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DOE OSTI2018

Estimation of Evaporation Rate from Gold-Silicon Alloy Based on the Nucleation Time and Nanowire Length Distributions

Abstract—: Nanowires are one of the most promising building blocks for various nanoelectronic devices. Nanowires are usually grown via the so-called vapor-liquid-solid mechanism on the surfaces activated by the droplets of a catalyst (e.g., Au). Here we theoretically studied the impact of the evaporation from the droplet on the nucleation statistics. Within the semi-analyticalapproach, we obtain the relation between the nucleation time distributions and the evaporation rate of atoms from the droplet. We analyze the Si NW length-time dependences to estimate theeffective lifetime of a silicon atom in a gold-silicon alloy at 550°C is about 5 s.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

DOE OSTI2019

Measurement of the Crab Nebula Spectrum Past 100 TeV with HAWC

In this study, we present TeV gamma-ray observations of the Crab Nebula, the standard reference source in ground-based gamma-ray astronomy, using data from the High Altitude Water Cherenkov (HAWC) Gamma-Ray Observatory. In this analysis we use two independent energy estimation methods that utilize extensive air shower variables such as the core position, shower angle, and shower lateral energy distribution. In contrast, the previously published HAWC energy spectrum roughly estimated the shower energy with only the number of photomultipliers triggered. This new methodology yields a much-improved energy resolution over the previous analysis and extends HAWC's ability to accurately measure gamma-ray energies well beyond 100 TeV. The energy spectrum of the Crab Nebula is well fit to a log-parabola shape $\left(\tfrac{{dN}}{{dE}}={\phi }_{0}{\left(E/7\mathrm{TeV}\right)}^{-\alpha -\beta \mathrm{ln}\left(E/7\mathrm{TeV}\right)}\right)$ with emission up to at least 100 TeV. For the first estimator, a ground parameter that utilizes fits to the lateral distribution function to measure the charge density 40 m from the shower axis, the best-fit values are ${\phi }_{o}=(2.35\pm {0.04}_{-0.21}^{+0.20})\times {10}^{-13}$ (TeV cm 2 s) -1 , $\alpha =2.79\pm {0.02}_{-0.03}^{+0.01}$, and $\beta =0.10\pm {0.01}_{-0.03}^{+0.01}$. For the second estimator, a neural network that uses the charge distribution in annuli around the core and other variables, these values are ${\phi }_{o}=(2.31\pm {0.02}_{-0.17}^{+0.32})\times {10}^{-13}$ (TeV cm 2 s) -1 , $\alpha =2.73\pm {0.02}_{-0.02}^{+0.03}$, and β = 0.06 ± 0.01 ± 0.02. The first set of uncertainties is statistical; the second set is systematic. Both methods yield compatible results. Finally, these measurements are the highest-energy observation of a gamma-ray source to date.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2024

Ensuring Solution Uniqueness in Three-Phase Power System State Estimation

This paper is concerned with the issue of potential non-unique solutions in three-phase state estimation. Theory of observability analysis for positive sequence power system state estimation is based on certain assumptions that avoid possibility of multiple solutions. Also, it is shown that observability of a positive sequence network remains independent of the network parameters or the operating state. When extending single-phase observability analysis directly to the three-phase case, this paper considers the possibility of converging to multiple solutions, i.e. solution non-uniqueness, even for cases where state estimator successfully converges. The study illustrates via numerical examples the likelihood of converging to entirely different solutions for certain network parameters. It also examines how the operating state, particularly under unbalanced loading, leads to solution non-uniqueness. The paper then describes an alternative approach to ensure a unique solution in three-phase state estimation. This method aims to accurately and uniquely estimate the state of any unbalanced three-phase system, irrespective of load imbalance, network configuration, existence of synchronous generators or transformers.

