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At least 343 records · Page 19

Frequency‐Locked Wireless Multifunctional Surface Acoustic Wave Sensors

Abstract Surface acoustic waves (SAWs) have shown great potential for developing sensors for structural health monitoring (SHM) and lab‐on‐a‐chip (LOC) applications. Existing SAW sensors mainly rely on measuring the frequency shifts of high‐frequency (e.g., >0.1 GHz) resonance peaks. This study presents frequency‐locked wireless multifunctional SAW sensors that enable multiple wireless sensing functions, including strain sensing, temperature measurement, water presence detection, and vibration sensing. These sensors leverage SAW resonators on piezoelectric chips, inductive coupling‐based wireless power transmission, and, particularly, a frequency‐locked wireless sensing mechanism that works at low frequencies (e.g., <0.1 GHz). This mechanism locks the input frequency on the slope of a sensor's reflection spectrum and monitors the reflection signal's amplitude change induced by the changes of sensing parameters. The proof‐of‐concept experiments show that these wireless sensors can operate in a low‐power active mode for on‐demand wireless strain measurement, temperature sensing, and water presence detection. Moreover, these sensors can operate in a power‐free passive mode for vibration sensing, with results that agree well with laser vibrometer measurements. It is anticipated that the designs and mechanisms of the frequency‐locked wireless SAW sensors will inspire researchers to develop future wireless multifunctional sensors for SHM and LOC applications.

Bo, Luyu↗

Advanced ceramic components with embedded sapphire optical fiber sensors for high temperature applications

Here this paper describes an extrusion-based additive manufacturing process that has been developed to enable embedment of sapphire optical fiber sensors in ceramic components during the part fabrication. In this process, an aqueous paste of ceramic particles is extruded through a moving nozzle to build the part layer-by-layer. In the case of sensor embedment, the fabrication process is halted after a certain number of layers have been deposited; the sensors are placed in their predetermined locations, and the remaining layers are deposited until the part fabrication is completed. Because the sensors are embedded during the fabrication process, they are fully integrated with the part and the problems of traditional sensor embedment can be eliminated. Scanning electron microscopy was used to observe the embedded sensors and to detect any possible flaws in the part or embedded sensor. Attenuation of the sensors was measured in near-infrared region (1500–1600 nm wavelength). Standard test methods were employed to examine the effect of embedded fibers on the strength and hardness of the parts. The results indicated that the sapphire fiber sensors with diameters smaller than 250 micrometers were able to endure the freeform extrusion fabrication process and the post-processing without compromising the part properties.

36 MATERIALS SCIENCE↗

Design of the first full size ATLAS ITk strip sensor for the endcap region

The ATLAS collaboration is designing the all-silicon Inner Tracker (ITk) that will operate in the HL-LHC replacing the current design. The silicon microstrip sensors for the barrel and the endcap regions in the ITk are fabricated in 6 inch, p-type, float-zone wafers, where large-area strip sensor designs are laid out together with a number of miniature sensors. The radiation tolerance and specific system issues like the need for slim edge of 450 μm have been tested with square shaped sensors intended for the barrel part of the tracker. This work presents the design of the first full size silicon microstrip sensor for the endcap region with a slim edge of 450 μm. The strip endcaps will consist of several wheels with two layers of silicon strip sensors each. The strips have to lie along the azimuthal direction, apart from a small stereo angle rotation (20 mrad on each side, giving 40 mrad total) for measuring the second coordinate of tracks. This stereo angle is built into the strip layout of the sensor and, in order to avoid orphan strips, the sensor edges are inclined by the stereo angle. On top of this, the top and bottom edges are designed as arcs to have equal length strips. Together with the design of this new Stereo Annulus sensor, we will report on the initial measurements of the leakage current as a function of bias voltage, after dicing, and the depletion voltage.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Results for pixel and strip centimeter-scale AC-LGAD sensors with a 120 GeV proton beam

