Search NASA⌕ Search

SEARCH · Search NASA

Results for “Function 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 1,711 records · Page 95
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

A study of explosive-induced fracture in polymethyl methacrylate (PMMA)

The fracture response of geologic materials is of interest for applications, including geothermal energy harnessing and containment of underground explosions. To better understand the explosively induced fracture response of geomaterials, polymethyl methacrylate (PMMA) was used as a transparent rock surrogate to allow imaging of internal shock propagation and fracture growth processes. Experiments were conducted using high-speed shadowgraphy and photon Doppler velocimetry (PDV), which were compared to numerical simulations. Experiments measured fractures produced in 304.8mm × 304.8mm × 304.8mm PMMA cubes with two simultaneously initiated detonators. The cubes were subjected to varying amounts and directions of externally applied uniaxial stresses, including no stress, 2 MPa stress, and 20 MPa stress. The fracture radius as a function of time was extracted from the high-speed videos. Post-test images of the PMMA cubes aided in the determination of three-dimensional effects not directly imaged by the cameras. The surface velocity history and the shock response captured in PDV and the high-speed videos were compared to the simulated explosive-induced shock response. The simulation results indicate that the shock drives the fracture for the first 20 μs corresponding to a fracture radius of approximately 15 mm in the experiments. The gas-driven fracture extent was estimated analytically using an equilibrium stress distribution calculated after the shock wave propagation through the sample. Reduction in the gas pressure due to the leakage of the explosive products through the crack as a function of time was accounted for. In conclusion, the estimated fracture lengths were in agreement with the experimentally observed fracture lengths.

15 GEOTHERMAL ENERGY↗
DOE OSTI2016

Stochastic modelling of intermittent fluctuations in the scrape-off layer: Correlations, distributions, level crossings, and moment estimation

A stochastic model is presented for intermittent fluctuations in the scrape-off layer of magnetically confined plasmas. The fluctuations in the plasma density are modeled by a super-position of uncorrelated pulses with fixed shape and duration, describing radial motion of blob-like structures. In the case of an exponential pulse shape and exponentially distributed pulse amplitudes, predictions are given for the lowest order moments, probability density function, auto-correlation function, level crossings, and average times for periods spent above and below a given threshold level. Also, the mean squared errors on estimators of sample mean and variance for realizations of the process by finite time series are obtained. These results are discussed in the context of single-point measurements of fluctuations in the scrape-off layer, broad density profiles, and implications for plasma–wall interactions due to the transient transport events in fusion grade plasmas. The results may also have wide applications for modelling fluctuations in other magnetized plasmas such as basic laboratory experiments and ionospheric irregularities.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2014

Investigation of thermochemical biorefinery sizing and environmental sustainability impacts for conventional supply system and distributed pre-processing supply system designs

The 2011 US Billion-Ton Update estimates that by 2030 there will be enough agricultural and forest resources to sustainably provide at least one billion dry tons of biomass annually, enough to displace approximately 30% of the country's current petroleum consumption. A portion of these resources are inaccessible at current cost targets with conventional feedstock supply systems because of their remoteness or low yields. Reliable analyses and projections of US biofuels production depend on assumptions about the supply system and biorefinery capacity, which, in turn, depend upon economic value, feedstock logistics, and sustainability. A cross-functional team has examined combinations of advances in feedstock supply systems and biorefinery capacities with rigorous design information, improved crop yield and agronomic practices, and improved estimates of sustainable biomass availability. A previous report on biochemical refinery capacity noted that under advanced feedstock logistic supply systems that include depots and pre-processing operations there are cost advantages that support larger biorefineries up to 10 000 DMT/day facilities compared to the smaller 2000 DMT/day facilities. This report focuses on analyzing conventional versus advanced depot biomass supply systems for a thermochemical conversion and refinery sizing based on woody biomass. The results of this analysis demonstrate that the economies of scale enabled by advanced logistics offsets much of the added logistics costs from additional depot processing and transportation, resulting in a small overall increase to the minimum ethanol selling price compared to the conventional logistic supply system. While the overall costs do increase slightly for the advanced logistic supply systems, the ability to mitigate moisture and ash in the system will improve the storage and conversion processes. In addition, being able to draw on feedstocks from further distances will decrease the risk of biomass supply to the conversion facility.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2016

