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Firmware development for the ATLAS TileCal sROD

TileCal is the central hadronic calorimeter of the ATLAS experiment at the Large Hadron Collider (LHC) at CERN. A main upgrade of the LHC (also called Phase-II) is planned in order to increase the instantaneous luminosity in 2022. At the TileCal level, the upgrade involves the redesign of the complete read-out architecture, affecting both the front-end and the back-end electronics. In the new read-out architecture, the front-end electronics will transmit digitized information of the full detector to the back-end system every single bunch crossing. Thus, the back-end system must provide digital calibrated information to the first level of trigger. Having all detector data per bunch crossing in the back-end will increase the precision and granularity of the trigger information, improving this way the trigger efficiencies. A reduced part of the detector, 1/256 of the total, will be equipped with the new electronics during 2014 to evaluate the proposed architecture in real conditions in the so-called 'demonstrator project'. The upgraded version of the Read-Out Driver (sROD) will be the core element of the back-end electronics in Phase-II. The sROD demonstrator is a prototype that is being developed to validate in the demonstrator project the future sROD for Phase-II. This module includes two Xilinx Series 7 Field Programmable Gate Arrays (FPGAs) for data receiving and processing and will be installed and working in an ATCA framework. A complete description of the sROD functionality in terms of firmware will be introduced. In addition, the status of the firmware development and a summary of the main milestones achieved and the future plans will be presented. (authors)

43 PARTICLE ACCELERATORS↗

Subsurface Characterization for Evaluating Geothermal Resource Potential from Existing Oil and Gas Wells in Tuttle, Oklahoma

Oil and gas (O&G) wells often encounter co-produced hot water, possibly suitable for geothermal direct-use applications. The City of Tuttle is located on the eastern part of the Anadarko sedimentary basin in Oklahoma with high heat-in-place potential and recovery capability at depth. This study aims at demonstrating the potential of geothermal energy production for direct-use applications in two public schools and 250 nearby houses in Tuttle via repurposing existing O&G wells. In this scope, geochemistry, geology, and borehole log data were collected and incorporated into a 3D conceptual subsurface model. A digital elevation model (DEM) was used to represent the study area topography with four O&G wells. In addition, hydrogeochemical characteristics of the geothermal fluid and scaling potential were analyzed using ternary diagrams and chemical ratios to develop mixing models. The subsurface geology model indicated that the study area primarily consists of Permian to Mississippian Sandstone and Limestone formations, implying a porosity ranging between 12% and 22%, and a permeability up to 3.90E-14 m2 in certain reservoir levels. The reservoir temperature is expected to be ranging between 80 degrees C to 95 degrees C around 3 km depth with an average temperature gradient of 22.8 degrees C/km. Chemical geothermometers also estimated the reservoir temperature as 90 degrees C. Findings of the chemical model demonstrated that the geothermal fluid is Sodium-Potassium-Chloride-Sulfate type and possibly mixed with shallow groundwater resulting in higher Ca and Mg concentrations and lower Na/K ratio implying lower calcite scaling. These results comprehensively characterize the potential of geothermal resources in the study area and imply that geothermal energy production by repurposing existing O&G wells is suitable for low-temperature direct-use applications.

gas wells↗

TH-EF-BRA-06: A Novel Retrospective 3D K-Space Sorting 4D-MRI Technique Using a Radial K-Space Acquisition MRI Sequence

