Search NASA⌕ Search

SEARCH · Search NASA

Results for “Distributed 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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 973 records · Page 54
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Palladized cells as suspension catalyst and electrochemical catalyst for reductively degrading aromatics contaminants: Roles of Pd size and distribution

The palladized cell (Pd-cell) could be used as an efficient catalyst in catalyzing the degradations of a wide variety of environmental contaminants. Nevertheless, when the Pd NPs associate with the bacteria, the catalytic activity likely significantly affected by the biomass. Quantitative indicators that characterize of Pd-cell are necessary and little attention has been paid to investigate how the catalytic efficiency of Pd-cell is affected by the size and distribution of Pd NPs. To fill this gap, we explored the roles of the above-mentioned key factors on the performance of Pd-cell in catalyzing the degradations of two aromatic contaminants (nitrobenzene and p-chlorophenol) in two commonly used scenarios: (1) using Pd-cell as suspended catalyst in solution and (2) using Pd-cell as electrocatalyst directly coated on electrode. In scenario (1), the relationship of exposing area to Pd particle size and distribution factors was established. Based on theoretical estimation and catalytic performance analysis, the results indicated that adjusting the exposing area to a large value (9.3 ± 0.1 × 10 5 nm 2 mg -1 Pd) was extremely effective for improving the catalytic activity of Pd-cell used as a suspension catalyst. In scenario (2), our results showed that the best electrocatalytic performances were achieved on the electrode decorated with Pd-cells with the largest NP size (54.3 ± 16.4 nm), which exerted maximum electrochemical active surface area (10.6 m 2 g -1 ) as well as favorable conductivity. The coverage of deposited Pd NPs (>95%) on the cell surface played a crucial role in boosting the conductivity of biocatalyst, thus determining the possibility of Pd-cell as an efficient electrocatalyst. The findings of this study provide a guidance for the synthesis and application of Pd-cell, which enables the design of Pd-cell to be suitable for different catalysis systems with high catalytic performance.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Quantification of Shallow Defect Suppression in Aminosilane-Passivated Lead Halide Perovskites via Optical and Electrochemical Methods

We combine fluence-dependent photoluminescence (PL) and electrochemical characterization to estimate defect-dependent trapping rates, energetic distributions, and densities of defects, in lead halide perovskite films Cs 0.1 FA 0.9 PbI 3 and Cs 0.17 FA 0.83 Pb­(I 0.75 Br 0.25 ) 3 , before and after trap passivation with vapor-deposited (3-aminopropyl)­trimethoxysilane (APTMS). For both compositions, the PL studies show that energetically shallow subgap near-valence defect densities lead to bimolecular nonradiative recombination which is reduced by 92% after APTMS treatment. Electrochemical characterization of these same active layers shows for the first time that APTMS passivation impacts mainly on near-valence (mobile anionic) defects that decrease in density by 4 orders of magnitude, from 10 18 cm –3 to 10 14 cm –3 , as a result of silane modification. Here, the combination of PL and electrochemical characterization promises a unique approach to speciation and quantification of a broader distribution of trap states in perovskites and provides straightforward assessments of the efficacy of defect mitigation strategies.

Defects↗
DOE OSTI2021

Computational Framework for Machine-Learning-Enabled 13 C Fluxomics

13 C metabolic flux analysis (MFA) has emerged as a powerful tool for synthetic biology. This optimization-based approach suffers long computation time and unstable solutions depending on the initial guess. Here, we develop a machine-learning-based framework for 13 C fluxomics. Specifically, training and test data sets are generated by metabolic network decomposition and flux sampling, in which flux ratios at metabolic nodes and simulated labeling patterns of metabolites are used as training targets and features, respectively. To improve prediction accuracy and simplify the model, automated processes are developed for flux ratio selection based on solvability and feature screening based on importance. We found that predictive performance can be significantly improved using both amino acids and central carbon metabolites in comparison with amino acids alone. Together with measured external fluxes, the predicted flux ratios determine the mass balance system, yielding global flux distributions. This approach is validated by flux estimation using both simulated and experimental data in comparison with canonical 13 C MFA. The approach represents a reliable fluxomics method readily applicable to high-throughput metabolic phenotyping, which highlights the advances of intelligent learning algorithms in synthetic biology, specifically in the Test and Learn stage of the Design-Build-Test-Learn cycle.