Investigation of methodology for uncertainty quantification of model parameters

Quantifying the uncertainty contributors of best-estimate thermal hydraulic code is getting more and more attention in safety analysis of nuclear industry during recent decades. Yet for uncertainties of certain model parameters which may not be directly measured, the quantification process is usually subjective and inaccurate. This paper investigates the statistical methodologies in order to get the probability density function (pdf) of model parameters more objectively based on observed experimental responses. The simplification of mathematical model is described for the parameter estimation, and solutions based on Bayesian theorem and Maximum Likelihood Estimation (MLE) are classified and demonstrated for both deterministic approach and stochastic approach. As an application, the uncertainties of model parameters related to reflood phenomena implemented in RELAP5 code are quantified. It is indicated that the statistical method which is independent of best-estimate code is feasible and easy to apply. And through the check of uncertainty propagation, it demonstrates that the uncertainty bands can envelope most of the experiment measurement with advantage of accuracy. (authors)

42 ENGINEERING↗
DOE OSTI2016

scraps: An open-source Python-based analysis package for analyzing and plotting superconducting resonator data

We present "scraps" (SuperConducting Analysis and Plotting Software), a Python package designed to aid in the analysis and visualization of large amounts of superconducting resonator data, specifically complex transmission as a function of frequency, acquired at many different temperatures and driving powers. The package includes a least-squares fitting engine as well as a Monte-Carlo Markov Chain sampler for sampling the posterior distribution given priors, marginalizing over nuisance parameters, and estimating covariances. A set of plotting tools for generating publication-quality figures is also provided in the package. Lastly, we discuss the functionality of the software and provide some examples of its utility on data collected from a niobium-nitride coplanar waveguide resonator fabricated at Argonne National Laboratory.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2016

TU-H-CAMPUS-IeP1-01: Bias and Computational Efficiency of Variance Reduction Methods for the Monte Carlo Simulation of Imaging Detectors

Purpose: Variance reduction techniques (VRTs) are employed in Monte Carlo simulations to obtain estimates with reduced statistical uncertainty for a given simulation time. In this work, we study the bias and efficiency of a VRT for estimating the response of imaging detectors. Methods: We implemented Directed Sampling (DS), preferentially directing a fraction of emitted optical photons directly towards the detector by altering the isotropic model. The weight of each optical photon is appropriately modified to maintain simulation estimates unbiased. We use a Monte Carlo tool called fastDETECT2 (part of the hybridMANTIS open-source package) for optical transport, modified for VRT. The weight of each photon is calculated as the ratio of original probability (no VRT) and the new probability for a particular direction. For our analysis of bias and efficiency, we use pulse height spectra, point response functions, and Swank factors. We obtain results for a variety of cases including analog (no VRT, isotropic distribution), and DS with 0.2 and 0.8 optical photons directed towards the sensor plane. We used 10,000, 25-keV primaries. Results: The Swank factor for all cases in our simplified model converged fast (within the first 100 primaries) to a stable value of 0.9. The root mean square error per pixel for DS VRT for the point response function between analog and VRT cases was approximately 5e-4. Conclusion: Our preliminary results suggest that DS VRT does not affect the estimate of the mean for the Swank factor. Our findings indicate that it may be possible to design VRTs for imaging detector simulations to increase computational efficiency without introducing bias.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Fine resolution remote sensing spectra improves estimates of gross primary production of croplands