Purpose: Current retrospective 4D-MRI provides superior tumor-to-tissue contrast and accurate respiratory motion information for radiotherapy motion management. The developed 4D-MRI techniques based on 2D-MRI image sorting require a high frame-rate of the MR sequences. However, several MRI sequences provide excellent image quality but have low frame-rate. This study aims at developing a novel retrospective 3D k-space sorting 4D-MRI technique using radial k-space acquisition MRI sequences to improve 4D-MRI image quality and temporal-resolution for imaging irregular organ/tumor respiratory motion. Methods: The method is based on a RF-spoiled, steady-state, gradient-recalled sequence with minimal echo time. A 3D radial k-space data acquisition trajectory was used for sampling the datasets. Each radial spoke readout data line starts from the 3D center of Field-of-View. Respiratory signal can be extracted from the k-space center data point of each spoke. The spoke data was sorted based on its self-synchronized respiratory signal using phase sorting. Subsequently, 3D reconstruction was conducted to generate the time-resolved 4D-MRI images. As a feasibility study, this technique was implemented on a digital human phantom XCAT. The respiratory motion was controlled by an irregular motion profile. To validate using k-space center data as a respiratory surrogate, we compared it with the XCAT input controlling breathing profile. Tumor motion trajectories measured on reconstructed 4D-MRI were compared to the average input trajectory. The mean absolute amplitude difference (D) was calculated. Results: The signal extracted from k-space center data matches well with the input controlling respiratory profile of XCAT. The relative amplitude error was 8.6% and the relative phase error was 3.5%. XCAT 4D-MRI demonstrated a clear motion pattern with little serrated artifacts. D of tumor trajectories was 0.21mm, 0.23mm and 0.23mm in SI, AP and ML directions, respectively. Conclusion: A novel retrospective 3D k-space sorting 4D-MRI technique has been developed and evaluated on human digital phantom. NIH (1R21CA165384-01A1)

60 APPLIED LIFE SCIENCES↗

Sloan Digital Sky Survey IV: Mapping the Milky Way, Nearby Galaxies, and the Distant Universe

We describe the Sloan Digital Sky Survey IV (SDSS-IV), a project encompassing three major spectroscopic programs. The Apache Point Observatory Galactic Evolution Experiment 2 (APOGEE-2) is observing hundreds of thousands of Milky Way stars at high resolution and high signal-to-noise ratios in the near-infrared. The Mapping Nearby Galaxies at Apache Point Observatory (MaNGA) survey is obtaining spatially resolved spectroscopy for thousands of nearby galaxies (median z∼0.03). The extended Baryon Oscillation Spectroscopic Survey (eBOSS) is mapping the galaxy, quasar, and neutral gas distributions between z∼0.6 and 3.5 to constrain cosmology using baryon acoustic oscillations, redshift space distortions, and the shape of the power spectrum. Within eBOSS, we are conducting two major subprograms: the SPectroscopic IDentification of eROSITA Sources (SPIDERS), investigating X-ray AGNs and galaxies in X-ray clusters, and the Time Domain Spectroscopic Survey (TDSS), obtaining spectra of variable sources. All programs use the 2.5 m Sloan Foundation Telescope at the Apache Point Observatory; observations there began in Summer 2014. APOGEE-2 also operates a second near-infrared spectrograph at the 2.5 m du Pont Telescope at Las Campanas Observatory, with observations beginning in early 2017. Observations at both facilities are scheduled to continue through 2020. In keeping with previous SDSS policy, SDSS-IV provides regularly scheduled public data releases; the first one, Data Release 13, was made available in 2016 July.

79 ASTRONOMY AND ASTROPHYSICS↗

Machine Learning Classification of Molten Salt Heat Exchanger Channel Plugging using Synthetic Data

This report addresses the requirements of Milestone M3.4 AI capability to identify and predict maintenance events. Development of digital twins (DT) for molten salt reactor (MSR) components is crucial for reducing operating and maintenance costs (O&M) and ensuring commercial viability of these reactors. Our focus is on development of DT for MSR primary system heat exchanger (HX), a critical component, the fault in which can reduce operating efficiency and force reactor shutdown. We are investigating the feasibility of a conceptual DT of HX consisting of internal distributed temperature sensing with fiber optics and machine learning (ML) algorithms to detect and localize faults. To determine the optimal approach to detection and localization of channel plugging, we benchmark seven different ML models: Logistic Regression, K-Nearest Neighbors (KNN), Gaussian Naïve Bayes, Support Vector Machines (SVM), Decision Tree Classifier, Random Forest Tree Classifier, and Feed-Forward Neural Network. ML algorithms are benchmarked using synthetic HX plugging data generated with computational fluid dynamics COMSOL software, with added brown noise to represent experimental noise. We show that the best performance is obtained with the Decision Tree classifier.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Active-Interrogation Measurements of Induced-Fission Neutrons from Low-Enriched Uranium

