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At least 919 records · Page 51

Variable Stars in the Giant Satellite Galaxy Antlia 2

We report 350 pulsating variable stars found in four DECam fields (~12 deg 2 ) covering the Antlia 2 satellite galaxy. The sample of variables includes 318 RR Lyrae stars and eight anomalous Cepheids in the galaxy. Reclassification of several objects designated previously to be RR Lyrae as anomalous Cepheids get rid of the satellite's stars intervening along the line of sight. This in turn removes the need for prolific tidal disruption of the dwarf, in agreement with the recently updated proper motion and pericenter measurements based on Gaia EDR3. There are also several bright foreground RR Lyrae stars in the field, and two distant background variables located ~45 kpc behind Antlia 2. We found RR Lyrae stars over the full search area, suggesting that the galaxy is very large and likely extends beyond our observed area. The mean period of the RRab in Antlia 2 is 0.599 days, while the RRc have a mean period of 0.368 days, indicating the galaxy is an Oosterhoff-intermediate system. The distance to Antlia 2 based on the RR Lyrae stars is 124.1 kpc (μ 0 = 20.47) with a dispersion of 5.4 kpc. We measured a clear distance gradient along the semimajor axis of the galaxy, with the southeast side of Antlia 2 being ~13 kpc farther away from the northwest side. This elongation along the line of sight is likely due to the ongoing tidal disruption of Ant 2.

79 ASTRONOMY AND ASTROPHYSICS↗

Multi defect detection and analysis of electron microscopy images with deep learning

Electron microscopy is widely used to explore defects in crystal structures, but human detecting of defects is often time-consuming, error-prone, and unreliable, and is not scalable to large numbers of images or real-time analysis. In this work, we discuss the application of machine learning approaches to find the location and geometry of different defect clusters in irradiated steels. We show that a deep learning based Faster R-CNN analysis system has a performance comparable to human analysis with relatively small training data sets. Furthermore, this study proves the promising ability to apply deep learning to assist the development of automated microscopy data analysis even when multiple features are present and paves the way for fast, scalable, and reliable analysis systems for massive amounts of modern electron microscopy data.

36 MATERIALS SCIENCE↗

System-of-systems optimization of hydrogen infrastructure for heavy-duty freight corridors: The interstate 10 case study

Medium and heavy-duty freight transportation requires hydrogen energy infrastructure that is cost-effective, operationally reliable, spatially coherent, and resilient to demand variability along major corridors. This paper presents an integrated hydrogen corridor planning framework using Oak Ridge National Laboratory's OR-AGENT that couples freight-driven, route-resolved hydrogen demand modeling with optimized station siting, sizing, and station-level techno-economic analysis. The framework is demonstrated for the Interstate 10 freight corridor and the Houston-to-Los-Angeles region. Hydrogen demand is derived from high-resolution origin–destination freight data, duty-cycle characterization, and physics-based energy consumption modeling. Candidate refueling sites are selected from existing heavy-duty diesel fueling locations and optimized subject to onboard storage and station capacity constraints. Resulting station throughputs are evaluated using established techno-economic models for electrolytic hydrogen production and dispensing infrastructure. Results show that a regional, portfolio-level aggregation, average dispensed electrolytic hydrogen cost of $6.87–$7.26/kg is currently feasible, and is strongly influenced by demand density and utilization.

Sujan, Vivek [ORNL] (ORCID:0000000269882342)↗

QuadConv: Quadrature-based convolutions with applications to non-uniform PDE data compression

We present a new convolution layer for deep learning architectures which we call QuadConv — an approximation to continuous convolution via quadrature. Our operator is developed explicitly for use on non-uniform, mesh-based data, and accomplishes this by learning a continuous kernel that can be sampled at arbitrary locations. Moreover, the construction of our operator admits an efficient implementation which we detail and construct. As an experimental validation of our operator, we consider the task of compressing partial differential equation (PDE) simulation data from fixed meshes. Here, we show that QuadConv can match the performance of standard discrete convolutions on uniform grid data by comparing a QuadConv autoencoder (QCAE) to a standard convolutional autoencoder (CAE). Further, we show that the QCAE can maintain this accuracy even on non-uniform data. In both cases, QuadConv also outperforms alternative unstructured convolution methods such as graph convolution.