13C metabolic flux analysis↗
DOE OSTI2023

A Decision-Relevant Factor-Fixing Framework: Application to Uncertainty Analysis of a High-Dimensional Water Quality Model

Factor Fixing (FF) is a common method for reducing the number of model parameters to lower computational cost. FF typically starts with distinguishing the insensitive parameters from the sensitive and pursues uncertainty quantification (UQ) on the resulting reduced-order model, fixing each insensitive parameter at a fixed value. There is a need, however, to expand such a common approach to consider the effects of decision choices in the FF-UQ procedure on metrics of interest. Therefore, to guide the use of FF and increase confidence in the resulting dimension-reduced model, we propose a new adaptive framework consisting of four principles: (a) re-parameterize the model first to reduce obvious non-identifiable parameter combinations, (b) focus on decision relevance especially with respect to errors in quantities of interest (QoI), (c) conduct adaptive evaluation and robustness assessment of errors in the QoI across FF choices as sample size increases, and (d) reconsider whether fixing is warranted. The framework is demonstrated on a spatially-distributed water quality model. The error in estimates of QoI caused by FF can be estimated using a Polynomial Chaos Expansion (PCE) surrogate model. Built with 70 model runs, the surrogate is computationally inexpensive to evaluate and can provide global sensitivity indices for free. For the selected catchment, just two factors may provide an acceptably accurate estimate of model uncertainty in the average annual load of Total Suspended Solids (TSS), suggesting that reducing the uncertainty in these two parameters is a priority for future work before undertaking further formal uncertainty quantification.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Compositional heterogeneity in Cs y FA 1- y Pb(Br x I 1- x ) 3 perovskite films and its impact on phase behavior

Hybrid organic inorganic lead halide perovskite semiconductors of the form Cs y FA 1-y Pb(Br x I 1-x ) 3 are promising candidate materials for high-efficiency photovoltaics. Notably, cation and anion substitution can be used to tune the band gaps to optimize performance and improve stability. However, multi-component materials can be prone to compositional and structural inhomogeneity and the extent, length scale and impact of this heterogeneity on lead halide perovskite properties are not well understood. Here we use synchrotron X-ray diffraction to probe the evolution of crystal structure across the tetragonal-to-cubic phase transition for a series of Cs y FA 1-y Pb(Br x I 1-x ) 3 thin films with x = 0.05 to 0.3 and y = 0.17 to 0.40. We find that the transition occurs across a broad temperature range of approximately 40 °C, much larger than for pure compounds such as MAPbI 3 and MAPbBr 3 . Finally, we hypothesize that this smearing of the phase transition is due to compositional inhomogeneities that give rise to a distribution of local transition temperatures and we estimate the composition varies by about 10% to 15% with likely greater heterogeneity for the halide anion than the cation. This approach of mapping the transition is a simple and effective method of assessing heterogeneity, enabling evaluation of its impact.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Changes in site-specific shape resonances in nitrogen K-shell photoionization of N 2 O induced by vibrational excitation

The central (Nc) and terminal (Nt) nitrogen K-shell photoelectron spectra (PESs) of N 2 O molecules have been measured in the σ shape resonance energy region at temperatures of ~300 and ~630 K. Estimating vibrational populations based on the Boltzmann distribution at these temperatures, PESs of vibrationally ground and bending-excited levels in the initial electronic ground state were extracted. Vibrationally integrated partial cross sections and asymmetry parameters for ionization from vibrationally ground and bending-excited levels were obtained as a function of the incident photon energy by integrating PESs over the vibrational levels of the core-hole states. In N c photoionization, the shape resonance from the bending-excited level was found to be shifted to the lower photon energy side and to become narrower than that from the ground vibrational level. In N t photoionization from the bending-excited level, the downward shift of the resonance is more significant than that in N c ionization. These experimental findings are qualitatively consistent with theoretical predictions and suggest that the shape resonance associated with the N t core hole is more sensitive to the bending angle of the initial state than is the shape resonance associated with the N c core hole. Finally, the asymmetry parameters for photoionization from the bending-excited level, however, showed almost the same behavior as those from the ground vibrational level for both K-shell photoionization channels and in the photon energy range studied here.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2019