Protection and control of nuclear fuels is paramount for nuclear security and safeguards; therefore, it is important to develop fast and robust controlling mechanisms to ensure the safety of nuclear fuels. Through both passive- and active-interrogation methods we can use fast-neutron detection to perform real-time measurements of fission neutrons for process monitoring. Active interrogation allows us to use different ranges of incident neutron energy to probe for different isotopes of uranium. With fast-neutron detectors, such as organic liquid scintillation detectors, we can detect the induced-fission neutrons and photons and work towards quantifying a sample’s mass and enrichment. Using MCNPX-PoliMi, a system was designed to measure induced-fission neutrons from U-235 and U-238. Measurements were then performed in the summer of 2010 at the Joint Research Centre in Ispra, Italy. Fissions were induced with an associated particle D-T generator and an isotopic Am-Li source. The fission neutrons, as well as neutrons from (n, 2n) and (n, 3n) reactions, were measured with five 5” by 5” EJ-309 organic liquid scintillators. The D-T neutron generator was available as part of a measurement campaign in place by Padova University. The measurement and data-acquisition systems were developed at the University of Michigan utilizing a CAEN V1720 digitizer and pulse-shape discrimination algorithms to differentiate neutron and photon detections. Low-enriched uranium samples of varying mass and enrichment were interrogated. Acquired time-of-flight curves and cross-correlation curves are currently analyzed to draw relationships between detected neutrons and sample mass and enrichment. In the full paper, the promise of active-interrogation measurements and fast-neutron detection will be assessed through the example of this proof-of-concept measurement campaign. Additionally, MCNPX-PoliMi simulation results will be compared to the measured data to validate the MCNPX-PoliMi code when used for active-interrogation simulations.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

THE DATA REDUCTION PIPELINE FOR THE SDSS-IV MaNGA IFU GALAXY SURVEY

Mapping Nearby Galaxies at Apache Point Observatory (MaNGA) is an optical fiber-bundle integral-field unit (IFU) spectroscopic survey that is one of three core programs in the fourth-generation Sloan Digital Sky Survey (SDSS-IV). With a spectral coverage of 3622–10354 Å and an average footprint of ∼500 arcsec{sup 2} per IFU the scientific data products derived from MaNGA will permit exploration of the internal structure of a statistically large sample of 10,000 low-redshift galaxies in unprecedented detail. Comprising 174 individually pluggable science and calibration IFUs with a near-constant data stream, MaNGA is expected to obtain ∼100 million raw-frame spectra and ∼10 million reduced galaxy spectra over the six-year lifetime of the survey. In this contribution, we describe the MaNGA Data Reduction Pipeline algorithms and centralized metadata framework that produce sky-subtracted spectrophotometrically calibrated spectra and rectified three-dimensional data cubes that combine individual dithered observations. For the 1390 galaxy data cubes released in Summer 2016 as part of SDSS-IV Data Release 13, we demonstrate that the MaNGA data have nearly Poisson-limited sky subtraction shortward of ∼8500 Å and reach a typical 10 σ limiting continuum surface brightness μ = 23.5 AB arcsec{sup −2} in a five-arcsecond-diameter aperture in the g -band. The wavelength calibration of the MaNGA data is accurate to 5 km s{sup −1} rms, with a median spatial resolution of 2.54 arcsec FWHM (1.8 kpc at the median redshift of 0.037) and a median spectral resolution of σ = 72 km s{sup −1}.

79 ASTRONOMY AND ASTROPHYSICS↗

TH-E-BRF-11: Dynamic Treatment of Clinical Margins Beyond the PET-Avid Target in Emission Guided Radiation Therapy: A Retrospective Patient Study

Purpose: Emission guided radiation therapy (EGRT) is a new modality that uses PET emissions for direct real-time tumor tracking. Radiation beamlets are delivered along PET lines of response (LOR's) by a fast rotating PET-Linac closed ring gantry. In this work, we develop a scheme to treat clinical margins defined proximal to the moving PET-avid tumor, while maintaining EGRT's inherent real-time tracking ability. Methods: The principle of EGRT is to deliver radiation along PET emission paths to concentrate dose in the PET-avid gross tumor volume (GTV). To account for adjacent non- PET avid regions in the clinical volume (CTV) a method was developed that expands the set of radiation beamlet responses to include the effective margin extension from the GTV to the CTV. An LOR detection may now Result in multiple beamlet responses: one along the original LOR, and others that are adjacent to it in the direction of margin extension. Evaluation studies were performed on a 4D digital patient as well as a clinical breast cancer patient with moving lung tumors. Emission data were obtained using GATE and a commercial PET scanner. Dose delivery was simulated using VMC++. For the patient study, Philips Pinnacle was used for planning and Mirada RTx was used for deformable dose registration across multiple breathing phases. Results: Compared with IMRT, the EGRT margin extension method achieved a 25.3% and 9.0% relative increase in dose to 95% of the CTV for the digital and clinical patients, respectively. The corresponding CTV dose increases without margin extension were 9.7% and 1.4%. The organs at risk doses were kept similar or lower for EGRT in both cases, with tumor tracking preserved. Conclusions: With the capability of accurate treatment of the moving CTV, EGRT has the potential to enable a practical and effective implementation of 4D biologically guided radiation therapy. Authors SRM and AN are stockholders of RefleXion Medical.