Here, we present the results of an extensive evaluation of strip and pixel AC-LGAD sensors tested with a 120 GeV proton beam, focusing on the influence of design parameters on the sensor temporal and spatial resolutions. Results show that reducing the thickness of pixel sensors significantly enhances their time resolution, with 20-μm-thick sensors achieving around 20 ps. Uniform performance is attainable with optimized n + sheet resistance, making these sensors ideal for future timing detectors. Conversely, 20-μm-thick strip sensors exhibit higher jitter than similar pixel sensors, negatively impacting time resolution, despite reduced Landau fluctuations with respect to the 50-μm-thick versions. Additionally, it is observed that a low resistivity in strip sensors limits signal size and time resolution, whereas higher resistivity improves performance. This study highlights the importance of tuning the n+ sheet resistance and suggests that further improvements should target specific applications like the Electron–Ion Collider or other future collider experiments. In addition, the detailed performance of four AC-LGADs sensor designs is reported as examples of possible candidates for specific detector applications. These advancements position AC-LGADs as promising candidates for future 4D tracking systems, pending the development of specialized readout electronics.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Global field reconstruction from sparse sensors with Veronoi tessellation-assisted deep learning

Achieving accurate and robust global situational awareness of a complex time-evolving field from a limited number of sensors has been a longstanding challenge. This reconstruction problem is especially difficult when sensors are sparsely positioned in a seemingly random or unorganized manner, which is often encountered in a range of scientific and engineering problems. Moreover, these sensors can be in motion and can become online or offline over time. The key leverage in addressing this scientific issue is the wealth of data accumulated from the sensors. As a solution to this problem, we propose a data-driven spatial field recovery technique founded on a structured grid-based deep-learning approach for arbitrary positioned sensors of any numbers. It should be noted that the naïve use of machine learning becomes prohibitively expensive for global field reconstruction and is furthermore not adaptable to an arbitrary number of sensors. In the present work, we consider the use of Voronoi tessellation to obtain a structured-grid representation from sensor locations enabling the computationally tractable use of convolutional neural networks. One of the central features of the present method is its compatibility with deep-learning based super-resolution reconstruction techniques for structured sensor data that are established for image processing. The proposed reconstruction technique is demonstrated for unsteady wake flow, geophysical data, and three-dimensional turbulence. The current framework is able to handle an arbitrary number of moving sensors, and thereby overcomes a major limitation with existing reconstruction methods. The presented technique opens a new pathway towards the practical use of neural networks for real-time global field estimation.

Fukami, Kai↗

Specifications and pre-production of n + -in-p large-format strip sensors fabricated in 6-inch silicon wafers, ATLAS18, for the Inner Tracker of the ATLAS Detector for High-Luminosity Large Hadron Collider

Abstract The ATLAS experiment is constructing new all-silicon inner tracking system for HL-LHC. The strip detectors cover the radial extent of 40 to 100 cm. A new approach is adopted to use p-type silicon material, making the readout in n + -strips, so-called n + -in-p sensors. This allows for enhanced radiation tolerance against an order of magnitude higher particle fluence compared to the LHC. To cope with varying hit rates and occupancies as a function of radial distance, there are two barrel sensor types, the short strips (SS) for the inner 2 and the long strips (LS) for the outer 2 barrel cylinders, respectively. The barrel sensors exhibit a square, 9.8 × 9.8 cm 2 , geometry, the largest possible sensor area from a 6-inch wafer. The strips are laid out in parallel with a strip pitch of 75.5 μm and 4 or 2 rows of strip segments. The strips are AC-coupled and biased via polysilicon resistors. The endcap sensors employ a “stereo-annulus” geometry exhibiting a skewed-trapezoid shapes with circular edges. They are designed in 6 unique shapes, R0 to R5, corresponding to progressively increasing radial extents and which allows them to fit within the petal geometry and the 6-inch wafer maximally. The strips are in fan-out geometry with an in-built rotation angle, with a mean pitch of approximately 75 μm and 4 or 2 rows of strip segments. The eight sensor types are labeled as ATLAS18xx where xx stands for SS, LS, and R0 to R5. According to the mechanical and electrical specifications, CAD files for wafer processing were laid out, following the successful designs of prototype barrel and endcap sensors, together with a number of optimizations. A pre-production was carried out prior to the full production of the wafers. The quality of the sensors is reviewed and judged excellent through the test results carried out by vendor. These sensors are used for establishing acceptance procedures and to evaluate their performance in the ATLAS collaboration, and subsequently for pre-production of strip modules and stave and petal structures.

