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At least 127 records · Page 7

Classification of Reactor Facility Operational State Using SPRT Methods with Radiation Sensor Networks

We consider the problem of inferring the operational state of a reactor facility by using measurements from a radiation sensor network, which is deployed around the facility’s ventilation stack. The radiation emissions from the stack decay with distance, and the corresponding measurements are inherently random with parameters determined by radiation intensity levels at the sensor locations. We fuse measurements from network sensors to estimate the intensity at the stack, and use this estimate in a one-sided Sequential Probability Ratio Test (SPRT) to infer the on/off state of the reactor facility. We demonstrate the superior performance of this method over conventional majority vote fusers and individual sensors using (i) test measurements from a network of NaI sensors, and (ii) emulated measurements using radioactive effluents collected at a reactor facility stack. We analytically quantify the performance improvements of individual sensors and their networks with adaptive thresholds over those with fixed ones, by using the packing number of the radiation intensity space.

Ramirez Aviles, Camila A.↗

Smart sensor for online situational awareness in power grids

Waveforms in power grids typically reveal a certain pattern with specific features and peculiarities driven by the system operating conditions, internal and external uncertainties, etc. This prompts an observation of different types of waveforms at the measurement points (substations). An innovative next-generation smart sensor technology includes a measurement unit embedded with sophisticated analytics for power grid online surveillance and situational awareness. The smart sensor brings additional levels of smartness into the existing phasor measurement units (PMUs) and intelligent electronic devices (IEDs). It unlocks the full potential of advanced signal processing and machine learning for online power grid monitoring in a distributed paradigm. Within the smart sensor are several interconnected units for signal acquisition, feature extraction, machine learning-based event detection, and a suite of multiple measurement algorithms where the best-fit algorithm is selected in real-time based on the detected operating condition. Embedding such analytics within the sensors and closer to where the data is generated, the distributed intelligence mechanism mitigates the potential risks to communication failures and latencies, as well as malicious cyber threats, which would otherwise compromise the trustworthiness of the end-use applications in distant control centers. The smart sensor achieves a promising classification accuracy on multiple classes of prevailing conditions in the power grid and accordingly improves the measurement quality across the power grid.

Dehghanian, Payman↗

Thermoelectric Generator Powered Wireless Sensor Node Prototype for Nuclear Applications

This report presents the development a TEG-powered WSN prototype that could be used in nuclear applications. Different design considerations that are important in assembling different components of a WSN were carefully taken into consideration. In designed WSN is compatible to operate with low-power generating TEG and high-power generating TEG based on application requirements. Also, to maintain appropriate power level across different sensor node components, direct current-to-direct current converter with maximum peak power tracking algorithm is implemented. Storage device with real-time clock is embedded to enable local data storage and real-time time stamping. The wireless communication module selected and implemented is Zig Bee protocol. To accommodate different operating conditions and any loss of power from TEG due to unforeseen reasons, backup battery system is also implemented. Entire assembly is performed on a 2-layer printed circuit board and tested for operation. The outcome was successful and it also provided data to validate the mathematical model developed to estimate average power consumption of a WSN under different operating conditions.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Neutron irradiation and electrical characterisation of the first 8” silicon pad sensor prototypes for the CMS calorimeter endcap upgrade

As part of its HL-LHC upgrade program, the CMS collaboration is replacing its existing endcap calorimeters with a high-granularity calorimeter (CE). The new calorimeter is a sampling calorimeter with unprecedented transverse and longitudinal readout for both electromagnetic and hadronic compartments. Due to its compactness, intrinsic time resolution, and radiation hardness, silicon has been chosen as active material for the regions exposed to higher radiation levels. The silicon sensors are fabricated as 20 cm (8”) wide hexagonal wafers and are segmented into several hundred pads which are read out individually. As part of the sensor qualification strategy, 8” sensor irradiation with neutrons has been conducted at the Rhode Island Nuclear Science Center (RINSC) and followed by their electrical characterisation in 2020-21. The completion of this important milestone in the CE's R&D program is documented in this paper and it provides detailed account of the associated infrastructure and procedures.The results on the electrical properties of the irradiated CE silicon sensors are presented.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Fully depleted CMOS pixel sensor development and potential applications

