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At least 1,063 records · Page 59

Development of Analysis Methods that Integrate Numeric and Textual Equipment Reliability Data

Within the Light Water Reactor Sustainability (LWRS) program, the Risk-Informed Systems Analysis (RISA) Pathway is performing collaborative research on the development and deployment of technologies designed to assist operating nuclear power plants (NPPs) to reduce operating costs improve plant reliability and availability. One of the RISA research areas is focusing on the development of methods and tools designed to optimize plant operations (e.g., maintenance/replacement schedules, optimal maintenance postures for plant structures, systems, and components [SSCs]) in a manner that is more cost effective than current approaches and makes better use of available SSC health data. The Risk-Informed Asset Management (RIAM) project targets this research area by creating a direct bridge between component equipment reliability (ER) data and system engineer decision making regarding maintenance activity scheduling and component aging management. In this respect, one challenge that NPP system engineers are facing is that the amount of ER data being continuously generated is not only extremely large in size, but it comes in different forms: textual (e.g., condition or maintenance reports) and numeric (e.g., generated by monitoring systems). All these data elements provide them with valuable insights and information regarding: 1) the discovery of anomalous behaviors or degradation trends, 2) the identification of the possible causes behind such behaviors/trends, and 3) the prediction of their direct consequences. However, several challenges have proved to be roadblocks to this process. While some of these challenges are technical in nature (i.e., data are often distributed over several physical servers/databases), others are conceptual in nature: data elements come in different formats (e.g., numeric or textual), and measured values have different scales (e.g., vibration spectra and oil temperature). The activities performed by the RIAM project during FY23 directly tackles the need to simultaneously integrate the analysis of ER data in all its forms, numeric and textual. Note that such task has never been performed before due to the complexity of the systems under consideration but, most importantly, because of the technical challenges behind the harmonization of ER data formats and the lack of adequate computational methods to analyze them. Our approach borrows ideas and concepts from the medical field where integration of several data sources is vital to assist medical practitioners to perform correct diagnosis and indicate optimal treatments. In our view a NPP asset is equivalent to a patient in a medical context. The main difference is the complexity of a human body is a magnitude more complex when compared to typical assets commonly present in NPPs (e.g., centrifugal pumps, or motor operated valves). This simplifies our first requirement when analyzing heterogenous ER data formats: to put data into “context”. Context is here intended as the additional piece of information that is needed by ER data analysis tools to understand what these data elements are referring to, i.e., which king of knowledge they are generating. In our context, this knowledge can be translated into models that capture the form and functional architecture of assets/systems, their dependencies, and how they interact. These models actually emulate the knowledge that that NPP system engineers possess about assets and systems; this is their key of success when analyzing ER data, their challenge is ability to handle large amount of data. Here, we employ model-based system engineering (MBSE) models of systems and assets to represent and capture their architecture and functional, i.e. cause-effect, relations. Then, ER data elements are processed by identifying first of all which elements of the developed MBSE elements they are referring to. For numeric ER data this task is fairly easy since it is possible to precisely pinpoint what MBSE elements the corresponding sensor are observing (e.g., bearing temperature of a centrifugal pump). Task is much harder for textual data since the information contained in issue or maintenance reports needs to “be understood” by a computational tool. Here we called this process as “knowledge extraction”. Once again, we borrow the experience in the medical field where methods to extract knowledge from textual data have been developed in the past decade. The missing element for us is the availability of a complete dictionary of NPP related concepts (in addition to the MBSE models presented earlier) that can put “text into context”. In FY23, such dictionary has been developed along with all the computational elements required for knowledge extraction. Lastly, once numeric and textual ER data elements have been processed and “understood”, then the last step is the discovery of possible cause-effect relations among them. This is performed by observing if a logical connection through the MBSE models exists, and if the