Instruments & Instrumentation↗

Using Bayesian Inference Framework towards Identifying Gas Species and Concentration from High Temperature Resistive Sensor Array Data

High temperature gas sensors have been highly demanded for combustion process optimization and toxic emissions control, which usually suffer from poor selectivity. In order to solve this selectivity issue and identify unknown reducing gas species (CO, CH 4 , and CH 8 ) and concentrations, a high temperature resistive sensor array data set was built in this study based on 5 reported sensors. As each sensor showed specific responses towards different types of reducing gas with certain concentrations, based on which calibration curves were fitted, providing benchmark sensor array response database, then Bayesian inference framework was utilized to process the sensor array data and build a sample selection program to simultaneously identify gas species and concentration, by formulating proper likelihood between input measured sensor array response pattern of an unknown gas and each sampled sensor array response pattern in benchmark database. This algorithm shows good robustness which can accurately identify gas species and predict gas concentration with a small error of less than 10% based on limited amount of experiment data. These features indicate that Bayesian probabilistic approach is a simple and efficient way to process sensor array data, which can significantly reduce the required computational overhead and training data.

Liu, Yixin↗

Temporal Study 2021-2022: Sensor-Based Time Series of Surface Water Temperature, Specific Conductance, Total Dissolved Solids, Turbidity, pH, and Dissolved Oxygen from across Multiple Watersheds in the Yakima River Basin in Washington, USA (v2)

This dataset supports a broader study examining the drivers of temporal variability in sediment respiration rates in the Yakima River Basin. The dataset provides periodic (weekly or biweekly) in situ hydrological and water chemistry sensor data, handheld sensor water chemistry data, general environmental context photos, and field metadata collected at six sites within multiple rivers in the Yakima River Basin in Washington, USA. In addition to the sensor data, there are plots of continuous in situ sensor data and R scripts used to generate the plots. Related sample-based water chemistry data are published separately at https://data.ess-dive.lbl.gov/datasets/doi:10.15485/1898912.The data package was originally published in September 2022. It was updated in June 2025 (v2; modified files). See the change history section in the readme for more details. For details on how to navigate data packages generated by this project, see https://data.ess-dive.lbl.gov/portals/PNNLRiverCorridorSFA/About. This dataset is comprised of one main data folder containing two sensor-specific subfolders, and one photographs folder. The main data folder includes file-level metadata (flmd), data dictionary (dd), installation methods, field metadata, handheld sensor data, field data collection protocols, international generic sample number (IGSN) mapping file, and a readme file. Each sensor subfolder (BarotrollAtm and MantaRiverData) contains a subfolder containing sensor timeseries data and plots. The BarotrollAtm Data subfolder contains In Situ Rugged BaroTROLL sensor pressure and air temperature data. The MantaRiverData subfolder contains Eureka Manta+ 35B multisonde temperature, specific conductance, and turbidity. The FieldPhotos folder contains environmental context photographs and videos. All files are .csv, .pdf, .R, .jpg, .jpeg, .heic, .mov, or .mp4.

54 ENVIRONMENTAL SCIENCES↗

Online, In-Situ Monitoring Combustion Turbines Using Wireless Passive Ceramic Sensors

The overall objective of this project is to develop high-temperature wireless passive ceramic sensors for online, real-time monitoring combustion turbines. During this project period, we have successfully demonstrated temperature sensors up to 1300°C and pressure sensors up to 800°C. The temperature sensor is based on a high-Q-factor dielectric resonator and the pressure sensor utilizes the evanescent-mode cavity to realize a pressure-sensitive high-Q-factor resonator. Both sensors are efficiently integrated with a compact antenna. These sensors are wirelessly interrogated. The resonant frequency change corresponding to either temperature or pressure can be identified using a time-domain gating technique. The sensors realized in this project can survive harsh environments characterized by high temperatures (>1000°C) and corrosive gases, owing to the excellent material properties of polymer-derived ceramics (PDCs) developed at University of Central Florida. It is anticipated that this work will significantly advance the capability of high-temperature sensor technologies and be of a great benefit to turbine industry and their customers.

