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At least 577 records · Page 32

Atmospheric Dynamics of Titan

Titan. after Venus, is the second example of an atmosphere with a global cyclostrophic circulation in the solar system, but one with a strong seasonal modulation in the middle atmosphere. Direct measurement of Titan's winds, particularly observations tracking the Huygens probe at 10degS, indicate that the zonal winds are generally in the sense of the satellite's rotation. They become cyclostrophic approx.35 km above the surface and generally increase with altitude, with the exception of a sharp minimum centered near 75 km, where the wind velocity decreases to nearly zero. Zonal winds derived from the temperature field retrieved from Cassini measurements using the thermal wind equation, indicate a strong winter circumpolar vortex, with maximum winds of 190 m/s near 300 km at mid-northern latitudes. One of the most intriguing findings is that the pole of stratospheric temperatures and winds appears to be offset from the IAU definition of Titan's pole by approx. 4deg. The mean meridional circulation can be inferred from the temperature field, and the meridional distribution of organic molecules and condensates and hazes.

Flasar, F. Michael↗

Chapter 13. Atmospheric Dynamics and Meteorology

Titan, after Venus, is the second example in the solar system of an atmosphere with a global cyclostrophic circulation, but in this case a circulation that has a strong seasonal modulation in the middle atmosphere. Direct measurement of Titan's winds, particularly observations tracking the Huygens probe at 10 deg S, indicate that the zonal winds are mostly in the sense of the satellite's rotation. They generally increase with altitude and become cyclostrophic near 35 km above the surface. An exception to this is a sharp minimum centered near 75 km, where the wind velocity decreases to nearly zero. Zonal winds derived from temperatures retrieved from Cassini orbiter measurements, using the thermal wind equation, indicate a strong winter circumpolar vortex, with maximum winds of 190 m/s at mid northern latitudes near 300 km. Above this level, the vortex decays. Curiously, the stratospheric zonal winds and temperatures in both hemispheres are symmetric about a pole that is offset from the surface pole by about 4 deg. The cause of this is not well understood, but it may reflect the response of a cyclostrophic circulation to the onset between the equator, where the distance to the rotation axis is greatest, and the seasonally varying subsolar latitude. The mean meridional circulation can be inferred from the temperature field and the meridional distribution of organic molecules and condensates and hazes. Both the warm temperatures near 400 km and the enhanced concentration of several organic molecules suggest subsidence in the north polar region during winter and early spring. Stratospheric condensates are localized at high northern latitudes, with a sharp cut-off near 50 deg N. Titan's winter polar vortex appears to share many of the same characteristics of isolating high and low-latitude air masses as do the winter polar vortices on Earth that envelop the ozone holes. Global mapping of temperatures, winds, and composition in the troposphere, by contrast, is incomplete. The few suitable discrete clouds that have been found for tracking indicate smaller velocities than aloft, consistent: with the Huygens measurements, Along the descent trajectory, the Huygens measurements indicate eastward zonal winds down to 7 km, where they shift westward, and then eastward again below 1 km dawn to the surface. The low-latitude dune fields seen in Cassini RADAR images have been interpreted as longitudinal dunes occurring in a mean eastward zonal wind. This is not like Earth, where the low-latitude winds are westward above the surface. Because the net zonal-mean time-averaged torque exerted by the surface on the atmosphere should vanish, there must be westward flow over part of the surface; the question is where and when. The meridional contrast in tropospheric temperatures deduced from radio occultations at low, mid, and high latitudes. is small, approximately 5 K at the tropopause and approximately 3 K at the surface. This implies efficient heat transport, probably by axisymmetric meridional circulations. The effect of the methane "hydrological" cycle on the atmospheric circulation is not well constrained by existing measurements, Understanding the mature of the surface-atmosphere coupling will be critical to elucidating the atmospheric transports of momentum, heat, and volatiles.

