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At least 1,063 records · Page 59

ED-cPSD: Fast Phase-Size Distribution via Sequential Erosion-Dilation

The Erosion-Dilation continuous Phase-Size Distribution, ED-cPSD, is an application for calculating continuous pore and particle-size distribution from digital reconstructions and/or image-based structural data. It is based on the erosion-dilation continuous phase-size distribution method. A continuous size distribution is a measure of the probability density of finding a particle or pore of a certain size. These distributions are of interest in any field of study involving porous media, including but not limited to electrochemistry, petroleum engineering, geology, and food science. The algorithm behind the software provides a computationally efficient way to calculate phase-size distributions for large domains. For a 3D battery electrode reconstruction with 1.3 x 10 8 voxels, the particle size distribution is derived in under 2 min on a desktop, while also retaining flexibility and computational efficiency for HPC-scale multi-threading. The software can handle structures with over 10 9 voxels. The algorithm is roughly 280 times faster than a previous version on the same task.

Characterization↗

Baryon acoustic oscillations at z = 2.34 from the correlations of Ly α absorption in eBOSS DR14

We measure the imprint of primordial baryon acoustic oscillations (BAOs) in the correlation function of Ly α absorption in quasar spectra from the Baryon Oscillation Spectroscopic Survey (BOSS) and the extended BOSS (eBOSS) in Data Release 14 (DR14) of the Sloan Digital Sky Survey (SDSS)-IV. In addition to 179 965 spectra with absorption in the Lyman- α (Ly α ) region, we use Ly α absorption in the Lyman- β region of 56 154 spectra for the first time. We measure the Hubble distance, D H , and the comoving angular diameter distance, D M , relative to the sound horizon at the drag epoch r d at an effective redshift z = 2.34. Using a physical model of the correlation function outside the BAO peak, we find D H (2.34)/ r d = 8.86 ± 0.29 and D M (2.34)/ r d = 37.41 ± 1.86, within 1 σ from the flat-ΛCDM model consistent with CMB anisotropy measurements. With the addition of polynomial “broadband” terms, the results remain within one standard deviation of the CMB-inspired model. Combined with the quasar-Ly α cross-correlation measurement presented in a companion paper, the BAO measurements at z = 2.35 are within 1.7 σ of the predictions of this model.

79 ASTRONOMY AND ASTROPHYSICS↗

APOGEE-2S Mg–Al anti-correlation of the metal-poor globular cluster NGC 2298

We present detailed elemental abundances and radial velocities of stars in the metal-poor globular cluster (GC) NGC 2298, based on near-infrared high-resolution ($R$ ~ 22 500) spectra of 12 members obtained during the second phase of the Apache Point Observatory Galactic Evolution Experiment (APOGEE-2) at Las Campanas Observatory as part of the seventeenth Data Release (DR 17) of the Sloan Digital Sky Survey IV (SDSS-IV). We employed the Brussels Automatic Code for Characterizing High accuracy Spectra (BACCHUS) software to investigate abundances for a variety of species including α elements (Mg, Si, and Ca), the odd-Z element Al, and iron-peak elements (Fe and Ni) located in the innermost regions of NGC 2298. We find a mean and median metallicity [Fe/H] = -1.76 and -1.75, respectively, with a star-to-star spread of 0.14 dex, which is compatible with the internal measurement errors. Thus, we find no evidence for an intrinsic [Fe/H] abundance spread in NGC 2298. The typical $α$-element enrichment in NGC 2298 is overabundant relative to the Sun, and it follows the trend of other metal-poor GCs. We confirm the existence of an Al-enhanced population in this cluster, which is clearly anti-correlated with Mg, indicating the prevalence of the multiple-population phenomenon in NGC 2298.