97 MATHEMATICS AND COMPUTING↗

CALIBRATING THE STAR FORMATION RATE AT z {approx} 1 FROM OPTICAL DATA

We present a star formation rate (SFR) calibration based on optical data that is consistent with average observed rates in both the red and blue galaxy populations at z {approx} 1. The motivation for this study is to calculate SFRs for DEEP2 Redshift Survey galaxies in the 0.7 < z < 1.4 redshift range, but our results are generally applicable to similar optically selected galaxy samples without requiring UV or IR data. Using SFR fits from UV/optical spectral energy distributions (SEDs) in the All-Wavelength Extended Groth Strip International Survey, we explore the behavior of rest-frame B-band magnitude, observed [O II] luminosity, and rest-frame color with SED-fit SFR for both red sequence and blue cloud galaxies. The resulting SFR calibration is based on three optical-band observables: M{sub B} , (U - B), and (B - V). The best-fit linear relation produces residual errors of 0.3 dex rms scatter for the full color-independent sample with minimal correlated residual error in L[O II] or stellar mass. We then compare the calibrated z {approx} 1 SFRs to two diagnostics that use L[O II] as a tracer in local galaxies and correct for dust extinction at intermediate redshifts through either galaxy B-band luminosity or stellar mass. We find that an L[O II]-M{sub B} SFR calibration commonly used in the literature agrees well with our calculated SFRs after correcting for the average B-band luminosity evolution in L{sub *} galaxies. However, we find better agreement with a local L[O II]-based SFR calibration that includes stellar mass to correct for reddening effects, indicating that stellar mass is a better tracer of dust extinction for all galaxy types and less affected by systematic evolution than galaxy luminosity from z = 1 to the current epoch.

79 ASTRONOMY AND ASTROPHYSICS↗

Extension of the sasCIF format and its applications for data processing and deposition

Recent advances in small-angle scattering (SAS) experimental facilities and data analysis methods have prompted a dramatic increase in the number of users and of projects conducted, causing an upsurge in the number of objects studied, experimental data available and structural models generated. To organize the data and models and make them accessible to the community, the Task Forces on SAS and hybrid methods for the International Union of Crystallography and the Worldwide Protein Data Bank envisage developing a federated approach to SAS data and model archiving. Within the framework of this approach, the existing databases may exchange information and provide independent but synchronized entries to users. At present, ways of exchanging information between the various SAS databases are not established, leading to possible duplication and incompatibility of entries, and limiting the opportunities for data-driven research for SAS users. In this work, a solution is developed to resolve these issues and provide a universal exchange format for the community, based on the use of the widely adopted crystallographic information framework (CIF). The previous version of the sasCIF format, implemented as an extension of the core CIF dictionary, has been available since 2000 to facilitate SAS data exchange between laboratories. The sasCIF format has now been extended to describe comprehensively the necessary experimental information, results and models, including relevant metadata for SAS data analysis and for deposition into a database. Processing tools for these files ( sasCIFtools ) have been developed, and these are available both as standalone open-source programs and integrated into the SAS Biological Data Bank, allowing the export and import of data entries as sasCIF files. Software modules to save the relevant information directly from beamline data-processing pipelines in sasCIF format are also developed. Lastly, this update of sasCIF and the relevant tools are an important step in the standardization of the way SAS data are presented and exchanged, to make the results easily accessible to users and to promote further the application of SAS in the structural biology community.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

Progress In The Scene-To-Map Registration Investigation

The geometric accuracy of the scene-to-map registration process for P-format LANDSAT MSS data for scenes from Kansas and Louisiana/Mississippi is discussed. Large scale row and column bias values and row and column standard deviation values were measured for the P-format data sets indicating a poor georegistration accuracy for these geometrically corrected LANDSAT MSS scenes. Experimental work is underway with A-format LANDSAT MSS scenes from the same locations to examine the influence of the number of ground control points and the spatial distribution of ground control points on geometric registration accuracy. An early conclusion from this work is that the root mean square approach for assessing how well the ground control points fit the mapping equations measures a different aspect of georegistration accuracy than does the approach of evaluating the bias (offset) and standard deviation using independently chosen ground reference points.

Dow, D. D.↗

Full-duplex optical communication system

A method of full-duplex electromagnetic communication wherein a pair of data modulation formats are selected for the forward and return data links respectively such that the forward data electro-magnetic beam serves as a carrier for the return data. A method of encoding optical information is used wherein right-hand and left-hand circular polarizations are assigned to optical information to represent binary states. An application for an earth to low earth orbit optical communications system is presented which implements the full-duplex communication and circular polarization keying modulation format.

