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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 415 records · Page 23
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Blind Modeling Validation Exercises Using the Horizontal Dry Cask Simulator

The U.S. Department of Energy (DOE) established a need to understand the thermal-hydraulic properties of dry storage systems for commercial spent nuclear fuel (SNF) in response to a shift towards the storage of high-burnup (HBU) fuel (> 45 gigawatt days per metric ton of uranium, or GWd/MTU). This shift raises concerns regarding cladding integrity, which faces increased risk at the higher temperatures within spent fuel assemblies present within HBU fuel compared to low-burnup fuel (≤ 45 GWd/MTU). A dry cask simulator (DCS) was built at Sandia National Laboratories (SNL) in Albuquerque, New Mexico to produce validation-quality data that can be used to test the accuracy of the modeling used to predict cladding temperatures. These temperatures are critical to evaluating cladding integrity throughout the storage cycle of commercial spent nuclear fuel. A model validation exercise was previously carried out for the DCS in a vertical configuration. Lessons learned during the previous validation exercise have been applied to a new, blind study using a horizontal dry cask simulator (HDCS). Three modeling institutions – the Nuclear Regulatory Commission (NRC), Pacific Northwest National Laboratory (PNNL), and Empresa Nacional del Uranio, S.A., S.M.E. (ENUSA) – were granted access to the input parameters from the DCS Handbook, SAND2017-13058R, and results from a limited data set from the horizontal BWR dry cask simulator tests reported in the HDCS update report, SAND2019-11688R. With this information, each institution was tasked to calculate peak cladding temperatures and air mass flow rates for ten HDCS test cases. Axial as well as vertical and horizontal transverse temperature profiles were also calculated. These calculations were done using modeling codes (ANSYS/Fluent, STAR-CCM+, or COBRA-SFS), each with their own unique combination of modeling assumptions and boundary conditions. For this validation study, the ten test cases of the horizontal dry cask simulator were defined by three independent variables – fuel assembly decay heat (0.5 kW, 1 kW, 2.5 W, and 5 kW), internal backfill pressure (100 kPa and 800 kPa), and backfill gas (helium and air). The plots provided in Chapter 3 of this report show the axial, vertical, and horizontal temperature profiles obtained from the dry cask simulator experiments in the horizontal configuration and the corresponding models used to describe the thermal-hydraulic behavior of this system. The tables provided in Chapter 3 illustrate the closeness of fit of the model data to the experiment data through root mean square (RMS) calculations of the error in peak cladding temperatures (PCTs), PCT axial locations, axial temperature profiles, vertical and horizontal temperature profiles at two different axial locations, and air mass flow rates for the ten test cases, normalized by the experimental results. The model results are assigned arbitrary model numbers to retain anonymity. Due to the relatively flat axial temperature profiles, small temperature gradients resulted in large deviations of all models’ PCT axial location from the experimental PCT axial location. When the PCT axial location error is excluded in the calculation of the combined RMS of the normalized errors that considers PCT, the temperature profiles, and the air mass flow rates, the model data fits the experimental data to within 5%. When the vault information is excluded, the model data fits the experimental data to within 2.5%. An error analysis was developed further for one model, using the model and experimental uncertainties in each validation parameter to calculate validation uncertainties. The uncertainties for each parameter were used to define quantifiable validation criteria. For this analysis, the model was considered validated for a given comparison metric if the normalized error in that metric divided by the validation uncertainty was less than or equal to 1. When considering the combined RMS of the normalized errors of all metrics divided by their validation uncertainties, the model was found to have satisfied the criterion for model validation.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

BayFlux: A Bayesian method to quantify metabolic Fluxes and their uncertainty at the genome scale