Flasar, F. M.↗

A Historical Perspective on Primary and Possible Secondary Sources of Atmospheric Carbon Tetrachloride

Atmospheric sources of Carbon Tetrachloride (CTC) have been controversial since its detection in the early 1970. Initial proposals were that it is globally uniformly distributed and its lack of current emissions and inferred lifetime indicated that it was likely of natural origin. Historical analysis of CTC use and emissions showed that atmospheric CTC was long-lived and mainly of man-made origin although small natural sources and sinks (e. g. oceans) could not be ruled out. This deduction was hard because a majority of emissions had occurred in early part of the 20th century when CTC was commonly used as a fumigant, a solvent, and a raw material for the manufacture of many chemicals. In the 1940's adverse health effects of exposure to CTC became evident and its emissions were greatly curtailed and substituted with C2Cl4 which was thought to be much safer. There were smog chamber studies that showed that C2Cl4, a widely used solvent during the late 20th century, could produce CTC with up to a 7% yield. Subsequently it was discovered that this chemistry probably required Cl atoms and since Cl atoms were not abundant in the atmosphere actual yields based on OH oxidation were probably closer to 0.1%. CTC was subsequently banned by the Montreal Protocol to prevent stratospheric ozone depletion and its preferred substitute C2Cl4 was also banned by EPA for reasons of potential carcinogenicity and toxicity. CTC since has been measured in many airborne NASA campaigns in which plumes have been sampled from a variety of regions which may still be emitting CTC. I will briefly discuss this historical perspective of CTC and show some recent data that may shed light on its current sources or lack there off.

atmosphere↗

On the Distance to the North Polar Spur and the Local CO-H2 Factor

Aims. Most models identify the X-ray bright North Polar Spur (NPS) with a hot interstellar (IS) bubble in the Sco-Cen star-forming region at approx. = to 130 pc. An opposite view considers the NPS as a distant structure associated with Galactic nuclear outflows. Constraints on the NPS distance can be obtained by comparing the foreground IS gas column inferred from X-ray absorption to the distribution of gas and dust along the line of sight. Absorbing columns towards shadowing molecular clouds simultaneously constrain the CO-H2 conversion factor. Methods. We derived the columns of X-ray absorbing matter N(sub Habs) from spectral fitting of dedicated XMM-Newton observations towards the NPS southern terminus (l(sup II) approx. = to 29 degrees, b(sup II) approx. = to +5 to +11 degrees). The distribution of the IS matter was obtained from absorption lines in stellar spectra, 3D dust maps and emission data, including high spatial resolution CO measurements recorded for this purpose. Results. N(sub Habs) varies from approx. = to 4.3 to approx. = to 1.3 x 10(exp 21) per sq cm along the 19 fields. Relationships between X-ray brightness, absorbing column and hardness ratio demonstrate a brightness decrease with latitude governed by increasing absorption. The comparison with absorption data, local and large-scale dust maps rules out a NPS near side closer than 300 pc. The correlation between N(sub Habs) and the reddening increases with the sightline length from 300 pc to 4 kpc and is the tightest with Planck tau(sub 353GHz) -based reddening, suggesting a much larger distance. N(H)/E(B-V)(sub tao) approx. = to 4.1 x 10(exp 21) per sq cm mag, close to Fermi-Planck determinations. N(sub Habs) absolute values are compatible with HI-CO clouds at -5 less than or equal to V(sub LSR) less than or equal to +25 to +45 km/s and a NPS potentially far beyond the Local Arm. A shadow cast by a b=+9 degree molecular cloud constrains X(sub CO) in that direction to less than or equal to 1.0 x 10(exp 20) sec/((sq cm)K km). The average X(sub CO) over the fields is less than or equal to 0.75 x 10(exp 20) sec/((sq cm)K km).

