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At least 1,063 records · Page 59

Multi-wavelength study of NGC 281 A

We present a study of the molecular cloud NGC 281 A and the associated compact and young star cluster NGC 281 (AS 179). Optical photometry leads to a new distance of 3500 pc for the star cluster which is in good agreement with the kinematical distance of the adjacent molecular cloud NGC 281 A. The exciting star HD 5005 of the optical nebulosity is a Trapezium system with O6 III as photometric spectral type for the component HD 5005 AB. For the age of the star cluster we estimated a value of about 3 x 10(exp 6) yr. The (12)CO (2 to 1), (13)CO (2 to 1), and (12)CO (3 to 2) emission shows that the molecular cloud NGC 281 A consists of two cloud fragments. The western fragment is more compact and massive than the eastern fragment and contains an NH3 core. This core is associated with the IRAS source 00494+5617, an H2O maser, and 1.3 millimeter dust continuum radiation. Both cloud fragments contain altogether 22 IRAS point sources which mostly share the properties of young stellar objects. They have luminosities between 150 and 8800 solar luminosity. The maxima of the 60 and 100 micrometers HIRES maps correspond to the maxima of the (12)CO (3 to 2) emission. The NGC 281 A region shares many properties with the Orion Trapezium-BN/KL region the main differences being a larger separation between the cluster centroid and the new site of star formation as well as a lower mass and luminosity of the molecular cloud and the infrared cluster.

Henning, TH.↗

Assessment of Cloud-based Applications for Enabling a Scalable Riskinformed Predictive Maintenance Strategy

The current light-water reactor fleet uses time-based maintenance strategies to achieve high-capacity factors. But to make nuclear more competitive in the energy market, these reactors could utilize emerging artificial intelligence (AI) and cloud computing technologies to achieve a cost-effective, predictive-maintenance strategy. This paper presents discussion and results on the application of cloud computing in the nuclear industry. The technical viability of cloud computing was analyzed using data from a boiling-water reactor’s safety relief valve. The models were hosted on three different systems: a local personal computer, Idaho National Laboratory’s high-performance computer system, and Microsoft Azure. The data were loaded and processed, and two types of models were trained in an A/B fashion. Based on the speed at which these actions were completed, it was determined that cloud computing affords adequate computing resources. Additionally, the computing power can scale with the demanded load. To enable cloud computing in the existing fleet, additional sensors, networks, and other requirements must be implemented to ensure a smooth transition from current maintenance strategies. However, the benefit is that the plants no longer need to manage their own servers, software, cybersecurity, and information technology support staff for in-house data analytics purpose. Many of these features can be offloaded to the cloud provider for a potential cost savings. Demonstrating how AI can improve the maintenance and operation of non-safety-related systems seems the likely path forward for implementing AI and cloud computing resources inside nuclear power plants.

azure↗

Sensitivity of a Cloud-Resolving Model to the Bulk and Explicit Bin Microphysical Schemes: Validations with a PRE-STORM Case - Part 1

A cloud-resolving model is used to study sensitivities of two different microphysical schemes, one is the bulk type, and the other is an explicit bin scheme, in simulating a mid-latitude squall line case (PRE-STORM, June 10-11, 1985). Simulations using different microphysical schemes are compared with each other and also with the observations. Both the bulk and bin models reproduce the general features during the developing and mature stage of the system. The leading convective zone, the trailing stratiform region, the horizontal wind flow patterns, pressure perturbation associated with the storm dynamics, and the cool pool in front of the system all agree well with the observations. Both the observations and the bulk scheme simulation serve as validations for the newly incorporated bin scheme. However, it is also shown that, the bulk and bin simulations have distinct differences, most notably in the stratiform region. Weak convective cells exist in the stratiform region in the bulk simulation, but not in the bin simulation. These weak convective cells in the stratiform region are remnants of the previous stronger convections at the leading edge of the system. The bin simulation, on the other hand, has a horizontally homogeneous stratiform cloud structure, which agrees better with the observations. Preliminary examinations of the downdraft core strength, the potential temperature perturbation, and the evaporative cooling rate show that the differences between the bulk and bin models are due mainly to the stronger low-level evaporative cooling in convective zone simulated in the bulk model. Further quantitative analysis and sensitivity tests for this case using both the bulk and bin models will be presented in a companion paper.