79 ASTRONOMY AND ASTROPHYSICS↗

Note: Optical receiver system for 152-channel magnetoencephalography

An optical receiver system composing 13 serial data restore/synchronizer modules and a single module combiner converted optical 32-bit serial data into 32-bit synchronous parallel data for a computer to acquire 152-channel magnetoencephalography (MEG) signals. A serial data restore/synchronizer module identified 32-bit channel-voltage bits from 48-bit streaming serial data, and then consecutively reproduced 13 times of 32-bit serial data, acting in a synchronous clock. After selecting a single among 13 reproduced data in each module, a module combiner converted it into 32-bit parallel data, which were carried to 32-port digital input board in a computer. When the receiver system together with optical transmitters were applied to 152-channel superconducting quantum interference device sensors, this MEG system maintained a field noise level of 3 fT/√Hz @ 100 Hz at a sample rate of 1 kSample/s per channel.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Three-dimensional full-field velocity measurements in shock compression experiments using stereo digital image correlation

Shock compression plate impact experiments conventionally rely on point-wise velocimetry measurements based on laser-based interferometric techniques. This study presents an experimental methodology to measure the free surface full-field particle velocity in shock compression experiments using high-speed imaging and three-dimensional (3D) digital image correlation (DIC). The experimental setup has a temporal resolution of 100 ns with a spatial resolution varying from 90 to 200 μm/pixel. Experiments were conducted under three different plate impact configurations to measure spatially resolved free surface velocity and validate the experimental technique. First, a normal impact experiment was conducted on polycarbonate to measure the macroscopic full-field normal free surface velocity. Second, an isentropic compression experiment on Y-cut quartz–tungsten carbide assembly is performed to measure the particle velocity for experiments involving ramp compression waves. To explore the capability of the technique in multiaxial loading conditions, a pressure shear plate impact experiment was conducted to measure both the normal and transverse free surface velocities under combined normal and shear loading. The velocities measured in the experiments using digital image correlation are validated against previous data obtained from laser interferometry. Numerical simulations were also performed using established material models to compare and validate the experimental velocity profiles for these different impact configurations. The novel ability of the employed experimental setup to measure full-field free surface velocities with high spatial resolutions in shock compression experiments is demonstrated for the first time in this work.

47 OTHER INSTRUMENTATION↗

A novel integrated time-resolved array avalanche photodiode detection system for nuclear resonant scattering measurements

Here, the nuclear resonant scattering (NRS) experiment requires photon-counting detectors with high time resolution, short dead time, large dynamic range, low noise, and large detection area. An 8-channel avalanche photodiode (APD) array detector system with high integrity, flexibility, and reliability has been developed to adapt to the demands of NRS experiments. The detector system mainly consists of four key parts: (i) an array-APD sensor, (ii) 8-channel integrated fast preamplifiers, (iii) the time-to-digital converter readout electronics, and (iv) a data acquisition system and EPICS support software. Remarkably, the system exhibits a time resolution of better than 500 ps and has a sufficiently low noise level, allowing for the lowest detection energy threshold of 4 keV. The performance of the new array-APD system as well as its real application in nuclear forward scattering (NFS) and nuclear resonant inelastic x-ray scattering (NRIXS) experiments was tested in two synchrotron facilities. With the new system, the NFS signal very close to the prompt electronic scattering signal can be extracted. Thanks to the customized EPICS-areaDetector-based control software, NRIXS spectra can be readily measured with time and energy information of the NRIXS signal stored in the raw data, which is promising for developing NRIXS data analysis in the time domain. The array-APD detector can be deployed for nuclear resonant scattering experiments at various synchrotron radiation facilities.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