47 OTHER INSTRUMENTATION↗

An Introduction to LANL Mixed Potential Sensors

These are slides for a webinar given on the topics of an introduction to LANL mixed potential sensors. Topics include the history of LANL electrochemical sensor work, an introduction to mixed potential sensors, LANL uniqueness, and an application of LANL mixed potential sensors. The summary is as follows: Improved understanding of the mixed-potential sensor mechanism (factors controlling the sensor response identified), sensor design optimized to maximize sensor sensitivity and durability (porous electrolyte/dense electrodes), electrodes selected for various specific applications (CO, HC, H 2 ), sensor operating parameters optimized for improved gas selectivity (NO x , NH 3 ).

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Development and Testing of Prototype Commercial Gasifier Sensor

This report presents the results of the sensor development and testing at the Wabash River gasifier. The project work was initiated with modification of the sensor software (Task 2) to enable real time temperature data acquisition, and to process and provide the obtained gasifier temperature information to the gasifier operators. The software modifications were conducted by the North Carolina State University (NCSU) researchers. The modified software was tested at the Gas Technology Institute (GTI) combustion laboratory to assess the temperature recognition algorithm accuracy and repeatability. Task 3 was focused on the sensor hardware modifications needed to improve reliability of the sensor system. NCSU conducted numerical modeling of the sensor probe’s purging flow. Based on the modeling results the probe purging system was redesigned to prevent carbon particulates deposition on the probe’s sapphire window. The modified design was evaluated and approved by the Wabash representative. The modified gasifier sensor was built and installed at the Wabash River gasifier on May 1 2014. (Task 4) The sensor was tested from the startup of the gasifier on May 5, 2015 until the planned autumn gasifier outage starting in the beginning of October, 2015. (Task 5) The project team successfully demonstrated the Gasifier Sensor system’s ability to monitor gasifier temperature while maintaining unobstructed optical access for six months without any maintenance. The sensor examination upon completion of the trial revealed that the system did not sustain any damage.

47 OTHER INSTRUMENTATION↗

NDE Technology Development Program for Hanford DST Non-Visual Volumetric Inspection Technology – Phase II; Technical Letter Report on Air-slot NDE Sensor Maturation Testing

The Pacific Northwest National Laboratory (PNNL) located in Richland, Washington, hosted and administered Phase II Flaw Detection Performance Tests in August 2018 that allowed the newly matured ultrasonic guided wave phased-array (GWPA) air-slot NDE sensor—“Hanford-Probe A”—developed by Guidedwave to be evaluated for its flaw detection capability and repeatability. A portion of the Phase II Flaw Detection Performance Tests was performed on a subset of test flaws on which the original GWPA sensor was evaluated during Phase I Sensor Effectiveness Testing (SET) to facilitate a comparison in flaw detection performance between Hanford-Probe A and the original GWPA sensor demonstrated in Phase I. The objective of the performance comparison was to determine the extent to which GWPA sensor design changes impacted the flaw detection performance upon which selection of the sensor technology was originally based for the purpose of determining whether the flaw detection performance of the newly matured Hanford-Probe A GWPA air-slot NDE sensor is at least equal to that of the original GWPA sensor evaluated under Phase I SET. This technical letter report presents the results produced by the new Hanford-Probe A on the Phase I test flaws and the results of the flaw detection performance comparison between Hanford-Probe A and the original GWPA sensor demonstrated in Phase I.