Li, Xiao-Wen↗

Spectral Retrieval of Latent Heating Profiles from TRMM PR Data: Comparison of Look-Up Tables

The primary goal of the Tropical Rainfall Measuring Mission (TRMM) is to use the information about distributions of precipitation to determine the four dimensional (i.e., temporal and spatial) patterns of latent heating over the whole tropical region. The Spectral Latent Heating (SLH) algorithm has been developed to estimate latent heating profiles for the TRMM Precipitation Radar (PR) with a cloud- resolving model (CRM). The method uses CRM- generated heating profile look-up tables for the three rain types; convective, shallow stratiform, and anvil rain (deep stratiform with a melting level). For convective and shallow stratiform regions, the look-up table refers to the precipitation top height (PTH). For anvil region, on the other hand, the look- up table refers to the precipitation rate at the melting level instead of PTH. For global applications, it is necessary to examine the universality of the look-up table. In this paper, we compare the look-up tables produced from the numerical simulations of cloud ensembles forced with the Tropical Ocean Global Atmosphere (TOGA) Coupled Atmosphere-Ocean Response Experiment (COARE) data and the GARP Atlantic Tropical Experiment (GATE) data. There are some notable differences between the TOGA-COARE table and the GATE table, especially for the convective heating. First, there is larger number of deepest convective profiles in the TOGA-COARE table than in the GATE table, mainly due to the differences in SST. Second, shallow convective heating is stronger in the TOGA COARE table than in the GATE table. This might be attributable to the difference in the strength of the low-level inversions. Third, altitudes of convective heating maxima are larger in the TOGA COARE table than in the GATE table. Levels of convective heating maxima are located just below the melting level, because warm-rain processes are prevalent in tropical oceanic convective systems. Differences in levels of convective heating maxima probably reflect differences in melting layer heights. We are now extending our study to simulations of other field experiments (e.g. SCSMEX and ARM) in order to examine the universality of the look-up table. The impact of look-up tables on the retrieved latent heating profiles will also be assessed.

Shige, Shoichi↗

Cloud Classification in Polar and Desert Regions and Smoke Classification from Biomass Burning Using a Hierarchical Neural Network

This research focuses on a new neural network scene classification technique. The task is to identify scene elements in Advanced Very High Resolution Radiometry (AVHRR) data from three scene types: polar, desert and smoke from biomass burning in South America (smoke). The ultimate goal of this research is to design and implement a computer system which will identify the clouds present on a whole-Earth satellite view as a means of tracking global climate changes. Previous research has reported results for rule-based systems (Tovinkere et at 1992, 1993) for standard back propagation (Watters et at. 1993) and for a hierarchical approach (Corwin et al 1994) for polar data. This research uses a hierarchical neural network with don't care conditions and applies this technique to complex scenes. A hierarchical neural network consists of a switching network and a collection of leaf networks. The idea of the hierarchical neural network is that it is a simpler task to classify a certain pattern from a subset of patterns than it is to classify a pattern from the entire set. Therefore, the first task is to cluster the classes into groups. The switching, or decision network, performs an initial classification by selecting a leaf network. The leaf networks contain a reduced set of similar classes, and it is in the various leaf networks that the actual classification takes place. The grouping of classes in the various leaf networks is determined by applying an iterative clustering algorithm. Several clustering algorithms were investigated, but due to the size of the data sets, the exhaustive search algorithms were eliminated. A heuristic approach using a confusion matrix from a lightly trained neural network provided the basis for the clustering algorithm. Once the clusters have been identified, the hierarchical network can be trained. The approach of using don't care nodes results from the difficulty in generating extremely complex surfaces in order to separate one class from all of the others. This approach finds pairwise separating surfaces and forms the more complex separating surface from combinations of simpler surfaces. This technique both reduces training time and improves accuracy over the previously reported results. Accuracies of 97.47%, 95.70%, and 99.05% were achieved for the polar, desert and smoke data sets.