60 APPLIED LIFE SCIENCES↗

SDSS-IV MaNGA IFS GALAXY SURVEY—SURVEY DESIGN, EXECUTION, AND INITIAL DATA QUALITY

The MaNGA Survey (Mapping Nearby Galaxies at Apache Point Observatory) is one of three core programs in the Sloan Digital Sky Survey IV. It is obtaining integral field spectroscopy for 10,000 nearby galaxies at a spectral resolution of R ∼ 2000 from 3622 to 10354 Å. The design of the survey is driven by a set of science requirements on the precision of estimates of the following properties: star formation rate surface density, gas metallicity, stellar population age, metallicity, and abundance ratio, and their gradients; stellar and gas kinematics; and enclosed gravitational mass as a function of radius. We describe how these science requirements set the depth of the observations and dictate sample selection. The majority of targeted galaxies are selected to ensure uniform spatial coverage in units of effective radius (R{sub e}) while maximizing spatial resolution. About two-thirds of the sample is covered out to 1.5 R{sub e} (Primary sample), and one-third of the sample is covered to 2.5 R{sub e} (Secondary sample). We describe the survey execution with details that would be useful in the design of similar future surveys. We also present statistics on the achieved data quality, specifically the point-spread function, sampling uniformity, spectral resolution, sky subtraction, and flux calibration. For our Primary sample, the median r -band signal-to-noise ratio is ∼70 per 1.4 Å pixel for spectra stacked between 1 R{sub e} and 1.5 R{sub e}. Measurements of various galaxy properties from the first-year data show that we are meeting or exceeding the defined requirements for the majority of our science goals.

79 ASTRONOMY AND ASTROPHYSICS↗

SU-E-J-02: 4D Digital Tomosynthesis Based On Algebraic Image Reconstruction and Total-Variation Minimization for the Improvement of Image Quality

Purpose: In this paper, we implemented the four-dimensional (4D) digital tomosynthesis (DTS) imaging based on algebraic image reconstruction technique and total-variation minimization method in order to compensate the undersampled projection data and improve the image quality. Methods: The projection data were acquired as supposed the cone-beam computed tomography system in linear accelerator by the Monte Carlo simulation and the in-house 4D digital phantom generation program. We performed 4D DTS based upon simultaneous algebraic reconstruction technique (SART) among the iterative image reconstruction technique and total-variation minimization method (TVMM). To verify the effectiveness of this reconstruction algorithm, we performed systematic simulation studies to investigate the imaging performance. Results: The 4D DTS algorithm based upon the SART and TVMM seems to give better results than that based upon the existing method, or filtered-backprojection. Conclusion: The advanced image reconstruction algorithm for the 4D DTS would be useful to validate each intra-fraction motion during radiation therapy. In addition, it will be possible to give advantage to real-time imaging for the adaptive radiation therapy. This research was supported by Leading Foreign Research Institute Recruitment Program (Grant No.2009-00420) and Basic Atomic Energy Research Institute (BAERI); (Grant No. 2009-0078390) through the National Research Foundation of Korea(NRF) funded by the Ministry of Science, ICT and Future Planning (MSIP)

62 RADIOLOGY AND NUCLEAR MEDICINE↗

TH-CD-206-07: Determination of Patient-Specific Myocardial Mass at Risk Using Computed Tomography Angiography