White dwarfs in the UKIRT infrared deep sky survey data release

We have identified 8 to 10 new cool white dwarfs from the Large Area Survey (LAS) Data Release 9 of the United Kingdom InfraRed Telescope (UKIRT) Infrared Deep Sky Survey (UKIDSS). The data set was paired with the Sloan Digital Sky Survey to obtain proper motions and a broad ugrizYJHK wavelength coverage. Optical spectroscopic observations were secured at Gemini Observatory and confirm the degenerate status for eight of our targets. The final sample includes two additional white dwarf candidates with no spectroscopic observations. We rely on improved one-dimensional model atmospheres and new multi-dimensional simulations with CO5BOLD to review the stellar parameters of the published LAS white dwarf sample along with our additional discoveries. Most of the new objects possess very cool atmospheres with effective temperatures below 5000 K, including two pure-hydrogen remnants with a cooling age between 8.5 and 9.0 Gyr, and tangential velocities in the range 40 km s{sup –1} ≤v {sub tan} ≤ 60 km s{sup –1}. They are likely thick disk 10-11 Gyr old objects. In addition, we find a resolved double degenerate system with v {sub tan} ∼ 155 km s{sup –1} and a cooling age between 3.0 and 5.0 Gyr. These white dwarfs could be disk remnants with a very high velocity or former halo G stars. We also compare the LAS sample with earlier studies of very cool degenerates and observe a similar deficit of helium-dominated atmospheres in the range 5000 < T {sub eff} (K) < 6000. We review the possible explanations for the spectral evolution from helium-dominated toward hydrogen-rich atmospheres at low temperatures.

79 ASTRONOMY AND ASTROPHYSICS↗

Extremely massive disc galaxies in the nearby Universe form through gas-rich minor mergers

ABSTRACT In our hierarchical structure-formation paradigm, the observed morphological evolution of massive galaxies – from rotationally supported discs to dispersion-dominated spheroids – is largely explained via galaxy merging. However, since mergers are likely to destroy discs, and the most massive galaxies have the richest merger histories, it is surprising that any discs exist at all at the highest stellar masses. Recent theoretical work by our group has used a cosmological, hydrodynamical simulation to suggest that extremely massive (M* > 1011.4 M⊙) discs form primarily via minor mergers between spheroids and gas-rich satellites, which create new rotational stellar components and leave discs as remnants. Here, we use UV-optical and H i data of massive galaxies, from the Sloan Digital Sky Survey, Galaxy Evolution Explorer, Dark Energy Camera Legacy Survey (DECaLS), and Arecibo Legacy Fast ALFA surveys, to test these theoretical predictions. Observed massive discs account for ∼13 per cent of massive galaxies, in good agreement with theory (∼11 per cent). ∼64 per cent of the observed massive discs exhibit tidal features, which are likely to indicate recent minor mergers, in the deep DECaLS images (compared to ∼60 per cent in their simulated counterparts). The incidence of these features is at least four times higher than in low-mass discs, suggesting that, as predicted, minor mergers play a significant (and outsized) role in the formation of these systems. The empirical star formation rates agree well with theoretical predictions and, for a small galaxy sample with H i detections, the H i masses and fractions are consistent with the range predicted by the simulation. The good agreement between theory and observations indicates that extremely massive discs are indeed remnants of recent minor mergers between spheroids and gas-rich satellites.

79 ASTRONOMY AND ASTROPHYSICS↗

Long-term follow-up observations of extreme coronal line emitting galaxies

We present new spectroscopic and photometric follow-up observations of the known sample of extreme coronal line-emitting galaxies (ECLEs) identified in the Sloan Digital Sky Survey (SDSS). With these new data, observations of the ECLE sample now span a period of two decades following their initial SDSS detections. We confirm the non-recurrence of the iron coronal line signatures in five of the seven objects, further supporting their identification as the transient light echoes of tidal disruption events (TDEs). Photometric observations of these objects in optical bands show little overall evolution. In contrast, mid-infrared (MIR) observations show ongoing long-term declines consistent with power-law decay. The remaining two objects had been classified as active galactic nuclei (AGNs) with unusually strong coronal lines rather than being TDE related, given the persistence of the coronal lines in earlier follow-up spectra. We confirm this classification, with our spectra continuing to show the presence of strong, unchanged coronal line features and AGN-like MIR colors and behavior. We have constructed spectral templates of both subtypes of ECLE to aid in distinguishing the likely origin of newly discovered ECLEs. We highlight the need for higher cadence, and more rapid, follow-up observations of such objects to better constrain their properties and evolution. We also discuss the relationships between ECLEs, TDEs, and other identified transients having significant MIR variability.

