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At least 217 records · Page 12

Design and optimization of a modular hydrogen-based integrated energy system to maximize revenue via nuclear-renewable sources

Here, this paper demonstrates a novel modular distributed framework that uses optimal energy-dispatching strategies to enable greater flexibility and profitability in nuclear-renewable integrated energy systems (NR-IES). Hydrogen is used as a commodity in this framework since its production can improve grid stability and system operational flexibility, decarbonize heavy industry, and create an additional revenue stream for electricity generators, particularly nuclear power plants with high operational expenses. The proposed solution addresses the challenges associated with merging multiple software and services from various domains by using functional mock-up units (FMU) to co-simulate diverse subsystems designed in various platforms. The tightly coupled integrated energy system (IES) is optimized to maximize revenue by utilizing the deep reinforcement learning (DRL) technique to make smart dispatching decisions based on variable electricity prices and the availability of renewable energy. Proximal policy optimization (PPO) algorithm is used in training and testing the DRL agent. Over a period of 120 days, the proposed hydrogen-based IES framework showed about 10% revenue boost compared to a non-hydrogen generating baseline IES while also providing an easily-adoptable framework which can help to improve the flexibility of future generation nuclear power plants.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Establishing a silica gel zone in well annulus and evaluating its performance in blocking vertical water flow

Wells are often constructed for monitoring purposes with relatively long screen lengths (e.g., >10 m). Vertical water flows can occur within the artificial or natural filterpack annulus that surrounds the screened interval, bypassing packer assemblies installed inside the wellbore. Attempts to isolate discrete vertical zones during groundwater sampling are unsuccessful when annular flow occurs and lead to remedy decisions based on biased or incorrect interpretations. Blocking vertical annular water flow and contaminant transport will help obtain more accurate concentrations of contaminants from sampling in targeted depth intervals. The application of silica gels formed from the injected colloidal silica CS suspensions is a novel approach to minimize or prevent movement of vertical movement of groundwater in the surrounding filterpack annulus. In this work, we tested the feasibility of injecting CS suspensions to target locations and developed a modified CS formulation that is injectable and prevents gravity sinking. We studied the distribution and penetration of silica gel at laboratory scale in mock well annulus with surrounding formations. We evaluated the performance of the silica gel in blocking vertical water flow in the annulus and in minimizing chemical transport through the gel zone. CS suspension formulations have been defined that are ready for injection, stay in target locations, and form gel within desired time frames. Injection of CS suspensions achieved uniform distribution in a well annulus filter pack, fully occupied the annulus pore space, and penetrated the formation surrounding the filter packer with a sufficient distance to create a hydraulic annular seal when the injection was applied at a sufficient rate. The depth of penetration into the formation was dependent on the permeability contrast between the filter pack and the surrounding formation. Silica gel that formed in the annulus blocked vertical water flow and stopped the chemical transport through the gel zone. In conclusion, this research reveals that using CS suspension injection and sequential gelation (CS-GEL) is a promising technology for blocking vertical water flow and chemical transport through the filter pack in targeted zones within the annulus of long-screened well systems.

Colloidal silica suspension↗

Assessment of the associated particle technique with high-resolution gamma-ray spectroscopy for in-field identification of chemical warfare agents and explosives

In this work, high-resolution prompt γ-ray neutron activation analysis (PGNAA) is performed using the associated particle (AP) technique with a deuterium-tritium neutron generator and high-purity germanium detector. Although the time resolution is inferior compared to similar systems employing fast scintillation γ-ray detectors, the strong background suppression combined with the high γ-ray energy resolution provides an important boost in sensitivity to certain key elements, especially relevant to field measurements of complex chemicals encased within thick layers of metal, such as in the case of recovered chemical warfare (CW) munitions. Results for various CW and explosive simulants contained within mock munitions are presented and compared with results obtained from traditional PGNAA measurements without the aid of the AP technique. Significant improvements in identification and discrimination between certain chemicals are achieved with the high energy resolution AP technique.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Design of a separate effects MiniFuel irradiation experiment investigating microstructure evolution in high burnup UO 2