Power System State Estimation, Three-Phase, Distri↗

DOE OSTI2024

Probabilistic Analysis of Long-Term Degradation of Microwave Cavity Flow Sensor

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2023

Final Report on Development of Microwave Resonant Cavity Transducer for Fluid Flow Sensing: Development of Microwave Cavity Flow Meter for Advanced Reactor High Temperature Fluids

We are investigating a microwave resonant cavity transducer for flow sensing in the vessel of a high temperature fluid advanced reactor (AR), such as a molten salt cooled reactor (MSCR) or a sodium fast reactor (SFR). This transducer is a hollow metallic cylindrical cavity, with one of the flat walls of the cylinder flexible enough to undergo microscopic deflection due to dynamic fluid pressure. Membrane deflection leads to a shift in the microwave resonant frequency, which can be detected with a spectrum analyzer. We have developed a continuum electromechanics model of the microwave resonant cavity transducer performance. The deflection of the membrane is calculated using equations from the theory of plates and shells for deflection of radially constrained thin circular disk under uniform load. The microwave frequency shift is calculated using the equations from the microwave cavity perturbation theory. The transducer model was validated with proof-of-concept experimental data of water flow sensing with a Brass 360 right circular cylinder with 22.2mm diameter and 203µm thick wall. The cavity was excited through a subwavelength hole in TE 011 mode with resonant frequency f ≈ 17.8GHz. Subsequently, we have performed a preliminary proof-of-principle test of flow sensing in high temperature liquid sodium in environment. For this test, we have developed a cylindrical resonator with the same dimensions as for the Brass 360 cavity. The resonator for high temperature liquid sodium test was machined from stainless steel 316 and electroplated with silver on the interior surfaces. We have also developed and insertion probe consisting of a 50cm WR-42 brass waveguide enclosed in a protective SS316 tube. The cavity was excited through a subwavelength hole on the side of the wall of the cylinder in the TE 011 mode with resonant frequency f ≈ 17.8GHz. The liquid sodium setup consists of a cylindrical vessel with a center feed line, where a transducer inserted through the top cap of the vessel measures velocity of the impinging liquid jet. The sodium flow sensing study was performed in a liquid sodium vessel at 340°C temperature and ambient pressure. The flow rate was changed by varying sodium pump power, and a frequency shift of several hundred kHz was observed. The transducer was removed after 70 days of testing. No visual damage was observed, and the electromagnetic response remained the same. As a calibration experiment, we have assembled a water vessel with a center feed, and with dimensions similar to those of the liquid sodium setup. Water flow sensing was performed before and after liquid sodium test. The responses in both cases are similar and agree with COMSOL computer simulations. Because long-term (multi-year) experimental tests of transducer resilience to harsh environment are not practical, we have developed a probabilistic model of creep to estimate transducer resilience to the harsh environment. The probabilistic model considers diffusion creep under the condition of high temperature and low stress, where the stress and temperature are allowed to be random variables with Gaussian distributions. Using the probabilistic model, we estimate inelastic membrane deflections due to creep for several temperature ranges. We conclude that for temperatures less than 650°C, creep has negligible long-term effect on the transducer performance.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2025

Chemistry imaging and distribution analysis of rare earth elements in coal using LIBS and LA-ICP-MS instruments

Currently, demand for rare earth elements (REEs) increased significantly. Coal is actively evaluated as potential economic sources for extraction of REEs. Here, in this work, laser-induced breakdown spectroscopy (LIBS) was evaluated for rapid estimation of REEs content and their distribution in the natural coal samples. The results were compared with similar laser ablation–inductively coupled plasma–mass spectrometry (LA-ICP-MS) measurements. Thirteen coal samples (nine standard samples and five natural samples) were used in this study. Powder samples were pressed into pellets while coal chunks were directly ablated for data recording. Pellets of the powder standard samples were used to optimize the data acquisition system and then data recorded with this optimized system was used to identify the proper data acquisition and analysis models. After establishing the proper data acquisition system and analysis model using the standard samples, natural coal samples in powder form and their chunks were utilized to record LIBS and LA-ICP-MS spectra. Multivariate calibration models were developed using four of the natural samples, which were evaluated by predicting the REE content in the fifth sample. Principal component analysis was performed on the LIBS data obtained from the natural samples and it classified all the samples with high accuracy. Two-dimensional (2D) elemental mapping on coal chunk samples was also performed using both LIBS and LA-ICP-MS to study the distribution of REEs in the samples. The resulting elemental images and their correlations can be used to infer mineral distributions.