Shay, Thomas M.↗

Reactivity of Redox Cycled Fe-bearing Subsurface Sediments Towards Hexavalent Chromium Reduction

Structural Fe(II) in clay minerals and natural sediments is known to reduce Cr(VI) to Cr(III), but the effect of redox-cycled Febearing natural sediments on Cr(VI) reduction kinetics is poorly understood. The objective of this study was to understand the kinetics and mechanisms of Cr(VI) reduction by Fe(II) in redox cycled natural sediment. Fe-bearing sediment was collected from the Ringold formation in the 300 area of Hanford, Washington, United States. Fe redox cycling of the sediment was accomplished via four cycles of bioreduction of structural Fe(III) in Hanford sediment and air oxidation of the resulting Fe(II). Bio-produced Fe(II) in Hanford sediment from each redox cycle was utilized to reduce Cr(VI) at three temperatures (10, 20 and 30° C). The initial rate of Cr(VI) reduction generally increased with each redox cycle, which was more pronounced at high temperatures. The amount of Fe(II) oxidized to the amount of Cr(VI) reduced was close to the expected stoichiometric ratio of 3. Aqueous concentrations of Si, Al, and Fe revealed some dissolution of the sediment after reaction with Cr(VI). Xray diffraction (XRD) and scanning electron microscopy (SEM) detected secondary mineral formation. Mössbauer data showed that the oxidation of Fe(II) was coupled with the reduction of Cr(VI) but no Feoxides/ oxyhydroxides formed. Transmission electron microscopy (TEM), electron energy loss spectroscopy (EELS), XANES, and EXAFS were performed for representative reduced Cr solids that formed from reduction of Cr(VI) by sediment-associated Fe(II) at 30oC. TEM revealed that the d-spacing of Cr-reacted montmorillonite at 30° C, a dominant Fe-bearing mineral in Hanford sediment, expanded from 10 Å to 13 Å. This layer expansion was likely due to intercalation of reduced Cr(III) into the interlayer space of the montmorillonite structure. EELS exhibited an L2 absorption peak at 586.0 eV and an L3 absorption peak at 577.0 eV, suggestive of Cr(III) in a hydroxide mineral phase. Similarly, XANES and EXAFS analyses confirmed Cr(VI) reduction to Cr(OH)3 at 30° C and indicated an edge-sharing coordination of the Cr(III) octahedra to 2-3 other Cr or metal ions. This study has important implications for understanding the reactivity of clay-rich sediment towards Cr(VI) reduction at contaminated sites and the stability of the reduced Cr(III).

