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DOE OSTI2017

Alternatives to argon for gas stopping volumes in the B194 neutron imager

In a recent experiment at Lawrence Berkeley National Laboratory, the 40Ar(d,p)41Ar excitation function between 3-7 MeV was measured, confirming a previous estimation that there may be an intolerable radiation dose from 41Ar production by slowing to rest 6.74 MeV deuterons in the gas cell of the neutron imaging facility being constructed in B194. Gas alternatives to argon are considered, including helium, nitrogen (N2), neon, sulfur hexafluoride (SF6), krypton, and xenon, as well as high atomic number solid backings such as tantalum.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2020

Real Time Applications Using Linear State Estimation Technology (RTA/LSE)

Electric Power Group, LLC (EPG) was awarded DOE OE0000849 to design, develop, and demonstrate three real-time applications for monitoring power system stability. The applications use phasor measurements and processing by a linear state estimator (LSE) to improve system visibility and accuracy. These applications leverage the large and expanding phasor measurement systems being deployed by utilities throughout the world, and specifically in the United States. Phasor measurements provide a much more detailed view of the power systems than traditional SCADA systems, so can provide better visibility of events and an early warning of developing problems. These three applications are real-time contingency analysis (RTCA), area angle monitoring (AAM), and a voltage stability index (VSI). The project was fully completed as proposed. All three applications were successfully implemented and demonstrated. There were challenges the caused project delays, however. While the RTCA is based on well-known concepts and readily available tools, its deployment using phasor measurements meant it needed to be adapted to sometimes sparse measurements and limited coverage areas. EPG met these challenges with extensive modeling and testing. The AAM is based on unproven research, so EPG had to deal with a lot of unknowns and develop additional methods for practical implementation. These activities took more time than anticipated, so required extra time for development. In addition, there was difficulty getting adequate measurement locations for successful deployment and utility installation delays. Consequently, the project required a time extension to complete. These three real-time applications, RTCA, AAM, and VSI, use only phasor measurement input. Since they do not require the EMS or other measurement systems, they can serve as a backup and security check for the EMS. Phasor measurements are validated and extended by an LSE. The LSE will always produce an output even when some inputs are impaired, so the RT applications will operate even when the EMS state estimator does not converge and the applications it supports cannot function. Consequently, these RT applications can provide valuable additional reliability for control center operation.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2018

Efficient Generalizable Deep Learning

Stochastic optimization is a fundamental field of research for machine learning. Stochastic gradient descent (SGD) and related methods provide a feasible means to train complicated prediction models over large datasets. SGD, however, does not explicitly address the problem of overfitting, which can lead to predictions that perform poorly on new data. This difference between loss performance on unseen testing data verses that of training data defines the generalization gap of a model. We introduce a new computational kernel called Stochastic Hessian Projection (SHP) that uses a maximum likelihood framework to simultaneously estimate gradient noise covariance and local curvature of the loss function. Our analysis illustrates that these quantities affect the evolution of parameter uncertainty and therefore generalizability. We show how these computations allow us to predict the generalization gap without requiring holdout data. Explicitly assessing this metric for generalizability during training may improve machine learning predictions when data is scarce and understanding prediction variability is critical.

42 ENGINEERING↗

DOE OSTI2026

Turbine Damage Probability

Damage probability maps for offshore wind turbines exposed to tropical cyclones (TCs) under both historical and future climate scenarios along the U.S. Atlantic and Gulf Coasts are presented in this dataset. TCs are generated using the Risk Analysis Framework for Tropical Cyclones (RAFT), forced by CMIP6 historical and future global climate simulations. Maximum wind speeds for 20- and 50-year TCs are processed through a fragility function specific to offshore wind (OSW) turbines in order to estimate the probability of damage – specifically yielding and buckling – based on wind speed intensity.