01 COAL, LIGNITE, AND PEAT↗

DOE OSTI2021

Application of Point Precipitation Frequency Estimates to Watersheds

This report documents work sponsored by the U.S. Nuclear Regulatory Commission (NRC) at the Oak Ridge National Laboratory (ORNL) as part of the RES project, “Application of Point Precipitation Frequency Estimates to Watersheds.” This project was implemented as part of the Probabilistic Flood Hazard Assessment (PFHA) Research Program. The objective of the PFHA Research Program is to develop tools and guidance on the use of PFHA methods to risk-inform NRC’s licensing of new facilities as well as licensing and oversight of currently operating facilities as they relate to flooding hazards. Many nuclear power plants (NPPs) are located on or near rivers so riverine flooding hazards need to be considered in their design and operation. Probabilistic riverine flood models are important tools for realistic assessment of flooding risks. However, these models require areal estimates of the depth, duration, and frequency of rainfall distributed over the watershed, which are not often available. Point precipitation frequency estimates are more widely available. For example, the National Oceanic and Atmospheric Administration (NOAA) has published NOAA Atlas 14, which provides point precipitation frequency estimates for 5-minute through 60-day durations at average recurrence intervals of 1-year through 1,000-year. The research documented in this report addresses areal reduction factors (ARFs), which can be used to convert the widely available point precipitation frequency estimates, to estimates of areal precipitation frequency over a watershed. The most widely used ARF source is Technical Paper 29 (TP-29) published by the then U.S. Weather Bureau in 1958. However, both the methods and the underlying precipitation data used to produce TP-29 are seriously out of date. For example, due to the small gauge network available at the time of TP-29’s compilation, ARF estimates developed are only for watersheds smaller than about 400 square miles. Due to the relatively short record lengths of precipitation data available, frequency considerations could not be accurately determined. Other factors such as regional climate and seasonality were not addressed. Several newer methods have been published since TP-29 was developed and both the type and quantity of precipitation data have increased significantly, along with computational resources and analytical tools such as geographic information systems. This report reviewed and assessed the available precipitation products and methods for conducting ARF analysis. The work applied up-to-date precipitation data products and analysis methods with a novel watershed-based approach to investigate how ARF estimates vary across different methods, data sources, geographical locations, return periods, and seasons. The overall findings reported here regarding basic ARF trends are in line with other recent studies showing that ARFs decrease with increasing area, increase with increasing duration, and decrease with increasing return period. This study found significant differences among the available ARF methods. This work also found a strong geographical variability across different US hydrologic regions, suggesting that the ARF are specific to regional climate patterns and geographical characteristics and should not be applied arbitrarily to other locations. The results also reveal the importance of data record length, especially for high return level ARFs. The work reported in NUREG/CR-7271 will assist NRC staff in assessing different classes of ARF methods in conjunction with available rainfall data sets. It will also support the development of guidance for application of point precipitation data in PFHAs. It should be noted that the ARF values presented in this report for any location or region were developed for the purposes of comparing methods and investigating the factors that influence ARFs. They should not be considered official and should not be used in leu of a site-specific analysis.

54 ENVIRONMENTAL SCIENCES↗

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 OSTI2022

Understanding Uncertainties in Tropical Cyclone Rainfall Hazard Modeling Using Synthetic Storms

Tropical cyclone (TC) rainfall hazard assessment is subject to the bias in TC climatology estimation from climate simulations or synthetic downscaling. In this study, we investigate the uncertainty in TC rainfall hazard assessment induced by this bias using both rain gauge and radar observations and synthetic-storm-model-coupled TC rainfall simulations. We identify the storm’s maximum intensity, impact duration, and minimal distance to the site to be the three most important storm parameters for TC rainfall hazard, and the relationship between the important storm parameters and TC rainfall can be well captured by a physics-based TC rainfall model. The uncertainty in the synthetic rainfall hazard induced by the bias in TC climatology can be largely explained by the bias in the important storm parameters simulated by the synthetic storm model. Correcting the distribution of the most biased parameter may significantly improve rainfall hazard estimation. Bias correction based on the joint distribution of the important parameters may render more accurate rainfall hazard estimations; however, the general technical difficulties in resampling from high-dimensional joint probability distributions prevent more accurate estimations in some cases. The results of the study also support future investigation of the impact of climate change on TC rainfall hazards through the lens of future changes in the identified important storm parameters.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Decentralized State Estimation-Based Optimal Integral Model Predictive Control of Voltage and Frequency in the Distribution System Microgrids

Not provided.