Bishop, Michael E.↗

HarDWR - Harmonized Water Rights Records

A dataset within the Harmonized Database of Western U.S. Water Rights (HarDWR). For a detailed description of the database, please see the meta-record v2.0. Changelog v2.0 - Recalculated based on data sourced from WestDAAT - Changed using a Site ID column to identify unique records to using aa combination of Site ID and Allocation ID - Removed the Water Management Area (WMA) column from the harmonized records. The replacement is a separate file which stores the relationship between allocations and WMAs. This allows for allocations to contribute to water right amounts to multiple WMAs during the subsequent cumulative process. - Added a column describing a water rights legal status - Added "Unspecified" was a water source category - Added an acre-foot (AF) column - Added a column for the classification of the right's owner v1.02 - Added a .RData file to the dataset as a convenience for anyone exploring our code. This is an internal file, and the one referenced in analysis scripts as the data objects are already in R data objects. v1.01 - Updated the names of each file with an ID number less than 3 digits to include leading 0s v1.0 - Initial public release Description Here we present an updated database of Western U.S. water right records. This database provides consistent unique identifiers for each water right record, and a consistent categorization scheme that puts each water right record into one of seven broad use categories. These data were instrumental in conducting a study of the multi-sector dynamics of inter-sectoral water allocation changes though water markets (Grogan et al., *in review*). Specifically, the data were formatted for use as input to a process-based hydrologic model, Water Balance Model (WBM), with a water rights module (Grogan et al., *in review*). While this specific study motivated the development of the database presented here, water management in the U.S. West is a rich area of study (e.g., Anderson and Woosly, 2005; Tidwell, 2014; Null and Prudencio, 2016; Carney et al., 2021) so releasing this database publicly with documentation and usage notes will enable other researchers to do further work on water management in the U.S. West. We produced the water rights database presented here in four main steps: (1) data collection, (2) data quality control, (3) data harmonization, and (4) generation of cumulative water rights curves. Each of steps (1)-(3) had to be completed in order to produce (4), the final product that was used in the modeling exercise in Grogan et al. (*in review*). All data in each step is associated with a spatial unit called a Water Management Area (WMA), which is the unit of water right administration utilized by the state in which the right came from. Steps (2) and (3) required use to make assumptions and interpretation, and to remove records from the raw data collection. We describe each of these assumptions and interpretations below so that other researchers can choose to implement alternative assumptions an interpretation as fits their research aims. Motivation for Changing Data Sources The most significant change has been a switch from collecting the raw water rights directly from each state to using the water rights records presented in WestDAAT, a product of the Water Data Exchange (WaDE) Program under the Western States Water Council (WSWC). One of the main reasons for this is that each state of interest is a member of the WSWC, meaning that WaDE is partially funded by these states, as well as many universities. As WestDAAT is also a database with consistent categorization, it has allowed us to spend less time on data collection and quality control and more time on answering research questions. This has included records from water right sources we had previously not known about when creating v1.0 of this database. The only major downside to utilizing the WestDAAT records as our raw data is that further updates are tied to when WestDAAT is updated, as some states update their public water right records daily. However, as our focus is on cumulative water amounts at the regional scale, it is unlikely most records updates would have a significant effect on our results. The structure of WestDAAT led to several important changes to how HarWR is formatted. The most significant change is that WaDE has calculated a field known as `SiteUUID`, which is a unique identifier for the Point of Diversion (POD), or where the water is drawn from. This separate from `AllocationNativeID`, which is the identifier for the allocation of water, or the amount of water associated with the water right. It should be noted that it is possible for a single site to have multiple allocations associated with it and for an allocation to be able to be extracted from multiple sites. The site-allocation structure has allowed us to adapt a more consistent, and hopefully more realistic, approach in organizing the water right records than we had with HarDWR v1.0. This was incredibly helpful as the raw data from many states had multiple water uses within a single field within a single row of their raw data, and it was not always clear if the first water use was the most important, or simply first alphabetically. WestDAAT has already addressed this data quality issue. Furthermore, with v1.0, when there were multiple records with the same water right ID, we selected the largest volume or flow amount and disregarded the rest. As WestDAAT was already a common structure for disparate data formats, we were better able to identify sites with multiple allocations and, perhaps more importantly, allocations with multiple sites. This is particularly helpful when an allocation has sites which cross WMA boundaries, instead of just assigning the full water amount to a single WMA we are now able to divide the amount of water between the number of relevant WMAs. As it is now possible to identify allocations with water used in multiple WMAs, it is no longer practical