Purpose: To evaluate the accuracy of a patient-specific coronary perfusion territory assignment algorithm that uses CT angiography (CTA) and a minimum-cost-path approach to assign coronary perfusion territories on a voxel-by-voxel basis for determination of myocardial mass at risk. Methods: Intravenous (IV) contrast (370 mg/mL iodine, 25 mL, 7 mL/s) was injected centrally into five swine (35–45 kg) and CTA was performed using a 320-slice CT scanner at 100 kVp and 200 mA. Additionally, a 4F catheter was advanced into the left anterior descending (LAD), left circumflex (LCX), and right coronary artery (RCA) and contrast (30 mg/mL iodine, 10 mL, 1.5 mL/s) was directly injected into each coronary artery for isolation of reference coronary perfusion territories. Semiautomatic myocardial segmentation of the CTA data was then performed and the centerlines of the LAD, LCX, and RCA were digitally extracted through image processing. Individual coronary perfusion territories were then assigned using a minimum-cost-path approach, and were quantitatively compared to the reference coronary perfusion territories. Results: The results of the coronary perfusion territory assignment algorithm were in good agreement with the reference coronary perfusion territories. The average volumetric assignment error from mitral orifice to apex was 5.5 ± 1.1%, corresponding to 2.1 ± 0.7 grams of myocardial mass misassigned for each coronary perfusion territory. Conclusion: The results indicate that accurate coronary perfusion territory assignment is possible on a voxel-by-voxel basis using CTA data and an assignment algorithm based on a minimum-cost-path approach. Thus, the technique can potentially be used to accurately determine patient-specific myocardial mass at risk distal to a coronary stenosis, improving coronary lesion assessment and treatment. Conflict of Interest (only if applicable): Grant funding from Toshiba America Medical Systems.

60 APPLIED LIFE SCIENCES↗

EVOLUTION IN THE H I GAS CONTENT OF GALAXY GROUPS: PRE-PROCESSING AND MASS ASSEMBLY IN THE CURRENT EPOCH

We present an analysis of the neutral hydrogen (H I) content and distribution of galaxies in groups as a function of their parent dark matter halo mass. The Arecibo Legacy Fast ALFA survey α.40 data release allows us, for the first time, to study the H I properties of over 740 galaxy groups in the volume of sky common to the Sloan Digital Sky Survey (SDSS) and ALFALFA surveys. We assigned ALFALFA H I detections a group membership based on an existing magnitude/volume-limited SDSS Data Release 7 group/cluster catalog. Additionally, we assigned group ''proximity' membership to H I detected objects whose optical counterpart falls below the limiting optical magnitude—thereby not contributing substantially to the estimate of the group stellar mass, but significantly to the total group H I mass. We find that only 25% of the H I detected galaxies reside in groups or clusters, in contrast to approximately half of all optically detected galaxies. Further, we plot the relative positions of optical and H I detections in groups as a function of parent dark matter halo mass to reveal strong evidence that H I is being processed in galaxies as a result of the group environment: as optical membership increases, groups become increasingly deficient of H I rich galaxies at their center and the H I distribution of galaxies in the most massive groups starts to resemble the distribution observed in comparatively more extreme cluster environments. We find that the lowest H I mass objects lose their gas first as they are processed in the group environment, and it is evident that the infall of gas rich objects is important to the continuing growth of large scale structure at the present epoch, replenishing the neutral gas supply of groups. Finally, we compare our results to those of cosmological simulations and find that current models cannot simultaneously predict the H I selected halo occupation distribution for both low and high mass halos.