Engineering↗

DOE OSTI2023

Distributed Energy Resource (DER) Reliability for Backup Electric Power Systems

Hospitals, emergency services, military bases, ports, airports, industries, commercial facilities, and others rely on backup power systems to provide electricity for their critical loads during grid outages. The purpose of this report it to provide accurate reliability information on commonly deployed distributed energy resources (DERs) to improve quantitative estimates for the reliability of these backup power systems during a grid outage. A backup power system consists of DERs, an electric distribution system with its associated switches and other devices, and mechanisms to control and manage the flow of electricity. Too often, facilities and campuses fail to properly quantify the reliability of their backup power systems. DERs are assumed to be 100% reliable, with the only concern being the availability of fuel. Such assumptions can lead to gross errors in the backup system's reliability estimates, particularly for long-duration outages. This report provides a set of estimates for reliability of emergency diesel generators (EDGs), natural gas prime generators and combined heat and power (CHP) prime movers, solar photovoltaics (PV), wind turbines, and Li-ion battery energy storage systems (BESS). The estimates are derived from empirical data when available and supplemented by modeling results when needed. These reliability estimates are for the DERs ability to provide power during a grid outage, ranging from an hour to 2 weeks.

14 SOLAR ENERGY↗

DOE OSTI2022

Exclusive J/$\psi$ detection and physics with ECCE

The EIC Comprehensive Chromodynamics Experiment (ECCE) detector has been recommended as a reference design for the proposed Electron-Ion Collider (EIC) program. Here, this paper presents simulation studies of exclusive J/$\psi$ detection and selected physics impact results in EIC using the projected ECCE detector concept. Exclusive quarkonium photoproduction is one of the most popular processes in EIC, which has a large cross section and a simple final state. Due to the gluonic nature of the exchange Pomeron, this process can be related to the gluon distributions in the nucleus. Preliminary results estimate the excellent statistics benefited from the large cross section of J/$\psi$ photoproduction and superior performance of ECCE detector concept. The precise measurement of exclusive J/$\psi$ photoproduction at EIC will help us to more deeply understand nuclear gluon distributions, near threshold production mechanism and nucleon mass structure.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2023

Velocity-dependent J-factors for Milky Way dwarf spheroidal analogues in cosmological simulations

We study the impact of the dark matter velocity distribution modelling on signals from velocity-dependent dark matter annihilation in Milky Way dwarf spheroidal galaxies. Using the high resolution APOSTLE simulations, we identify analogues corresponding to Milky Way dwarf spheroidal galaxies, and from these directly determine the dark matter pair-wise relative velocity distribution, and compare to best-fitting Maxwell-Boltzmann distribution models. For three velocity-dependent annihilation models, p-wave, d-wave, and the Sommerfeld model, we quantify the errors introduced when using the Maxwell-Boltzmann parameterization. We extract a simple power-law relation between the maximum circular velocity of the dwarf spheroidal analogue and the peak speed of the Maxwell-Boltzmann distribution. We show that this relation can be used to accurately calculate the dark matter relative velocity distribution, and find that it allows us to estimate the dark matter annihilation signal without the need to directly calculate the relative velocity distribution for each galaxy. The scatter in the J-factors calculated from the analogues dominates the uncertainty obtained when compared to the J-factor as determined from the observational data for each dwarf spheroidal, with the largest scatter from d-wave models and the smallest from Sommerfeld models.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2019

Attack Identification and Correction for PMU GPS Spoofing in Unbalanced Distribution Systems

Due to the vulnerability of civilian global positioning system (GPS) signals, the accuracy of phasor measurement units (PMUs) can be greatly compromised by GPS spoofing attacks (GSAs), which introduce phase shifts into true phase angle measurements. Focusing on simultaneous GSAs for multiple PMU locations, this paper proposes a novel identification and correction algorithm in distribution systems. A sensitivity analysis of state estimation residuals on a single GSA phase angle is firstly implemented. An identification algorithm using a probing technique is proposed to determine the locations of spoofed PMUs and the ranges of GSA phase shifts. Based on the identification results, these GSA phase shifts are determined via an estimation algorithm that minimizes the mismatch between measurements and system states. Finally, with the attacked PMU data corrected, the system states are recovered. Simulations in unbalanced IEEE 34-bus and 123-bus distribution systems demonstrates the efficiency and accuracy of the proposed method.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2019