Gross primary production (GPP) is a fundamental measure of the terrestrial carbon cycle critical to our understanding of ecosystem function under the changing climate and land use. Remote sensing enables access to continuous spatial coverage, but remains challenged in heterogeneous croplands. Coarse resolution products, like MOD17A (500 m), may aggregate fragmented land cover types commonly found in heavily managed landscapes and misrepresent their respective contribution to carbon production. Consequently, this study demonstrates the capability of fine-resolution imagery (20-30 m) and available red-edge vegetation indices to characterize GPP across seven Midwest cropping systems. Four sites were established on a 22-year-old USDA Conservation Reserve Program (CRP); and the other three on land conventionally farmed with corn-soybean-wheat rotation (AGR). We compare in situ GPP estimates from eddy-covariance towers with ten satellite models: eight variants of the vegetation photosynthesis models (VPM), of which five include a red-edge vegetation index, as well as conventional products Landsat CONUS GPP (30 m) and MOD17A2H V6 (500 m). Daily and cumulative fine-resolution imagery integrated within VPM generally agreed with tower-based GPP in heterogeneous landscapes more than those from MODIS 500 m VPM or conventional GPP products from MOD17AH V6 or Landsat 8 CONUS. Here, replacing EVI2 with red-edge indices NDRE2, NDRE1, and MTCI in Sentinel 2 VPMs notably improved explanation of variance and estimation of cumulative GPP. While existing methods using MODIS- and Landsat-derived GPP are important baselines for regional and global studies, future research may benefit from the higher spatial, temporal, and radiometric resolution.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

δ 2 H isotopic offsets in xylem water measurements under cryogenic vacuum distillation: Quantifying and correcting wood‐water hydrogen exchange influences

Stable isotopes δ 18 O and δ 2 H are used to infer vegetation water sources. In some studies, significant xylem water δ 2 H offsets from potential source waters have been observed. The offsets appear to be more prevalent with cryogenic vacuum distillation (CVD) of plant water. Hypothesized mechanisms for these offsets include changes during plant water uptake and transport, and methodological problems. We propose that a large portion of the offsets are due to hydrogen isotope exchange between xylem water and non-crystalline hydroxyl groups of wood cellulose and hemicellulose during CVD. We present a method for estimating the hypothesized isotopic exchange between wood tissues and water, which is the result of Rayleigh and equilibrium fractionation. To estimate the exchange, we use published wood properties for North American tree species and isotope chemical relationships as a function of moisture content, CVD temperature and water extraction efficiency. A simple model of exchange between xylem water and hydroxyl groups captures the range of observations in studies in which CVD and non-CVD methods were compared. To evaluate the model, we compared observed δ 2 H offsets (sw-excess) values from two field datasets (90°C, n = 364, and 170°C, n = 43) to δ 2 H offsets estimated with our chemical model. We found good agreement between observed and estimated δ 2 H offsets for samples extracted at 90°C (r 2 = 0.69) but not for samples extracted at 170°C (r 2 = 0.20). The offset may be eliminated by increasing the extraction temperature to 229°C or by adding a standard sufficient to raise the moisture content to >150%. A correction can also be approximated by applying a theoretical calculation based on the extraction temperature, moisture content and water extraction efficiency.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Hot Deformation and Processing Maps of B{sub 4}C/6061Al Nanocomposites Fabricated by Spark Plasma Sintering

We developed 3 vol.% B{sub 4}C/6061Al nanocomposites by spark plasma sintering. We then characterized their flow and hot deformation behaviors using isothermal compression tests at deformation temperatures of 673-823 K and strain rates of 0.001-1 s{sup −1}. Results indicated that their steady flow characteristic can be described by the Zener–Hollomon parameter (Z) as a hyperbolic-sine function of flow stress. Based on pinning effect from B{sub 4}C nanoparticles, the estimated activation energy was calculated to be 274.80 kJ/mol. At the unstable deformation condition (723 K/1 s{sup −1}) with high Z, flow localization appeared; the main softening mechanisms involved are dynamic recovery and dynamic recrystallization (DRX). At the stable deformation condition (823 K/0.001 s{sup −1}) with low Z, adequate DRX occurred. Based on the processing map and microstructure evolution, the optimum hot working conditions for B{sub 4}C/6061Al nanocomposites were determined to be a deformation temperature of 773-823 K and a strain rate of 0.001-0.003 s{sup −1}. These working conditions were verified by a hot extrusion test.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Mesostructure and porosity effects on the thermal conductivity of additively manufactured interpenetrating phase composites