Metabolic fluxes, the number of metabolites traversing each biochemical reaction in a cell per unit time, are crucial for assessing and understanding cell function. 13 C Metabolic Flux Analysis ( 13 C MFA) is considered to be the gold standard for measuring metabolic fluxes. 13 C MFA typically works by leveraging extracellular exchange fluxes as well as data from 13 C labeling experiments to calculate the flux profile which best fit the data for a small, central carbon, metabolic model. However, the nonlinear nature of the 13 C MFA fitting procedure means that several flux profiles fit the experimental data within the experimental error, and traditional optimization methods offer only a partial or skewed picture, especially in “non-gaussian” situations where multiple very distinct flux regions fit the data equally well. Here, we present a method for flux space sampling through Bayesian inference (BayFlux), that identifies the full distribution of fluxes compatible with experimental data for a comprehensive genome-scale model. This Bayesian approach allows us to accurately quantify uncertainty in calculated fluxes. We also find that, surprisingly, the genome-scale model of metabolism produces narrower flux distributions (reduced uncertainty) than the small core metabolic models traditionally used in 13 C MFA. The different results for some reactions when using genome-scale models vs core metabolic models advise caution in assuming strong inferences from 13 C MFA since the results may depend significantly on the completeness of the model used. Based on BayFlux, we developed and evaluated novel methods (P- 13 C MOMA and P- 13 C ROOM) to predict the biological results of a gene knockout, that improve on the traditional MOMA and ROOM methods by quantifying prediction uncertainty.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

Development of an Advanced Force Field for Water Using Variational Energy Decomposition Analysis

Given the piecewise approach to modeling intermolecular interactions for force fields, they can be difficult to parametrize since they are fit to data like total energies that only indirectly connect to their separable functional forms. Furthermore, by neglecting certain types of molecular interactions such as charge penetration and charge transfer, most classical force fields must rely on, but do not always demonstrate, how cancellation of errors occurs among the remaining molecular interactions accounted for such as exchange repulsion, electrostatics, and polarization. In this work we present the first generation of the (many-body) MB-UCB force field that explicitly accounts for the decomposed molecular interactions commensurate with a variational energy decomposition analysis, including charge transfer, with force field design choices that reduce the computational expense of the MB-UCB potential while remaining accurate. We optimize parameters using only a single water molecule and water cluster data up through pentamers, with no fitting to condensed phase data, and we demonstrate that high accuracy is maintained when the force field is subsequently validated against conformational energies of larger water cluster data sets, radial distribution functions of the liquid phase, and the temperature dependence of thermodynamic and transport water properties. Finally, we conclude that MB-UCB is comparable in performance to MB-Pol but is less expensive and more transferable by eliminating the need to represent short-ranged interactions through large parameter fits to high order polynomials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2014

Curve fitting methods for solar radiation data modeling

This paper studies the use of several type of curve fitting method to smooth the global solar radiation data. After the data have been fitted by using curve fitting method, the mathematical model of global solar radiation will be developed. The error measurement was calculated by using goodness-fit statistics such as root mean square error (RMSE) and the value of R{sup 2}. The best fitting methods will be used as a starting point for the construction of mathematical modeling of solar radiation received in Universiti Teknologi PETRONAS (UTP) Malaysia. Numerical results indicated that Gaussian fitting and sine fitting (both with two terms) gives better results as compare with the other fitting methods.

14 SOLAR ENERGY↗
NASA NTRS1988

Estimation of time- and state-dependent delays and other parameters in functional differential equations

A parameter estimation algorithm is developed which can be used to estimate unknown time- or state-dependent delays and other parameters (e.g., initial condition) appearing within a nonlinear nonautonomous functional differential equation. The original infinite dimensional differential equation is approximated using linear splines, which are allowed to move with the variable delay. The variable delays are approximated using linear splines as well. The approximation scheme produces a system of ordinary differential equations with nice computational properties. The unknown parameters are estimated within the approximating systems by minimizing a least-squares fit-to-data criterion. Convergence theorems are proved for time-dependent delays and state-dependent delays within two classes, which say essentially that fitting the data by using approximations will, in the limit, provide a fit to the data using the original system. Numerical test examples are presented which illustrate the method for all types of delay.