to store this information within a single column. Instead the stAllocationToWMATab.csv file was created, which is an allocation by WMA matrix containing the percent Place of Use area overlap with each WMA. We then use this percentage to divide the allocation's flow amount between the given WMAs during the cumulation process to hopefully provide more realistic totals of water use in each area. However, not every state provides areas of water use, so like HarDWR v1.0, a hierarchical decision tree was used to assign each allocation to a WMA. First, if a WMA could be identified based on the allocation ID, then that WMA was used; typically, when available, this applied to the entire state and no further steps were needed. Second was the spatial analysis of Place of Use to WMAs. Third was a spatial analysis of the POD locations to WMAs, with the assumption that allocation's POD is within the WMA it should belong to; if an allocation still had multiple WMAs based on its POD locations, then the allocation's flow amount would be divided equally between all WMAs. The fourth, and final, process was to include water allocations which spatially fell outside of the state WMA boundaries. This could be due to several reasons, such as coordinate errors / imprecision in the POD location, imprecision in the WMA boundaries, or rights attached with features, such as a reservoir, which crosses state boundaries. To include these records, we decided for any POD which was within one kilometer of the state's edge would be assigned to the nearest WMA. Other Changes WestDAAT has Allowed In addition to a more nuanced and consistent method of assigning water right's data to WMAs, there are other benefits gained from using the WestDAAT dataset. Among those is a consistent categorization of a water right's legal status. In HarDWR v1.0, legal status was effectively ignored, which led to many valid concerns about the quality of the database related to the amounts of water the rights allowed to be claimed. The main issue was that rights with legal status' such as "application withdrawn", "non-active", or "cancelled" were included within HarDWR v1.0. These, and other water rights status' which were deemed to not be in use have been removed from this version of the database. Another major change has been the addition of the "unspecified water source category. This is water that can come from either surface water or groundwater, or the source of which is unknown. The addition of this source category brings the total number of categories to three. Due to reviewer feedback, we decided to add the acre-foot (AF) column so that the data may be more applicable to a wider audience. We added the ownerClassification column so that the data may be more applicable to a wider audience. File Descriptions The dataset is a series of various files organized by state sub-directories. In addition, each file begins with the state's name, in case the file is separate from its sub-directory for some reason. After the state name is the text which describes the contents of the file. Here is each file described in detail. Note that st is a placeholder for the state's name. stFullRecords_HarmonizedRights.csv: A file of the complete water records for each state. The column headers for each of this type of file are: state - The name of the state to which the allocations belong to. FIPS - The two digit numeric state ID code. siteID - The site location ID for POD locations. A site may have multiple allocations, which are the actual amount of water which can be drawn. In a simplified hypothetical, a farm stead may have an allocation for "irrigation" and an allocation for "domestic" water use, but the water is drawn from the same pumping equipment. It should be noted that many of the site ID appear to have been added by WaDE, and therefore may not be recognized by a given state's water rights database. allocationID - The allocation ID for the water right. For most states this is the water right ID, and what is recommended to use should a right be looked up on a given state's water rights database. The water amounts associated with these IDs tend to be finer scaled than those associated with siteID. It should be noted that some allocations may be extracted from multiple sites, particularly for larger Places of Use. ownerClassification - A classification of the types of owners for water rights. The most common is `Private` which incorporates a wide range of entities. Several classifications would be grouped into a government category, most of which are for the U.S. Federal Government. These allocations could be listed as "Federal", "United States of America", or as the names of any number of federal agencies. The last major grouping of entities is for "Native American"s. priorityDate - The date we use as the water right priority date for our modeling analysis. This is the legal priority date when it is available. However, for some rights, specifically from California and New Mexico, we used a pseudo priority date (e.g. well completion date or start of well drilling date) when a legal priority date was not available. The most questionable dates come from New Mexico, where the only date associated with certain water right records was the date the allocation was recorded in the database. As the allocation record creation tended to be within a few months of the filing of the application of the water right, from manually double checking the water rights, and our analysis focuses on aggregating water rights on the timescale of years, we determined it was acceptable to use such dates to include as many records as possible. primaryBeneficialUse - From the numerous state water use categories, WaDE categorized them into 21 categories WestDAAT. This column is the original WaDE category for the primary water use at the PoD site. allocationBeneficialUse - From the numerous state water use categories, WaDE categorized them into 21 categories for WestDAAT. This column is the original WaDE category