79 ASTRONOMY AND ASTROPHYSICS↗

Distributed Fiber Sensors With High Spatial Resolution in Extreme Radiation Environments in Nuclear Reactor Cores

This paper is a comprehensive experimental report on the neutron radiation effects of distributed optical fiber sensors with enhanced Rayleigh scattering profiles in an in-pile environment. Femtosecond laser direct writing was used to inscribe Type-II modifications in standard telecom fibers and radiation-hardened fibers with fluorine-doped cores. Rayleigh backscattering signals were enhanced for continuous 1.5 m. In-pile lead-out sensors tests were carried out at the MIT Research Reactor for two months, which was operated at a nominal power of 5.7 MW with fast neutron (>0.1 MeV) flux of 1.29 × 1014 n/cm2/s and an in-core temperature of up to 560°C. Using the Optical Frequency Domain Reflectometry technique, the backscattering profiles of fiber sensors were interrogated with a 3-cm spatial resolution to monitor the temperature profile of the reactor. Results show that laser inscribed Type-II modifications in the form of nanogratings are highly stable against extreme temperature and ionizing radiation. Both standard telecom fibers and radiation-hardened fibers with laser-enhanced Rayleigh profiles can continuously perform distributed temperature measurements over the entire duration of the in-pile testing. Temperature coefficients of sensors and spectral shift quality were studied as functions of total radiation fluence. To the best of our knowledge, we present for the first time, the temperature profile of an operating nuclear reactor core with 3-cm spatial resolution, enabled by distributed fiber sensors with laser-enhanced Rayleigh scattering profiles. The high spatial resolution measurements can provide valuable data for the design and validation of digital twin and virtual reality of nuclear energy systems.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Dual Inductor Hybrid Converter for Point-of-Load Voltage Regulator Modules

Achieving high-efficiency power conversion with high power density for large conversion ratio is crucially needed yet challenging in point-of-load applications because of increasing demands of loads. This paper presents a new hybrid converter to address this need. The converter uses two interleaved inductors for complete soft charging of flying capacitors to efficiently provide high output currents with no capacitor hard-charge loss. This dual inductor hybrid (DIH) converter features a smaller number of switches and more effective switch utilization than a recently reported Hybrid Dickson converter, yielding substantially less switch losses represented by smaller volt-ampere products and smaller equivalent output resistance. Converter operation principle is analyzed in detail to confirm the feasibility and benefits, and design considerations are provided to identify a practical design process. Experimental results verify the converter's operation principles and advantages with a 300-kHz 20-W prototype achieving 95.02% peak efficiency and 225 W/in 3 power density. Its advantages and performance promise a good candidate point-of-load converter architecture for demanding applications, such as in data centers, telecommunication, and high-performance digital systems.

24 POWER TRANSMISSION AND DISTRIBUTION↗

MO-G-BRF-02: Enhancement of Texture-Based Metastasis Prediction Models Via the Optimization of PET/MRI Acquisition Protocols

Purpose: We have previously identified a prediction model of lung metastases at diagnosis of soft-tissue sarcomas (STS) that is composed of two textural features extracted from FDG-PET and T1-weighted (T1w) MRI scans. The goal of this study is to evaluate whether the optimization in FDGPET and MRI acquisition parameters would enhance the prediction performance of texture-based models. Methods: Ten FDG-PET and T1w- MRI digitized tumor models were generated from imaging data of STS patients who underwent pre-treatment clinical scans between 2005 and 2011. Five of ten patients eventually developed lung metastases. Numerically simulated MR images were produced using echo times (TE) of 2 and 4 times the nominal clinical parameter (TEc), and repetition times (TR) of 0.5, 0.67, 1.5 and 2 times the nominal clinical parameter (TRc) found in the DICOM headers (TEc range: 9–13 ms, TRc range: 410-667 ms). PET 2D images were simulated using Monte-Carlo and were reconstructed using an ordered-subsets expectation maximization (OSEM) algorithm with 1 to 32 iterations and a post-reconstruction Gaussian filter of 0, 2, 4 or 6 mm width. For all possible combinations of PET and MRI acquisition parameters, the prediction model was constructed using logistic regression with new coefficients, and its associated prediction performance for lung metastases was evaluated using the area under the ROC curve (AUC). Results: The prediction performance over all simulations yielded AUCs ranging from 0.7 to 1. Notably, TR values below or equal to TRc and higher PET post-reconstruction filter widths yielded higher prediction performance. The best results were obtained with a combination of 4*TEc, TRc, 30 OSEM iterations and 2mm filter width. Conclusion: This work indicates that texture-based metastasis prediction models could be improved using optimized choices of FDG-PET and MRI acquisition protocols. This principle could be generalized to other texture-based models.

