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At least 1,225 records · Page 68

Si/TiO 2 Tandem-Junction Microwire Arrays for Unassisted Solar-Driven Water Splitting

In this work, tandem-junction microwire array photoelectrodes have been fabricated by coating np + -Si radial homojunction microwire arrays sequentially with fluorine-doped tin oxide (FTO) and titanium dioxide (TiO 2 ). These photoelectrodes effected unassisted water splitting under simulated 1 Sun conditions with an open-circuit potential ($E_{\text{oc}}$) of –1.5 V vs the formal potential for oxygen evolution, $E^0$'(OH – /O 2 ), a current density at $E = E^0$'(OH – /O 2 ) of 0.78 mA cm –2 , a fill factor ($\textit{ff}$) = 0.51, and a photovoltaic-biased photoelectrochemical ideal regenerative cell efficiency of 0.6%.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Comparison of Machine Learning Algorithms for Natural Gas Identification with Mixed Potential Electrochemical Sensor Arrays

Mixed-potential electrochemical sensor arrays consisting of indium tin oxide (ITO), La 0.87 Sr 0.13 CrO 3 , Au, and Pt electrodes can detect the leaks from natural gas infrastructure. Algorithms are needed to correctly identify natural gas sources from background natural and anthropogenic sources such as wetlands or agriculture. We report for the first time a comparison of several machine learning methods for mixture identification in the context of natural gas emissions monitoring by mixed potential sensor arrays. Random Forest, Artificial Neural Network, and Nearest Neighbor methods successfully classified air mixtures containing only CH 4 , two types of natural gas simulants, and CH 4 +NH 3 with >98% identification accuracy. The model complexity of these methods were optimized and the degree of robustness against overfitting was determined. Finally, these methods are benchmarked on both desktop PC and single-board computer hardware to simulate their application in a portable internet-of-things sensor package. The combined results show that the random forest method is the preferred method for mixture identification with its high accuracy (>98%), robustness against overfitting with increasing model complexity, and had less than 10 ms training time and less than 0.1 ms inference time on single-board computer hardware.

03 NATURAL GAS↗

Compact and multi-view solid state neutral particle analyzer arrays on National Spherical Torus Experiment-Upgrade

A compact and multi-view Solid State Neutral Particle Analyzer (SSNPA) diagnostic based on silicon photodiode arrays has been successfully tested on the National Spherical Torus Experiment-Upgrade (NSTX-U). The SSNPA diagnostic provides spatially, temporally, and pitch-angle resolved measurements of fast-ion distribution by detecting fast neutral flux resulting from charge exchange (CX) reactions. The system consists of three 16-channel subsystems: t-SSNPA viewing the plasma mid-radius and neutral beam (NB) line #2 tangentially, r-SSNPA viewing the plasma core and NB line #1 radially and p-SSNPA with no intersection with any NB lines. Due to the setup geometry, the active CX signals of t-SSNPA and r-SSNPA are mainly sensitive to passing and trapped particles respectively. In addition, both t-SSNPA and r-SSNPA utilize three vertically stacked arrays with different filter thickness to obtain coarse energy information. The experimental data show that all channels are operational. The signal to noise ratio is typically larger than 10 and the main noise is x-ray induced signal. The active and passive CX signals are clearly observed on t-SSNPA and r-SSNPA during NB modulation. The SSNPA data also indicate significant losses of passing particles during sawteeth, while trapped particles are weakly affected. Fluctuations up to 120 kHz, have been observed on SSNPA, and they are strongly correlated with magnetohydrodynamics (MHD) instabilities.

Charge exchange neutral particle fast ion distribu↗

Geometric concepts for stellarator permanent magnet arrays

The development of stellarators that use permanent magnet arrays to shape their confining magnetic fields has been a topic of recent interest, but the requirements for how such magnets must be shaped, manufactured, and assembled remain to be determined. To address these open questions, we have performed a study of geometric concepts for magnet arrays with the aid of the newly developed MAGPIE code. A proposed experiment similar to the National Compact Stellarator Experiment (NCSX) is used as a test case. Two classes of magnet geometry are explored: curved bricks that conform to a regular grid in cylindrical coordinates, and hexahedra that conform to the toroidal plasma geometry. In addition, we test constraints on the magnet polarization. While magnet configurations constrained to be polarized normally to a toroidal surface around the plasma are unable to meet the required magnetic field parameters when subject to physical limitations on the strength of present-day magnets, configurations with unconstrained polarizations are shown to satisfy the physics requirements for a targeted plasma.

stellarator, permanent magnet, optimization↗

CasCollect: Detecting cas genes and CRISPR arrays in raw sequence data v1

This software examines raw Illumina sequence data files for cas genes and CRISPR arrays, either to be used as evidence of genome editing or for basic analysis of bacterial genomes. It translates sequencing reads into peptide sequences, and runs these against sensitive hidden Markov models for numerous Cas protein families. The set of hit read seeds is then expanded leftward and rightward by sequence matching to remaining reads, and after multiple cycles, this small fraction of the original reads is assembled to produce Cas operons. A separate mode using known CRISPR repeat sequences for a genus are used to identify CRISPR arrays that may be in genomic locations that are isolated from Cas genes.SAND2019-11770 M Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA0003525.