17 WIND ENERGY↗

DOE OSTI2021

Training Restricted Boltzmann Machines With a D-Wave Quantum Annealer

Restricted Boltzmann Machine (RBM) is an energy-based, undirected graphical model. It is commonly used for unsupervised and supervised machine learning. Typically, RBM is trained using contrastive divergence (CD). However, training with CD is slow and does not estimate the exact gradient of the log-likelihood cost function. In this work, the model expectation of gradient learning for RBM has been calculated using a quantum annealer (D-Wave 2000Q), where obtaining samples is faster than Markov chain Monte Carlo (MCMC) used in CD. Training and classification results of RBM trained using quantum annealing are compared with the CD-based method. The performance of the two approaches is compared with respect to the classification accuracies, image reconstruction, and log-likelihood results. The classification accuracy results indicate comparable performances of the two methods. Image reconstruction and log-likelihood results show improved performance of the CD-based method. It is shown that the samples obtained from quantum annealer can be used to train an RBM on a 64-bit “bars and stripes” dataset with classification performance similar to an RBM trained with CD. Though training based on CD showed improved learning performance, training using a quantum annealer could be useful as it eliminates computationally expensive MCMC steps of CD.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2023

Systematic comparison of local approaches for isotopically nonstationary metabolic flux analysis

Quantification of reaction fluxes of metabolic networks can help us understand how the integration of different metabolic pathways determine cellular functions. Yet, intracellular fluxes cannot be measured directly but are estimated with metabolic flux analysis (MFA) that relies on the patterns of isotope labeling of metabolites in the network. For metabolic systems, typical for plants, where all potentially labeled atoms effectively have only one source atom pool, only isotopically nonstationary MFA can provide information about intracellular fluxes. There are several global approaches that implement MFA for an entire metabolic network and estimate, at once, a steady-state flux distribution for all reactions with identifiable fluxes in the network. In contrast, local approaches deal with estimation of fluxes for a subset of reactions, with smaller data demand for flux estimation. Here we present a systematic comparative review and benchmarking of the existing local approaches for isotopically nonstationary MFA. The comparison is conducted with respect to the required data and underlying computational problems solved on a synthetic network example. Furthermore, we benchmark the performance of these approaches in estimating fluxes for a subset of reactions using data obtained from the simulation of nitrogen fluxes in the Arabidopsis thaliana core metabolism. The findings pinpoint practical aspects that need to be considered when applying local approaches for flux estimation in large-scale plant metabolic networks.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2025

Mesoscale Linear Elastic Modeling and Homogenization of Marine Energy Composites

The design of fiber-reinforced composite (FRC)-based components for marine energy applications necessitates a fundamental understanding of material properties and the resulting geometry to predict long-term performance. In this work, we present a modeling workflow to predict linear elastic and diffusive bulk properties at the mesoscale for an idealized geometry based on knowledge of fiber and resin properties. A parametric study was performed to identify the key model input parameters that influence bulk properties. Furthermore, we demonstrate how bulk properties can be leveraged in high-fidelity image-based simulations, where imperfections in tow geometry and voids captured during X-ray computed tomography imaging are explicitly represented within the simulation. Bulk properties of interest include moduli, Poisson’s ratios, hygroscopic swelling, diffusivity, and moisture uptake, which are key parameters for characterizing FRC performance within marine environments. Modeling predictions agreed well with experimental data, except for estimating swelling coefficients, likely due to crack accumulation as a function of moisture uptake. The mesoscale modeling workflow ultimately highlights a versatile framework for understanding the influence of material and geometric properties, which can be leveraged to rapidly assess new FRC-based components.

computational mechanics↗

DOE OSTI2017

Orbits for 18 Visual Binaries and Two Double-line Spectroscopic Binaries Observed with HRCAM on the CTIO SOAR 4 m Telescope, Using a New Bayesian Orbit Code Based on Markov Chain Monte Carlo

We present orbital elements and mass sums for 18 visual binary stars of spectral types B to K (five of which are new orbits) with periods ranging from 20 to more than 500 yr. For two double-line spectroscopic binaries with no previous orbits, the individual component masses, using combined astrometric and radial velocity data, have a formal uncertainty of ∼0.1 M{sub ⊙}. Adopting published photometry and trigonometric parallaxes, plus our own measurements, we place these objects on an H-R diagram and discuss their evolutionary status. These objects are part of a survey to characterize the binary population of stars in the Southern Hemisphere using the SOAR 4 m telescope+HRCAM at CTIO. Orbital elements are computed using a newly developed Markov chain Monte Carlo (MCMC) algorithm that delivers maximum-likelihood estimates of the parameters, as well as posterior probability density functions that allow us to evaluate the uncertainty of our derived parameters in a robust way. For spectroscopic binaries, using our approach, it is possible to derive a self-consistent parallax for the system from the combined astrometric and radial velocity data (“orbital parallax”), which compares well with the trigonometric parallaxes. We also present a mathematical formalism that allows a dimensionality reduction of the feature space from seven to three search parameters (or from 10 to seven dimensions—including parallax—in the case of spectroscopic binaries with astrometric data), which makes it possible to explore a smaller number of parameters in each case, improving the computational efficiency of our MCMC code.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2021