60 APPLIED LIFE SCIENCES↗

Enabling the High Level Synthesis of Data Analytics Accelerators

Conventional High Level Synthesis (HLS) tools mainly tar- get compute intensive kernels typical of digital signal pro- cessing applications. We are developing techniques and ar- chitectural templates to enable HLS of data analytics appli- cations. These applications are memory intensive, present fine-grained, unpredictable data accesses, and irregular, dy- namic task parallelism. We discuss an architectural tem- plate based around a distributed controller to efficiently ex- ploit thread level parallelism. We present a memory in- terface that supports parallel memory subsystems and en- ables implementing atomic memory operations. We intro- duce a dynamic task scheduling approach to efficiently ex- ecute heavily unbalanced workload. The templates are val- idated by synthesizing queries from the Lehigh University Benchmark (LUBM), a well know SPARQL benchmark.

Data Analytics↗

DataXray

Lab experiments involving digital signal processing tend to capture heterogeneous data that is binned into individual files. The structure of the whole experiment tends to get lost in this process, generating a "mess" of data that is difficult to summarize, and even more difficult to analyze in a consistent way. DataXray is a set of python routines that wraps publicly available open-source codes to create a consistent workflow for data and experiments, involving imaging, spectral and hyperspectral data. Routines are provided for data translation, slicing, visualization, multivariate statistics, integral transforms, feature extraction and reporting in the form of publication-grade figures.

Maksymovych, Petro↗

Mingus Discontinuous Multiphysics

Mingus provides hybrid coupled local/non-local mechanics analysis capabilities that extend several traditional methods to applications with inherent discontinuities. Its primary features include adaptations of solid mechanics, fluid dynamics and digital image correlation that naturally accommodate dijointed data or irregular solution fields by assimilating a variety of discretizations (such as control volume finite elements, peridynamics and meshless control point clouds). The goal of this software is to provide an analysis framework form multiphysics engineering problems with an integrated image correlation capability that can be used for experimental validation and model

Turner, Dan↗

Integrated Predictive Tools for Customizing Microstructure and Material Properties of Additively Manufactured Aerospace Components

Additive Manufacturing (AM) refers to a process by which digital three-dimensional (3-D) design data is converted to build up a component by depositing material layer-by-layer. United Technologies Corporation (UTC) is currently involved in fabrication and certification of several AM aerospace structural components made from aerospace materials. This is accomplished by using optimized process parameters determined through numerous design-of-experiments (DOE)-based studies. Certification of these components is broadly recognized as a significant challenge, with long lead times, very expensive new product development cycles and very high energy consumption. Because of these challenges, United Technologies Research Center (UTRC), together with UTC business units have been developing and validating an advanced physics-based process model. The specific goal is to develop a physics-based framework of an AM process and reliably predict fatigue properties of built-up structures as based on detailed solidification microstructures. Microstructures are predicted using process control parameters including energy source power, scan velocity, deposition pattern, and powder properties. The multi-scale multi-physics model requires solution and coupling of governing physics that will allow prediction of the thermal field and enable solution at the microstructural scale. The state-of-the-art approach to solve these problems requires a huge computational framework and this kind of resource is only available within academia and national laboratories. The project utilized the parallel phase-fields codes at Oak Ridge National Laboratory (ORNL) and Lawrence Livermore National Laboratory (LLNL), along with the high-performance computing (HPC) capabilities existing at the two labs to demonstrate the simulation of multiple dendrite growth in threedimensions (3-D). The LLNL code AMPE was used to implement the UTRC phase field model that was previously developed for a model binary alloy, and the simulation results were compared against the UTRC simulation results, followed by extension of the UTRC model to simulate multiple dendrite growth in 3-D. The ORNL MEUMAPPS code was used to simulate dendritic growth in a model ternary alloy with the same equilibrium solidification range as the Ni-base alloy 718 using realistic model parameters, including thermodynamic integration with a Calphad based model for the ternary alloy. Implementation of the UTRC model in AMPE met with several numerical and parametric issues that were resolved and good comparison between the simulation results obtained by the two codes was demonstrated for two dimensional (2-D) dendrites. 3-D dendrite growth was then demonstrated with the AMPE code using nondimensional parameters obtained in 2-D simulations. Multiple dendrite growth in 2-D and 3-D were demonstrated using ORNL’s MEUMAPPS code using simple thermal boundary conditions. MEUMAPPS was then modified to incorporate the complex, time-dependent thermal boundary conditions obtained by UTRC’s thermal modeling of single track AM experiments to drive the phase field simulations. The results were in good agreement with UTRC’s experimental measurements.