The microstructural evolution of UO 2 fuel pellets during commercial operation in light water reactors (LWRs) is known to vary significantly across the pellet radius due to spatial variations in local temperature and burnup. The primary obstacle to extending LWR refueling cycles to 24-month intervals is the susceptibility of certain high burnup fuel microstructures to fuel fragmentation, relocation, and dispersal (FFRD) during a loss of coolant accident (LOCA). Although FFRD of the high burnup structure in the rim region of a pellet is well studied, the fine fragmentation that has been observed in a second region, near the midradius of the pellet (termed the “dark zone”) following mock LOCA testing of high burnup commercial fuel rods is less understood. This paper describes the design, analysis, and execution of a separate effects MiniFuel irradiation experiment that aims to identify the specific temperature and burnup regimes under which FFRD-susceptible dark zone microstructures form. The small disc specimens (3 mm diameter by ∼0.3 mm thick) enable more precise control of the relatively uniform temperature and burnup conditions. A total of 42 specimens were fabricated with typical LWR fuel densities (∼96%–98% of theoretical density) and grain sizes (∼12 μm) and are being irradiated over a range of temperatures (600°C–1000°C) and discharge burnups (50–72 MWd/kg-U) that bound the midradius region of high burnup LWR fuel. Fuel specimens with identical 235 U enrichments were inserted in two irradiation locations in the High Flux Isotope Reactor and are currently undergoing irradiation to further evaluate the impact of rate effects (fission rate, time at temperature) on the microstructural evolution. The fuel fabrication and the thermal and neutronic simulations used for designing the experiment are detailed in this paper. A secondary objective of the experiment is to observe fission gas release (FGR) under the various irradiation conditions, and this work provides first-order predictions of FGR from all fuel specimens. The insights gained from these experiments will inform future high burnup core designs that could minimize the formation of susceptible microstructures and ultimately enable 24-month refueling cycles while minimizing the fraction of the fuel susceptible to FFRD.

FFRD↗

Composite binder, processing, and particle size effects on mechanical properties of non-hazardous high explosive surrogates

Plastic-bonded explosives (PBX) are polymer matrix composites that are highly loaded with micron-scale explosive crystals. The thermal and mechanical properties of these materials must be well-understood so that appropriate engineering models can be developed, but testing such properties under many scenarios can be hazardous and expensive. A non-hazardous PBX surrogate (“mock”) may be used in place of a PBX in many experiments if the thermomechanical properties are well-matched. Our previous research has shown that 5-iodo-2'-deoxyuridine (IDOX) is a promising crystalline filler material for the explosive cyclotetramethylene-tetranitramine (HMX). In this study, we investigate how the binder composition, variations in the IDOX particle size distribution, and pressing temperature affect the compressive strength and elastic modulus. We observe that while the binder system used in the composite dominates the mechanical response, the particle size distribution and pressing conditions do have a measurable effect on the material compliance and strength.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

Accurate Identification of Deamidation and Citrullination from Global Shotgun Proteomics Data Using a Dual-Search Delta Score Strategy

While proteins with deamidated/citrullinated amino acids play critical roles in the pathogenesis of many human diseases, identifying these modifications in complex biological samples has been an ongoing challenge. Herein we present a method to accurately identify these modifications from shotgun proteomics data from a deep proteome profiling study of human pancreatic islets obtained by laser capture microdissection. All MS/MS spectra were searched against database by MSGF+ twice with or without a +0.9840 Da mass shift on amino acids asparagine, glutamine, and arginine (NQR) as a dynamic modification. Consequently, for each spectrum the resulting two peptide-to-spectrum matches (PSM) with their respective MSGF+ scores were used for Delta Score calculation. It was observed that all PSMs with positive Delta Score values were clustered with mass errors around 0 ppm, while PSMs with negative Delta Score values were distributed nearly equally within the defined mass error range (20 ppm) for database searching. To estimate false discovery rate (FDR), a “pseudo-decoy” approach was applied whether datasets were searched against a database with a “real modification” mass shift (+0.9840 Da) and a “mock modification” mass shift (+1.0227 Da). FDR was controlled to ~2% with a Delta Score filter greater than zero. Manual inspection of spectra showed that PSMs with positive Delta Score value contained deamidated/citrullinated fragments in their MS/MS spectra. Finally, the results demonstrated that in-situ deamidated/citrullinated peptides can be accurately identified from shotgun tissue proteomics data by the Dual-search Delta Score Strategy.