A biokinetic model for trivalent or hexavalent chromium in adult humans

Chromium exists in several oxidation states, with the trivalent state (Cr(III)) being the dominant naturally occurring form. Chromium in other oxidation states tends to be converted to the trivalent oxide in the natural environment and in biological systems. Chromium(III) has been shown to be an essential nutrient for humans and several non-human species. Chromium(VI), the second most stable form of chromium, is an important environmental contaminant that is mostly of industrial origin and is associated with lung cancer and nose tumours in chromium workers. This paper proposes a biokinetic model for chromium that addresses the distinctive behaviours of Cr(III) and Cr(VI) following uptake to blood of an adult human. Additionally, the model is based on biokinetic data derived from relatively short-term studies involving administration of chromium tracers to adult human subjects or laboratory animals, supplemented with data on the long-term distribution of chromium in adult humans as estimated from autopsy measurements. The model is part of a comprehensive update of biokinetic models of the International Commission on Radiological Protection, used to project or evaluate radiation doses from occupational intake of radionuclides.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2024

Emergency department visits in California associated with wildfire PM 2.5 : differing risk across individuals and communities

The threats to human health from wildfires and wildfire smoke (WFS) in the United States (US) are increasing due to continued climate change. A growing body of literature has documented important adverse health effects of WFS exposure, but there is insufficient evidence regarding how risk related to WFS exposure varies across individual or community level characteristics. To address this evidence gap, we utilized a large nationwide database of healthcare utilization claims for emergency department (ED) visits in California across multiple wildfire seasons (May through November, 2012–2019) and quantified the health impacts of fine particulate matter <2.5 μm (PM 2.5 ) air pollution attributable to WFS, overall and among subgroups of the population. We aggregated daily counts of ED visits to the level of the Zip Code Tabulation Area (ZCTA) and used a time-stratified case-crossover design and distributed lag non-linear models to estimate the association between WFS and relative risk of ED visits. We further assessed how the association with WFS varied across subgroups defined by age, race, social vulnerability, and residential air conditioning (AC) prevalence. Over a 7 day period, PM 2.5 from WFS was associated with elevated risk of ED visits for all causes (1.04% (0.32%, 1.71%)), non-accidental causes (2.93% (2.16%, 3.70%)), and respiratory disease (15.17% (12.86%, 17.52%)), but not with ED visits for cardiovascular diseases (1.06% (–1.88%, 4.08%)). Analysis across subgroups revealed potential differences in susceptibility by age, race, and AC prevalence, but not across subgroups defined by ZCTA-level Social Vulnerability Index scores. These results suggest that PM 2.5 from WFS is associated with higher rates of all cause, non-accidental, and respiratory ED visits with important heterogeneity across certain subgroups. Notably, lower availability of residential AC was associated with higher health risks related to wildfire activity.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