In this paper, we have investigated the relationship between structure and thermal conductivity in additively manufactured interpenetrating A356/316L composites. We used X-ray microcomputed tomography to characterize the pore structure in as-fabricated composites, finding microporosity in both constituents as well as a 50 μm thick layer of interfacial porosity separating the constituents. We measured the thermal conductivity of a 43 vol% 316L composite to be 53 Wm -1 K -1 , which is significantly less than that predicted by a simple rule-of-mixtures approximation, presumably because of the residual porosity. Motivated by these experimental results we used periodic homogenization theory to determine the combined effects of porosity and unit cell structure on the effective thermal conductivity. This analysis showed that in fully dense composites, the topology of the constituents has a weak effect on the thermal conductivity, whereas in composites with interfacial porosity, the size and structure of the unit cell strongly influence the thermal conductivity. Finally, we also found that an approximation formula of the strong contrast expansion method gives excellent estimates of the effective thermal conductivity of these composites, providing a powerful tool for designing functionally graded composites and for identifying mesostructures with optimal thermal conductivity values.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Photometric redshifts for the S-PLUS Survey: Is machine learning up to the task?

The Southern Photometric Local Universe Survey (S-PLUS) is a novel project that aims to map the Southern Hemisphere using a twelve filter system, comprising five broad-band SDSS-like filters and seven narrow-band filters optimized for important stellar features in the local universe. In this paper we use the photometry and morphological information from the first S-PLUS data release (S-PLUS DR1) cross-matched to unWISE data and spectroscopic redshifts from Sloan Digital Sky Survey DR15. We explore three different machine learning methods (Gaussian Processes with GPz and two Deep Learning models made with TensorFlow) and compare them with the currently used template-fitting method in the S-PLUS DR1 to address whether machine learning methods can take advantage of the twelve filter system for photometric redshift prediction. Using tests for accuracy for both single-point estimates such as the calculation of the scatter, bias, and outlier fraction, and probability distribution functions (PDFs) such as the Probability Integral Transform (PIT), the Continuous Ranked Probability Score (CRPS) and the Odds distribution, we conclude that a deep-learning method using a combination of a Bayesian Neural Network and a Mixture Density Network offers the most accurate photometric redshifts for the current test sample. In conclusion, it achieves single-point photometric redshifts with scatter (σ NMAD ) of 0.023, normalized bias of -0.001, and outlier fraction of 0.64% for galaxies with r_auto magnitudes between 16 and 21.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Empirical estimation of densities in NaCl-KCl-UCl 3 and NaCl-KCl-YCl 3 molten salts using Redlich-Kister expansion

Densities of molten KCl-NaCl-UCl 3 and KCl-NaCl-YCl 3 ternary systems have been estimated using a multidimensional Redlich-Kister model. Temperature and composition dependent Redlich-Kister functions have been used to generate binary interaction parameters in the outlined ternary salt systems. These binary interactions have been used in the extrapolation to ternary system densities. The results of the density extrapolations by Muggianu interpolation scheme provide agreement within 2–3% for the NaCl-KCl-YCl 3 liquids and 11% in NaCl-KCl-UCl 3 liquids compared to the available experimental data. Modeling NaCl-KCl-UCl 3 molten phase density with a ternary interaction parameter improved the agreement within 4%. Thermophysical modeling used in this study has shown promising results for use in other material properties, such as viscosity, thermal conductivity, and heat capacity of the molten salts. Lastly, the outlined modeling method applied in these specific molten salt ternaries can be used for quaternary or higher multicomponent molten salt systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

