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At least 739 records · Page 41

Characterization of Fissile Assemblies Using Low-Efficiency Detection Systems

Here, we have investigated the possibility that the amount, chemical form, multiplication, and shape of the fissile material in an assembly can be passively assayed using scintillator detection systems by only measuring the fast neutron pulse height distribution and distribution of time intervals Δt between fast neutrons. We have previously demonstrated that the alpha-ratio can be obtained from the observed pulse height distribution for fast neutrons. In this paper we report that we report that when the distribution of time intervals is plotted as a function of logΔt, the position of the correlated neutron peak is nearly independent of detector efficiency and determines the internal relaxation rate for fast neutrons. If this information is combined with knowledge of the alpha-ratio, then the position of the minimum between the correlated and uncorrelated peaks can be used to rapidly estimate the mass, multiplication, and shape of fissile material. This method does not require a priori knowledge of either the efficiency for neutron detection or the alpha-ratio. Although our method neglects 3-neutron correlations, we have used previously obtained experimental data for metallic and oxide forms of Pu to demonstrate that our method yields good estimates for multiplications as large as 2, and that the only constraint on detector efficiency/observation time is that a peak in the interval time distribution due to correlated neutrons is visible.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

A Computational Simulation of Using Tungsten Gratings in Near-Field Thermophotovoltaic Devices

Near-field thermophotovoltaic (NFTPV) devices have received much attention lately as an alternative energy harvesting system, whereby a heated emitter exchanges super-Planckian thermal radiation with a photovoltaic (PV) cell to generate electricity. This work describes the use of a grating structure to enhance the power throughput of NFTPV devices, while increasing the energy conversion efficiency by ensuring that a large portion of the radiation entering the PV cell is above the band gap. The device contains a high-temperature tungsten grating that radiates photons to a room-temperature In 0.18 Ga 0.82 Sb PV cell through a vacuum gap of several tens of nanometers. Scattering theory is used along with the rigorous coupled-wave analysis (RCWA) to calculate the radiation energy exchange between the grating emitter and the TPV cell. A parametric study is performed by varying the grating depth, period, and ridge width in the range that can be fabricated using available fabrication technologies. It is found that the power output can be increased by 40% while improving the efficiency from 29.9% to 32.0% with a selected grating emitter as compared to the case of a flat tungsten emitter. Reasons for the enhancement are found to be due to the enhanced energy transmission coefficient close to the band gap. Furthermore, this work shows a possible way of improving NFTPV and sheds light on how grating structures interact with thermal radiation at the nanoscale.

42 ENGINEERING↗

Atomic layer deposition of tin oxide and zinc tin oxide using tetraethyltin and ozone

Silicon or glass substrates exposed to sequential pulses of tetraethyltin (TET) and ozone (O{sub 3}) were coated with thin films of SnO{sub 2}. Self-limiting deposition was found using 8 s pulse times, and a uniform thickness per cycle (TPC) of 0.2 nm/cycle was observed in a small, yet reproducible, temperature window from 290 to 320 °C. The as-deposited, stoichiometric SnO{sub 2} films were amorphous and transparent above 400 nm. Interspersing pulses of diethylzinc and O{sub 3} among the TET:O{sub 3} pulses resulted in deposition of zinc tin oxide films, where the fraction of tin, defined as [at. % Sn/(at. % Sn + at. % Zn)], was controlled by the ratio of TET pulses, specifically n{sub TET}:(n{sub TET} + n{sub DEZ}) where n{sub TET} and n{sub DEZ} are the number of precursor/O{sub 3} subcycles within each atomic layer deposition (ALD) supercycle. Based on film thickness and composition measurements, the TET pulse time required to reach saturation in the TPC of SnO{sub 2} on ZnO surfaces was increased to >30 s. Under these conditions, film stoichiometry as a function of the TET pulse ratio was consistent with the model devised by Elliott and Nilsen. The as-deposited zinc tin oxide (ZTO) films were amorphous and remained so even after annealing at 450 °C in air for 1 h. The optical bandgap of the transparent ZTO films increased as the tin concentration increased. Hall measurements established that the n-type ZTO carrier concentration was 3 × 10{sup 17} and 4 × 10{sup 18} cm{sup −3} for fractional tin concentrations of 0.28 and 0.63, respectively. The carrier mobility decreased as the concentration of tin increased. A broken gap pn junction was fabricated using ALD-deposited ZTO and a sputtered layer of cuprous oxide. The junction demonstrated ohmic behavior and low resistance consistent with similar junctions prepared using sputter-deposited ZTO.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Vapor deposition of molybdenum oxide using bis(ethylbenzene) molybdenum and water