CMOS pixel sensors are often opposed to hybrid pixel sensors due to their very different sensitive layer. In standard CMOS imaging processes, a thin (about 20 μm) low resistivity epitaxial layer acts as the sensitive volume and charge collection is mostly driven by thermal agitation. In contrast, the so-called hybrid pixel technology exploits a thick (typically 300 μm) silicon sensor with high resistivity allowing for the depletion of this volume, hence charges drift toward collecting electrodes. But this difference is fading away with the recent availability of some CMOS imaging processes based on a relatively thick (about 50 μm) high resistivity epitaxial layer which allows for full depletion. This evolution extents the range of applications for CMOS pixel sensors where their known assets, high sensitivity and granularity combined with embedded signal treatment, could potentially foster breakthrough in detection performances for specific scientific instruments. One such domain is the Xray detection for soft energies, typically below 10 keV, where the thin sensitive layer was previously severely impeding CMOS sensor usage. Another application becoming realistic for CMOS sensors, is the detection in environment with a high fluence of non-ionizing radiation, such as hadron colliders. However, when considering highly demanding applications, it is still to be proven that micro-circuits required to uniformly deplete the sensor at the pixel level, do not mitigate the sensitivity and efficiency required. Prototype sensors in two different technologies with resistivity higher than 1 kΩ, sensitive layer between 40 and 50 μm and featuring pixel pitch in the range 25 to 50 μm, have been designed and fabricated. Various biasing architectures were adopted to reach full depletion with only a few volts. Laboratory investigations with three types of sources (X-rays, β-rays and infrared light) demonstrated the validity of the approach with respect to depletion, keeping a low noise figure. Especially, an energy resolution of about 400 eV for 5 keV X-rays was obtained for single pixels. The prototypes have then been exposed to gradually increased fluences of neutrons, from 10{sup 13} to 5x10{sup 14} neq/cm{sup 2}. Again laboratory tests allowed to evaluate the signal over noise persistence on the different pixels implemented. Currently our development mostly targets the detection of soft X-rays, with the ambition to develop a pixel sensor matching counting rates as affordable with hybrid pixel sensors, but with an extended sensitivity to low energy and finer pixel about 25 x 25 μm{sup 2}. The original readout architecture proposed relies on a two tiers chip. The first tier consists of a sensor with a modest dynamic in order to insure low noise performances required by sensitivity. The interconnected second tier chip enhances the read-out speed by introducing massive parallelization. Performances reachable with this strategy combining counting and integration will be detailed. (authors)

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

ON-LINE MONITORING OF I&C TRANSMITTERS AND SENSORS FOR CALIBRATION VERIFICATION AND RESPONSE TIME TESTING WAS SUCCESSFULLY IMPLEMENTED AT ATR

The Advanced Test Reactor (ATR) has always had a comprehensive procedure to verify the performance of its critical transmitters and sensors, including RTDs, and pressure, level, and flow transmitters. These transmitters and sensors have been periodically tested for response time and calibration verification to ensure accuracy. With implementation of online monitoring techniques at ATR, the calibration verification and response time testing of these transmitters and sensors are verified remotely, automatically, hands off, include more portions of the system, and can be performed at almost any time during process operations. The work was done under a DOE funded SBIR project carried out by AMS. As a result, ATR is now able to save the manpower that has been spent over the years on manual calibration verification and response time testing of its temperature and pressure sensors and refocus those resources towards more equipment reliability needs. More importantly, implementation of OLM will help enhance the overall availability, safety, and efficiency. Together with equipment reliability programs of ATR, the integration of OLM will also help with I&C aging management goals of the Department of Energy and long-time operation of ATR.

47 OTHER INSTRUMENTATION↗

On-line monitoring of I and C transmitters and sensors for calibration verification and response time testing was successfully implemented at ATR - 326

The Advanced Test Reactor (ATR) has always had a comprehensive procedure to verify the performance of its critical transmitters and sensors, including RTDs, and pressure, level, and flow transmitters. These transmitters and sensors have been periodically tested for response time and calibration verification to ensure accuracy. With implementation of on-line monitoring techniques at ATR, the calibration verification and response time testing of these transmitters and sensors are verified remotely, automatically, hands off, include more portions of the system, and can be performed at almost any time during process operations. The work was done under a DOE funded SBIR project carried out by AMS. As a result, ATR is now able to save the manpower that has been spent over the years on manual calibration verification and response time testing of its temperature and pressure sensors and refocus those resources towards more equipment reliability needs. More importantly, implementation of OLM will help enhance the overall availability, safety, and efficiency. Together with equipment reliability programs of ATR, the integration of OLM will also help with I and C aging management goals of the Department of Energy and long-time operation of ATR. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

System and method for controlling ammonia levels in a selective catalytic reduction catalyst using a nitrogen oxide sensor

A system according to the principles of the present disclosure includes an air/fuel ratio determination module and an emission level determination module. The air/fuel ratio determination module determines an air/fuel ratio based on input from an air/fuel ratio sensor positioned downstream from a three-way catalyst that is positioned upstream from a selective catalytic reduction (SCR) catalyst. The emission level determination module selects one of a predetermined value and an input based on the air/fuel ratio. The input is received from a nitrogen oxide sensor positioned downstream from the three-way catalyst. The emission level determination module determines an ammonia level based on the one of the predetermined value and the input received from the nitrogen oxide sensor.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Analysis of the failures and corrective actions for the LHC cryogenics radiation tolerant electronics and its field instruments