3-D decoupled inversion of complex conductivity data in the real number domain

Complex conductivity inversion, aslo called spectral induced polarization inversion, involves estimating the frequency dependent complex electrical conductivity distribution of the subsurface. The superior diagnostic capabilities provided by complex conductivity spectra have driven advancements in mechanistic understanding of complex conductivity as well as modelling and inversion appraoches over the past several decades. In this work, we demonstrate the theory and application for an approach to three-dimensional modeling and inversion of complex conductivity data in the real number domain. Beginning from first principles, we demonstrate how the equations for the real and imaginary components of the complex potential may be decoupled. This leads to a description of the real and imaginary source current terms, and a corresponding assessment of error arising from an assumption necessary complete the decoupled modeling. We show that for most earth materials, which exhibit relatively small phases (e.g. less than 0.2 radians) in complex conductivity, these errors become insignificant. For higher phase materials, the errors may be quantified and corrected through an iterative procedure. We demonstrate the accuracy of numerical forward solutions by direct comparison to corresponding analytic solutions. We demonstrate the inversion using both synthetic and field examples with data collected over a waste infiltration trench, at frequencies ranging from 0.5 to 7.5 Hz. In addition to insight provided by the decoupled equations, we see three primary advantages of the decoupled inversion in comparison to fully coupled inversion in complex number domain. First, memory requirements are reduced by a factor of two because it is unnecessary to simultaneously store both the real and complex components and associated Jacobian matrices. Second, data noise is specified separately for the real and imaginary components of potential (or magnitude and phase), which removes the ambiguity in data misfit residuals that exists in the complex number domain, thereby enabling the inversion to appropriately fit the data. Final, except for the source current terms, the modeling and inversion algorithms are equivalent to the direct current electrical resistivity tomography counterpart. In conclusion, this enables direct application of advancements and approaches developed originally for electrical resistivity tomography.

58 GEOSCIENCES↗
DOE OSTI2020

The Completed SDSS-IV extended Baryon Oscillation Spectroscopic Survey: Large-scale structure catalogues for cosmological analysis

ABSTRACT We present large-scale structure catalogues from the completed extended Baryon Oscillation Spectroscopic Survey (eBOSS). Derived from Sloan Digital Sky Survey (SDSS) IV Data Release 16 (DR16), these catalogues provide the data samples, corrected for observational systematics, and random positions sampling the survey selection function. Combined, they allow large-scale clustering measurements suitable for testing cosmological models. We describe the methods used to create these catalogues for the eBOSS DR16 Luminous Red Galaxy (LRG) and Quasar samples. The quasar catalogue contains 343 708 redshifts with 0.8 < z < 2.2 over 4808 deg2. We combine 174 816 eBOSS LRG redshifts over 4242 deg2 in the redshift interval 0.6 < z < 1.0 with SDSS-III BOSS LRGs in the same redshift range to produce a combined sample of 377 458 galaxy redshifts distributed over 9493 deg2. Improved algorithms for estimating redshifts allow that 98 per cent of LRG observations result in a successful redshift, with less than one per cent catastrophic failures (Δz > 1000 km s−1). For quasars, these rates are 95 and 2 per cent (with Δz > 3000 km s−1). We apply corrections for trends between the number densities of our samples and the properties of the imaging and spectroscopic data. For example, the quasar catalogue obtains a χ2/DoF = 776/10 for a null test against imaging depth before corrections and a χ2/DoF= 6/8 after. The catalogues, combined with careful consideration of the details of their construction found here-in, allow companion papers to present cosmological results with negligible impact from observational systematic uncertainties.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

Reconstructing small-scale lenses from the cosmic microwave background temperature fluctuations

Cosmic microwave background (CMB) lensing is a powerful probe of the matter distribution in the Universe. The standard quadratic estimator, which is typically used to measure the lensing signal, is known to be suboptimal for low-noise polarization data from next-generation experiments. In this paper, we explain why the quadratic estimator will also be suboptimal for measuring lensing on very small scales, even for measurements in temperature where this estimator typically performs well. Though maximum likelihood methods could be implemented to improve performance, we explore a much simpler solution, revisiting a previously proposed method to measure lensing that involves a direct inversion of the background gradient. An important application of this simple formalism is the measurement of cluster masses with CMB lensing. We find that directly applying a gradient inversion matched filter to simulated lensed images of the CMB can tighten constraints on cluster masses compared to the quadratic estimator. While the difference is not relevant for existing surveys, for future surveys it can translate to significant improvements in mass calibration for distant clusters, where galaxy lensing calibration is ineffective due to the lack of enough resolved background galaxies. Improvements can be as large as ~50 per cent for a cluster at z = 2 and a next-generation CMB experiment with 1 μK arcmin noise, and over an order of magnitude for lower noise levels. For future surveys, this simple matched filter or gradient inversion method approaches the performance of maximum likelihood methods, at a fraction of the computational cost.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

