Identifying divertor detachment using a machine learning model trained on divertor camera images from DIII-D
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Physics - Plasma physics↗
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Examining astrophysical gas cloud collapse using an optical depth-scaled, x-ray-irradiated, carbon-foam sphere
When stellar radiation interacts with a molecular cloud, the cloud's fate depends on the strength of the incident radiation and the radiation's mean-free-path within the cloud [F. Bertoldi, Astrophys. J. 346, 735–755 (1989)]. Under the right conditions, the radiation compresses the cloud and a star formation may occur. Where and when the stellar formation occurs in the cloud's collapse are open questions. Direct observation of the complete star–cloud lifecycle is nearly impossible due to the immense timescales and distances over which the interaction occurs. Laboratory astrophysics offers a way to investigate such a system by scaling the important astrophysical parameters to the laboratory. This work describes laboratory experiments to study the radiation-driven implosion of clouds, using x rays from a laser-irradiated, thin, gold foil as a surrogate star and a carbon-foam sphere as a surrogate cloud. An optically thick system, theoretically corresponding to a star-forming regime, was selected by choice of the foam density. Gold foil and sphere motions were imaged by x-ray radiography. Radiographic images show the formation of an interface between rarefied gold and carbon plasmas, a shock moving into the sphere, and a blunting of the initial sphere's shape. Measurements show that the shock moved linearly around 64 μm/ns into the sphere, and the gold–carbon interface formed by 2 ns at the sphere edge remained stationary. The deformation of the sphere was driven by the incident radiation and not by mechanical pressures applied by gold plasma. The blunting of the sphere was likely due to the geometric reduction of flux near the sphere's poles. Higher x-ray flux near the sphere's equator caused high compression and a faster shock, which flattened the sphere. We will discuss the results and implications of our observations.
VanDervort, R. W. [University of Michigan 1 , Ann ↗
Automated defect detection in spent nuclear fuel using combine Cerenkov and Gamma Emission Tomography data
Spent fuel monitoring and characterization has been a pillar of safeguards and nuclear facility monitoring for many years. The Digital Cerenkov Viewing Device (DCVD) has been used since the 1980s as a method of defect detection in spent fuel. In recent years, the accounting of large quantities of spent fuel before storage has renewed interest in this relatively quick and inexpensive method. This has an impact not only in safeguards, but also in for nuclear power facilities, as accounting can be a long and arduous process. Additionally, the DCVD demonstrates limited accuracy in more complex cases such as substitution of a fuel rod with steel, or a partial defect detection. A second method, Gamma Emission Tomography (GET) has been explored as an improved defect detection method, but is much more expensive and invasive than DCVD. This work identifies deficiencies in both methods, and proposes a combination of data gathered from each method to address these deficiencies for improved spent fuel characterization. Initial results are promising, showing 97% detection of a single missing fuel rod when the data types are combined, versus approximately 50% and 70%respectively for DCVD and GET data on their own. Finally, these classification results are obtained with algorithms derived from facial recognition and applied to this problem, yielding unique accuracy in near real-time while also maintaining the information barrier between output and measurement desired in safeguards.
11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
Radiation Source Localization Using Surrogate Models Constructed from 3-D Monte Carlo Transport Physics Simulations
Recent research has focused on the development of surrogate models for radiation source localization in a simulated urban domain. We employ the Monte Carlo N-Particle (MCNP) code to provide high- delity simulations of radiation transport within an urban domain. The model is constructed to employ a source location (x, y, z) as input and return the estimated count rate for a set of speci ed detector locations. Because MCNP simulations are computationally expensive, we develop e cient and accurate surrogate models of the detector responses. We construct surrogate models using Gaussian processes (GP) and neural networks (NN) that we train and verify using the MCNP simulations. The trained surrogate models provide an e cient framework for Bayesian inference and experimental design. We employ Delayed Rejection Adaptive Metropolis (DRAM), a Markov Chain Monte Carlo (MCMC) algorithm, to infer the location and intensity of an unknown source. The DRAM results yield a posterior probability distribution for the source's location conditioned on the observed detector count rates. The posterior distribution exhibits regions of high and low probability within the simulated environment identifying potential source locations. In this manner, we can quantify the source location to within at least one of these regions of high probability in the considered cases. Employing these methods, we are able to reduce the space of potential source locations by at least 60%.