Compression↗

A novel transient infrared imaging method for non-intrusive, low-cost, fast, and accurate air leakage detection in building envelopes

Air leakage through the building envelope in the U.S. accounts for about four quads of energy annually, costing approximately $40 billion per year. However, a high-fidelity and non-intrusive method to detect air leakage has not been demonstrated to date. Here, in this paper, we propose a novel non-intrusive and low-cost method called Transient Infrared (IR) Imaging (TIRI) that can rapidly and accurately identify air leakage locations and relative rates on building envelopes. When the interior and exterior temperatures are different, and a small internal pressure pulse is created by HVAC, the temperature at locations with air leakages will change rapidly, while the areas without a leakage do not change. Based on a heat transfer model, we have derived the temperature change as a function of time after the HVAC is turned on. By tracking the temperature change, which depends on leakage rate and size, we have obtained the air leakage map in the case studies. Using an exterior door as an example, we took transient IR images in different seasons and different times of the day, and successfully obtained the leakage map in all the scenarios. Successfully obtained the air leakage map even when the indoor-outdoor air temperature difference is as small as 2 °C. We have also realized a detection speed of 10s and demonstrated that this method also worked for windows, which have mirror-like IR reflections. Our TIRI method will accelerate the improvement of airtightness in buildings, save building energy, and help reduce greenhouse gas emissions.

42 ENGINEERING↗

Role of Ribosomal Protein bS1 in Orthogonal mRNA Start Codon Selection

In many bacteria, the location of the mRNA start codon is determined by a short ribosome binding site sequence that base pairs with the 3'-end of 16S rRNA (rRNA) in the 30S subunit. Many groups have changed these short sequences, termed the Shine-Dalgarno (SD) sequence in the mRNA and the anti-Shine-Dalgarno (ASD) sequence in 16S rRNA, to create "orthogonal" ribosomes to enable the synthesis of orthogonal polymers in the presence of the endogenous translation machinery. However, orthogonal ribosomes are prone to SD-independent translation. Ribosomal protein bS1, which binds to the 30S ribosomal subunit, is thought to promote translation initiation by shuttling the mRNA to the ribosome. Thus, a better understanding of how the SD and bS1 contribute to start codon selection could help efforts to improve the orthogonality of ribosomes. Here, we engineered the Escherichia coli ribosome to prevent binding of bS1 to the 30S subunit and separate the activity of bS1 binding to the ribosome from the role of the mRNA SD sequence in start codon selection. We find that ribosomes lacking bS1 are slightly less active than wild-type ribosomes in vitro. Furthermore, orthogonal 30S subunits lacking bS1 do not have an improved orthogonality. Our findings suggest that mRNA features outside the SD sequence and independent of binding of bS1 to the ribosome likely contribute to start codon selection and the lack of orthogonality of present orthogonal ribosomes.

59 BASIC BIOLOGICAL SCIENCES↗

The Illumination of Thunderclouds by Lightning: 1. The Extent and Altitude of Optical Lightning Sources

Abstract Optical space‐based lightning sensors including NOAA's Geostationary Lightning Mapper (GLM) detect lightning though its transient illumination of the surrounding clouds. What space‐based optical lightning sensors measure is influenced by the physical attributes of the light source, the location of the source within the cloud scene, and the spatial variations in cloud composition. We focus on the lightning channels that serve as optical sources for GLM groups and flashes in this first part of our thundercloud illumination study. We match Lightning Mapping Array (LMA) sources with GLM groups and flashes during two thunderstorms to examine channel segments that are active during optical emission. We find that in each storm, the LMA sources matched with GLM groups are small (median: 3 km) compared to GLM pixels (nominal: 8 km), and preferentially come from high altitudes in the cloud (>8–10 km). The detection advantage for high‐altitude sources permits GLM to resolve faint optical pulses near the cloud top that might be missed from lower altitudes. However, the most energetic groups can be detected from all altitudes, and the largest groups largely originate at low altitudes. The relationship between group energy and illuminated area depends on flash development within the cloud medium, and flash development into different cloud regions can be identified by tracking GLM metrics of cloud illumination over time.

58 GEOSCIENCES↗

Comparative study of boron and neon injections on divertor heat fluxes using SOLPS-ITER simulations

Here, based on the EAST equilibrium, the effects of boron (B) and neon (Ne) injected at different locations on the target heat load, and the distributions of B and Ne particles were investigated by transport code SOLPS-ITER. It was found that the B injection was more sensitive to the injection location for heat flux control than impurity Ne. The high electron and ion densities near the inner target in the discharge with impurity B injected from over X-point (R 1 ) led to plasma detachment only at the inner target, and the localized B ions in the cases with injection from outer target location (R 2 ) and upstream location (R 3 ) led to far-SOL detachment at the outer target, but not at the inner target. In contrast, for Ne, the spatial distributions of Ne ions and electrons were found to be similar in all the cases at the three injection locations, and the detached plasma was achieved at the inner target and the electron temperature was reduced at the outer target. For locations R 2 and R 3 , impurity B showed a more pronounced effect on the heat flux at the far-SOL of the outer target. Further analysis indicated that Ne atoms came mainly from the recycling sources, whereas B atoms came mainly from injection, and that their distinct atomic distributions resulted from the difference in the ionization threshold and ionization mean free path. In addition, the radiation proportion of B in the divertor region was larger than that of Ne when the total radiation power was similar, which suggests that B has less influence on the core region.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Crack Propagation Modeling of a High-Speed Outer Rotor Motor