Constraints for stellar electron-capture rates on 86 Kr via the 86 Kr(t, 3 He +γ) 86 Br reaction and the implications for core-collapse supernovae

Background: In the late stages of stellar core collapse just prior to core bounce, electron captures on medium-heavy nuclei drive deleptonization. Therefore, simulations require the use of accurate reaction rates. Nuclei with neutron number near N=50 above atomic number Z=28 play an important role. Rates presently used in astrophysical simulations rely primarily on a relatively simple single-state approximation. In order to improve the accuracy of the astrophysical simulations, experimental data are needed to test the electron-capture rates and to guide the development of better theoretical models and astrophysical simulations. Purpose: The purpose of the present work was to measure the Gamow-Teller transition strength from 86 Kr to 86 Br, to derive the stellar electron-capture rates based on the extracted strengths, and to compare the derived rates with rates based on shell-model and quasiparticle random-phase approximation (QRPA) Gamow-Teller strengths calculations, as well as the single-state approximation. An additional purpose was to test the impact of using improved electron-capture rates on the late evolution of core-collapse supernovae. Method: The Gamow-Teller strengths from 86 Kr were extracted from the 86 Kr(t, 3 He +γ) charge-exchange reaction at 115MeV/u. The electron-capture rates were calculated as a function of stellar density and temperature. Besides the case of 86 Kr, the electron-capture rates based on the QRPA calculations were calculated for 78 additional isotopes near N=50 above Z=28. The impact of using these rates instead of those based on the single-state approximation is studied in a spherically symmetrical simulation of core collapse just prior to bounce. Results: The derived electron-capture rates on 86 Kr from the experimental Gamow-Teller strength distribution are much smaller than the rates estimated based on the single-state approximation. Rates based on Gamow-Teller strengths estimated in shell-model and QRPA calculations are more accurate. The core-collapse supernova simulation with electron-capture rates based on the QRPA calculations indicate a significant reduction in the deleptonization during the collapse phase. Conclusions: It is important to utilize microscopic theoretical models that are tested by experimental data to constrain and estimate Gamow-Teller strengths and derived electron-capture rates for nuclei near N=50 that are inputs for astrophysical simulations of core-collapse supernovae and their multimessenger signals, such as the emission of neutrinos and gravitational waves.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

Nucleon transverse momentum-dependent parton distributions in lattice QCD: Renormalization patterns and discretization effects

Lattice QCD calculations of transverse momentum-dependent parton distribution functions (TMDs) in nucleons are presented in this paper, based on the evaluation of nucleon matrix elements of quark bilocal operators with a staple-shaped gauge connection. Both time-reversal odd effects, namely, the generalized Sivers and Boer-Mulders transverse momentum shifts, as well as time-reversal even effects, namely, the generalized transversity and one of the generalized worm-gear shifts, are studied. Results are obtained on two different n f = 2 + 1 flavor ensembles with approximately matching pion masses but very different discretization schemes: domain-wall fermions (DWF) with lattice spacing a = 0.084 fm and pion mass 297 MeV, and Wilson-clover fermions with a = 0.114 fm and pion mass 317 MeV. Comparison of the results on the two ensembles yields insight into the length scales at which lattice discretization errors are small, and into the extent to which the renormalization pattern obeyed by the continuum QCD TMD operator continues to apply in the lattice formulation. For the studied TMD observables, the results are found to be consistent between the two ensembles at sufficiently large separation of the quark fields within the operator, whereas deviations are observed in the local limit and in the case of a straight link gauge connection, which is relevant to the studies of parton distribution functions. Finally and furthermore, the lattice estimates of the generalized Sivers shift obtained here are confronted with, and are seen to tend towards, a phenomenological estimate extracted from experimental data.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

Comparison of Load Models for Estimating Electrical Efficiency in DC Microgrids: Preprint

This paper compares several electrical load models for estimating the efficiency of DC vs. AC distribution in microgrids. Candidate models include energy balance, harmonic power flow, and time-domain modeling. Model results are compared with numerical studies and validated with experimental measurements. Based on quantitative and qualitative considerations, the most appropriate load modeling approach for larger-scale DC distribution efficiency studies is proposed.