36 MATERIALS SCIENCE↗

Volume Imaging & Tracking Radar Open Research Topics

The Volume Imaging & Tracking Radar (VITR) is a multistatic broadband system designed to track multiple centimeter sized objects whose velocities exceed 1 km/s. The VITR characteristics are: Multistatic, multiple transmitters & receivers; Spatially diverse & aperiodic: The transmitting and receiving antennas may be arbitrarily located; Pulsed, broad band (6-13 GHz); Time-domain; One pulse in the air at a time; No carrier; Returns digitized, processed & analyzed at RF frequencies. The data products are: Three dimensional object of interest (OOI) tracks; Multistatic Doppler velocity estimates of the OOIs; Evolution of radar cross-section (RCS) as a function of time along the track; Volume movies (three spatial dimensions and time) of the OOIs; Bistatic inverse synthetic aperture radar (ISAR) processing.

42 ENGINEERING↗

Development of a Framework for Data Integration, Assimilation, and Learning for Geological Carbon Sequestration (DIAL-GCS) (Final Report)

This project aimed to develop and demonstrate a Data Integration, Assimilation, and Learning framework for geologic carbon sequestration projects (DIAL-GCS). DIAL-GCS is an intelligence monitoring system (IMS) for automating GCS closed-loop management by leveraging recent developments in machine learning technologies, complex event processing (CEP), and reduced-order modeling. The safe and efficient operation of GCS repositories requires integrated monitoring to track the injected CO¬2 as it moves within a storage reservoir. GCS projects are data intensive, as a result of proliferation of digital instrumentation and smart-sensing technologies. GCS projects are also resource intensive, often requiring multidisciplinary teams performing different monitoring, verification, accounting (MVA) tasks throughout the lifecycle of a project to ensure secure containment of injected CO2. The success of GCS thus depends in a large part on our ability to access, assimilate, and analyze heterogeneous data and information sources in a timely manner. This project included a number of meaningful and necessary tasks to transform the human domain knowledge into machine-interpretable rules for automating knowledge extraction and discovery in GCS. The specific technical objectives of the proposed DIAL-GCS project were to develop an ontology-driven GCS data management module for storing, querying, and exchanging GCS data (both historic and live sensor data) from multiple sources and in heterogeneous formats. Incorporate a CEP engine for detecting abnormal situations by seamlessly combining expert knowledge, rule-based reasoning, and machine learning. Enable uncertainty quantification and predictive analytics using a combination of coupled-process modeling, AI/ML methods, and reduced-order modeling, and integrate and demonstrate the system’s capabilities with both real and simulated data. As far as we know, this is one of the first projects aimed to develop intelligent monitoring systems (IMS) targeting the GCS. Under this project, the team had developed a large number of web applications and scientific algorithms that contribute the main theme of intelligent monitoring. The team has published more than a dozen peer reviewed papers and disseminated the research results at multiple technical meetings.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