Alexander, June↗

On the Response of the Special Sensor Microwave/Imager to the Marine Environment: Implications for Atmospheric Parameter Retrievals

A reasonably rigorous basis for understanding and extracting the physical information content of Special Sensor Microwave/Imager (SSM/I) satellite images of the marine environment is provided. To this end, a comprehensive algebraic parameterization is developed for the response of the SSM/I to a set of nine atmospheric and ocean surface parameters. The brightness temperature model includes a closed-form approximation to microwave radiative transfer in a non-scattering atmosphere and fitted models for surface emission and scattering based on geometric optics calculations for the roughened sea surface. The combined model is empirically tuned using suitable sets of SSM/I data and coincident surface observations. The brightness temperature model is then used to examine the sensitivity of the SSM/I to realistic variations in the scene being observed and to evaluate the theoretical maximum precision of global SSM/I retrievals of integrated water vapor, integrated cloud liquid water, and surface wind speed. A general minimum-variance method for optimally retrieving geophysical parameters from multichannel brightness temperature measurements is outlined, and several global statistical constraints of the type required by this method are computed. Finally, a unified set of efficient statistical and semi-physical algorithms is presented for obtaining fields of surface wind speed, integrated water vapor, cloud liquid water, and precipitation from SSM/I brightness temperature data. Features include: a semi-physical method for retrieving integrated cloud liquid water at 15 km resolution and with rms errors as small as approximately 0.02 kg/sq m; a 3-channel statistical algorithm for integrated water vapor which was constructed so as to have improved linear response to water vapor and reduced sensitivity to precipitation; and two complementary indices of precipitation activity (based on 37 GHz attenuation and 85 GHz scattering, respectively), each of which are relatively insensitive to variations in other environmental parameters.

Petty, Grant W.↗

ROSAT observations of the x ray binary HD 154791

We have been surveying the Taurus dark cloud for young stars using a variety of techniques. Two optical proper motion surveys identified 8 new pre-main sequence stars; an IRAS-based program discovered 6 new embedded sources and 4-6 new T Tauri stars. Finally, an optical objective prism survey found 12 new T Tauri stars. Our goal in this project is to examine and compare star formation in the dark clouds: Heiles cloud 2 (HCL2), L1537, L1538, and L1544. HCL2 is a very dense region actively forming young stars and contains 5-6 very young, deeply embedded sources; L1537 and L1538 have no known pre-main sequence stars; L1544 contains 7 optically visible T Tauri stars. These clouds appear roughly similar on optical sky survey plates. We would like to know why some of the clouds are active and why some are not. The first goal of the project is to survey the regions using IR photometry to identify very red pre-main sequence stars and X-ray imaging to identify solar-type young stars missed in the near-IR survey. We will follow up these observations with molecular line surveys to compare the conditions in various clouds with their star formation efficiencies.

Kenyon, Scott J.↗

Assessment of Cloud-Based Applications Enabling a Scalable Risk-Informed Predictive Maintenance Strategy Across the Nuclear Fleet

The current light water reactor fleet uses time-based or failure-based maintenance strategies to achieve high-capacity factors. But to make nuclear more competitive in the energy market, these reactors could utilize emerging technologies in terms of artificial intelligence (AI) and cloud computing to enable a cost-effective, predictive maintenance strategy. This report examines the feasibility of cloud computing for the nuclear industry’s needs in terms of the cloud’s computing capabilities, feasibility, and regulatory concerns. The technical viability of cloud computing was analyzed using one year worth of data from a boiling water reactor’s safety relief valve. Models were hosted on a local desktop, Idaho National Laboratory’s high-performance computer, and Microsoft Azure. Data was loaded, processed, and two types of models were trained in an A/B fashion. Based on the speed at which these actions were completed, it was used to determined that cloud computing has adequate computing resources. Additionally, the computing power can scale with the demanded load. To enable cloud computing in the existing fleet, additional sensors, networks, and other requirements must be implemented to ensure a smooth transition from current maintenance strategies. However, there is a benefit as the plant no longer needs manage their own servers, software, cybersecurity, and IT support staff. Many of these features can be offloaded on to the cloud provider. A comprehensive analysis was completed that showed the current annual cost of operating is more expensive than using cloud computing resources. Lastly, the regulatory framework does not explicitly address AI or autonomous control. Currently, the NRC and other regulatory bodies are evaluating providing guidance to address gaps rather than new regulations to address the use of AI and ML. But since many of the AI applications are focused on non-safety related applications, such as balance-of-plant components, they will likely have little or no regulatory restrictions or necessary approvals. Demonstrating how AI can improve maintenance and operation of these non-safety related systems seems like the likely path forward for implementing AI and cloud computing resources inside nuclear power plants (NPPs).