46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
Search for photons with energies above 10 18 eV using the hybrid detector of the Pierre Auger Observatory
A search for ultra-high energy photons with energies above 1 EeV is performed using nine years of data collected by the Pierre Auger Observatory in hybrid operation mode. An unprecedented separation power between photon and hadron primaries is achieved by combining measurements of the longitudinal air-shower development with the particle content at ground measured by the fluorescence and surface detectors, respectively. Only three photon candidates at energies 1 - 2 EeV are found, which is compatible with the expected hadron-induced background. Upper limits on the integral flux of ultra-high energy photons of 0.027, 0.009, 0.008, 0.008 and 0.007 km$^{-2}$ sr$^{-1}$ yr$^{-1}$ are derived at 95% C.L. for energy thresholds of 1, 2, 3, 5 and 10 EeV. These limits bound the fractions of photons in the all-particle integral flux below 0.1%, 0.15%, 0.33%, 0.85% and 2.7%. For the first time the photon fraction at EeV energies is constrained at the sub-percent level. The improved limits are below the flux of diffuse photons predicted by some astrophysical scenarios for cosmogenic photon production. Here, the new results rule-out the early top-down models $-$ in which ultra-high energy cosmic rays are produced by, e.g., the decay of super-massive particles $-$ and challenge the most recent super-heavy dark matter models.
72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
Characterizing the Lyα forest flux probability distribution function using Legendre polynomials
The Lyman-α forest is a highly non-linear field with considerable information available in the data beyond the power spectrum. The flux probability distribution function (PDF) has been used as a successful probe of small-scale physics. In this paper we argue that measuring coefficients of the Legendre polynomial expansion of the PDF offers several advantages over measuring the binned values as is commonly done. In particular, the n -th Legendre coefficient can be expressed as a linear combination of the first n moments, allowing these coefficients to be measured in the presence of noise and allowing a clear route for marginalisation over mean flux. Moreover, in the presence of noise, our numerical work shows that a finite number of coefficients are well measured with a very sharp transition into noise dominance. This compresses the available information into a small number of well-measured quantities. In conclusion, we find that the amount of recoverable information is a very non-linear function of spectral noise that strongly favors fewer quasars measured at better signal to noise.
79 ASTRONOMY AND ASTROPHYSICS↗
Large-Eddy Simulations of Idealized Atmospheric Boundary Layers Using Nalu-Wind
Accurate prediction of wind-plant performance relies, in part, on properly characterizing the turbulent atmospheric boundary layer (ABL) flow in which wind turbines operate. Large-eddy simulation (LES) is a powerful tool for simulating ABLs because it resolves the largest, most energetic scales of three-dimensional turbulent motions. Yet LES predictions are well known to depend on modeling choices such as grid resolution, numerical discretization schemes, and closures for unresolved scales of turbulence. Here, we evaluate how these choices influence predictions of ABL winds using Nalu-Wind, a wind-specific fork of the open-source, generalized, unstructured, massively parallel flow solver NaluCFD/Nalu.
17 WIND ENERGY↗
Electron and photon energy calibration with the ATLAS detector using 2015–2016 LHC proton-proton collision data
This paper presents the electron and photon energy calibration obtained with the ATLAS detector using about 36 fb –1 of LHC proton-proton collision data recorded at √s = 13 TeV in 2015 and 2016. The different calibration steps applied to the data and the optimization of the reconstruction of electron and photon energies are discussed. The absolute energy scale is set using a large sample of Z boson decays into electron-positron pairs. The systematic uncertainty in the energy scale calibration varies between 0.03% to 0.2% in most of the detector acceptance for electrons with transverse momentum close to 45 GeV . For electrons with transverse momentum of 10 GeV the typical uncertainty is 0.3% to 0.8% and it varies between 0.25% and 1% for photons with transverse momentum around 60 GeV . Validations of the energy calibration with J/ψ → e + e – decays and radiative Z boson decays are also presented.
72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
Revisiting the climate impacts of cool roofs around the globe using an Earth system model
Not Available
Zhang, Jiachen↗
Fixation of CO 2 and CO on a diverse range of carbohydrates using anaerobic, non-photosynthetic mixotrophy
Biological CO 2 fixation is an important technology that can assist in combating climate change. Here, we show an approach called anaerobic, non-photosynthetic mixotrophy can result in net CO 2 fixation when using a reduced feedstock. This approach uses microbes called acetogens that are capable of concurrent utilization of both organic and inorganic substrates. In this study, we investigated the substrate utilization of 17 different acetogens, both mesophilic and thermophilic, on a variety of different carbohydrates and gases. Compared to most model acetogen strains, several non-model mesophilic strains displayed greater substrate flexibility, including the ability to utilize disaccharides, glycerol and an oligosaccharide, and growth rates. Three of these non-model strains ( Blautia producta , Clostridium scatologenes and Thermoanaerobacter kivui ) were chosen for further characterization, under a variety of conditions including H 2 - or syngas-fed sugar fermentations and a CO 2 -fed glycerol fermentation. In all cases, CO 2 was fixed and carbon yields approached 100%. Finally, the model acetogen C. ljungdahlii was engineered to utilize glucose, a non-preferred sugar, while maintaining mixotrophic behavior. This work demonstrates the flexibility and robustness of anaerobic, non-photosynthetic mixotrophy as a technology to help reduce CO 2 emissions.
09 BIOMASS FUELS↗
To use or not to use synthetic stellar spectra in population synthesis models?