59 BASIC BIOLOGICAL SCIENCES↗

The DNA glycosylase NEIL2 is protective during SARS-CoV-2 infection

SARS-CoV-2 infection-induced aggravation of host innate immune response not only causes tissue damage and multiorgan failure in COVID-19 patients but also induces host genome damage and activates DNA damage response pathways. To test whether the compromised DNA repair capacity of individuals modulates the severity of COVID-19 infection, we analyze DNA repair gene expression in publicly available patient datasets and observe a lower level of the DNA glycosylase NEIL2 in the lungs of severely infected COVID-19 patients. This observation of lower NEIL2 levels is further validated in infected patients, hamsters and ACE2 receptor-expressing human A549 (A549-ACE2) cells. Furthermore, delivery of recombinant NEIL2 in A549-ACE2 cells shows decreased expression of proinflammatory genes and viral E-gene, as well as lowers the yield of viral progeny compared to mock-treated cells. Mechanistically, NEIL2 cooperatively binds to the 5’-UTR of SARS-CoV-2 genomic RNA to block viral protein synthesis. Collectively, these data strongly suggest that the maintenance of basal NEIL2 levels is critical for the protective response of hosts to viral infection and disease.

60 APPLIED LIFE SCIENCES↗

CheckV assesses the quality and completeness of metagenome-assembled viral genomes

Abstract Millions of new viral sequences have been identified from metagenomes, but the quality and completeness of these sequences vary considerably. Here we present CheckV, an automated pipeline for identifying closed viral genomes, estimating the completeness of genome fragments and removing flanking host regions from integrated proviruses. CheckV estimates completeness by comparing sequences with a large database of complete viral genomes, including 76,262 identified from a systematic search of publicly available metagenomes, metatranscriptomes and metaviromes. After validation on mock datasets and comparison to existing methods, we applied CheckV to large and diverse collections of metagenome-assembled viral sequences, including IMG/VR and the Global Ocean Virome. This revealed 44,652 high-quality viral genomes (that is, >90% complete), although the vast majority of sequences were small fragments, which highlights the challenge of assembling viral genomes from short-read metagenomes. Additionally, we found that removal of host contamination substantially improved the accurate identification of auxiliary metabolic genes and interpretation of viral-encoded functions.

59 BASIC BIOLOGICAL SCIENCES↗

Benchmarking second and third-generation sequencing platforms for microbial metagenomics

Shotgun metagenomic sequencing is a common approach for studying the taxonomic diversity and metabolic potential of complex microbial communities. Current methods primarily use second generation short read sequencing, yet advances in third generation long read technologies provide opportunities to overcome some of the limitations of short read sequencing. Here, we compared seven platforms, encompassing second generation sequencers (Illumina HiSeq 300, MGI DNBSEQ-G400 and DNBSEQ-T7, ThermoFisher Ion GeneStudio S5 and Ion Proton P1) and third generation sequencers (Oxford Nanopore Technologies MinION R9 and Pacific Biosciences Sequel II). We constructed three uneven synthetic microbial communities composed of up to 87 genomic microbial strains DNAs per mock, spanning 29 bacterial and archaeal phyla, and representing the most complex and diverse synthetic communities used for sequencing technology comparisons. Our results demonstrate that third generation sequencing have advantages over second generation platforms in analyzing complex microbial communities, but require careful sequencing library preparation for optimal quantitative metagenomic analysis. Our sequencing data also provides a valuable resource for testing and benchmarking bioinformatics software for metagenomics.