Three molybdenum precursors—bis(acetylacetonate) dioxomolybdenum, molybdenum isopropoxide, and bis(ethylbenzene) molybdenum—were tested for molybdenum oxide vapor deposition. Quartz crystal microbalance studies were performed to monitor growth. Molybdenum isopropoxide and bis(ethylbenzene) molybdenum achieved linear growth rates 0.01 and 0.08 Å/cycle, respectively, using atomic layer deposition techniques. Negligible MoO{sub x} growth was observed on alumina powder using molybdenum isopropoxide, as determined by inductively coupled plasma optical emission spectroscopy. Bis(ethylbenzene) molybdenum achieved loadings of 0.5, 1.1, and 1.9 Mo/nm{sup 2} on alumina powder after one, two, and five cycles, respectively, using atomic layer deposition techniques. The growth window for bis(ethylbenzene) molybdenum is 135–150 °C. An alternative pulsing strategy was also developed for bis(ethylbenzene) molybdenum that results in higher growth rates in less time compared to atomic layer deposition techniques. The outlined process serves as a methodology for depositing molybdenum oxide for catalytic applications. All as-deposited materials undergo further calcination prior to characterization and testing.

36 MATERIALS SCIENCE↗

Using nature’s blueprint to expand catalysis with Earth-abundant metals

Original title changed for publication from; " Using Nature's Blueprint to Enable Catalysis with Earth-Abundant Metals" A diverse array of redox transformations that are essential to life are catalyzed by metalloenzymes that feature an earth-abundant metal. In contrast, platinum-group metals have been the cornerstone of many industrial catalytic reactions for decades, providing high activity, thermal stability and tolerance to chemical poisons. We assert that Nature’s blueprint provides the fundamental principles for vastly expanding the use of abundant metals in catalysis. We highlight the key physical properties of abundant metals that distinguish them from precious metals, and we look to Nature to understand how the inherent attributes of abundant metals can be embraced, leading to unique, highly efficient catalysts, emphasizing reactions crucial to the sustainable production and transformation of fuels and chemicals.

Bullock, Ronald M.↗

Electron and photon energy calibration with the ATLAS detector using LHC Run 1 data

This paper presents the electron and photon energy calibration achieved with the ATLAS detector using about 25 fb -1 of LHC proton–proton collision data taken at centre-of-mass energies of √s=7 and 8 TeV. The reconstruction of electron and photon energies is optimised using multivariate algorithms. The response of the calorimeter layers is equalised in data and simulation, and the longitudinal profile of the electromagnetic showers is exploited to estimate the passive material in front of the calorimeter and reoptimise the detector simulation. After all corrections, the Z resonance is used to set the absolute energy scale. For electrons from Z decays, the achieved calibration is typically accurate to 0.05 % in most of the detector acceptance, rising to 0.2 % in regions with large amounts of passive material. The remaining inaccuracy is less than 0.2–1 % for electrons with a transverse energy of 10 GeV, and is on average 0.3 % for photons. The detector resolution is determined with a relative inaccuracy of less than 10 % for electrons and photons up to 60 GeV transverse energy, rising to 40 % for transverse energies above 500 GeV.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Measurement of the photon identification efficiencies with the ATLAS detector using LHC Run-1 data

The algorithms used by the ATLAS Collaboration to reconstruct and identify prompt photons are described. Measurements of the photon identification efficiencies are reported, using 4.9 fb –1 of pp collision data collected at the LHC at √s = 7 TeV and 20.3 fb –1 at √s = 8 TeV. The efficiencies are measured separately for converted and unconverted photons, in four different pseudorapidity regions, for transverse momenta between 10 GeV and 1.5 TeV. The results from the combination of three data-driven techniques are compared to the predictions from a simulation of the detector response, after correcting the electromagnetic shower momenta in the simulation for the average differences observed with respect to data. Data-to-simulation efficiency ratios used as correction factors in physics measurements are determined to account for the small residual efficiency differences. These factors are measured with uncertainties between 0.5% and 10% in 7 TeV data and between 0.5% and 5.6% in 8 TeV data, depending on the photon transverse momentum and pseudorapidity.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

A strategy for a general search for new phenomena using data-derived signal regions and its application within the ATLAS experiment

This paper describes a strategy for a general search used by the ATLAS Collaboration to find potential indications of new physics. Events are classified according to their final state into many event classes. For each event class an automated search algorithm tests whether the data are compatible with the Monte Carlo simulated expectation in several distributions sensitive to the effects of new physics. The significance of a deviation is quantified using pseudo-experiments. A data selection with a significant deviation defines a signal region for a dedicated follow-up analysis with an improved background expectation. The analysis of the data-derived signal regions on a new dataset allows a statistical interpretation without the large look-elsewhere effect. The sensitivity of the approach is discussed using Standard Model processes and benchmark signals of new physics. As an example, results are shown for 3.2 fb –1 of proton–proton collision data at a centre-of-mass energy of 13 TeV collected with the ATLAS detector at the LHC in 2015, in which more than 700 event classes and more than 10 5 regions have been analysed. Furthermore, no significant deviations are found and consequently no data-derived signal regions for a follow-up analysis have been defined.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Mapping of exhaust gas recirculation and combustion-residual backflow in the intake ports of a heavy-duty diesel engine using a multiplexed multi-species absorption spectroscopy sensor [Mapping of EGR and combustion residual backflow in the intake ports of a heavy duty diesel engine using a multiplexed multi-species absorption spectroscopy sensor]