Economics↗

Litter Production of Oak-Hickory Forest at Missouri Ozark (MOFLUX) Site: 2003-2022

This dataset contains measurements of litter production at the second-growth upland oak-hickory forest at the Missouri Ozark AmeriFlux (MOFLUX) site. The MOFLUX site is located in the University of Missouri Baskett Forest situated in the Ozark Border Region of central Missouri, USA, and is part of the AmeriFlux network (site ID: US-MOz). During 2003, 24 circular vegetation plots (each 0.08 hectares) were established in the MOFLUX forest. The plots were situated 50 meters apart on 5 linear transects radiating out from the flux tower base in southeast, south, southwest, west, and northwest directions—there were 5 plots per transect except for the northwest one, which had only 4 due to the presence of a small pond at the terminus (Fig. 1). Litter measurements were initiated in October 2003 and continue to the present. Data through 2022 are reported in this dataset. On each plot, two subplots were established for the collection of litter. Subplots were setup using a stratified random design to ensure the collectors were not immediately adjacent to one another. Litter collectors were usually emptied at monthly intervals, or less during the autumn leaf drop. Samples were dried to constant mass and then sorted before determining the dry mass of leaf, vegetative and woody litter. These litter data have been valuable in modeling efforts to examine the impacts of intensifying moisture extremes (i.e., moisture excess and deficit conditions) on soil carbon cycling. More recent data will be added periodically with no changes to previously released data or the format and structure of the data file. This dataset contains one data file in comma separate (.csv) format. Additional metadata are provided: one data dictionary and a file-level metadata file in comma separate (.csv) format and a user guide in PDF (*.pdf) format.

54 ENVIRONMENTAL SCIENCES↗

The availability of hydrogeologic data associated with areas identified by the US Geological Survey as experiencing potentially induced seismicity resulting from subsurface injection

A critical need exists for site-specific hydrogeologic data in order to determine potential hazards of induced seismicity and to manage risk. By 2015, the United States Geological Survey (USGS) had identified 17 locations in the USA that are experiencing an increase in seismicity, which may be potentially induced through industrial subsurface injection. These locations span across seven states, which vary in geological setting, industrial exposure and seismic history. Comparing the research across the 17 locations revealed patterns for addressing induced seismicity concerns, despite the differences between geographical locations. Most induced seismicity studies evaluate geologic structure and seismic data from areas experiencing changes in seismic activity levels, but the inherent triggering mechanism is the transmission of hydraulic pressure pulses. This research conducted a systematic review of whether data are available in these locations to generate accurate hydrogeologic predictions, which could aid in managing seismicity. After analyzing peer-reviewed research within the 17 locations, this research confirms a lack of site-specific hydrogeologic data availability for at-risk areas. Commonly, formation geology data are available for these sites, but hydraulic parameters for the seismically active injection and basement zones are not available to researchers conducting peer-reviewed research. Obtaining hydrogeologic data would lead to better risk management for injection areas and provide additional scientific evidential support for determining a potentially induced seismic area.

58 GEOSCIENCES↗

THE MILKY WAY TOMOGRAPHY WITH SLOAN DIGITAL SKY SURVEY. IV. DISSECTING DUST

We use Sloan Digital Sky Survey (SDSS) photometry of 73 million stars to simultaneously constrain best-fit main-sequence stellar spectral energy distribution (SED) and amount of dust extinction along the line of sight toward each star. Using a subsample of 23 million stars with Two Micron All Sky Survey (2MASS) photometry, whose addition enables more robust results, we show that SDSS photometry alone is sufficient to break degeneracies between intrinsic stellar color and dust amount when the shape of extinction curve is fixed. When using both SDSS and 2MASS photometry, the ratio of the total to selective absorption, R{sub V} , can be determined with an uncertainty of about 0.1 for most stars in high-extinction regions. These fits enable detailed studies of the dust properties and its spatial distribution, and of the stellar spatial distribution at low Galactic latitudes (|b| < 30 Degree-Sign ). Our results are in good agreement with the extinction normalization given by the Schlegel et al. (SFD) dust maps at high northern Galactic latitudes, but indicate that the SFD extinction map appears to be consistently overestimated by about 20% in the southern sky, in agreement with recent study by Schlafly et al. The constraints on the shape of the dust extinction curve across the SDSS and 2MASS bandpasses disfavor the reddening law of O'Donnell, but support the models by Fitzpatrick and Cardelli et al. For the latter, we find a ratio of the total to selective absorption to be R{sub V} = 3.0 {+-} 0.1(random){+-}0.1 (systematic) over most of the high-latitude sky. At low Galactic latitudes (|b| < 5 Degree-Sign ), we demonstrate that the SFD map cannot be reliably used to correct for extinction because most stars are embedded in dust, rather than behind it, as is the case at high Galactic latitudes. We analyze three-dimensional maps of the best-fit R{sub V} and find that R{sub V} = 3.1 cannot be ruled out in any of the 10 SEGUE stripes at a precision level of {approx}0.1-0.2. Our best estimate for the intrinsic scatter of R{sub V} in the regions probed by SEGUE stripes is {approx}0.2. We introduce a method for efficient selection of candidate red giant stars in the disk, dubbed 'dusty parallax relation', which utilizes a correlation between distance and the extinction along the line of sight. We make these best-fit parameters, as well as all the input SDSS and 2MASS data, publicly available in a user-friendly format. These data can be used for studies of stellar number density distribution, the distribution of dust properties, for selecting sources whose SED differs from SEDs for high-latitude main-sequence stars, and for estimating distances to dust clouds and, in turn, to molecular gas clouds.