ABSTRACT Stellar population synthesis (SPS) models are invaluable to study star clusters and galaxies. They provide means to extract stellar masses, stellar ages, star formation histories, chemical enrichment, and dust content of galaxies from their integrated spectral energy distributions, colours, or spectra. As most models, they contain uncertainties that can hamper our ability to model and interpret observed spectra. This work aims at studying a specific source of model uncertainty: the choice of an empirical versus a synthetic stellar spectral library. Empirical libraries suffer from limited coverage of parameter space, while synthetic libraries suffer from modelling inaccuracies. Given our current inability to have both ideal stellar-parameter coverage with ideal stellar spectra, what should one favour: better coverage of the parameters (synthetic library) or better spectra on a star-by-star basis (empirical library)? To study this question, we build a synthetic stellar library mimicking the coverage of an empirical library, and SPS models with different choices of stellar library tailored to these investigations. Through the comparison of model predictions and the spectral fitting of a sample of nearby galaxies, we learned that predicted colours are more affected by the coverage effect than the choice of a synthetic versus empirical library; the effects on predicted spectral indices are multiple and defy simple conclusions; derived galaxy ages are virtually unaffected by the choice of the library, but are underestimated when SPS models with limited parameter coverage are used; metallicities are robust against limited HRD coverage, but are underestimated when using synthetic libraries.
Coelho, Paula R. T.↗
Overcoming GNA/RNA base-pairing limitations using isonucleotides improves the pharmacodynamic activi
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Schlegel, Mark K.↗
Where’s Swimmy?: Mining unique color features buried in galaxies by deep anomaly detection using Subaru Hyper Suprime-Cam data
Abstract We present the Swimmy (Subaru WIde-field Machine-learning anoMalY) survey program, a deep-learning-based search for unique sources using multicolored (grizy) imaging data from the Hyper Suprime-Cam Subaru Strategic Program (HSC-SSP). This program aims to detect unexpected, novel, and rare populations and phenomena, by utilizing the deep imaging data acquired from the wide-field coverage of the HSC-SSP. This article, as the first paper in the Swimmy series, describes an anomaly detection technique to select unique populations as “outliers” from the data-set. The model was tested with known extreme emission-line galaxies (XELGs) and quasars, which consequently confirmed that the proposed method successfully selected $\sim\!\! 60\%$–$70\%$ of the quasars and $60\%$ of the XELGs without labeled training data. In reference to the spectral information of local galaxies at z = 0.05–0.2 obtained from the Sloan Digital Sky Survey, we investigated the physical properties of the selected anomalies and compared them based on the significance of their outlier values. The results revealed that XELGs constitute notable fractions of the most anomalous galaxies, and certain galaxies manifest unique morphological features. In summary, deep anomaly detection is an effective tool that can search rare objects, and, ultimately, unknown unknowns with large data-sets. Further development of the proposed model and selection process can promote the practical applications required to achieve specific scientific goals.
Astronomy & Astrophysics↗
Estimates of Ta strength at ultrahigh pressures and strain rates using thin-film graded-density impactors
In this paper, we present results from an experimental technique used to estimate the strength of Ta at extreme pressures (150 GPa) and strain rates (10 7 s -1 ). A graded-density impactor (GDI) was fabricated using sputter deposition to produce an approximately 40-μm-thick film containing alternating layers of Al and Cu. The thicknesses of the respective layers are adjusted to give an effective density gradient through the film. The GDIs were launched with a 2-stage light gas gun, and shock-ramp-release velocity profiles were measured over timescales of ~10 ns. Results are presented for the direct impact of the film onto LiF windows, which allows for a dynamic characterization of the GDI, as well as from impact onto thin (~40μm) sputtered Ta samples backed by a LiF window. The measurements were coupled with mesoscale numerical simulations to infer the strength of Ta, and the results agree well with other high-pressure platforms, particularly when strain-rate, microstructural, and thermodynamic-path differences are considered.
75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
Photoproduction of Λ and Σ 0 hyperons using linearly polarized photons
Not Available
72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
Measurement of the top quark polarization and t t ¯ spin correlations using dilepton final states in proton-proton collisions at s = 13 TeV
Not Available
72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
Feasibility study to use neutron capture for an ultralow energy nuclear-recoil calibration in liquid xenon
The feasibility of an ultra-low energy nuclear-recoil measurement in liquid xenon using neutron capture is investigated for a small (sub-kilogram) liquid xenon detector that is optimized for a high scintillation gain, and a pulsed neutron source. Further, the measurement uses the recoil energies imparted to xenon nuclei during the de-excitation process following neutron capture, where promptly emitted γ cascades can provide the nuclei with up to 0.3 keV nr of recoil energy due to conservation of momentum. A successful calibration of scintillation photon and ionization electron yields below this energy will contribute to a greater sensitivity for liquid xenon experiments in searches for light WIMPs.
72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