47 OTHER INSTRUMENTATION↗

Performance Evaluation of Comparative Vacuum Monitoring and Piezoelectric Sensors for Structural Health Monitoring of Rotorcraft Components

The costs associated with the increasing maintenance and surveillance needs of aging structures are rising at an unexpected rate. Multi-site fatigue damage, hidden cracks in hard-to-reach locations, disbonded joints, erosion, impact, and corrosion are among the major flaws encountered in today’s extensive fleet of aging aircraft and space vehicles. Aircraft maintenance and repairs represent about a quarter of a commercial fleet’s operating costs. The application of Structural Health Monitoring (SHM) systems using distributed sensor networks can reduce these costs by facilitating rapid and global assessments of structural integrity. The use of in-situ sensors for real-time health monitoring can overcome inspection impediments stemming from accessibility limitations, complex geometries, and the location and depth of hidden damage. Reliable, structural health monitoring systems can automatically process data, assess structural condition, and signal the need for human intervention. The ease of monitoring an entire on-board network of distributed sensors means that structural health assessments can occur more often, allowing operators to be even more vigilant with respect to flaw onset. SHM systems also allow for condition-based maintenance practices to be substituted for the current time-based or cycle-based maintenance approach thus optimizing maintenance labor. The Federal Aviation Administration has conducted a series of SHM validation and certification programs intended to comprehensively support the evolution and adoption of SHM practices into routine aircraft maintenance practices. This report presents one of those programs involving a Sandia Labs-aviation industry effort to move SHM into routine use for aircraft maintenance. The Airworthiness Assurance NDI Validation Center (AANC) at Sandia Labs, in conjunction with Sikorsky, Structural Monitoring Systems Ltd., Anodyne Electronics Manufacturing Corp., Acellent Technologies Inc., and the Federal Aviation Administration (FAA) carried out a trial validation and certification program to evaluate Comparative Vacuum Monitoring (CVM) and Piezoelectric Transducers (PZT) as a structural health monitoring solution to specific rotorcraft applications. Validation tasks were designed to address the SHM equipment, the health monitoring task, the resolution required, the sensor interrogation procedures, the conditions under which the monitoring will occur, the potential inspector population, adoption of CVM and PZT systems into rotorcraft maintenance programs and the document revisions necessary to allow for their routine use as an alternate means of performing periodic structural inspections. This program addressed formal SHM technology validation and certification issues so that the full spectrum of concerns, including design, deployment, performance and certification were appropriately considered. Sandia Labs designed, implemented, and analyzed the results from a focused and statistically relevant experimental effort to quantify the reliability of a CVM system applied to Sikorsky S-92 fuselage frame application and a PZT system applied to an S-92 main gearbox mount beam application. The applications included both local and global damage detection assessments. All factors that affect SHM sensitivity were included in this program: flaw size, shape, orientation and location relative to the sensors, as well as operational and environmental variables. Statistical methods were applied to performance data to derive Probability of Detection (POD) values for SHM sensors in a manner that agrees with current nondestructive inspection (NDI) validation requirements and is acceptable to both the aviation industry and regulatory bodies. The validation work completed in this program demonstrated the ability of both CVM and PZT SHM systems to detect cracks in rotorcraft components. It proved the ability to use final system response parameters to provide a Green Light/Red Light (“GO” – “NO GO”) decision on the presence of damage. In additional to quantifying the performance of each SHM system for the trial applications on the S-92 platform, this study also identified specific methods that can be used to optimize damage detection, guidance on deployment scenarios that can affect performance and considerations that must be made to properly apply CVM and PZT sensors. These results support the main goal of safely integrating SHM sensors into rotorcraft maintenance programs. Additional benefits from deploying rotorcraft Health and Usage Monitoring Systems (HUMS) may be realized when structural assessment data, collected by an SHM system, is also used to detect structural damage to compliment the operational environment monitoring. The use of in-situ sensors for health monitoring of rotorcraft structures can be a viable option for both flaw detection and maintenance planning activities. This formal SHM validation will allow aircraft manufacturers and airlines to confidently make informed decisions about the proper utilization of CVM and PZT technology. It will also streamline future regulatory actions and formal certification measures needed to assure the safe application of SHM solutions.