DC distribution↗
DOE OSTI2019

Chemical Composition Analysis for X-Ray Transport Container Scans

It is important for national security to control the movement of dangerous or strategically cargo such as explosives, radioactive materials, rare and precious metals. This control can be provided by scanning transport containers by gamma rays. In this report the existing technique for scanning (dual energy method) is considered and the alternative method based on measuring the energy distribution of gamma rays is proposed. For estimation perspectives of the proposing method, the corresponding simulation was conducted by using the GEANT4 toolkit. The example of the algorithm of reconstruction the chemical composition of the scanned object is also considered. In addition the experiment for estimation energy resolution of the detector based on a scintillation crystal BGO and SiPM was carried out.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

Comparative analysis of energy deposition modes available in Serpent 2 within the framework of the supercritical water reactor - Fuel qualification test reactor physics benchmark

A joint European Canadian Chinese development of a supercritical water-cooled small modular reactor (SCW-SMR) technology is in progress since September 2020 in the framework of a Horizon 2020 project called ECC-SMART. As a main purpose of the project, proper estimates of energy deposition and its spatial distribution are prerequisites for the accurate analysis of safety related parameters of the SCW-SMR concept under development. A supercritical water reactor fuel computational benchmark model, provided by Canadian Nuclear Laboratories, was applied for detailed comparison of different energy deposition calculation options available in the Serpent 2 Monte Carlo code. The effect of energy deposition options on the normalization of the results as well as on the spatial distribution of the energy deposition are discussed. Consistent energy deposition calculation methods are presented between three Monte Carlo codes, viz., Serpent 2, MCNP6 and OpenMC. Although resource-intensive, the use of the coupled neutron-photon transport mode of Serpent 2 is recommended for accurate spatial and quantitative characterization of energy deposition in the SCW-SMR fuel assemblies, accounting for both neutron and photon heating of all the materials. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2020

Generating Uncertainty Distributions for Seismic Signal Onset Times

Signal arrival-time estimation plays a critical role in a variety of downstream seismic analyses, including location estimation and source characterization. Any arrival-time errors propagate through subsequent data-processing results. In this article, we detail a general framework for refining estimated seismic signal arrival times along with full estimation of their associated uncertainty. Using the standard short-term average/long-term average threshold algorithm to identify a search window, we demonstrate how to refine the pick estimate through two different approaches. In both cases, new waveform realizations are generated through bootstrap algorithms to produce full a posteriori estimates of uncertainty of onset arrival time of the seismic signal. The onset arrival uncertainty estimates provide additional data-derived information from the signal and have the potential to influence seismic analysis along several fronts.

58 GEOSCIENCES↗
DOE OSTI2020

Surface Cloud Grid Version 2 (SFCCLDGRID2) Value-Added Product: Description of Update"

This document describes the algorithm used for the Surface Cloud Grid Value-Added Product (VAP). This VAP uses as input the 15-min. output from the Shortwave (SW) Flux Analysis VAP (see Long 2001; Long and Ackerman 2000; Long et al. 1999) from the Atmospheric Radiation Measurement (ARM) Climate Reseach Facility (ACRF) Southern Great Plains (SGP) Central Facility and extended facilities. This network of 21 sites is unevenly spaced over northern Oklahoma into southern Kansas, covering an area from 95.5° to 99.5° west longitude and 34.5° to 38.5° north latitude. For research applications such as single-column modeling, an estimate of the cloud and cloud effects distribution over this entire domain is desirable. The Surface Cloud Grid VAP applies a multi-pass weighted sum analytic approximation technique (Caracena 1987), which uses Gaussian weighting and an imposed scale length, to interpolate to a 0.25° by 0.25° lat/long grid over the SGP domain. The output, like the input, includes solar elevation angles of 10° or greater.

97 MATHEMATICS AND COMPUTING↗