Murphy, K. A.↗
NASA NTRS1990

Estimation of time- and state-dependent delays and other parameters in functional differential equations

A parameter estimation algorithm is developed which can be used to estimate unknown time- or state-dependent delays and other parameters (e.g., initial condition) appearing within a nonlinear nonautonomous functional differential equation. The original infinite dimensional differential equation is approximated using linear splines, which are allowed to move with the variable delay. The variable delays are approximated using linear splines as well. The approximation scheme produces a system of ordinary differential equations with nice computational properties. The unknown parameters are estimated within the approximating systems by minimizing a least-squares fit-to-data criterion. Convergence theorems are proved for time-dependent delays and state-dependent delays within two classes, which say essentially that fitting the data by using approximations will, in the limit, provide a fit to the data using the original system. Numerical test examples are presented which illustrate the method for all types of delay.

Murphy, K. A.↗
NASA NTRS1992

Magellan ephemeris improvement using synthetic aperture radar landmark measurements

A technique is described for measuring the positions of landmarks in multiple SAR images of the surface of Venus taken aboard the Magellan spacecraft. These measurements are then used to improve the spacecraft orbit estimate. The Venus-fixed coordinates of the landmarks are also estimated, as are the low-order coefficients of the gravitational field. Sample results are shown for five-orbit and 13-orbit data arcs using hundreds of landmark measurements. Reasonably good fits to the data are obtained for the short-arc solutions, while the data fits over long arcs are poorer, possibly due to higher-order uncertainties in the gravitational field. A comparison of post-fit orbit uncertainties shows that the SAR data significantly improves the orbit estimate.

Chodas, Paul W.↗
DOE OSTI2014

Constraining primordial vector mode from B-mode polarization

The B-mode polarization spectrum of the Cosmic Microwave Background (CMB) may be the smoking gun of not only the primordial tensor mode but also of the primordial vector mode. If there exist nonzero vector-mode metric perturbations in the early Universe, they are known to be supported by anisotropic stress fluctuations of free-streaming particles such as neutrinos, and to create characteristic signatures on both the CMB temperature, E-mode, and B-mode polarization anisotropies. We place constraints on the properties of the primordial vector mode characterized by the vector-to-scalar ratio r{sub v} and the spectral index n{sub v} of the vector-shear power spectrum, from the Planck and BICEP2 B-mode data. We find that, for scale-invariant initial spectra, the ΛCDM model including the vector mode fits the data better than the model including the tensor mode. The difference in χ{sup 2} between the vector and tensor models is Δχ{sup 2} = 3.294, because, on large scales the vector mode generates smaller temperature fluctuations than the tensor mode, which is preferred for the data. In contrast, the tensor mode can fit the data set equally well if we allow a significantly blue-tilted spectrum. We find that the best-fitting tensor mode has a large blue tilt and leads to an indistinct reionization bump on larger angular scales. The slightly red-tilted vector mode supported by the current data set can also create O(10{sup -22})-Gauss magnetic fields at cosmological recombination. Our constraints should motivate research that considers models of the early Universe that involve the vector mode.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1995

Determination of plasma temperatures and luminosities using multiple extreme-ultraviolet and X-ray filters

We carefully examine the techniques used to infer temperatures of stellar coronal plasmas from the count rates of several broadband instruments in the X-ray and extreme-ultraviolet spectral ranges. In particular, we determine to what extent temperatures can be constrained and the corresponding uncertainties in the luminosities and emission measures lowered by fitting simultaneously count rates from the Einstein imaging proportional counter (IPC), the ROSAT Position Sensitive Proportional Counter (PSPC), the ROSAT Wide Field Camera (WFC) (both filters), and the EXOSAT Low Energy Telescope (LET) with the 3-Lex filter. We use published plasma emissivities with solar photospheric abundances. Since it has been found that single-temperature plasmas do not fit IPC data well, we assume a two-temperature plasma model. We find that, even with count rates from all of the above filters and overly optimistic error estimates, it is still not possible to determine a unique two-temperature solution. However, since the use of count rates from many filters can reduce substantially the number of possible solutions, temperature solutions determined by other means can be tested. We carry out such an analysis on a set of 18 nearby late-type stars to determine possible two-temperature solutions using multifilter photometry, and we compare these results with the temperature solutions derived by Schmitt et al. (1990) using IPC spectral data. In general, the two-temperature fits derived from the IPC spectral data are inconsistent with our results, with our data implying that, for many stars, the two temperatures derived by the IPC may be too low by about a factor of 2. The EXOSAT transmission grating Spectrometer (TGS) spectra of capella and sigma(exp 2) CrB support this conclusion. For Procyon and 70 Oph, though, the presence of a temperature component cooler than a million degress (not detected by the IPC) is deduced. While our analysis suggests the existence of more than one temperature in the coronae of late-type stars, in many instances our WFC data appear to be inconsistent with the presence of significant emission measure over a broad temperature distribution. This, together with the success of two-temperature plasmas in fitting IPC and TGS data, implies that for many stars, the coronal emission measure distribution may in fact be dominated by two distinct temperature regimes.