Orbits and Masses of Binaries from Speckle Interferometry at SOAR

We present results from Speckle inteferometric observations of 15 visual binaries and one double-line spectroscopic binary, carried out with the HRCam Speckle camera of the SOAR 4.1 m telescope. These systems were observed as a part of an on-going survey to characterize the binary population in the solar vicinity, out to a distance of 250 pc. We obtained orbital elements and mass sums for our sample of visual binaries. The orbits were computed using a Markov Chain Monte Carlo algorithm that delivers maximum likelihood estimates of the parameters, as well as posterior probability density functions that allow us to evaluate their uncertainty. Their periods cover a range from 5 yr to more than 500 yr; and their spectral types go from early A to mid M, implying total system masses from slightly more than 4M{sub ⊙} down to 0.2M {sub ⊙}. They are located at distances between approximately 12 and 200 pc, mostly at low Galactic latitude. For the double-line spectroscopic binary YSC8, we present the first combined astrometric/radial-velocity orbit resulting from a self-consistent fit, leading to individual component masses of 0.897 ± 0.027 M {sub ⊙} and 0.857 ± 0.026 M {sub ⊙}; and an orbital parallax of 26.61 ± 0.29 mas, which compares very well with the Gaia DR2 trigonometric parallax (26.55 ± 0.27 mas). In combination with published photometry and trigonometric parallaxes, we place our objects on an H-R diagram and discuss their evolutionary status. We also present a thorough analysis of the precision and consistency of the photometry available for them.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2017

The Correlation between Halo Mass and Stellar Mass for the Most Massive Galaxies in the Universe

We present measurements of the clustering of galaxies as a function of their stellar mass in the Baryon Oscillation Spectroscopic Survey. We compare the clustering of samples using 12 different methods for estimating stellar mass, isolating the method that has the smallest scatter at fixed halo mass. In this test, the stellar mass estimate with the smallest errors yields the highest amplitude of clustering at fixed number density. We find that the PCA stellar masses of Chen et al. clearly have the tightest correlation with halo mass. The PCA masses use the full galaxy spectrum, differentiating them from other estimates that only use optical photometric information. Using the PCA masses, we measure the large-scale bias as a function of M{sub ∗} for galaxies with logM{sub ∗}⩾11.4, correcting for incompleteness at the low-mass end of our measurements. Using the abundance matching ansatz to connect dark matter halo mass to stellar mass, we construct theoretical models of b(M{sub ∗}) that match the same stellar mass function but have different amounts of scatter in stellar mass at fixed halo mass, σ{sub logM∗}. Using this approach, we find σ{sub logM∗}=0.18{sub −0.02}{sup +0.01}. This value includes both intrinsic scatter as well as random errors in the stellar masses. To partially remove the latter, we use repeated spectra to estimate statistical errors on the stellar masses, yielding an upper limit to the intrinsic scatter of 0.16 dex.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2014

Evaluating Safeguards Benefits of Process Monitoring as compared with Nuclear Material Accountancy

This paper illustrates potential safeguards benefits that process monitoring (PM) may have as a diversion deterrent and as a complementary safeguards measure to nuclear material accountancy (NMA). This benefit is illustrated by quantifying the standard deviation associated with detecting a considered material diversion scenario using either an NMA-based method or a PM-based approach. To illustrate the benefits of PM for effective safeguards, we consider a reprocessing facility. We assume that the diversion of interest for detection manifests itself as a loss of Pu caused by abnormally operating a dissolver for an extended period to accomplish protracted diversion (or misdirection) of Pu to a retained (unconditioned) waste stream. For detecting the occurrence of this diversion (which involves anomalous operation of the dissolver), we consider two different data evaluation and integration (DEI) approaches, one based on NMA and the other based on PM. The approach based on PM does not directly do mass balance calculations, but rather monitors for the possible occurrence of anomaly patterns related to potential loss of nuclear material. It is thus assumed that the loss of a given mass amount of nuclear material can be directly associated with the execution of proliferation-driven activities that trigger the occurrence of an anomaly pattern consisting of series of events or signatures occurring at different unit operations and time instances. By effectively assessing these events over time and space, the PM-based DEI approach tries to infer whether this specific pattern of events has occurred and how many times within a given time period. To evaluate the goodness of PM, the 3 Sigma of the estimated mass loss is computed under both DEI approaches as function of the number of input batches processed. Simulation results are discussed.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗

DOE OSTI2018

Method of solar power prediction

Techniques for estimating direct and diffuse sunlight reaching a location as a function of time using color whole sky images are provided. In one aspect, a method for forecasting solar insolation is provided that includes the steps of: obtaining color whole sky images using a digital camera which are taken at different times, and wherein an image of a solar disk is present in at least one of the color whole sky images; creating sky transparency images from the color whole sky images; determining atmospheric solar scattering based on a width of the solar disk in the color whole sky images; determining cloud motion trajectories from a time series of the sky transparency images; and calculating the solar insolation as a function of time using the sky transparency, the atmospheric solar scattering, and the cloud motion trajectories. A system for forecasting solar insolation is also provided.

Hamann, Hendrik F.↗

DOE OSTI2016

Material Properties and Temperature Effects Quantified for Slurry Wear - 16141

Literature indicates that the hardness of solid particles relative to the target material hardness and temperature influence erosion. Investigations of temperature effects on erosion also show that erosion resistance is a function of target material's homologous temperature to melting point temperature. While relative hardness effects on erosion and temperature effects on erosion have been investigated independently, their combined effect has not been evaluated. This paper summarizes a review of relevant literature on relative hardness and temperature effects on erosion and via probabilistic calculations, quantifies the combined effect of relative hardness and temperature on liquid-particle induced wear, or slurry wear. These insights can assist material selection and plant operations at waste processing facilities. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2016

Effect of reaction atmosphere on structural and optical properties of hexagonal molybdenum oxide (h-MoO{sub 3})

The present work aims to synthesize single phase h-MoO{sub 3} nanocrytals by chemical precipitation method exposed under different reaction atmospheres. The reaction atmosphere have been successfully tuned as air, nitrogen and argon and studied its effects on structural, functional, morphology and optical properties by using X-ray diffraction (XRD), scanning electron microscopy (SEM), Fourier transform infrared (FT-IR) spectroscopy and diffuse reflectance spectroscopy (DRS) measurements. The XRD result indicates that the sample exhibits characteristic hexagonal phase of MoO{sub 3}. The crystallite size is estimated by well known Scherrer’s method. The crystallite size is relative small in the case of sample prepared at argon atmosphere. The functional groups such as Mo-O, N-H and O-H are identified from FT-IR spectroscopy. The particle exhibits rod like morphology with perfect hexagonal cross-section. The optical absorption observed at 420-450 nm corresponds to fundamental optical absorption by h-MoO{sub 3}. The band gap values are estimated using Kublka-Munk (K-M) function and found to be 2. 87 eV, 2.93 eV and 2.97 eV for samples synthesized under air, nitrogen and argon, respectively.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2014

Accurate adiabatic correction in the hydrogen molecule

A new formalism for the accurate treatment of adiabatic effects in the hydrogen molecule is presented, in which the electronic wave function is expanded in the James-Coolidge basis functions. Systematic increase in the size of the basis set permits estimation of the accuracy. Numerical results for the adiabatic correction to the Born-Oppenheimer interaction energy reveal a relative precision of 10{sup −12} at an arbitrary internuclear distance. Such calculations have been performed for 88 internuclear distances in the range of 0 < R ⩽ 12 bohrs to construct the adiabatic correction potential and to solve the nuclear Schrödinger equation. Finally, the adiabatic correction to the dissociation energies of all rovibrational levels in H{sub 2}, HD, HT, D{sub 2}, DT, and T{sub 2} has been determined. For the ground state of H{sub 2} the estimated precision is 3 × 10{sup −7} cm{sup −1}, which is almost three orders of magnitude higher than that of the best previous result. The achieved accuracy removes the adiabatic contribution from the overall error budget of the present day theoretical predictions for the rovibrational levels.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2023

Bootstrapping outperforms community‐weighted approaches for estimating the shapes of phenotypic distributions