79 ASTRONOMY AND ASTROPHYSICS↗

CHARACTERIZING THE GALACTIC WHITE DWARF BINARY POPULATION WITH SPARSELY SAMPLED RADIAL VELOCITY DATA

We present a method to characterize statistically the parameters of a detached binary sample-binary fraction, separation distribution, and mass-ratio distribution-using noisy radial velocity data with as few as two, randomly spaced, epochs per object. To do this, we analyze the distribution of {Delta}RV{sub max}, the maximum radial velocity difference between any two epochs for the same object. At low values, the core of this distribution is dominated by measurement errors, but for large enough samples there is a high-velocity tail that can effectively constrain the parameters of the binary population. We discuss our approach for the case of a population of detached white dwarf (WD) binaries with separations that are decaying via gravitational wave emission. We derive analytic expressions for the present-day distribution of separations, integrated over the star formation history of the Galaxy, for parameterized initial WD separation distributions at the end of the common-envelope phase. We use Monte Carlo techniques to produce grids of simulated {Delta}RV{sub max} distributions with specific binary population parameters, and the same sampling cadences and radial velocity errors as the observations, and we compare them to the real {Delta}RV{sub max} distribution to constrain the properties of the binary population. We illustrate the sensitivity of the method to both the model and observational parameters. In the particular case of binary WDs, every model population predicts a merger rate per star which can easily be compared to specific Type Ia supernova rates. In a companion paper, we apply the method to a sample of {approx}4000 WDs from the Sloan Digital Sky Survey. The binary fractions and separation distribution parameters allowed by the data indicate a rate of WD-WD mergers per unit stellar mass in the Galactic disk, {approx}1 Multiplication-Sign 10{sup -13} mergers yr{sup -1} M{sup -1}{sub Sun }, remarkably similar to the rate per unit mass of Type Ia supernovae in Milky Way like galaxies.

79 ASTRONOMY AND ASTROPHYSICS↗

Interrelationships between information and energy using knowledge management tools

Edward Fredkin was an enthusiastic advocate of information-based theoretical physics, who, in the early 1980s, proposed a new theory of physics based on the idea that the universe is ultimately composed of software. According to Fredkin, reality should be considered as being composed not of particles, matter and forces or energy but of bits of data or information modified according to computational rules. Fredkin went on to demonstrate that, while energy is necessary for storing and retrieving information, it can be arbitrarily reduced in order to carry out any particular instance of information processing, and this operation does not have a lower bound. This implies that it is information rather than matter or energy that should be considered at the ultimate fundamental constituent of reality. This possibility had already been suggested by other scientists. Norbert Wiener heralded a fundamental shift from energy to information and suggested that the universe was founded essentially on the transformation of information, not energy. However, Konrad Zuse was the first, back in 1967, to defend the idea that a digital computer is computing the universe. Richard P. Feynman showed this possibility in a similar light in his reflections on how information related to matter and energy. Other pioneering research on the theory of digital physics was published by Kantor in 1977 and more recently by Stephen Wolfram in 2002, who thereby joined the host of voices upholding that it is patterns of information, not matter and energy, that constitute the cornerstones of reality. In this paper, we introduce the use of knowledge management tools for the purpose of analysing this topic.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

MO-F-16A-06: Implementation of a Radiation Exposure Monitoring System for Surveillance of Multi-Modality Radiation Dose Data

Purpose: We have implemented a commercially available Radiation Exposure Monitoring System (REMS) to enhance the processes of radiation dose data collection, analysis and alerting developed over the past decade at our sites of practice. REMS allows for consolidation of multiple radiation dose information sources and quicker alerting than previously developed processes. Methods: Thirty-nine x-ray producing imaging modalities were interfaced with the REMS: thirteen computed tomography scanners, sixteen angiography/interventional systems, nine digital radiography systems and one mammography system. A number of methodologies were used to provide dose data to the REMS: Modality Performed Procedure Step (MPPS) messages, DICOM Radiation Dose Structured Reports (RDSR), and DICOM header information. Once interfaced, the dosimetry information from each device underwent validation (first 15–20 exams) before release for viewing by end-users: physicians, medical physicists, technologists and administrators. Results: Before REMS, our diagnostic physics group pulled dosimetry data from seven disparate databases throughout the radiology, radiation oncology, cardiology, electrophysiology, anesthesiology/pain management and vascular surgery departments at two major medical centers and four associated outpatient clinics. With the REMS implementation, we now have one authoritative source of dose information for alerting, longitudinal analysis, dashboard/graphics generation and benchmarking. REMS provides immediate automatic dose alerts utilizing thresholds calculated through daily statistical analysis. This has streamlined our Closing the Loop process for estimated skin exposures in excess of our institutional specific substantial radiation dose level which relied on technologist notification of the diagnostic physics group and daily report from the radiology information system (RIS). REMS also automatically calculates the CT size-specific dose estimate (SSDE) as well as provides two-dimensional angulation dose maps for angiography/interventional procedures. Conclusion: REMS implementation has streamlined and consolidated the dosimetry data collection and analysis process at our institutions while eliminating manual entry error and providing immediate alerting and access to dosimetry data to both physicists and physicians. Brent Stewart has funded research through GE Healthcare.