X-rays: ISM / radio lines: ISM / local insterstell↗

Mercury's Internal Structure

We describe the current state of knowledge about Mercury's interior structure. We review the available observationalconstraints, including mass, size, density, gravity eld, spin state, composition, and tidal response. These data enablethe construction of models that represent the distribution of mass inside Mercury. In particular, we infer radial prolesof the pressure, density, and gravity in the core, mantle, and crust. We also examine Mercury's rotational dynamicsand the inuence of an inner core on the spin state and the determination of the moment of inertia. Finally, we discussthe wide-ranging implications of Mercury's internal structure on its thermal evolution, surface geology, capture in aunique spin-orbit resonance, and magnetic eld generation.

Mercury↗

Benchmarking of Different Inverse Point Kinetics Implementations for an Autocorrected Reactimeter Algorithm

In November 2017, the Transient Reactor Test Facility returned to operation. Since that time, many transient test series have been completed; each has provided valuable data for materials performance, reactor safety that can be applied in future designs. During each experimental series, detector count rates provided important information on the core behavior during transients. However, a limitation of these data is that variations in the neutron distribution during experiments cause errors when attempting to infer reactivity evolution from detector signals. Neutron physics codes can be used to compute the flux shape variations. However, this is a poor solution when the experimental data is used to do verification, validation and uncertainty quantification (VVUQ) on codes. Indeed, if the output of the code is used both as a reference and to correct what the reference is compared to, the circular dependency limits the quality of the VVUQ approach. To overcome this problem, an Autocorrected Reactimeter Algorithm (ACRA) has been developed. This approach infers time-dependent reactivity evolution by testing different spatial corrections and selecting the one that minimizes reactivity variations when the core is in a frozen configuration (i.e. when there is no variation in parameters affecting reactivity). However, the scope of this method was limited to transients where there were negligible thermal feedback. Indeed, the core is never in a frozen configuration when the fuel temperature varies during the whole transient. This is our motivation for the development of an improved version of the ACRA which does not require frozen configurations

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Mapping of CO2 at High Spatiotemporal Resolution using Satellite Observations: Global distributions from OCO-2

Satellite observations of CO2 offer new opportunities to improve our understanding of the global carbon cycle. Using such observations to infer global maps of atmospheric CO2 and their associated uncertainties can provide key information about the distribution and dynamic behavior of CO2, through comparison to atmospheric CO2 distributions predicted from biospheric, oceanic, or fossil fuel flux emissions estimates coupled with atmospheric transport models. Ideally, these maps should be at temporal resolutions that are short enough to represent and capture the synoptic dynamics of atmospheric CO2. This study presents a geostatistical method that accomplishes this goal. The method can extract information about the spatial covariance structure of the CO2 field from the available CO2 retrievals, yields full coverage (Level 3) maps at high spatial resolutions, and provides estimates of the uncertainties associated with these maps. The method does not require information about CO2 fluxes or atmospheric transport, such that the Level 3 maps are informed entirely by available retrievals. The approach is assessed by investigating its performance using synthetic OCO-2 data generated from the PCTM/ GEOS-4/CASA-GFED model, for time periods ranging from 1 to 16 days and a target spatial resolution of 1deg latitude x 1.25deg longitude. Results show that global CO2 fields from OCO-2 observations can be predicted well at surprisingly high temporal resolutions. Even one-day Level 3 maps reproduce the large-scale features of the atmospheric CO2 distribution, and yield realistic uncertainty bounds. Temporal resolutions of two to four days result in the best performance for a wide range of investigated scenarios, providing maps at an order of magnitude higher temporal resolution relative to the monthly or seasonal Level 3 maps typically reported in the literature.