Here, the combustion-residual backflow into the intake ports of a commercial diesel engine (Cummins ISX series) was spatiotemporally mapped using a multiplexed multi-species absorption spectroscopy sensor system; the resulting cycle- and cylinder-resolved measurements are applicable for assessing cylinder charge uniformity, control strategies, and computational fluid dynamics tools. On-engine measurements were made using four compact (3/8 in Outside Diameter) stainless steel probes which enabled simultaneous multi-point measurements, required minimal engine hardware modification, and featured a novel tip design for measurement of gas flows parallel to the probe axis. Three sensor probes were used to perform simultaneous backflow measurements in intake runners corresponding to three of the six engine cylinders, and a fourth probe was installed in the intake manifold plenum for tracking dynamics introduced by an external exhaust gas recirculation mixer. Near-crank-angle resolved measurements (5 kHz, that is, 1.2 crank angle resolution at 1000 RPM) were performed during steady-state engine operation at various levels of external exhaust gas recirculation to measure the gas properties and penetration distance of the backflow into the intake runners on a cylinder- and cycle-basis. Validation of computational fluid dynamics model results is also presented to demonstrate the utility of such measurements in advancing engine research.

33 ADVANCED PROPULSION SYSTEMS↗

High-throughput prediction of eucalypt lignin syringyl/guaiacyl content using multivariate analysis: A comparison between mid-infrared, near-infrared, and Raman spectroscopies for model development

Background: In order to rapidly and efficiently screen potential biofuel feedstock candidates for quintessential traits, robust high-throughput analytical techniques must be developed and honed. The traditional methods of measuring lignin syringyl/guaiacyl (S/G) ratio can be laborious, involve hazardous reagents, and/or be destructive. Vibrational spectroscopy can furnish high-throughput instrumentation without the limitations of the traditional techniques. Spectral data from mid-infrared, near-infrared, and Raman spectroscopies was combined with S/G ratios, obtained using pyrolysis molecular beam mass spectrometry, from 245 different eucalypt and Acacia trees across 17 species. Iterations of spectral processing allowed the assembly of robust predictive models using partial least squares (PLS). Results: The PLS models were rigorously evaluated using three different randomly generated calibration and validation sets for each spectral processing approach. Root mean standard errors of prediction for validation sets were lowest for models comprised of Raman (0.13 to 0.16) and mid-infrared (0.13 to 0.15) spectral data, while near-infrared spectroscopy led to more erroneous predictions (0.18 to 0.21). Correlation coefficients (r) for the validation sets followed a similar pattern: Raman (0.89 to 0.91), mid-infrared (0.87 to 0.91), and near-infrared (0.79 to 0.82). These statistics signify that Raman and mid-infrared spectroscopy led to the most accurate predictions of S/G ratio in a diverse consortium of feedstocks. Conclusion: Eucalypts present an attractive option for biofuel and biochemical production. Given the assortment of over 900 different species of Eucalyptus and Corymbia , in addition to various species of Acacia , it is necessary to isolate those possessing ideal biofuel traits. This research has demonstrated the validity of vibrational spectroscopy to efficiently partition different potential biofuel feedstocks according to lignin S/G ratio, significantly reducing experiment and analysis time and expense while providing non-destructive, accurate, global, predictive models encompassing a diverse array of feedstocks.

09 BIOMASS FUELS↗

Quantitative 2D thermometry in turbulent sooting non-premixed flames using filtered Rayleigh scattering

This paper demonstrates the application of a thermometry method in turbulent sooting non-premixed flames using filtered Rayleigh scattering (FRS). Fuel tailoring is used to establish a specific C 2 H 2 -based fuel mixture such that temperature can be determined accurately by a single FRS measurement over the entirety of mixture fraction space, or equivalently, for all relevant thermo-chemical states. Evaluation is performed in a hierarchy of flows to establish measurement precision and accuracy. Initial assessments in a series of heated fuel mixtures; non-sooting, near-adiabatic flat flames; and laminar non-premixed sooting flames show accuracy of the approach over a full range of expected temperatures and high single-shot measurement precision (e.g., 65 < <#comment/> S N R < <#comment/> 80 ) for temperatures between 1900 and 2200 K. Subsequently, 2D temperature measurements are evaluated in a turbulent non-premixed sooting flame. For the current fuel mixture, the local mixture-averaged Rayleigh scattering cross section is nearly constant over all composition space, and thus traditional laser Rayleigh scattering (LRS) is used as a measurement standard in the absence of soot. The results show excellent agreement between the proposed FRS thermometry approach and LRS in non-sooting regions. In the presence of soot, the proposed FRS-based approach shows no signs of interference. In addition, 2D temperature imaging shows high SNR (60–74) over all temperature conditions. Thus, we believe the proposed methodology successfully provides a high-resolution 2D temperature method under turbulent sooting flame conditions.