Wood, Brian E.↗
DOE OSTI2011

RESOLVING THE SUB-AU-SCALE GAS AND DUST DISTRIBUTION IN FU ORIONIS SOURCES

We present Keck Interferometer observations of the three prototypical FU Orionis stars, FU Ori, V1057 Cyg, and V1515 Cyg. With a spatial resolution of a few milliarcseconds and a spectral resolution of {lambda}/{Delta}{lambda} = 2000, our near-infrared observations spatially resolve gas and dust emission extending from stellocentric radii of {approx}0.05 AU to several AU. We fit these data with accretion disk models where each stellocentric radius of the disk is represented by a supergiant-type stellar emission spectrum at the disk temperature. A disk model is consistent with the data for FU Ori, although we require some local asymmetry in the disk. For V1057 Cyg the disk model does not fit our data well, especially compared to the fit quality achieved for FU Ori. We speculate that a disk wind may be contributing substantially to the observed near-IR emission in this source. The data for V1515 Cyg are noisier than the data obtained for the other two objects and do not strongly constrain the validity of an accretion disk model.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2025

An Efficient GPU-Accelerated Multi-Source Global Fit Pipeline for LISA Data Analysis

The large-scale analysis task of deciphering gravitational wave signals in the LISA data stream will be difficult, requiring a large amount of computational resources and extensive development of computational methods. Its high dimensionality, multiple model types, and complicated noise profile require a global fit to all parameters and input models simultaneously. In this work, we detail our global fit algorithm, called “Erebor,” designed to accomplish this challenging task. It is capable of analysing current state-of-the-art datasets and then growing into the future as more pieces of the pipeline are completed and added. We describe our pipeline strategy, the algorithmic setup, and the results from our analysis of the LDC2A Sangria dataset, which contains Massive Black Hole Binaries, compact Galactic Binaries, and a parameterized noise spectrum whose parameters are unknown to the user. The Erebor algorithm includes three unique and very useful contributions: GPU acceleration for enhanced computational efficiency; ensemble MCMC sampling with multiple MCMC walkers per temperature for better mixing and parallelized sample creation; and special online updates to reversible-jump (or trans-dimensional) sampling distributions to ensure sampler mixing and accurate initial estimates for detectable sources in the data. We recover posterior distributions for all 15 (6) of the injected MBHBs in the LDC2A training (hidden) dataset. We catalog ∼12000 Galactic Binaries (∼8000 as high confidence detections) for both the training and hidden datasets. All of the sources and their posterior distributions are provided in publicly available catalogs.

LISA global fit↗
DOE OSTI2022

Apodization Specific Fitting for Improved Resolution, Charge Measurement, and Data Analysis Speed in Charge Detection Mass Spectrometry