Size Selectivity of Sampling Gears Used to Sample Kokanee

Abstract Kokanee Oncorhynchus nerka provide valued recreational fisheries and also serve as a prey resource for economically, socially, and ecologically important fishes. As such, management of kokanee is a major focus of natural resource agencies. Kokanee are typically monitored using midwater trawls, but the interpretation of data collected using midwater trawls is difficult due to the unknown size selectivity of the gear. We sought to assess the length selectivity of midwater trawls by comparing estimates obtained from midwater trawls with estimates obtained from gill nets adjusted for size selectivity. Experimental curtain gill nets and midwater trawls were used in conjunction to sample kokanee in seven lentic systems in Idaho. The size selectivity of gill nets was estimated by accounting for the probability of encounter and the probability of retention. Estimates of size selectivity were then used to adjust the length distribution of fish sampled in gill nets. The adjusted length distribution of fish sampled in gill nets was compared with estimates obtained from midwater trawls to identify potential size selectivity of midwater trawls. A pattern of size selectivity was apparent for both sampling techniques. The average length of kokanee sampled with midwater trawls was 111 mm; whereas, kokanee sampled with gill nets had a mean length of 235 mm. Our results suggest experimental gill nets are useful for common sampling of kokanee (e.g., trend monitoring) because the gear is less size selective than midwater trawls and is adjustable for size selectivity. However, midwater trawls are likely the best gear for addressing questions associated with early life history. Overall, our results provide a better understanding of gill-net and midwater trawl selectivity and ultimately improve the ability to sample and manage the species.

Klein, Zachary B.↗

DOE OSTI2021

Rare Events via Cross-Entropy Population Monte Carlo

Rare events are events that happen with very low frequency. Estimating rare event probabilities using Monte Carlo techniques is computationally expensive, often to the point of intractability, and special methods are required. Importance sampling (IS) is a well known technique that uses a proposal distribution in place of a target distribution to lower the variance of the estimator. Key to the success of IS methods is the choice of a proposal distribution, or the parameters governing the distribution. Adaptive importance sampling improves the parameters of a family or population of proposal distributions iteratively through trials. We present a novel cross-entropy population Monte Carlo algorithm, which adapts the parameters of proposals through the cross-entropy method. The proposed method stands apart from previous work in that we are not optimizing a mixture distribution. Instead, we leverage deterministic mixture weights and optimize the distributions individually through a reinterpretation of the typical derivation of the cross-entropy method. Demonstrations on rare event examples show that the algorithm can outperform existing resampling based population Monte Carlo methods, especially for higher-dimensional problems. Finally, we also demonstrate efficacy on a conjunction analysis problem.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2018

Clusterdv: a simple density-based clustering method that is robust, general and automatic

Abstract Motivation How to partition a dataset into a set of distinct clusters is a ubiquitous and challenging problem. The fact that data vary widely in features such as cluster shape, cluster number, density distribution, background noise, outliers and degree of overlap, makes it difficult to find a single algorithm that can be broadly applied. One recent method, clusterdp, based on search of density peaks, can be applied successfully to cluster many kinds of data, but it is not fully automatic, and fails on some simple data distributions. Results We propose an alternative approach, clusterdv, which estimates density dips between points, and allows robust determination of cluster number and distribution across a wide range of data, without any manual parameter adjustment. We show that this method is able to solve a range of synthetic and experimental datasets, where the underlying structure is known, and identifies consistent and meaningful clusters in new behavioral data. Availability and implementation The clusterdv is implemented in Matlab. Its source code, together with example datasets are available on: https://github.com/jcbmarques/clusterdv. Supplementary information Supplementary data are available at Bioinformatics online.

Marques, João C.↗

DOE OSTI2020

eFESTA: Ensemble Feature Exploration with Surface Density Estimates

We propose surface density estimate (SDE) to model the spatial distribution of surface features-isosurfaces, ridge surfaces, and streamsurfaces-in 3D ensemble simulation data. The inputs of SDE computation are surface features represented as polygon meshes, and no field datasets are required (e.g., scalar fields or vector fields). The SDE is defined as the kernel density estimate of the infinite set of points on the input surfaces and is approximated by accumulating the surface densities of triangular patches. We also propose an algorithm to guide the selection of a proper kernel bandwidth for SDE computation. An ensemble Feature Exploration method based on Surface densiTy EstimAtes (eFESTA) is then proposed to extract and visualize the major trends of ensemble surface features. For an ensemble of surface features, each surface is first transformed into a density field based on its contribution to the SDE, and the resulting density fields are organized into a hierarchical representation based on the pairwise distances between them. The hierarchical representation is then used to guide visual exploration of the density fields as well as the underlying surface features. We demonstrate the application of our method using isosurface in ensemble scalar fields, Lagrangian coherent structures in uncertain unsteady flows, and streamsurfaces in ensemble fluid flows.

Computational modeling↗