The LHC cryogenic system radiation tolerant electronics and their associated field instruments have been in nominal conditions since before the commissioning of the first LHC beams in September 2008. This system is made of about 15’000 field instruments (thermometers, pressure sensors, liquid helium level gauges, electrical heaters and position switches), 7’500 electronic cards and 853 electronic crates. Since mid-2008 a software tool has been deployed, this allows an operator to report a problem and then lists the corrective actions. The tool is a great help in detecting recurrent problems that may be tackled by a hardware or software consolidation. The corrective actions range from simple resets, exchange of defective equipment, repair of electrical connectors, etc. However a recurrent problem that heals by itself is present on some channels. This type of fault is extremely difficult to diagnose and it appears as a temporary opening of an electrical circuit; its duration can range from a few minutes to several months. This paper presents the main type of problems encountered during the last four years, their evolution over time, the various hardware or software consolidations that have resulted and whether they have had an impact in the availability of the LHC beam.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Dynamic Tuning of Seismic Signal Detector Trigger Levels for Local Networks

The quality of automatic signal detections from sensor networks depends on individual detector trigger levels (TLs) from each sensor. The largely manual process of identifying effective TLs is painstaking and does not guarantee optimal configuration settings, yet achieving superior automatic detection of signals and ultimately, events, is closely related to these parameters. In this paper, we present a Dynamic Detector Tuning (DDT) system that automatically adjusts effective TL settings for signal detectors to the current state of the environment by leveraging cooperation within a local neighborhood of network sensors. After a stabilization period, the DDT algorithm can adapt in near-real time to changing conditions and automatically tune a signal detector to identify (detect) signals from only events of interest. Our current work focuses on reducing false signal detections early in the seismic signal processing pipeline, which leads to fewer false events and has a significant impact on reducing analyst time and effort. This system provides an important new method to automatically tune detector TLs for a network of sensors and is applicable to both existing sensor performance boosting and new sensor deployment. Finally, with ground truth on detections from a local neighborhood of seismic sensors within a network monitoring the Mount Erebus volcano in Antarctica, we show that DDT reduces the number of false detections by 18% and the number of missed detections by 11% when compared with optimal fixed TLs for all sensors.

58 GEOSCIENCES↗

Utilizing Geo-located Sensors and Social Media for Studying Population Dynamics and Land Classification

The ability to understand where, when, and why humans move across space and time has always been essential to research areas such as urban planning, transportation, population dynamics, and emergency preparedness and response. The increasing sources of activity data is generating novel opportunities to understand human dynamics that previously was not possible; Geo-located user generated content from mobile devices and sensors allow a level of spatial and temporal granularity that could possibly answer the reasons for human movement at a high-resolution. This work discusses a broad array of research agenda in human dynamics and land use by proposing an explicit model that assists in delineating and articulating the opportunities, challenges, and limitations of using new forms of unauthoritated data, such as social media in main-stream GIS research. We study mobile phone call volume and GPS locations to characterize human activity patterns and provide inference on land use. Later, we demonstrate the ability of geo-located social media posts to provide insight on population density estimates for special events and Points of Interest detection. The chapter underpins the need to utilize new forms of data collection mechanism as well as their use to augment our understanding of human dynamics research and future application of geographical information systems.

Thakur, Gautam Malviya↗

Engineering uranyl-chelating peptides from NikR for electrochemical peptide-based sensing applications

We have, for the first time, designed three uranyl-chelating peptides by modeling after the uranyl binding pocket found in a mutated Ni(II)-dependent transcriptional repressor (NikR). All three thiolated and methylene blue (MB)-modified peptides, NikR-5, NikR-11, and NikR-15, contain the five core amino acids responsible for target recognition, but the two longer peptides have either one or two additional glycine residues in between the five amino acids. These three peptide probes were then used in the fabrication of electrochemical peptide-based (E-PB) uranyl ion (U(VI)) sensors, with the goal of elucidating the effects of the added glycine residues and probe flexibility on target recognition. The sensing mechanism is similar to other “signal-off” E-PB sensors, in which binding of the target rigidifies the probe, resulting in a decrease in the redox signal from the tethered MB label. Although all three sensors responded to U(VI), the NikR-15 sensor's behavior was irreproducible and thus precluded from the rest of the study. The NikR-11 sensor showed the largest response to U(VI), whereas the NikR-5 sensor showed higher specificity for U(VI). The limit of detection was 50 nM for both sensors, which is well below the U.S. Environmental Protection Agency maximum contaminant level for uranium. Both sensors were further tested and proven functional in a 50% synthetic aquifer sample. Overall, the NikR-11 sensor, fabricated with the 11-amino acid probe, is deemed the optimal design. Incorporating glycine residues is a strategic way to lengthen the peptide slightly to improve target binding. This simple yet versatile approach to recreating binding pockets on electrode surfaces can potentially be employed in the design of other E-PB and surface-based metal ion sensors.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Adsorption Behavior of Organic Molecules: A Study of Benzotriazole on Cu(111) with Spectroscopic and Theoretical Methods