79 ASTRONOMY AND ASTROPHYSICS↗

Short gamma-ray burst formation rate from BATSE data using E{sub p} -L{sub p} correlation and the minimum gravitational-wave event rate of a coalescing compact binary

Using 72 short gamma-ray bursts (SGRBs) with well determined spectral data observed by BATSE, we determine their redshift and luminosity by applying the E{sub p} -L{sub p} correlation for SGRBs found by Tsutsui et al. For 53 SGRBs with an observed flux brighter than 4 × 10{sup –6} erg cm{sup –2} s{sup –1}, the cumulative redshift distribution up to z = 1 agrees well with that of 22 Swift SGRBs. This suggests that the redshift determination by the E{sub p} -L{sub p} correlation for SGRBs works well. The minimum event rate at z = 0 is estimated as R{sub on−axis}{sup min}=6.3{sub −3.9}{sup +3.1}× 10{sup −10} events Mpc{sup −3} yr{sup −1}, so that the minimum beaming angle is 0.°6-7.°8 assuming a merging rate of 10{sup –7}- 4 × 10{sup –6} events Mpc{sup –3} yr{sup –1} suggested from the binary pulsar data. Interestingly, this angle is consistent with that for SGRB 130603B of ∼4°-8°. On the other hand, if we assume a beaming angle of ∼6° suggested from four SGRBs with the observed beaming angle value, then the minimum event rate including off-axis SGRBs is estimated as R{sub all}{sup min}=1.15{sub −0.66}{sup +0.56} × 10{sup −7} events Mpc{sup −3} yr{sup −1}. If SGRBs are induced by the coalescence of binary neutron stars (NSs) and/or black holes (BHs), then this event rate leads to a minimum gravitational-wave detection rate of 3.8{sub −2.2}{sup +1.8} (146{sub −83}{sup +71}) events yr{sup −1} for an NS-NS (NS-BH) binary, respectively, by a worldwide network with KAGRA, advanced-LIGO, advanced-VIRGO, and GEO.

79 ASTRONOMY AND ASTROPHYSICS↗

Robot for Investigations and Assessments of Nuclear Areas

RIANA is a remote controlled Robot dedicated for Investigations and Assessments of Nuclear Areas. The development of RIANA is motivated by the need to have at disposal a proven robot, tested in hot cells; a robot capable of remotely investigate and characterise the inside of nuclear facilities in order to collect efficiently all the required data in the shortest possible time. It is based on a wireless medium sized remote carrier that may carry a wide variety of interchangeable modules, sensors and tools. It is easily customised to match specific requirements and quickly configured depending on the mission and the operator's preferences. RIANA integrates localisation and navigation systems. The robot will be able to generate / update a 2D map of its surrounding and exploring areas. The position of the robot is given accurately on the map. Furthermore, the robot will be able to autonomously calculate, define and follow a trajectory between 2 points taking into account its environment and obstacles. The robot is configurable to manage obstacles and restrict access to forbidden areas. RIANA allows an advanced control of modules, sensors and tools; all collected data (radiological and measured data) are displayed in real time in different format (chart, on the generated map...) and stored in a single place so that may be exported in a convenient format for data processing. This modular design gives RIANA the flexibility to perform multiple investigation missions where humans cannot work such as: visual inspections, dynamic localization and 2D mapping, characterizations and nuclear measurements of floor and walls, non destructive testing, samples collection: solid and liquid. The benefits of using RIANA are: - reducing the personnel exposures by limiting the manual intervention time, - minimizing the time and reducing the cost of investigation operations, - providing critical inputs to set up and optimize cleanup and dismantling operations. (authors)