Williams, Kelly↗

Temporal light modulation: A phantom array visibility measure

At temporal light modulation (TLM) frequencies between 80 Hz and 20 000 Hz observers may perceive a series of repeated images called the phantom array effect (PAE) when they move their eyes in large saccades across a modulating light source or across a scene lit by the modulating light source. To date, there is no well-established measure for quantifying PAE visibility, but there is growing awareness of the need for one among design professionals and sensitive populations. This paper documents a new measure, the phantom array visibility measure (PAVM), which is based on the results of recent human factors experiments. The measure follows the mathematical underpinning used by the flicker visibility measure and the stroboscopic visibility measure, where the time-domain TLM waveform is converted into its Fourier frequency components; each component is evaluated through a threshold curve of modulation depth, then summed through an equation employing a Minkowski exponent. This scales the PAVM so that a value of 1 indicates a waveform at a threshold visibility in the conditions of the underlying experiment.

Tan, J.↗

STILGAR Seismic Array Data

Two three-component dense seismic arrays were deployed above an active limestone mine in Pleasant Gap, Pennsylvania; one in the fall and one in the spring of 2023. Each campaign lasted approximately four weeks and included 80 to 100 seismic stations with stations spaced between 100 and 400 meters apart. Each campaign also included several small dense seismic arrays. Two types of seismic stations were deployed including FairfieldNodal ZLand 3C All-in-One seismometers and Geospace 3C GS-ONE geophone paired with GSX3 and GSX4 dataloggers. This dataset includes ~ 4 TB of three-component continuously recorded seismic data in the miniseed format data from both campaigns as well as a readme file for the data structure.

58 GEOSCIENCES↗

Fourier-method beam analysis for coherent vertical cavity surface emitting laser arrays

Effective engineering and exploitation of coherently coupled vertical cavity surface emitting laser arrays will benefit from simple and fast characterization of the optical coupling and coherence. We propose a Fourier method of analyzing beam profiles as an alternative to the prior beam visibility analysis and show that the mode suppression ratio and phase between a pair of supermodes can be extracted. Our analysis enables fast quantitative determination of the array coherence and supermode characteristics.

Strzebonski, Pawel (ORCID:0000000156286296)↗

Altering apparent optical properties with an array of semitransparent mesoscale structures

The ability to control and optimize interactions between light and matter has much utility in engineering design. A well-researched way to achieve optical property modulation is via the use of optical metamaterials, which feature sub-wavelength scale surface structures. In this work, an alternative approach for modulating optical properties is presented using a composite surface modified with a periodic array of semitransparent hemispherical shell mesoscale structures which are larger than the incident light wavelength. A ray-tracing simulation approach is used to predict the optical behavior for an arrayed surface. At oblique angles of incidence, significant increases and decreases in apparent absorptance are achieved via the use of optically thick and thin shells, respectively. Additionally, a potential application to solar cells is described with optimal spectral behavior achieved via the use of semitransparent external structures.

Kucuktas, Onur A.↗

Interplay between gain and loss in arrays of nonlinear plasmonic nanoparticles: toward parametric downconversion and amplification

With the help of a theoretical model and finite-difference time-domain (FDTD) simulations based on the hydrodynamic–Maxwell model, we examine the effect of difference-frequency generation (DFG) in an array of L-shaped metal nanoparticles (MNPs) characterized by intrinsic plasmonic nonlinearity. The outcomes of the calculations reveal the spectral interplay between gain and loss in the vicinity of the fundamental frequency of the localized surface plasmon resonances. Subsequently, we identify different array thicknesses and pumping regimes facilitating parametric amplification and spontaneous parametric downconversion. Our results suggest that the parametric amplification regime becomes feasible on a scale of hundreds of nanometers and spontaneous parametric downconversion on the scale of tens of nanometers, opening up new exciting opportunities for developing building blocks of photonic metasurfaces.