Abstract Estimating phenotypic distributions of populations and communities is central to many questions in ecology and evolution. These distributions can be characterized by their moments (mean, variance, skewness and kurtosis) or diversity metrics (e.g. functional richness). Typically, such moments and metrics are calculated using community‐weighted approaches (e.g. abundance‐weighted mean). We propose an alternative bootstrapping approach that allows flexibility in trait sampling and explicit incorporation of intraspecific variation, and show that this approach significantly improves estimation while allowing us to quantify uncertainty. We assess the performance of different approaches for estimating the moments of trait distributions across various sampling scenarios, taxa and datasets by comparing estimates derived from simulated samples with the true values calculated from full datasets. Simulations differ in sampling intensity (individuals per species), sampling biases (abundance, size), trait data source (local vs. global) and estimation method (two types of community‐weighting, two types of bootstrapping). We introduce the traitstrap R package, which contains a modular and extensible set of bootstrapping and weighted‐averaging functions that use community composition and trait data to estimate the moments of community trait distributions with their uncertainty. Importantly, the first function in the workflow, trait_fill , allows the user to specify hierarchical structures (e.g. plot within site, experiment vs. control, species within genus) to assign trait values to each taxon in each community sample. Across all taxa, simulations and metrics, bootstrapping approaches were more accurate and less biased than community‐weighted approaches. With bootstrapping, a sample size of 9 or more measurements per species per trait generally included the true mean within the 95% CI. It reduced average percent errors by 26%–74% relative to community‐weighting. Random sampling across all species outperformed both size‐ and abundance‐biased sampling. Our results suggest randomly sampling ~9 individuals per sampling unit and species, covering all species in the community and analysing the data using nonparametric bootstrapping generally enable reliable inference on trait distributions, including the central moments, of communities. By providing better estimates of community trait distributions, bootstrapping approaches can improve our ability to link traits to both the processes that generate them and their effects on ecosystems.

Maitner, Brian S.↗

DOE OSTI2019

Seismoacoustic Analysis of Chemical Explosions at the Nevada National Security Site

In recent years, two sets of chemical explosions have been conducted at the Nevada National Security Site (NNSS): 6 explosions from Phase I of the Source Physics Experiment (SPE) and 4 explosions from the Forensics Surface Events (FSE). We have estimated the explosive yield and depth-of-burial/height-of-burst of both from the synthesis of seismic and low-frequency acoustic data. Analysis of the seismic signal is performed using a waveform envelope technique. Using seismic data only, however, there is a tradeoff between the yield and depth or height of the explosion, which becomes especially acute for near-surface events. This tradeoff between yield and depth/height can be broken by including complementary analysis of the acoustic signal using the acoustic waveform inversion method. The acoustic signal also has a strong tradeoff between a yield and depth/height, but the slope is opposite that of the seismic for near-surface events. We use a likelihood function to combine the seismic and acoustic analysis and improve our estimates of yield and depth/height for these sets of explosions. The results are generally consistent with the known parameters, but can be improved upon by higher-frequency seismic analysis and improved acoustic impulse scaling for large scaled depths-of-burial. These events serve as prime examples of data fusion from multiple data streams. The challenge will be to apply the method to events at longer regional distances where the seismic signals will include phases traveling in the upper mantle, and the acoustic signals will be recorded as infrasound signals, which are subject to atmospheric variability.

58 GEOSCIENCES↗

DOE OSTI2016

CHIRP-Like Signals: Estimation, Detection and Processing A Sequential Model-Based Approach

Chirp signals have evolved primarily from radar/sonar signal processing applications specifically attempting to estimate the location of a target in surveillance/tracking volume. The chirp, which is essentially a sinusoidal signal whose phase changes instantaneously at each time sample, has an interesting property in that its correlation approximates an impulse function. It is well-known that a matched-filter detector in radar/sonar estimates the target range by cross-correlating a replicant of the transmitted chirp with the measurement data reflected from the target back to the radar/sonar receiver yielding a maximum peak corresponding to the echo time and therefore enabling the desired range estimate. In this application, we perform the same operation as a radar or sonar system, that is, we transmit a “chirp-like pulse” into the target medium and attempt to first detect its presence and second estimate its location or range. Our problem is complicated by the presence of disturbance signals from surrounding broadcast stations as well as extraneous sources of interference in our frequency bands and of course the ever present random noise from instrumentation. First, we discuss the chirp signal itself and illustrate its inherent properties and then develop a model-based processing scheme enabling both the detection and estimation of the signal from noisy measurement data.

42 ENGINEERING↗