Pu, Jinpeng↗

Microseismic Event Detection Using Multiple Geophone Arrays in Southwestern Utah

We conducted four geophone array experiments in southwestern Utah between July 2016 and October 2017 to characterize regional levels of microseismicity. Each experiment comprised between 48 and 93 geophones and recorded continuously for ~30 days. Using a new frequency domain array-based detector and a traditional STA/LTA detector, we identified 242 earthquakes. We were able to precisely locate 203 of these earthquakes using HYPOINVERSE. During the same time period the University of Utah Seismograph Stations (UUSS) catalog contained 68 earthquakes in the study area, therefore, we were able to locate 135 additional events. We estimate local magnitudes for events using maximum peak-to-trough amplitude and epicentral distance. As expected, our detection threshold becomes lower with higher station density. We find sparse seismicity across the study area apart from two areas that contain clustered and more frequent activity (Dog Valley and Cove Fort), which together account for roughly 70% of the recorded seismicity. A third prominent cluster in the central Mineral Mountains contains about 15% of the recorded seismicity. Lastly, the remainder of the detected seismicity is spread across the study area.

58 GEOSCIENCES↗

Using Machine Learning to Discern Eruption in Noisy Environments: A Case Study Using CO2-Driven Cold-Water Geyser in Chimayó, New Mexico

In this paper, we present an approach based on machine learning (ML) to distinguish eruption and precursory signals of Chimayó geyser (New Mexico, U.S.A.) under noisy environmental conditions. This geyser can be considered a natural analog of CO 2 intrusion into shallow water aquifers. By studying this geyser, we can understand upwelling of CO 2 -rich fluids from depth, which has relevance to leak monitoring in a CO 2 sequestration project. ML methods such as random forests (RFs) are known to be robust multiclass classifiers and perform well under unfavorable, noisy conditions. However, the extent of the RF method’s accuracy is poorly understood for this CO 2 -driven geysering application. The current study aims to quantify the performance of RF classifiers to discern the geyser state. Toward this goal, we first present the data collected from the seismometer that is installed near the Chimayó geyser. The seismic signals collected at this site contain different types of noises such as daily temperature variations, animal movement near the geyser, and human activity. First, we filter the signals from these noises by combining the Butterworth high-pass (BH) filter and an autoregressive (AR) method in a multilevel fashion. We show that by combining these filtering techniques in a hierarchical fashion leads to a reduction in noise in the seismic data without removing the precursors and eruption event signals. We then use RF on the filtered data to classify the state of geyser into three classes: remnant noise, precursor, and eruption states. RF classifier is constructed based on the comprehensive features extracted using the Tsfresh Python package. We show that the classification accuracy using RF on the filtered data is greater than 90%. We also evaluate the accuracy of other classical time-series methods such as dynamic time warping (DTW) on filtered data along with RF on partially filtered data in which we remove the daily trends. Classification accuracy shows that DTW performs poorly (44%) and RF on partially filtered data performs decently (87%). Denoising seismic signals from both daily trends and human activity enhances RF classifier performance by 7%. Finally, these aspects make the proposed ML framework attractive for event discrimination and signal enhancement under noisy conditions, with strong potential for application to monitor leaks in CO 2 sequestration.

58 GEOSCIENCES↗

Dissolution of Used Nuclear Fuel Using a TBP/N-Paraffin Solvent

The dissolution of unirradiated used nuclear fuel (UNF) pellets pretreated for tritium removal was demonstrated using a tributly phosphate (TBP) solvent. Dissolution of pretreated fuel in TBP could potentially combine dissolution with two cycle of solvent extraction required for separating the actinides and lanthanides from other fission products. Dissolutions were performed using UNF surrogates prepared from both uranyl nitrate and uranium trioxide produced from the pretreatment process by adding selected actinide and stable fission product elements. In laboratory-scale experiments, the U dissolution efficiency ranged from 80-99+% for both the nitrate and oxide surrogate fuels. On average, 80% of the Pu and 50% of the Np and Am in the nitrate surrogate dissolved; however, little of the transuranic elements dissolved in the oxide form. The majority of the 3+ lanthanide elements dissolved. Only small amounts of Sr (0-1.6%) and Mo (0.1-1.7%) and essentially no Cs, Ru, Zr, or Pd dissolved.

##CAI suggestions##↗