59 BASIC BIOLOGICAL SCIENCES↗

Passive high explosive neutron inspection (PHENIX): a new method to confirm the presence or absence of high explosives for nuclear treaty verification

Advanced instruments and methods need to be developed now to create a technical basis to support the negotiation of future nuclear arms control treaties. One new capability that is anticipated is the ability to confirm either the declared presence or declared absence of high explosive (HE) material in the presence of special nuclear material (SNM). Towards this goal, Passive HE Neutron Inspection (PHENIX) has been developed and demonstrated as a method for confirming the presence or absence of HE in the presence of plutonium. The method exploits the inherent presence of neutrons associated with the decay of plutonium as an internal probe source for performing prompt gamma-ray neutron activation analysis (PGNAA), searching for the presence of HE as revealed by the emission of characteristic gamma rays following neutron absorption in hydrogen and nitrogen which are building blocks of present-day, military-grade HE. Tests using stoichiometrically-correct hemishells of mock HE with plutonium show that a system can be expected to positively confirm the presence or absence of these signatures, supporting determination of HE presence or absence with Pu, in a few hours. To protect other potentially sensitive gamma-ray signatures from a treaty accountable item, an analog information barrier has been conceptualized and tested which physically prevents the collection of gamma-ray spectral data outside of user selected energy windows strategically chosen to view only narrow spectral regions corresponding to the hydrogen (2223.2 keV) and nitrogen (9807.2 keV, 10,318.2 keV, and 10,829.2 keV) PGNAA signatures.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Diversity of Antibiotic Resistance genes and Transfer Elements-Quantitative Monitoring (DARTE-QM): a method for detection of antimicrobial resistance in environmental samples

Effective monitoring of antibiotic resistance genes and their dissemination in environmental ecosystems has been hindered by the cost and efficiency of methods available for the task. We developed the Diversity of Antibiotic Resistance genes and Transfer Elements-Quantitative Monitoring (DARTE-QM), a method implementing TruSeq high-throughput sequencing to simultaneously sequence thousands of antibiotic resistant gene targets representing a full-spectrum of antibiotic resistance classes common to environmental systems. In this study, we demonstrated DARTE-QM by screening 662 antibiotic resistance genes within complex environmental samples originated from manure, soil, and livestock feces, in addition to a mock-community reference to assess sensitivity and specificity. DARTE-QM offers a new approach to studying antibiotic resistance in environmental microbiomes, showing advantages in efficiency and the ability to scale for many samples. This method provides a means of data acquisition that will alleviate some of the obstacles that many researchers in this area currently face.

59 BASIC BIOLOGICAL SCIENCES↗

A group finder algorithm optimised for the study of local galaxy environments

Context. The majority of galaxy group catalogues available in the literature use the popular friends-of-friends algorithm which links galaxies using a linking length. One potential drawback to this approach is that clusters of points can be linked with thin bridges which may not be desirable. In order to study galaxy groups, it is important to obtain realistic group structures. Aim. Here, in this study, we present a new simple group finder algorithm, TD-ENCLOSER, that finds the group that encloses a target galaxy of interest. Methods. TD-ENCLOSER is based on the kernel density estimation method which treats each galaxy, represented by a zero-dimensional particle, as a two-dimensional circular Gaussian. The algorithm assigns galaxies to peaks in the density field in order of density in descending order (‘top down’) so that galaxy groups ‘grow’ around the density peaks. Outliers in under-dense regions are prevented from joining groups by a specified hard threshold, while outliers at the group edges are clipped below a soft (blurred) interior density level. Results. The group assignments are largely insensitive to all free parameter variations apart from the hard density threshold and the kernel standard deviation, although this is a known feature of density-based group finder algorithms and it operates with a computing speed that increases linearly with the size of the input sample. In preparation for a companion paper, we also present a simple algorithm to select unique representative groups when duplicates occur. Conclusions. TD-ENCLOSER is tested on a mock galaxy catalogue using a smoothing scale of 0.3 Mpc and is found to be able to recover the input group distribution with sufficient accuracy to be applied to observed galaxy distributions.

79 ASTRONOMY AND ASTROPHYSICS↗

Cataloging accreted stars within Gaia DR2 using deep learning

The goal of this study is to present the development of a machine learning based approach that utilizes phase space alone to separate the Gaia DR2 stars into two categories: those accreted onto the Milky Way from those that are in situ. Traditional selection methods that have been used to identify accreted stars typically rely on full 3D velocity, metallicity information, or both, which significantly reduces the number of classifiable stars. The approach advocated here is applicable to a much larger portion of Gaia DR2. Methods. A method known as “transfer learning” is shown to be effective through extensive testing on a set of mock Gaia catalogs that are based on the F IRE cosmological zoom-in hydrodynamic simulations of Milky Way-mass galaxies. The machine is first trained on simulated data using only 5D kinematics as inputs and is then further trained on a cross-matched Gaia /RAVE data set, which improves sensitivity to properties of the real Milky Way. Results. The result is a catalog that identifies ~767 000 accreted stars within Gaia DR2. This catalog can yield empirical insights into the merger history of the Milky Way and could be used to infer properties of the dark matter distribution.