Shah, Syed A.↗

Data Arrays for Microearthquake (MEQ) Monitoring using Deep Learning for the Newberry EGS Sites

The 'Machine Learning Approaches to Predicting Induced Seismicity and Imaging Geothermal Reservoir Properties' project looks to apply machine learning (ML) methods to Microearthquake (MEQ) data for imaging geothermal reservoir properties and forecasting seismic events, in order to advance geothermal exploration and safe geothermal energy production. As part of the project, this submission provides data arrays for 149 microearthquakes between the year 2012 and 2013 at the Newberry EGS Site for use with the Deep Learning Algorithm that has been developed. The data provided includes raw waveform data, location data, normalized waveform data, and processed waveform data. Penn State Geothermal Team has shared the following files from the project: - 149 microearthquakes (MEQs) between 2012 and 2013 at Newberry EGS sites, 'Normalized Waveform Inputs.npz' are normalized waveforms. - labels of 149 MEQs: Processed Waveform Inputs.npz - location labels of 149 MEQs: Location Data.npz Note: .npz is the python file format by NumPy that provides storage of array data.

15 GEOTHERMAL ENERGY↗

Using Dense Array Waveform Correlations to Build a Velocity Model with Stochastic Variability

In an ongoing effort to improve 3D seismic-wave propagation modeling for frequencies up to 10 Hz, we used cross correlations between vertical-component waveforms from an underground chemical explosion to estimate the statistical properties of small-scale velocity heterogeneities. The waveforms were recorded by a dense 2D seismic array deployed during the Source Physics Experiments for event number 5 (SPE-5) in a series of six underground chemical explosions, conducted at the Nevada National Security Site. The array consisted of 996 geophones with a 50–100 m grid spacing, deployed at the SPE site at the north end of the Yucca Flat basin. The SPE were conducted to investigate the generation and propagation of seismic and acoustic waves from underground explosions. Comparisons of decay rates of waveform cross correlations as function of interstation distance, computed for observed and synthetic seismograms from the SPE-5 chemical explosion, were used to constrain statistical properties of correlated stochastic velocity perturbations representing small-scale heterogeneities added to a geology-based velocity model of the Yucca Flat basin. Using comparisons between recorded and simulated waveform cross correlations, we were able to recover sets of statistical properties of small-scale velocity perturbations in the velocity model that produce the best-fit between the recorded and simulated ground motion. The stochastic velocity fluctuations in the velocity model that produced the smallest misfits have a horizontal correlation distance of between 400 and 800 m, a vertical correlation distance between 100 and 200 m, and a standard deviation of 10% from the nominal model velocity in the alluvium basin layers. They also have a horizontal correlation distance of 1000 m, a vertical correlation distance of 250 m, and a standard deviation of 6% in the underlying and consolidated sedimentary layers, up to a depth of 4 km. Comparisons between observed and simulated wavefields were used to assess the proposed small-scale heterogeneity enhancements to the Yucca Flat basin model. We found that adding a depth-resolved stochastic variability to the geology-based velocity model improves the overall performance of ground-motion simulations of an SPE-5 explosion in the modeled frequency range up to 10 Hz. The results may be applicable to other similar basins.

58 GEOSCIENCES↗

The Source Physics Experiment Large N Array

To improve the understanding of S wave generation from an explosion, a temporary deployment of 996 geophones, including both one component (Z) and three component sensors (3C), was installed from April 15 to May 23, 2016 at the Nevada National Security Site (NNSS). Sensor spacing varied from 25 to 100 m and consisted of 500 Z and 496 3C 5-Hz geophones. Data were continuously recorded during the deployment at low-gain (0 db) from April 15 to April 28 and high-gain (36 db) from April 29 to May 23. A buried (76.5 m depth) 5035 kg TNT equivalent chemical explosion (SPE-5) was recorded on April 26. It was situated in a weathered granite body surrounded by volcanic tuffs, Paleozoic carbonates, and alluvium. The array was deployed approximately 400 to 3000 m from the explosion. A set of large weight-drop shots (13,000 kg source) at 53 locations both inside and outside the geophone array were also recorded, as were local, regional, and teleseismic earthquakes. Data recovery was good, with 95% of data recovered from the chemical explosion and up to 99% in the following weeks, including both the weightdrop shots campaign and the continuous data. Important initial results from the deployment include estimates of the spatial correlation length of velocity heterogeneities and a higher resolution velocity model. Observations of the data and synthetics, indicate that some far-field (elastic) S wave energy is generated by scattering and conversion outside the near-field (inelastic) region. Interferometric processing was conducted on a Hadoop ‘big-data’ cluster.