Hammerling, Dorit M.↗

A Deep Generative Model for Non-Intrusive Identification of EV Charging Profiles

The proliferation of electric vehicles (EVs) brings environmental benefits and technical challenges to power grids. An identification algorithm which can accurately extract individual EV charging profiles out of widely available smart meter measurements has attracted great interests. This paper proposes a non-intrusive identification framework for EV charging profile extraction, which is driven by deep generative models (DGM). First, the proposed DGM is designed as a representation layer embedded into the Markov process and used to model the joint probability distribution of available time-series data. A novel contribution is to approximate posterior distributions by neural networks whose parameters are obtained by variational inference and supervised learning. Second, the EV charging status is inferred from the DGM via dynamic programming. Lastly, the desired EV charging profile can be reconstructed by the rated power of EV models and inferred status. Compared with the benchmark Hidden Markov Models, the proposed framework can better handle noise in data with less computational complexity and better overall accuracy performances with smaller recall. The proposed framework is validated by numerical experiments on the Pecan Street dataset.

33 ADVANCED PROPULSION SYSTEMS↗

Redshift data and statistical inference

Frequency histograms and the 'power spectrum analysis' (PSA) method, the latter developed by Yu & Peebles (1969), have been widely employed as techniques for establishing the existence of periodicities. We provide a formal analysis of these two classes of methods, including controlled numerical experiments, to better understand their proper use and application. In particular, we note that typical published applications of frequency histograms commonly employ far greater numbers of class intervals or bins than is advisable by statistical theory sometimes giving rise to the appearance of spurious patterns. The PSA method generates a sequence of random numbers from observational data which, it is claimed, is exponentially distributed with unit mean and variance, essentially independent of the distribution of the original data. We show that the derived random processes is nonstationary and produces a small but systematic bias in the usual estimate of the mean and variance. Although the derived variable may be reasonably described by an exponential distribution, the tail of the distribution is far removed from that of an exponential, thereby rendering statistical inference and confidence testing based on the tail of the distribution completely unreliable. Finally, we examine a number of astronomical examples wherein these methods have been used giving rise to widespread acceptance of statistically unconfirmed conclusions.

Newman, William I.↗

The Effect of the Velocity Distribution on Kilonova Emission

The electromagnetic emission from the nonrelativistic ejecta launched in neutron star mergers (either dynamically or through a disk wind) has the potential to probe both the total mass and composition of this ejecta. These observations are crucial in understanding the role of these mergers in the production of r-process elements in the Universe. However, many properties of the ejecta can alter the light curves and we must both identify which properties play a role in shaping this emission and understand the effects these properties have on the emission before we can use observations to place strong constraints on the amount of r-process elements produced in the merger. This paper focuses on understanding the effect of the velocity distribution (amount of mass moving at different velocities) for lanthanide-rich ejecta on the light curves and spectra. The simulations use distributions guided by recent calculations of disk outflows and compare the velocity-distribution effects to those of ejecta mass, velocity, and composition. Our comparisons show that uncertainties in the velocity distribution can lead to a factor of 2–4 uncertainties in the inferred ejecta mass based on peak infrared luminosities. We also show that early-time UV or optical observations may be able to constrain the velocity distribution, reducing the uncertainty in the ejecta mass.

79 ASTRONOMY AND ASTROPHYSICS↗

The Effect of the Velocity Distribution on Kilonova Emission

Abstract The electromagnetic emission from the nonrelativistic ejecta launched in neutron star mergers (either dynamically or through a disk wind) has the potential to probe both the total mass and composition of this ejecta. These observations are crucial in understanding the role of these mergers in the production of r -process elements in the Universe. However, many properties of the ejecta can alter the light curves and we must both identify which properties play a role in shaping this emission and understand the effects these properties have on the emission before we can use observations to place strong constraints on the amount of r -process elements produced in the merger. This paper focuses on understanding the effect of the velocity distribution (amount of mass moving at different velocities) for lanthanide-rich ejecta on the light curves and spectra. The simulations use distributions guided by recent calculations of disk outflows and compare the velocity-distribution effects to those of ejecta mass, velocity, and composition. Our comparisons show that uncertainties in the velocity distribution can lead to a factor of 2–4 uncertainties in the inferred ejecta mass based on peak infrared luminosities. We also show that early-time UV or optical observations may be able to constrain the velocity distribution, reducing the uncertainty in the ejecta mass.