Short-time Fourier transforms with short segment lengths are typically used to analyze single ion charge detection mass spectrometry (CDMS) data either to overcome effects of frequency shifts that may occur during the trapping period or to more precisely determine the time at which an ion changes mass or charge, or enters an unstable orbit. The short segment lengths can lead to scalloping loss unless a large number of zero-fills are used, making computational time a significant factor in real-time analysis of data. Apodization specific fitting leads to a 9-fold reduction in computation time compared to zero-filling to a similar extent of accuracy. This makes possible real-time data analysis using a standard desktop computer. Rectangular apodization leads to higher resolution than the more commonly used Gaussian or Hann apodization and makes it possible to separate ions with similar frequencies, a significant advantage for experiments in which the masses of many individual ions are measured simultaneously. Equally important is a >20% increase in S/N obtained with rectangular apodization compared to Gaussian or Hann, which directly translates to a corresponding improvement in accuracy of both charge measurements and ion energy measurements that rely on the amplitudes of the fundamental and harmonic frequencies. Finally, combined with computing the fast Fourier transform in a lower-level language, this fitting procedure eliminates computational barriers and should enable real-time processing of CDMS data on a laptop computer.

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

Single-crystal equations of state of magnesiowüstite at high pressures

Solid solutions of (Mg,Fe)O with high iron enrichment may be an important component of ultralow-velocity zones at Earth’s core-mantle boundary. However, to date there have been few high-precision studies on the elastic properties of these materials. In this study we present results on the compression of (Mg 0.22 Fe 0.78 )O magnesiowüstite in both neon and helium pressure media using single-crystal diffraction to ~55 GPa. In addition, our sample was characterized by time-domain synchrotron Mössbauer spectroscopy at ambient pressure using an extended time range that resulted in vastly improved energy resolution. The combination of these high-resolution techniques tightly constrains the presence of a defect-structure component at room pressure due to 4.7 mol% tetrahedrally-coordinated ferric iron, resulting in a renormalized composition of (Mg 0.215 Fe 0.762 ⟂ 0.023 )O. Both high-pressure diffraction datasets are well described by a 3rd-order Birch-Murnaghan equation of state. The best fit-parameters for a crystal with cubic structure in helium are K 0T = 148(3) GPa, K' 0T = 4.09(12), and V 0 = 78.87(6) Å 3 . Increasing differential stress in the neon-containing sample chamber was correlated with increasing apparent distortion of the initially cubic unit cell, requiring a lower-symmetry hexagonal cell to fit the data above ~20 GPa. For fit equations of state, we determine the pressure-dependent correlation ellipses for the equation of state parameters and compare with previously published single-crystal diffraction data from (Mg,Fe)O crystals in a helium medium. We make two main observations from the datasets using a helium pressure medium: K 0T decreases as a function of increasing iron content from periclase to wüstite and K' 0T is consistent with an approximately constant value of 4.0 that is independent of iron content, at least up to (Mg,Fe)O containing ~78 mol% FeO. Finally, in combination with previously reported thermal parameters, we compute the density of Mw78 at core-mantle boundary conditions and discuss the implications.

58 GEOSCIENCES↗
NASA NTRS1990

Spectroscopic analysis of global tide gauge sea level data

Yearly and monthly global tide-gage sea-level data are fitted to numerically generated tidal data in order to search for the 18.6-yr lunar nodal tide and 14-month pole tide. Both of these tides are clearly evident, with amplitudes and phases that are consistent with a global equilibrium response. The ocean's response to atmospheric pressure is studied with the least-squares fit technique. Consideration is given to the global rise in sea level, the effects of postglacial rebound, and the possible causes of the enhanced pole tides in the North Sea, the Baltic Sea, and the Gulf of Bothnia. The results support O'Connor's (1986) suggestion that the enhanced pole tide in these regions is due to meteorological forcing rather than a basin-scale resonance. Also, the global average of the tide-gage data show an increase in sea level over tha last 80 yr of between 1.1 and 1.9 mm/yr.

Trupin, A.↗
NASA NTRS2017

Raising the Albedo of 2010 GY6: Fitting ATPM to Wise Data

Near-Earth Asteroid 462775 (2010 GY6) is in the Apollo orbit-family with a 1.46 year orbital period. 2010 GY6 was measured by WISE and fitted with NEATM, yielding NEATM model parameters of D=1.1 km, pv=0.028 and eta=2.3.The NEATM-derived geometric albedo of 2010 GY6 is lower than the surface of comet 67P/C-G. The eta value is considerably higher than typical for its phase angle of 33 deg, indicating a cooler surface due to non-zero thermal inertia and/or surface roughness are important. If the thermal inertia and surface roughness are constrained by fitting the Advanced Thermophysical Model (ATPM) to the WISE data, what would the resulting geometric albedo? We find pv=0.06-0.08, in the same range as B- or C-type NEAs like Bennu or JU3.