The adsorption of organic molecules on solid substrates is important to applications in fields such as catalysis, photovoltaics, corrosion inhibition, adhesion, and sensors. The molecular level description of the surface–molecule interaction and of the adsorption structures in these complex systems is crucial to understand their properties and function. Here, we present an investigation of one such system, benzotriazole (BTAH) on single-crystal Cu(111) in vacuum conditions. BTAH is the most widely used corrosion inhibitor for copper and thus a molecule of great industrial relevance. We show that the co-application of a wide range of spectroscopic techniques with theoretical methods provides unique insight in the description of the atomistic details of the adsorbed structures. Specifically, spectroscopic photoemission, absorption, and standing wave experiments combined with ab initio computational modeling allowed us to identify that benzotriazole forms overlayers of intact BTAH when deposited at low temperature, and it dissociates into BTA and H at room temperature and above. The dissociated molecule then forms complex structures of mixed chains and dimers of BTA bound to copper adatoms. Our work also reveals that copper adatoms at low concentrations, such as the theoretically predicted superstructures, cannot be resolved by means of current X-ray photoelectron spectroscopy as the modeled Cu 2p spectra are practically indistinguishable from those for a Cu surface without adatoms. Overall this study significantly deepens understanding of BTAH on Cu, a system studied for more than 50 years, and it highlights the benefits of combining spectroscopic and computational methods to obtain a complete picture of a complex adsorption system.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Utah FORGE: Sanvean Technologies Drilling Data from Well 16B(78)-32

Included here is Sanvean Technologies bit sensor data amalgamated with data from National Oilwell Varco's (NOV) BlackBox tool for Reed Hycalog bits used during drilling of Well 16B(78)-32. The dataset contains information collected at the bit while drilling including rate of penetration (ROP), top drive torque, and bit box temperature. The data was recorded at the bit box and top sub of the motor. RPM was measured by onboard gyro recording continuously in each sensor, and shock levels were also recorded on X, Y and Z axis. This data was merged with EDR in time format and saved in file sets (the zipped files) then output into CSV files. Please note: fields in the CSV files, such as the date field, may need to be formatted to display properly. There is an additional zipped folder in each dataset that is password protected. Sanvean GameChanger Viewer software must be used to view this password protected data. Information on how to use and download this free software is also included here.

15 GEOTHERMAL ENERGY↗

Camp Fire processed Landsat 8 images, pre-fire, during-fire, post-fire

The Camp Fire rapidly spread across a landscape in Butte County, California, toward the city of Paradise in the early morning hours of 8 November 2018. GEE acquires L8 data products from USGS that include Real-Time Tier 1 DN values, representing scaled, calibrated at-sensor radiance, and Level-1 Precision Terrain (L1TP) processing. We carried out additional processing on the pre- and post-fire images, including an illumination correction to account for effects of steep topography, and radiometric normalization to ensure homogeneity between images. We also identified and processed high-quality images for both the pre-fire condition(25 Oct 2013), and the post-fire burn scar (26 Dec 2018). Using the tools we provided in the paper, we estimate that, over the first hour, the Camp Fire was consuming ~200 ha/minute of vegetation with a linear spread rate of 14 km over the fire’s first 25 minutes, or ~33km/hr. We briefly discuss broader use of remote sensing and geospatial analysis for fire research and risk management. A visualization app (sliderApp) that includes pre-fire, active fire, and post-fire images: https://caralyngorman.users.earthengine.app/view/camp-fire-sliding-map-3-9-19

54 ENVIRONMENTAL SCIENCES↗

AmeriFlux US-MWW Allegan Wetland

This is the AmeriFlux version of the carbon flux data for the site US-MWW Allegan Wetland. Site Description - Privately owned and managed wetland along the Rabbit River, a tributary to the Kalamazoo River. Land owner controls water level at site. Sensors are at the edge of open water and emergent vegetation, with wet forests surrounding the wetland. Site was chosen to represent managed wetlands along the Kalamazoo River watershed.

Chen, Jiquan↗