This study aims to investigate the propagation of initial cracks in electric motors and their rate of spread through the rotor structure under various operating conditions. Traction motors are subjected to high centrifugal load owing to their speed and rapid acceleration and deceleration. In the manufacturing process, some initial imperfections or cracks in the rotor components are likely to occur. Under the influence of loading, these cracks will grow, and factors such as loading frequency, material strength, and location of material voids will affect this threshold speed. In the current study, a fracture mechanics–based approach has been used to investigate the crack growth rate for a 100 kW outer rotor motor with a rated speed of 6,000 rpm and a peak speed of 20,000 rpm for an integrated drive application.

Barua, Himel↗

Adaptive Threshold-Based Zonal Isolation of Faults in a Multiterminal DC Using Local Measurements

Fast and accurate methods of fault detection and isolation are a pre-emptive measure in multiterminal dc (MTdc) systems. Zonal isolation of faults is necessary to prevent any misopertation of the dc breakers that can lead to a shutdown of the network. Existing techniques require fast-communication or data synchronization methods have their own disadvantages. This article proposes a method for efficient fault zone isolation without the need of a communication link that prevents any misoperation of the dc breakers in a radial MTdc. This method provides individual local measurement-based control to the hybrid dc circuit breakers (dcCB). Faults created outside the zone of protection for a breaker create a change in the rate of change of current or voltage leading to misoperation. To avoid detection using a fixed threshold, an adaptive threshold based approach is suggested that updates the threshold based on the present operating status. Sensitivity analysis by varying the current limiting inductance and fault location is performed. In conclusion, a three terminal radial model of an MTdc is used for zonal isolation using power system computer aided design/electromagnetic transients including dc.

24 POWER TRANSMISSION AND DISTRIBUTION↗

SDN-Based Dynamic Cybersecurity Framework of IEC-61850 Communications in Smart Grid

In recent years, critical infrastructure and power grids have experienced a series of cyber-attacks, leading to temporary, widespread blackouts of considerable magnitude. Since most substations are unmanned and have limited physical security protection, cyber breaches into power grid substations present a risk. Nowadays, the susceptibility of SDN architecture to cyber-attacks has exhibited a notable increase in recent years, as indicated by research findings. This suggests a growing concern regarding the potential for cybersecurity breaches within the SDN framework. In this paper, we propose a hybrid intrusion detection system (IDS)-integrated SDN architecture for detecting and preventing the injection of malicious IEC 61850-based generic object-oriented system event (GOOSE) messages in a digital substation. Additionally, this program locates the fault’s location and, as a form of mitigation, disables a certain port. Furthermore, implementation examples are demonstrated and verified using a hardware-in-the-loop (HIL) testbed that mimics the functioning of a digital substation.

Liu, Chen-Ching [Virginia Tech] (ORCID:00000002894↗

A Power Outage Data Informed Resilience Assessment Framework

Catastrophic impacts to power systems due to disruptive events have increased significantly during the last decade. These events highlight the need to develop approaches to assess the resilience of power systems against extreme events. However, the availability of data that capture power system performance during and after disruptive events is scarce. This paper proposes an assessment framework to evaluate the performance aspects of the grid system during extreme outage events using the Environment for Analysis of Geo-Located Energy Information (EAGLE-I) data. EAGLE-I includes information related to the number of impacted customers, duration, and location of power outages in the United States. Statistical analyses were conducted to extract resilient-based outage data and derive probability distribution functions of their impact and recovery characteristics. A list of extreme events is identified based on few predetermined threshold values. Metrics from other power outage assessments were used to measure the characteristics of each event, including impact rate and duration, recovery rate and duration, and impact level. A probability distribution function is obtained for each metric. The obtained results provide a representation of national grid performance during extreme events, which can be applied as a framework to evaluate various resilience enhancement techniques.