Astronomy & Astrophysics↗

TDCOSMO - IV. Hierarchical time-delay cosmography – joint inference of the Hubble constant and galaxy density profiles

The H0LiCOW collaboration inferred via strong gravitational lensing time delays a Hubble constant value of H0 = 73.3−1.8+1.7 km s−1 Mpc−1, describing deflector mass density profiles by either a power-law or stars (constant mass-to-light ratio) plus standard dark matter halos. The mass-sheet transform (MST) that leaves the lensing observables unchanged is considered the dominant source of residual uncertainty in H0. We quantify any potential effect of the MST with a flexible family of mass models, which directly encodes it, and they are hence maximally degenerate with H0. Our calculation is based on a new hierarchical Bayesian approach in which the MST is only constrained by stellar kinematics. The approach is validated on mock lenses, which are generated from hydrodynamic simulations. We first applied the inference to the TDCOSMO sample of seven lenses, six of which are from H0LiCOW, and measured H0 = 74.5−6.1+5.6 km s−1 Mpc−1. Secondly, in order to further constrain the deflector mass density profiles, we added imaging and spectroscopy for a set of 33 strong gravitational lenses from the Sloan Lens ACS (SLACS) sample. For nine of the 33 SLAC lenses, we used resolved kinematics to constrain the stellar anisotropy. From the joint hierarchical analysis of the TDCOSMO+SLACS sample, we measured H0 = 67.4−3.2+4.1 km s−1 Mpc−1. This measurement assumes that the TDCOSMO and SLACS galaxies are drawn from the same parent population. The blind H0LiCOW, TDCOSMO-only and TDCOSMO+SLACS analyses are in mutual statistical agreement. The TDCOSMO+SLACS analysis prefers marginally shallower mass profiles than H0LiCOW or TDCOSMO-only. Without relying on the form of the mass density profile used by H0LiCOW, we achieve a ∼5% measurement of H0. While our new hierarchical analysis does not statistically invalidate the mass profile assumptions by H0LiCOW – and thus the H0 measurement relying on them – it demonstrates the importance of understanding the mass density profile of elliptical galaxies. The uncertainties on H0 derived in this paper can be reduced by physical or observational priors on the form of the mass profile, or by additional data.Key words: gravitational lensing: strong / galaxies: general / galaxies: kinematics and dynamics / distance scale / cosmological parameters / cosmology: observations⋆ The full analysis is available at https://github.com/TDCOSMO/hierarchy_analysis_2020_public.

79 ASTRONOMY AND ASTROPHYSICS↗

An algorithm to locate the centers of baryon acoustic oscillations

The cosmic structure formed from baryon acoustic oscillations (BAO) in the early universe is imprinted in the galaxy distribution observable in large-scale surveys and is used as a standard ruler in contemporary cosmology. Typically, BAOs are detected as a preferential length scale in two-point statistics, which gives little information about the location of the BAO structures in real space. The aim of the algorithm described in this paper is to find probable centers of BAOs in the cosmic matter distribution. The algorithm convolves the three-dimensional distribution of matter density with a spherical shell kernel of variable radius placed at different locations. The locations that correspond to the highest values of the convolution correspond to the probable centers of BAOs. This method is realized in an open-source, computationally efficient algorithm. Here, we describe the algorithm and present the results of applying it to the SDSS DR9 CMASS survey and associated mock catalogs. A detailed performance study demonstrates the ability of the algorithm to locate BAO centers and in doing so presents a novel detection of the BAO scale in galaxy surveys.