Near-Earth Asteroid 462775↗
DOE OSTI2017

Novel Histogram Based Unsupervised Classification Technique to Determine Natural Classes From Biophysically Relevant Fit Parameters to Hyperspectral Data

Hyperspectral image analysis has benefited from an array of methods that take advantage of the increased spectral depth compared to multispectral sensors; however, the focus of these developments has been on supervised classification methods. Lack of a priori knowledge regarding land cover characteristics can make unsupervised classification methods preferable under certain circumstances. An unsupervised classification technique is presented in this paper that utilizes physically relevant basis functions to model the reflectance spectra. These fit parameters used to generate the basis functions allow clustering based on spectral characteristics rather than spectral channels and provide both noise and data reduction. Histogram splitting of the fit parameters is then used as a means of producing an unsupervised classification. Unlike current unsupervised classification techniques that rely primarily on Euclidian distance measures to determine similarity, the unsupervised classification technique uses the natural splitting of the fit parameters associated with the basis functions creating clusters that are similar in terms of physical parameters. The data set used in this work utilizes the publicly available data collected at Indian Pines, Indiana. This data set provides reference data allowing for comparisons of the efficacy of different unsupervised data analysis. The unsupervised histogram splitting technique presented in this paper is shown to be better than the standard unsupervised ISODATA clustering technique with an overall accuracy of 34.3/19.0% before merging and 40.9/39.2% after merging. Finally, this improvement is also seen as an improvement of kappa before/after merging of 24.8/30.5 for the histogram splitting technique compared to 15.8/28.5 for ISODATA.

58 GEOSCIENCES↗
DOE OSTI2016

Quantifying Transient Uncertainty in the BEAVRS Benchmark Using Time Series Analysis Methods

Advances in computation have brought about significant improvements in creating fast-running high-fidelity simulations of nuclear cores. The BEAVRS benchmark is a highly-detailed PWR specification with two cycles of measured operational data used to validate high-fidelity core analysis methods. This PWR depletion benchmark captures the fine details of the LWR fuel assemblies, burnable absorbers, in-core fission detectors, core loading and shuffling patterns. Specifically, 58 of the 193 assemblies contain in-core detectors with measurements taken over 61 axial positions every month. These detectors are U-235 fission chambers with slightly varying mass of U-235. The collected signals are normalized on a given assembly permitting full core comparisons. The fuel layout for cycle 1 and instrument tube locations for the reactor are given in figures 1 and 2 respectively. Through a series of data processing and comparisons, it was shown that axially integrated radial maps of reaction rates were in close agreement between provided detector data and calculated data. More recently, the focus of the BEAVRS project has been on quantifying uncertainty to further assess the validity of aforementioned results. A close investigation of sources of error shows that uncertainties from operational nuclear data arise primarily from data measurements and processing. While the errors in axial realignment and interpolation seem significant, these sources affect only a small subset of data points near grid spacers and do not persist throughout the entire core. Instead, measurement uncertainty from detector count rates and radial integration dominate the uncertainty in measured data are determined as the most significant sources of error. This uncertainty analysis treated each given burnup step as independent of comparable data at neighboring burnup steps. More recent work has been targeted at understanding how reaction rates vary over time, in order to determine whether calculated reaction rates follow any observable trends. This abstract hones in on transient uncertainty quantification, in order to compare observed data against models for transient behavior. The first section of the paper uses linear regression tools to fit operational data, while the latter portion of the paper explores more complex simulation tools to fit operational data. Ultimately, the BEAVRS benchmark aims to serve as a true non-proprietary international benchmark for the validation of high-fidelity tools. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