58 GEOSCIENCES↗

A Data-Driven Framework for Automated Detection of Aircraft-Generated Signals in Seismic Array Data Using Machine Learning

Abstract Ground motions associated with aircraft overflights can cover a significant portion of the seismic data collected by shallowly emplaced seismometers, such as new nodal and Distributed Acoustic Sensing systems. This article describes the first published framework for automated detection of aircraft on single channel and multichannel seismic data. The seismic data are converted to spectrograms in a sliding time window and classified as aircraft or nonaircraft in each window using a deep convolutional neural network trained with analyst-labeled data. A majority voting scheme is used to convert the output from the sequence of sliding time windows onto a decision time sequence for each channel and to combine the binary classifications on the decision time sequences across multiple channels. Precision, recall, and F-score are used to quantify the detection performance of the algorithm on nodal data using fourfold time-series cross validation. By applying our framework to data from the Sage Brush Flats nodal array in Southern California, we provide a benchmark performance and demonstrate the advantage of using an array of sensors.

Geochemistry & Geophysics↗

Ultrasonic Phased Arrays and Interactive Reflectivity Tomography for Nondestructive Inspection of Injection and Production Wells in Geothermal Energy Systems (Quarterly Research Performance Progress Report (2015 Q3))

For the past quarter, we have placed our effort in implementing the first version of the Model-Based Iterative Reconstruction (MBIR) algorithm, assembling and testing the electronics, designing transducers mounts, and defining our laboratory test samples. We have successfully developed the first implementation of MBIR for ultrasound imaging. The current algorithm was tested with synthetic data and we are currently making new modifications for the reconstruction of real ultrasound data. Beside assembling and testing the electronics, we developed a LabView graphic user interface (GUI) to fully control the ultrasonic phased array, adjust the time-delays of the transducers, and store the measured reflections. As part of preparing for a laboratory-scale demonstration, the design and fabrication of the laboratory samples has begun. Three cement blocks with embedded objects will be fabricated, characterized, and used to demonstrate the capabilities of the system. During the next quarter, we will continue to improve the current MBIR forward model and integrate the reconstruction code with the LabView GUI. In addition, we will define focal laws for the ultrasonic phased array and perform the laboratory demonstration. We expect to perform laboratory demonstration by the end of October 2015.

15 GEOTHERMAL ENERGY↗

Aluminum Nitride Based MEMS IF Filter Array for Analog Spectral Processors

The purpose of this project was to enable new levels of performance in radio frequency systems, such as adaptability, size and stability, based on aluminum nitride microresonator technology. Early in the project, in 2008, Sandia developed arrays of filters for realizing high scan rate spectrum analyzers at 20 MHz and Rockwell Collins demonstrated a high scan rate spectrum analyzer leveraging this technology in 2009. The filter arrays, because of the transduction physics, demonstrated massively reduced size, loss and impedance compared to existing filter technologies. These device level benefits translated to reduced size and power for the spectrum analyzers at the system level.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Phased Array Ultrasonic Examination of Reactor Coolant System (Carbon Steel-to-CASS) Dissimilar Metal Weld Mockup Specimen

In the summer of 2009, Pacific Northwest National Laboratory (PNNL) staff traveled to the Electric Power Research Institute (EPRI) NDE Center in Charlotte, North Carolina, to conduct phased-array ultrasonic testing on a large bore, reactor coolant pump nozzle-to-safe-end mockup. This mockup was fabricated by FlawTech, Inc. and the configuration originated from the Port St. Lucie nuclear power plant. These plants are Combustion Engineering-designed reactors. This mockup consists of a carbon steel elbow with stainless steel cladding joined to a cast austenitic stainless steel (CASS) safe-end with a dissimilar metal weld and is owned by Florida Power & Light. The objective of this study, and the data acquisition exercise held at the EPRI NDE Center, were focused on evaluating the capabilities of advanced, low-frequency phased-array ultrasonic testing (PA-UT) examination techniques for detection and characterization of implanted circumferential flaws and machined reflectors in a thick-section CASS dissimilar metal weld component. This work was limited to PA-UT assessments using 500 kHz and 800 kHz probes on circumferential flaws only, and evaluated detection and characterization of these flaws and machined reflectors from the CASS safe-end side only. All data were obtained using spatially encoded, manual scanning techniques. The effects of such factors as line-scan versus raster-scan examination approaches were evaluated, and PA-UT detection and characterization performance as a function of inspection frequency/wavelength, were also assessed. A comparative assessment of the data is provided, using length-sizing root-mean-square-error and position/localization results (flaw start/stop information) as the key criteria for flaw characterization performance. In addition, flaw signal-to-noise ratio was identified as the key criterion for detection performance.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