79 ASTRONOMY AND ASTROPHYSICS↗

Risk Assessment in a Chemical Laboratory Following an Explosive Incident Involving a Novel Diazonium Compound: Retrospective Analysis and Lessons Learned

Diazonium compounds are synthetically useful in the production of dyes and textiles, however they are highly explosive under dry conditions. Explosion prevention becomes more difficult when new diazonium compounds are synthesized, because while some syntheses include a counterion to increase their stability, this is not always a reliable method to prevent an explosive incident. Due to the uncertainty surrounding the explosiveness of different diazonium compounds, it is important to understand how to safely clean up after an incident and how to determine when it is safe to return a laboratory to typical operational use, particularly when the incident involves a novel compound where a standard does not exist for instrument calibration. Here, an explosive event is discussed involving the synthesis of 4-bromo-benzenediazonium-2-carboxylate. Following the explosive incident and 3-step cleanup, which involved a precautionary neutralization step, samples were collected from the fume hood where the incident occurred. Because the incident involved an unstable, novel compound that is not commercially available and was deemed unsafe to resynthesize for instrument calibration, we assessed the risk of further explosion by analyzing for the stable decomposition products. Mass spectrometry analysis confirmed that the residue in the fume hood contained 5-bromosalicylic acid, a decomposition product of 4-bromo-benzenediazonium-2-carboxylate. Samples were taken from multiple points in the fume hood and analyzed to estimate the spatial distribution of the decomposition product. Based on this analysis, we inferred that the primary decomposition product was far more abundant than residual energetic, indicating the energetic had been consumed or neutralized to a trace quantity where the risk of further explosion was low. Furthermore, the steps presented here─specifically, initial neutralization and then analyzing the spatial distribution of expected decomposition products to assess risk when a novel explosive material is detonated in a confined space─were our approach to assess further risk following an explosion due to a novel diazonium compound without the need for any further handling or resynthesis of the energetic. Here, we present our approach and critically analyze these steps by discussing retrospective lessons learned and alternative analytical approaches.

Computer simulations↗

Consequences of Asteroid Characterization on the State of Knowledge about Inferred Physical Properties and Impact Risk

Physical characteristics of Near-Earth Objects (NEOs) are essential inputs to planetary defense assessments. The size, density, and strength of an NEO are critical inputs to modeling behavior during atmospheric entry as well as assessing the risk of impact. Similarly, knowledge of the physical characteristics of an object are necessary to evaluate the probable result of a mitigation mission. Usually, these attributes cannot be directly measured, but increasingly sophisticated methods have been developed to infer physical properties from related measurements of asteroids, meteors, and/or meteorites. Fortuitously, some of these measurements have been obtained for enough NEOs to elucidate the distribution of values across the sampled population. However, the situation becomes more challenging when considering a specific asteroid, since it is unlikely that all the relevant measurements have been made for any given object. We have developed a Bayesian network that can combine available information about a particular NEO with knowledge of the larger population to infer probabilistic values and uncertainties for physical characteristics of interest. Distributions of asteroid population albedos, taxonomic classes, and macroporosities, along with meteorite density distributions and associations between taxonomic classes and meteorite classes, provide the default distributions for the network’s parameter nodes. The inference network links parameters for each virtual asteroid either deterministically or probabilistically as appropriate, and eliminates any unphysical combinations of parameters. Within the context of planetary defense, our Bayesian network can be used to constrain the ranges of likely impactor properties, which can subsequently reduce the uncertainty in modelling of atmospheric entry, mitigation efficacy, and impact risk assessment. When additional measurements become available for a specific object, the network incorporates those measurements to generate virtual asteroids with property distributions that are consistent with the measurements. We will use the 2023 PDC scenario to demonstrate how the inference network can be combined with plausible characterization measurements to refine the state of knowledge about likely combinations of physical parameters and the resulting impact risk.

risk assessment↗

Consequences of Asteroid Characterization on the State of Knowledge about Inferred Physical Properties and Impact Risk