42 ENGINEERING↗

Sub-Second Parallel State Estimation

This report describes the performance of Pacific Northwest National Laboratory (PNNL) sub-second parallel state estimation (PSE) tool using the utility data from the Bonneville Power Administrative (BPA) and discusses the benefits of the fast computational speed for power system applications. The test data were provided by BPA. They are two-days’ worth of hourly snapshots that include power system data and measurement sets in a commercial tool format. These data are extracted out from the commercial tool box and fed into the PSE tool. With the help of advanced solvers, the PSE tool is able to solve each BPA hourly state estimation problem within one second, which is more than 10 times faster than today’s commercial tool. This improved computational performance can help increase the reliability value of state estimation in many aspects: (1) the shorter the time required for execution of state estimation, the more time remains for operators to take appropriate actions, and/or to apply automatic or manual corrective control actions. This increases the chances of arresting or mitigating the impact of cascading failures; (2) the SE can be executed multiple times within time allowance. Therefore, the robustness of SE can be enhanced by repeating the execution of the SE with adaptive adjustments, including removing bad data and/or adjusting different initial conditions to compute a better estimate within the same time as a traditional state estimator’s single estimate. There are other benefits with the sub-second SE, such as that the PSE results can potentially be used in local and/or wide-area automatic corrective control actions that are currently dependent on raw measurements to minimize the impact of bad measurements, and provides opportunities to enhance the power grid reliability and efficiency. PSE also can enable other advanced tools that rely on SE outputs and could be used to further improve operators’ actions and automated controls to mitigate effects of severe events on the grid. The power grid continues to grow and the number of measurements is increasing at an accelerated rate due to the variety of smart grid devices being introduced. A parallel state estimation implementation will have better performance than traditional, sequential state estimation by utilizing the power of high performance computing (HPC). This increased performance positions parallel state estimators as valuable tools for operating the increasingly more complex power grid.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Continuous-Energy Data Checks

The purpose of this report is to provide an overview of all Quality Assurance tests that have to be performed on a nuclear data set to be transformed into an ACE formatted nuclear data file. The ACE file is capable of containing different types of data such as continuous energy neutron data, thermal scattering data, etc. Within this report, we will limit ourselves to continuous energy neutron data.

99 GENERAL AND MISCELLANEOUS↗

Release of the NDI 2.2.0

The Nuclear Data Interface 2.2.0 has been released. It includes the addition of charged particle dE/dx (stopping power) data, the ability to read in NDI-formatted binary data, corrections to TN data, and other minor changes and bug fixes.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Release of the NDI 2.2.0alpha

The Nuclear Data Interface 2.2.0alpha has been released. It includes the addition of charged particle dE/dx (stopping power) data, the ability to read in NDI-formatted binary data, corrections to TN data, CP 2011 and CP 2020 data, and other minor changes and bug fixes.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

sfccldgrid2longstation

The site data in a station data product format used to produce the gridded cloud grid data product, sfccldgrid2caracena.

54 ENVIRONMENTAL SCIENCES↗

Compilation of fatigue, fatigue-crack propagation, and fracture data for 2024 and 7075 aluminum, Ti-6Al-4V titanium, and 300M steel. Volume 1: Description of data and data storage on magnetic tape. Volume 2: Data tape (7-track magnetic tape)

Fatigue, fatigue-crack-propagation, and fracture data compiled and stored on magnetic tape are documented. Data for 202 and 7075 aluminum alloys, Ti-6Al-4V titanium alloy, and 300M steel are included in the compilation. Approximately 4,500 fatigue, 6,500 fatigue-crack-propagation, and 1,500 fracture data points are stored on magnetic tape. Descriptions of the data, an index to the data on the magnetic tape, information on data storage format on the tape, a listing of all data source references, and abstracts of other pertinent test information from each data source reference are included.

Rice, R. C.↗