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Improving Assimilated Global Climate Data Using TRMM and SSM/I Rainfall and Moisture Data

Current global analyses contain significant errors in primary hydrological fields such as precipitation, evaporation, and related cloud and moisture in the tropics. Work has been underway at NASA's Data Assimilation Office to explore the use of TRMM and SSM/I-derived rainfall and total precipitable water (TPW) data in global data assimilation to directly constrain these hydrological parameters. We found that assimilating these data types improves not only the precipitation and moisture estimates but also key climate parameters directly linked to convection such as the outgoing longwave radiation, clouds, and the large-scale circulation in the tropics. We will present results showing that assimilating TRMM and SSM/I 6-hour averaged rain rates and TPW estimates significantly reduces the state-dependent systematic errors in assimilated products. Specifically, rainfall assimilation improves cloud and latent heating distributions, which, in turn, improves the cloudy-sky radiation and the large-scale circulation, while TPW assimilation reduces moisture biases to improve radiation in clear-sky regions. Rainfall and TPW assimilation also improves tropical forecasts beyond 1 day.

Hou, Arthur Y.↗

eROSITA study of the globular cluster 47 Tucanae

Here, we present the results of the analysis of five observations of the globular clutser 47 Tucanae (47 Tuc) with the extended Roentgen Survey with an Imaging Telescope Array (eROSITA) on board the Spektrum-Roentgen-Gamma (Spektr-RG, SRG). We study the X-ray population in the field of one of the most massive globular clusters in our Milky Way. We focused on the classification of point-like sources in the field of 47 Tuc. The unresolved dense core of 47 Tuc (1.7 radius) and also sources that show extended emission are excluded from this study. We applied different methods of X-ray spectral and timing analysis together with multi-wavelength studies to classify the X-rays sources in the field of 47 Tuc. We detected 888 point-like sources in the energy range of 0.2–5.0 keV. We identified 126 background active galactic nuclei and 25 foreground stars. One of the foreground stars is classified as a variable M dwarf. We also classified 14 X-ray sources as members of 47 Tuc, including one symbiotic star, two quiescent low-mass X-ray binaries, and four cataclysmic variables. There are also five X-ray sources that can either be a cataclysmic variable or a contact binary, and also one X-ray source can be an active binary (type RS CVn). We identified one X-ray binary that belongs to the Small Magellanic Cloud. Moreover, we calculated the X-ray luminosity function of 47 Tuc. No significant population that seems to belong to the globular cluster is observed in the energy range of 0.5–2.0 keV using eROSITA observations.

79 ASTRONOMY AND ASTROPHYSICS↗

The Statistics of Extended Debris Disks Measured with Gaia and Planck

Thermal emission from debris disks around stars has been measured using targeted and resolved observations. We present an alternative likelihood-based approach in which temperature maps from the Planck cosmic microwave background (CMB) survey at 857 and 545 GHz are analyzed in conjunction with stellar positions from Gaia to estimate the fraction of stars hosting disks and the thermal emission from the disks. The debris disks are not resolved (or even necessarily detected individually), but their statistical properties and the correlations with stellar properties are measured for several thousand stars. We compare our findings with higher sensitivity surveys of smaller samples of stars. For dimmer stars, in particular K and M dwarfs, we find that about 10% of stars within 80 pc have emission consistent with debris disks. We also report on 80 candidate disks, the majority of which are not previously identified. We have previously constrained the properties of Exo-Oort clouds using Planck data—with future CMB surveys, both components can be measured for different stellar types, providing a new avenue to study the outer parts of planetary systems.

79 ASTRONOMY AND ASTROPHYSICS↗

Project Fog Drops 5. Task 1: A numerical model of advection fog. Task 2: Recommendations for simplified individual zero-gravity cloud physics experiments

A two-dimensional numerical model was used to investigate the formation of marine advection fog. The model predicts the evolution of potential temperature, horizontal wind, water vapor content, and liquid water content in a vertical cross section of the atmosphere as determined by vertical turbulent transfer and horizontal advection, as well as radiative cooling and drop sedimentation. The model is designed to simulate the formation, development, or dissipation of advection fog in response to transfer of heat and moisture between the atmosphere and the surface as driven by advection over horizontal discontinuities in the surface temperature. Results from numerical simulations of advection fog formation are discussed with reference to observations of marine fog. A survey of candidate fog or cloud microphysics experiments which might be performed in the low gravity environment of a shuttle-type spacecraft in presented. Recommendations are given for relatively simple experiments which are relevent to fog modification problems.

