of numerous impurities in both source and target material (243Am, 237Np, 154Eu, 23Na, and 9Be). Neutron-gamma production ratios were applied to the intensity of the Doppler-broadened peaks from alpha-induced reactions with 7Li, 9Be, and 23Na to calculate neutron rates for both sources. A neutron/alpha production yield (derived in this work) was then related to the atomic concentration of these isotopes to find the approximate masses within each source. Ultimately, the AmLi source density was estimated with prompt gamma analysis based on partial source volumes as 0.45±0.08 g/cm^3.

DTRA, AmLi, neutron↗
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.↗
DOE OSTI2020

A Drift‐Kinetic Method for Obtaining Gradients in Plasma Properties From Single‐Point Distribution Function Data

Abstract In this paper, we derive a new drift‐kinetic method for estimating gradients in the plasma properties through a velocity space distribution at a single point. The gradients are intrinsically related to agyrotropic features of the distribution function. This method predicts the gradients in the magnetized distribution function and can predict gradients of arbitrary moments of the gyrotropic background distribution function. The method allows for estimates on density and pressure gradients on the scale of a Larmor radius, proving to resolve smaller scales than any method currently available to spacecraft. The model is verified with a set of fully kinetic VPIC particle‐in‐cell simulations.

Wetherton, B. A.↗
DOE OSTI2026

Quantum-classical embedding via ghost Gutzwiller approximation for enhanced simulations of correlated electron systems

Simulating correlated materials on present-day quantum hardware remains challenging due to limited quantum resources. Quantum embedding methods offer a promising route by reducing computational complexity through the mapping of bulk systems onto effective impurity models, allowing more feasible simulations on pre- and early-fault-tolerant quantum devices. Here, this work develops a quantum-classical embedding framework based on the ghost Gutzwiller approximation to enable quantum-enhanced simulations of ground-state properties and spectral functions of correlated electron systems. Circuit complexity is analyzed using an adaptive variational quantum algorithm on a statevector simulator, applied to the infinite-dimensional Hubbard model with increasing ghost mode numbers from 3 to 5, resulting in circuit depths growing from 16 to 104. Noise effects are examined using a realistic error model, revealing significant impact on the spectral weight of the Hubbard bands. To mitigate these effects, the Iceberg quantum error detection code is employed, achieving up to 40% error reduction in simulations. Finally, the accuracy of the density matrix estimation and the derived spectral function is benchmarked on IBM and Quantinuum quantum hardware, featuring distinct qubit-connectivity and employing multiple levels of error mitigation techniques.

Chen, I-Chi [Ames Laboratory (AMES), Ames, IA (Uni↗
DOE OSTI2022

Octahedral oxide glass network in ambient pressure neodymium titanate

Abstract Rare-earth titanates form very fragile liquids that can be made into glasses with useful optical properties. We investigate the atomic structure of 83TiO 2 -17Nd 2 O 3 glass using pair distribution function (PDF) analysis of X-ray and neutron diffraction with double isotope substitutions for both Ti and Nd. Six total structure factors are analyzed (5 neutron + 1 X-ray) to obtain complementary sensitivities to O and Ti/Nd scattering, and an empirical potential structure refinement (EPSR) provides a structural model consistent with the experimental measurements. Glass density is estimated as 4.72(13) g cm −3 , consistent with direct measurements. The EPSR model indicates nearest neighbor interactions for Ti-O at $$\overline{r}_{TiO}$$ r ¯ TiO = 1.984(11) Å with coordination of $$n_{TiO}$$ n TiO = 5.72(6) and for Nd-O at $$\overline{r}_{NdO}$$ r ¯ NdO = 2.598(22) Å with coordination of $$n_{NdO}$$ n NdO = 7.70(26), in reasonable agreement with neutron first order difference functions for Ti and Nd. The titanate glass network comprises a mixture of distorted Ti-O 5 and Ti-O 6 polyhedra connected via 71% corner-sharing and 23% edge-sharing. The O-Ti coordination environments include 15% nonbridging O-Ti 1 , 51% bridging O-Ti 2 , and 32% tricluster O-Ti 3 . This structure is highly unusual for oxide glasses melt-quenched at ambient pressure, as it consists of Ti-O x predominantly in octahedral (with nearly no tetrahedral) coordination.

36 MATERIALS SCIENCE↗