EAGLE-I↗

Analysis of the ARTIC Version 3 and Version 4 SARS-CoV-2 Primers and Their Impact on the Detection of the G142D Amino Acid Substitution in the Spike Protein

The ARTIC Network provides a common resource of PCR primer sequences and recommendations for amplifying SARS-CoV-2 genomes. The initial tiling strategy was developed with the reference genome Wuhan-01, and subsequent iterations have addressed areas of low amplification and sequence drop out. Recently, a new version (V4) was released, based on new variant genome sequences, in response to the realization that some V3 primers were located in regions with key mutations. Herein, we compare the performance of the ARTIC V3 and V4 primer sets with a matched set of 663 SARS-CoV-2 clinical samples sequenced with an Illumina NovaSeq 6000 instrument. We observe general improvements in sequencing depth and quality, and improved resolution of the SNP causing the D950N variation in the spike protein. Importantly, we also find nearly universal presence of spike protein substitution G142D in Delta-lineage samples. Due to the prior release and widespread use of the ARTIC V3 primers during the initial surge of the Delta variant, it is likely that the G142D amino acid substitution is substantially underrepresented among early Delta variant genomes deposited in public repositories. In addition to the improved performance of the ARTIC V4 primer set, this study also illustrates the importance of the primer scheme in downstream analyses.

59 BASIC BIOLOGICAL SCIENCES↗

Dissolved oxygen sensor in an automated hyporheic sampling system reveals biogeochemical dynamics

Many river corridor systems frequently experience rapid variations in river stage height, hydraulic head gradients, and residence times. The integrated hydrology and biogeochemistry of such systems is challenging to study, particularly in their associated hyporheic zones. Here we present an automated system to facilitate 4-dimensional study of dynamic hyporheic zones. It is based on combining real-time in-situ and ex-situ measurements from sensor/sampling locations distributed in 3-dimensions. A novel dissolved oxygen (DO) sensor was integrated into the system during a small scale study. We measured several biogeochemical and hydrologic parameters at three subsurface depths in the riverbed of the Columbia River in Washington State, USA, a dynamic hydropeaked river corridor system. During the study, episodes of significant DO variations (~+/- 4 mg/l) were observed, with minor variation in other parameters (e.g., <~+/-0.15 mg/l NO 3 ). DO concentrations were related to hydraulic head gradients, showing both hysteretic and non-hysteretic relationships with abrupt (hours) transitions between the two types of relationships. The observed relationships provide a number of hypotheses related to the integrated hydrology and biogeochemistry of dynamic hyporheic zones. We suggest that preliminary high-frequency monitoring is advantageous in guiding the design of long term monitoring campaigns. The study also demonstrated the importance of measuring multiple parameters in parallel, where the DO sensor provided the key signal for identifying/detecting transient phenomena.

54 ENVIRONMENTAL SCIENCES↗

53BP1 Repair Kinetics for Prediction of In Vivo Radiation Susceptibility in 15 Mouse Strains

We present a novel mathematical formalism to predict the kinetics of DNA damage repair after exposure to both low- and high-LET radiation (X rays; 350 MeV/n 40 Ar; 600 MeV/n 56 Fe). Our method is based on monitoring DNA damage repair protein 53BP1 that forms radiation-induced foci (RIF) at locations of DNA double-strand breaks (DSB) in the nucleus and comparing its expression in primary skin fibroblasts isolated from 15 mice strains. We previously reported strong evidence for clustering of nearby DSB into single repair units as opposed to the classic "contact-first" model where DSB are considered immobile. Here we apply this clustering model to evaluate the number of remaining RIF over time. We also show that the newly introduced kinetic metrics can be used as surrogate biomarkers for in vivo radiation toxicity, with potential applications in radiotherapy and human space exploration. In particular, we observed an association between the characteristic time constant of RIF repair measured in vitro and survival levels of immune cells collected from irradiated mice. Moreover, the speed of DNA damage repair correlated not only with radiation-induced cellular survival in vivo, but also with spontaneous cancer incidence data collected from the Mouse Tumor Biology database, suggesting a relationship between the efficiency of DSB repair after irradiation and cancer risk.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗

AmeriFlux US-PFb NW1 Pine-1 CHEESEHEAD 2019

This is the AmeriFlux version of the carbon flux data for the site US-PFb NW1 Pine-1 CHEESEHEAD 2019. Site Description - This tower (32m, trailer-based, telescoping) is the northwestern most tower in the 10 x 10km study domain. It is located in a red pine forest (canopy height ~25m). There is a regrowing/trap layer consisting of broadleaf aspen and other deciduous vegetation.

Desai, Ankur↗

AmeriFlux FLUXNET-1F US-PFb NW1 Pine-1 CHEESEHEAD 2019

This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-PFb NW1 Pine-1 CHEESEHEAD 2019. This is the FLUXNET version of the carbon flux data for the site US-PFb NW1 Pine-1 CHEESEHEAD 2019 produced by applying the standard ONEFlux (1F) software. Site Description - This tower (32m, trailer-based, telescoping) is the northwestern most tower in the 10 x 10km study domain. It is located in a red pine forest (canopy height ~25m). There is a regrowing/trap layer consisting of broadleaf aspen and other deciduous vegetation.

Desai, Ankur↗