Probabilistic Risk Assessment of CO2 Trapping Mechanisms in a Sandstone CO2-EOR Field in Northern Texas, USA

This study employs a polynomial chaos expansion (PCE) technique to develop the reduced order models (ROMs) integrated with the Monte Carlo simulations to quantify uncertainties of CO 2 storage associated with enhanced oil recovery (EOR) in a commercial-scale CO 2 -EOR field. The Morrow B sandstone at the Farnsworth Unit (FWU) EOR field in northern Texas was selected as a case study. A 3-D reservoir model, including simulation of a five-spot injection/production well pattern, was constructed based on the data from well logs and cores, and an updated seismic interpretation in the FWU. Porosity and permeability were considered as sources of uncertainty. The 1000-realization heterogeneous random fields of porosity and permeability were generated based on the variogram analysis on the core measurements of the FWU. Three model outputs of interest include the amount of CO 2 trapped by three trapping mechanisms, i.e. hydrodynamic trapping, oil dissolution trapping, and aqueous dissolution trapping. The total of 25 runs were conducted with the simulations of a 20-year CO 2 -EOR period, and a 20-year monitoring period to develop the ROMs between uncertain model input parameters (i.e., porosity and permeability in this study) and model outputs at the end of simulation for each grid cell using PCE approach. The high coefficient of determination (R 2 ) and small normalized root mean square error (NRMSE) between the simulated (using reservoir modeling) and predicted (using ROMs) CO 2 storage indicate that the ROMs are acceptable and reliable to be used for the predictions. Given the 1000 Monte Carlo samplings of the model input parameters, cumulative distribution functions (CDFs) and uncertainty bounds (10 th and 90 th percentiles) of model outputs were estimated based on ROMs. At the end of simulation, the most injected CO 2 at the FWU was stored by hydrodynamic trapping (between 121,400 and 166,860 tonnes), followed by oil dissolution trapping (between 55,303 and 76,816 tonnes), and aqueous dissolution trapping (between 1979 and 2751 tonnes).

58 GEOSCIENCES↗
DOE OSTI2018

Primary radiation damage: A review of current understanding and models

Scientific understanding of any kind of radiation effects starts from the primary damage, i.e. the defects that are produced right after an initial atomic displacement event initiated by a high-energy particle. In this Review, we consider the extensive experimental and computer simulation studies that have been performed over the past several decades on what the nature of the primary damage is. We review both the production of crystallographic or topological defects in materials as well as radiation mixing, i.e. the process where atoms in perfect crystallographic positions exchange positions with other ones in non-defective positions. All classes of materials except biological materials are considered. We also consider the recent effort to provide alternatives to the current international standard for quantifying this energetic particle damage, the Norgett-Robinson-Torrens displacements per atom (NRT-dpa) model for metals. We present in detail new complementary displacement production estimators (“athermal recombination corrected dpa”, arc-dpa) and atomic mixing (“replacements per atom”, rpa) functions that extend the NRT-dpa, and discuss their advantages and limitations.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Neutron angular distribution in plutonium-240 spontaneous fission

Nuclear safeguards applications require accurate fission models that exhibit prompt neutron anisotropy. We observed an anisotropic neutron angular distribution, in the laboratory reference frame, because prompt fission neutrons carry momentum from fully accelerated fission fragments. Furthermore, a liquid organic scintillation detector array was used with pulse shape discrimination techniques to produce neutron-neutron cross-correlation time distributions and angular distributions from spontaneous fission in a 252 Cf, a 0.84 g 240 Pu eff metal, and a 1.63 g 240 Pu eff metal sample. The effect of cross-talk, estimated with MCNPX-PoliMi simulations, is removed from neutron-neutron coincidences as a function of the angle between detector pairs. Fewer coincidences were observed at detector angles near 90°, relative to higher and lower detector angles. As light output threshold increases, the observed anisotropy increases due to spectral effects arising from fission fragment momentum transfer to emitted neutrons. Stronger anisotropy was observed in Cf-252 spontaneous fission prompt neutrons than in Pu-240 neutrons.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2018