Rogers, C. W.↗

Improved position and new optical candidate for A0538-66

An analysis of HEAO 1 modulation collimator data leading to an improved position determination and a new optical counterpart candidate for the transient X-ray source A0538-66 is reported. Data obtained during five outbursts, all of which were separated by 16.7 days or a small multiple thereof, indicates that the outbursts, although of varying duration, intensity, and hardness ratio originated from the same source, at a position of 5 h 35 min 42.7 sec RA and 66 deg 53 arcmin 44 arcsec dec. The improved position determination is found to exclude the previously suggested optical counterpart, and a search of archive plates of the Large Magellanic cloud in the refined error regions has lead to the tentative identification of a B-type star with an observed B variability of 1 mag with the X-ray source.

Johnston, M. D.↗

A study of the Mg II k line in Beta Persei

Spectral scans of the Mg II k line in Beta Per were obtained with Copernicus during two primary eclipses. A brief description of observation in a short frame mode is given. The observed data are compared with computed line profiles based on the eclipse geometry of spherical stars. It is shown that a nonuniform circumstellar envelope, or cloud, probably is present. In one scan, a red-shifted line of P Cygni-type profile appeared, indicating the occurrence of an unusual event in the close binary system.

Chen, K.-Y.↗

Interstellar silicon sulfide

Silicon sulfide has been observed in Sgr B2 at 108.92 GHz and 90.77 GHz and in Orion A at 108.92 GHz. The column density is 1-2 x 10 to the 13th/sq cm in both sources. SiS was not seen in two other molecular clouds where SiO has been detected; nor was it seen in a variety of late-type stars with varying C/O ratios. It appears that SiS is significantly less abundant than SiO in the interstellar medium and probably at least somewhat less abundant in oxygen-rich late-type variable stars.

Dickinson, D. F.↗

OH emission in the direction of TV Gem and BI Cyg

The NRAO-Green Bank 43-m telescope and 18-cm receiver have detected OH maser main-line emission at 1665 MHz, in the direction of the two late-type supergiants TV Gem and BI Cyg. The detection of the two new OH maser sources is noteworthy in view of the small number of late-type supergiants known to be molecular radio sources, or associated in close proximity with OH emission clouds. The IR, UV and radio properties of the two stars are discussed.

Brown, L. W.↗

Kinematics of supernova remnants in the Galaxy and LMC

The optical emission lines of six SNRs have been observed at very high angular and kinematic resolutions. Kinematic ion temperatures were derived, and evidence was found in shocked regions for Maxwellian microturbulence on scales approximately equal to or less than 0.01 pc, and for non-Maxwellian macroturbulence on scales greater than 0.1 pc. The widths of shocked regions in the Cygnus Loop and the existence of three types of spectral feature in the LMC remnants are discussed in terms of SNR evolution in cloudly interstellar media.

Shull, P., Jr.↗

The terminal area simulation system. Volume 1: Theoretical formulation

A three-dimensional numerical cloud model was developed for the general purpose of studying convective phenomena. The model utilizes a time splitting integration procedure in the numerical solution of the compressible nonhydrostatic primitive equations. Turbulence closure is achieved by a conventional first-order diagnostic approximation. Open lateral boundaries are incorporated which minimize wave reflection and which do not induce domain-wide mass trends. Microphysical processes are governed by prognostic equations for potential temperature water vapor, cloud droplets, ice crystals, rain, snow, and hail. Microphysical interactions are computed by numerous Orville-type parameterizations. A diagnostic surface boundary layer is parameterized assuming Monin-Obukhov similarity theory. The governing equation set is approximated on a staggered three-dimensional grid with quadratic-conservative central space differencing. Time differencing is approximated by the second-order Adams-Bashforth method. The vertical grid spacing may be either linear or stretched. The model domain may translate along with a convective cell, even at variable speeds.

Proctor, F. H.↗