79 ASTRONOMY AND ASTROPHYSICS↗

ConKer: An algorithm for evaluating correlations of arbitrary order

Context. High order correlations in the cosmic matter density have become increasingly valuable in cosmological analyses. However, computing these correlation functions is computationally expensive. Aims. We aim to circumvent these challenges by developing a new algorithm called ConKer for estimating correlation functions. Methods. This algorithm performs convolutions of matter distributions with spherical kernels using FFT. Since matter distributions and kernels are defined on a grid, it results in some loss of accuracy in the distance and angle definitions. We study the algorithm setting at which these limitations become critical and suggest ways to minimize them. Results. ConKer is applied to the CMASS sample of the SDSS DR12 galaxy survey and corresponding mock catalogs, and is used to compute the correlation functions up to correlation order n = 5. We compare the n = 2 and n = 3 cases to traditional algorithms to verify the accuracy of the new algorithm. We perform a timing study of the algorithm and find that three of the four distinct processes within the algorithm are nearly independent of the catalog size N , while one subdominant component scales as O ( N ). The dominant portion of the calculation has complexity of O ( N c 4/3 log N c ), where N c is the of cells in a three-dimensional grid corresponding to the matter density. Conclusions. We find ConKer to be a fast and accurate method of probing high order correlations in the cosmic matter density, then discuss its application to upcoming surveys of large-scale structure.

79 ASTRONOMY AND ASTROPHYSICS↗

Search of strong lens systems in the Dark Energy Survey using convolutional neural networks

We present our search for strong lens, galaxy-scale systems in the first data release of the Dark Energy Survey (DES), based on a color-selected parent sample of 18 745 029 luminous red galaxies (LRGs). We used a convolutional neural network (CNN) to grade this LRG sample with values between 0 (non-lens) and 1 (lens). Our training set of mock lenses is data-driven, that is, it uses lensed sources taken from HST-COSMOS images and lensing galaxies from DES images of our LRG sample. A total of 76 582 cutouts were obtained with a score above 0.9, which were then visually inspected and classified into two catalogs. The first one contains 405 lens candidates, of which 90 present clear lensing features and counterparts, while the other 315 require more evidence, such as higher resolution imaging or spectra, to be conclusive. A total of 186 candidates are newly identified by our search, of which 16 are among the 90 most promising (best) candidates. The second catalog includes 539 ring galaxy candidates. This catalog will be a useful false positive sample for training future CNNs. For the 90 best lens candidates we carry out color-based deblending of the lens and source light without fitting any analytical profile to the data. This method is shown to be very efficient in the deblending, even for very compact objects and for objects with a complex morphology. Finally, from the 90 best lens candidates, we selected 52 systems with one single deflector to test an automated modeling pipeline that has the capacity to successfully model 79% of the sample within an acceptable computing runtime.

79 ASTRONOMY AND ASTROPHYSICS↗

TDCOSMO VIII. A key test of systematics in the hierarchical method of time-delay cosmography

The largest source of systematic errors in the time-delay cosmography method likely arises from the lens model mass distribution, where an inaccurate choice of model could in principle bias the value of $H$ 0 . A Bayesian hierarchical framework has been proposed which combines lens systems with kinematic data, constraining the mass profile shape at a population level. The framework has been previously validated using a small sample of lensing galaxies drawn from hydro-simulations. The goal of this work is to expand the validation to a more general set of lenses consistent with observed systems, as well as confirm the capacity of the method to combine two lens populations: one which has time delay information and one which lacks time delays and has systematically different image radii. For this purpose, we generated samples of analytic lens mass distributions made of baryons+dark matter and fit the subsequent mock images with standard power-law models. Corresponding kinematics data were also emulated. The hierarchical framework applied to an ensemble of time-delay lenses allowed us to correct the $H$ 0 bias associated with model choice to find $H$ 0 within 1.5σ of the fiducial value. We then combined this set with a sample of corresponding lens systems which have no time delays and have a source at lower $z$, resulting in a systematically smaller image radius relative to their effective radius. The hierarchical framework has successfully accounted for this effect, recovering a value of $H$ 0 which is both more precise (σ ~ 2%) and more accurate (0.7% median offset) than the time-delay set alone. This result confirms that non-time-delay lenses can nonetheless contribute valuable constraining power to the determination of $H$ 0 via their kinematic constraints, assuming they come from the same global population as the time-delay set.

79 ASTRONOMY AND ASTROPHYSICS↗