Physical characteristics of Near-Earth Objects (NEOs) are essential inputs to planetary defense assessments. The size, density, and strength of an NEO are critical inputs to modeling behavior during atmospheric entry as well as assessing the risk of impact. Similarly, knowledge of the physical characteristics of an object are necessary to evaluate the probable result of a mitigation mission. Usually, these attributes cannot be directly measured, but increasingly sophisticated methods have been developed to infer physical properties from related measurements of asteroids, meteors, and/or meteorites. Fortuitously, some of these measurements have been obtained for enough NEOs to elucidate the distribution of values across the sampled population. However, the situation becomes more challenging when considering a specific asteroid, since it is unlikely that all the relevant measurements have been made for any given object. We have developed a Bayesian network that can combine available information about a particular NEO with knowledge of the larger population to infer probabilistic values and uncertainties for physical characteristics of interest. Distributions of asteroid population albedos, taxonomic classes, and macroporosities, along with meteorite density distributions and associations between taxonomic classes and meteorite classes, provide the default distributions for the network’s parameter nodes. The inference network links parameters for each virtual asteroid either deterministically or probabilistically as appropriate, and eliminates any unphysical combinations of parameters. Within the context of planetary defense, our Bayesian network can be used to constrain the ranges of likely impactor properties, which can subsequently reduce the uncertainty in modelling of atmospheric entry, mitigation efficacy, and impact risk assessment. When additional measurements become available for a specific object, the network incorporates those measurements to generate virtual asteroids with property distributions that are consistent with the measurements. We will use the 2023 PDC scenario to demonstrate how the inference network can be combined with plausible characterization measurements to refine the state of knowledge about likely combinations of physical parameters and the resulting impact risk.

risk assessment↗

γIn-beam angular distribution and linear polarization measurements with GRETINA using a simple energy-ordering approach

Angular distribution and linear polarization measurements are powerful tools for inferring the spins and parities of nuclear levels. In this work, the performance of the Gamma-Ray Energy Tracking In-beam Nuclear Array (GRETINA) as a Compton polarimeter was characterized in a fusion-evaporation reaction experiment using a simple energy-ordering approach for the interaction points assigned in the signal decomposition process. A variety of multipolarities and characters for γ-ray transitions in the reaction products 25 Mg, 25 Na, and 22 Ne, formed from fusion-evaporation of an 18 O beam on a 9 Be target, were examined. The experimental angular distributions and linear polarization asymmetries were consistent with predictions using the theoretical formalism accounting for the Lorentz boost.

Angular distribution↗

Visualization of newt aragonitic otoconial matrices using transmission electron microscopy

Otoconia are calcified protein matrices within the gravity-sensing organs of the vertebrate vestibular system. These protein matrices are thought to originate from the supporting or hair cells in the macula during development. Previous studies of mammalian calcitic, barrel-shaped otoconia revealed an organized protein matrix consisting of a thin peripheral layer, a well-defined organic core and a flocculent matrix inbetween. No studies have reported the microscopic organization of the aragonitic otoconial matrix, despite its protein characterization. Pote et al. (1993b) used densitometric methods and inferred that prismatic (aragonitic) otoconia have a peripheral protein distribution, compared to that described for the barrel-shaped, calcitic otoconia of birds, mammals, and the amphibian utricle. By using tannic acid as a negative stain, we observed three kinds of organic matrices in preparations of fixed, decalcified saccular otoconia from the adult newt: (1) fusiform shapes with a homogenous electron-dense matrix; (2) singular and multiple strands of matrix; and (3) more significantly, prismatic shapes outlined by a peripheral organic matrix. These prismatic shapes remain following removal of the gelatinous matrix, revealing an internal array of organic matter. We conclude that prismatic otoconia have a largely peripheral otoconial matrix, as inferred by densitometry.