Improving atomic displacement and replacement calculations with physically realistic damage models

Atomic collision processes are fundamental to numerous advanced materials technologies such as electron microscopy, semiconductor processing and nuclear power generation. Extensive experimental and computer simulation studies over the past several decades provide the physical basis for understanding the atomic-scale processes occurring during primary displacement events. The current international standard for quantifying this energetic particle damage, the Norgett-Robinson-Torrens displacements per atom (NRT-dpa) model, has nowadays several well-known limitations. In particular, the number of radiation defects produced in energetic cascades in metals is only ~1/3 the NRT-dpa prediction, while the number of atoms involved in atomic mixing is about a factor of 30 larger than the dpa value. Here we propose two new complementary displacement production estimators (athermal recombination corrected dpa, arc-dpa) and atomic mixing (replacements per atom, rpa) functions that extend the NRT-dpa by providing more physically realistic descriptions of primary defect creation in materials and may become additional standard measures for radiation damage quantification.

36 MATERIALS SCIENCE↗
DOE OSTI2014

Planck 2013 results. XXV. Searches for cosmic strings and other topological defects

Planck data have been used to provide stringent new constraints on cosmic strings and other defects. We describe forecasts of the CMB power spectrum induced by cosmic strings, calculating these from network models and simulations using line-of-sight Boltzmann solvers. We have studied Nambu-Goto cosmic strings, as well as field theory strings for which radiative effects are important, thus spanning the range of theoretical uncertainty in the underlying strings models. We have added the angular power spectrum from strings to that for a simple adiabatic model, with the extra fraction defined as f 10 at multipole = 10. This parameter has been added to the standard six parameter fit using COSMOMC with flat priors. For the Nambu-Goto string model, we have obtained a constraint on the string tension of G μ/c 2 < 1.5 × 10 -7 and f 10 < 0.015 at 95% confidence that can be improved to G μ/c 2 < 1.3 × 10-7 and f 10 < 0.010 on inclusion of high-&ell; CMB data. For the Abelian-Higgs field theory model we find, G μ AH /c 2 < 3.2 × 10 -7 and f 10 < 0.028. The marginalised likelihoods for f 10 and in the f 10 -Ω b h 2 plane are also presented. We have additionally obtained comparable constraints on f 10 for models with semilocal strings and global textures. In terms of the effective defect energy scale these are somewhat weaker at G μ/c 2 < 1.1 × 10 -6 . We have made complementarity searches for the specific non-Gaussian signatures of cosmic strings, calibrating with all-sky Planck resolution CMB maps generated from networks of post-recombination strings. We have validated our non-Gaussian searches using these simulated maps in a Planck -realistic context, estimating sensitivities of up to Δ G μ/c 2 &approx; 4 × 10 -7 . We have obtained upper limits on the string tension at 95% confidence of G μ/c 2 < 9.0 × 10 -7 with modal bispectrum estimation and G μ/c 2 < 7.8 × 10 -7 for real space searches with Minkowski functionals. These are conservative upper bounds because only post-recombination string contributions have been included in the non-Gaussian analysis.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2014

First-principles study of vacancy-assisted impurity diffusion in ZnO

Group-III elements act as donors in ZnO when incorporated on the Zn site. Their incorporation and behavior upon annealing is governed by diffusion, which proceeds mainly through a vacancy-assisted process. We report first-principles calculations for the migration of Al, Ga, and In donors in ZnO, based on density functional theory using a hybrid functional. From the calculated migration barriers and formation energies, we determine diffusion activation energies and estimate annealing temperatures. Impurity-vacancy binding energies and migration barriers decrease from Al to In. Activation energies for vacancy-assisted diffusion are lowest for In and highest for Al.

36 MATERIALS SCIENCE↗