60 APPLIED LIFE SCIENCES↗

Delineation of endorheic drainage basins in the MERIT-Plus dataset for 5 and 15 minute upscaled river networks

Abstract The MERIT-Hydro networks re-gridded by the Iterative Hydrography Upscaling (IHU) algorithm do not retain exo- or endorheic basin attributes from the original data. Here we developed methods to assign such attributes to those and any other digital river networks. The motivation is that endorheic inland drainage basins are essential for hydrologic modelling of global and regional water balances, land surface water storage, gravity anomalies, sea level rise, etc. First, we create basin attributes that explicitly label endorheic and exorheic catchments by the criteria of direct or hidden connectivity to the ocean without changing their flow direction grid. In the second step we alter the delineation of endorheic basins by the merging algorithm that eliminates small inland watersheds to the adjacent host basins. The resulting datasets have a significantly reduced number of endorheic basins while preserving the total land portion and topology of the inland basins. The data was validated using the Water Balance Model by comparing volume of endorheic inland depressions with modelled water accumulation in their inland lakes.

58 GEOSCIENCES↗

Digital Analytics, Causal Knowledge Acquisition and Reasoning for Technical Language Processing

Complex engineering systems such as nuclear power plants (NPPs) generate and collect large amounts of equipment reliability (ER) data elements that contain information on the status of components, assets, and systems. Some of this information is textual in form and can be found in documents such as incident reports (IRs) and work orders (WOs). Analyses of textual data in current NPPs-using natural language processing (NLP) methods-have been expanded over the last decade, and it is only recently that the true potential of such analyses has emerged. So far, applications of NLP methods have mostly been limited to classification and prediction, the goal being to identify the nature of the textual element (e.g., safety or non-safety related). Here, we target a more complex problem: automatically extracting knowledge from a textual element in order to assist system engineers in conducting system health assessments. Knowledge extraction is a very broad concept, and its definition may vary depending on the application context. Our methods are a blend of both rule-based and machine learning (ML) algorithms. For our purposes, knowledge extraction means identifying the systems or assets mentioned in a given textual element, as well as the type of event described (e.g., component failure or maintenance activity). In addition, we want to capture details such as measured quantities and the temporal/cause-effect relations between events. In this tool, we also demonstrate how textual data elements are preprocessed in order to handle typos, acronyms, and abbreviations. One main feature of these methods is that they are not based solely on data, but are in fact model-based. In other words, they also rely on MBSE models that are designed to capture-from a functional point of view-the architecture of the systems/assets under consideration. The main purpose of such models is to digitally emulate system engineers' knowledge of system and asset architecture and to identify dependencies among systems, assets, and components. Provided these models, analyses of textual and numeric ER data can be performed by first identifying the OPM model elements to which the ER data elements are referring. The relationships between ER data elements are then identified by checking for any temporal or logical dependencies.

Mandelli, Diego [Idaho National Laboratory (INL), ↗

The Readout Electronics of the Mu2e Electromagnetic Calorimeter

The Mu2e electromagnetic calorimeter has been designed to measure ~100 MeV electrons with energy resolution σE/E <10%, time resolution σt < 500ps and position resolution σx < 1cm. The detector is composed of 1348 un-doped CsI crystals coupled to two large area Silicon Photomultipliers (SiPMs). Each SiPM is connected to a Front End Electronics (FEE) chip which hosts the shaping amplifier and the high voltage linear regulator. A group of 20 FEE is controlled by one Mezzanine Board (MB) which transmits the amplified signals to one Digitizer ReAdout Controller board (DiRAC). The DiRAC samples the waveforms at 200 MHz with 12-bit ADCs, packs the data according to the Mu2e custom format and transmits them to the event builder through an optical transceiver. To limit the number of pass-through connectors and the length of the cables, the readout and digitization electronics is located inside the detector cryostat and close to the interaction target. The boards will have to sustain a neutron fluence of about 5x10 10 n/cm 2 @ 1 MeVeq (Si)/y and a Total Ionizing Dose of about 12 krad, while working into a 1T magnetic field and a vacuum of 10 (-4) Torr. This harsh operational environment has made the electronics design challenging and required an extended campaign of tests to select and qualify the employed electronic components. In this paper we report on the board architecture and design, on the qualification of the prototypes, as well as on the results of the first vertical slice test of the Mu2e calorimeter.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