NASA Discipline Neuroscience↗

Measuring the giant radio galaxy length distribution with the LoTSS

Many massive galaxies launch jets from the accretion disk of their central black hole, but only ~10 3 instances are known in which the associated outflows form giant radio galaxies (GRGs, or giants): luminous structures of megaparsec extent that consist of atomic nuclei, relativistic electrons, and magnetic fields. Large samples are imperative to understanding the enigmatic growth of giants, and recent systematic searches in homogeneous surveys constitute a promising development. For the first time, it is possible to perform meaningful precision statistics with GRG lengths, but a framework to do so is missing. We measured the intrinsic GRG length distribution by combining a novel statistical framework with a LOFAR Two-metre Sky Survey (LoTSS) sample of freshly discovered giants. In turn, this allowed us to answer an array of questions on giants. For example, we can now assess how rare a 5 Mpc giant is compared with one of 1 Mpc, and how much larger – given a projected length – the corresponding intrinsic length is expected to be. Notably, we can now also infer the GRG number density in the Local Universe. We assumed the intrinsic GRG length distribution to be Paretian (i.e. of power-law form) with tail index ξ, and predicted the observed distribution by modelling projection and selection effects. To infer ξ, we also systematically searched the LoTSS for hitherto unknown giants and compiled the largest catalogue of giants to date. We show that if intrinsic GRG lengths are Pareto distributed with index ξ, then projected GRG lengths are also Pareto distributed with index ξ. Selection effects induce curvature in the observed projected GRG length distribution: angular length selection flattens it towards the lower end, while surface brightness selection steepens it towards the higher end. We explicitly derived a GRG’s posterior over intrinsic lengths given its projected length, laying bare the ξ dependence. We also discovered 2060 giants within LoTSS DR2 pipeline products; our sample more than doubles the known population. Spectacular discoveries include the largest, second-largest, and fourth-largest GRG known (l p = 5.1 Mpc, l p = 5.0 Mpc, and l p = 4.8 Mpc), the largest GRG known hosted by a spiral galaxy (l p = 2.5 Mpc), and the largest secure GRG known beyond redshift 1 (l p = 3.9 Mpc). We increase the number of known giants whose angular length exceeds that of the Moon from 10 to 23; among the discoveries is the angularly largest known radio galaxy in the Northern Sky, which is also the angularly largest known GRG ($\phi$ = 2°). Combining theory and data, we determined that intrinsic GRG lengths are well described by a Pareto distribution, and measured the index ξ = –3.5 ± 0.5. This implies that, given its projected length, a GRG’s intrinsic length is expected to be just 15% larger. Finally, we determined the comoving number density of giants in the Local Universe to be n GRG = 5 ± 2(100 Mpc) –3 . We developed a practical mathematical framework that elucidates the statistics of giant radio galaxy lengths. Through a LoTSS search, we also discovered 2060 new giants. By combining both advances, we determined that intrinsic GRG lengths are well described by a Pareto distribution with index ξ = –3.5 ± 0.5, and that giants are truly rare in a cosmological sense: most clusters and filaments of the Cosmic Web are not currently home to a giant. Thus, our work yields new observational constraints for analytical models and simulations featuring radio galaxy growth.

79 ASTRONOMY AND ASTROPHYSICS↗

Probabilistic Physics-Informed Graph Convolutional Network for Active Distribution System Voltage Prediction

Here this letter proposes a novel data-driven probabilistic physics-informed graph convolutional network (GCN) for active distribution system voltage prediction with PVs and EVs. It leverages both measurements and network topology to accurately and efficiently predict node voltages without the need for an accurate distribution system power flow model. The dropout-enabled Bayesian inference is developed to achieve uncertainty quantification of the voltage prediction. Thanks to the network model embedding, it also has robustness against topology changes, a key difference with existing machine learning-based approaches. Comparison results with other state-of-the-art machine learning methods on a realistic 759-node distribution system demonstrate that the proposed method can achieve better accuracy and robustness under different scenarios.

24 POWER TRANSMISSION AND DISTRIBUTION↗