42 ENGINEERING↗

Integration of Wireless Sensor Networks and Battery-free RFID for Advanced Reactors

To address an important need for Nuclear Power Plants (NPPs) to significantly reduce the amount of the required cables for sensor data communications, this Phase I SBIR effort successfully developed and demonstrated a novel low-cost proof-of-concept prototype of a secure wireless sensor network backbone communications system. This system combines commercially available low power, low cost XBEE wireless communications network and passive (battery-free) Radio Frequency Identification (RFID) systems to report individual sensor data and their location through the containment wall for rapid response to anomalies in nuclear facilities. This WIreless Sensing and Locating (WISLO) system network architecture allows non-intrusive wireless collection of sensor data with the sensor’s accurate location information from inside of the instrumentation or containment area with minimal need for power sources. The multi-node sensor data in the containment area is wirelessly transmitted to outside through the metal reinforced concrete walls without the need for any batteries. The WISLO system could be readily used in current reactor fleet and future advanced reactors, as well as in small modular reactors (SMR). The WISLO system is the first dual frequency battery-free trough the wall communications backbone system developed specifically for use in nuclear power plants. It not only can modernize the sensor monitoring practices in the existing reactor fleet, but also offers a secure, low-cost solution to advanced reactors and SMRs by removing cables and issues related to them such as cable integrity, reporting delays, and installation and maintenance costs. The intent is to improve process safety, reliability, efficiency, and cost effectiveness to the monitoring and maintenance process in current and future plants. As we address the next productization and manufacturing capabilities in the next phase, this system will serve the needs of many commercial and government applications in remote monitoring of sensor data that demand battery-free transmission of sensor data such as Internet-of-Things (IOT).

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Performance of Pixel and Strip AC-LGAD Sensors with Different Design Parameter on a 120 GeV Proton Beam

We present the results of an extensive evaluation of strip and pixel AC-LGAD sensors tested with a 120 GeV proton beam, focusing on the influence of design parameters on the sensor temporal and spatial resolutions. Results show that reducing the thickness of pixel sensors significantly enhances their time resolution, with 20- μm-thick sensors achieving around 20 ps. Uniform performance is attainable with optimized sheet resistance, making these sensors ideal for future timing detectors. Conversely, 20-μm-thick strip sensors exhibit higher jitter than similar pixel sensors, negatively impacting time resolution, despite reduced Landau fluctuations with respect to the 50-μm-thick versions. Additionally, it is observed that a low resistivity in strip sensors limits signal size and time resolution, whereas higher resistivity improves performance. This study highlights the importance of tuning the n+ sheet resistance and suggests that further improvements should target specific applications like the Electron-Ion Collider or other future collider experiments. In addition, the detailed performance of four AC-LGADs sensor designs is reported as examples of possible candidates for specific detector applications. These advancements position AC-LGADs as promising candidates for future 4D tracking systems, pending the development of specialized readout electronics.

Lara, Carlos Pérez↗

Precision Agriculture using Networks of Degradable Analytical Sensors (PANDAS) (Final Technical Report)

Precision agriculture, where sensing of soil, environment and crop conditions are used to precisely synchronize inputs (such as water and fertilizer) to crop needs enhances input use efficiency. This can improve yields and farm profitability while mitigating environmental losses, improving soil carbon content and substantially decreasing energy use for food, feed and fuel crops. Unfortunately, farmers are not yet able to harness the full potential of these management technologies as there is a lack of available management information, and there is therefore a need for sensors that are able to economically measure spatio-temporal variability in soil and crop properties of extremely heterogeneous farm fields precisely at high resolution and at low cost. Real-time, in-situ monitoring of agricultural soil conditions is today carried out using devices that limit the total number of nodes that can be used economically to typically one per acre or less. Higher spatio-temporal resolution sensing would enable more precise agricultural input optimization, with significant benefits to the farmer and the environment. In order to address this issue, this project focused on developing additively manufactured, biodegradable, soil sensors with predicted costs of < $\$$1 per unit to monitor crop inputs (such as water and fertilizer) that predictably, harmlessly degrade away into the soil when no longer needed. These sensor nodes should be easy to place, accurately and continuously monitor soil and crop conditions for an entire season, be read remotely using existing farm equipment, require no ongoing maintenance, not impede farm operations and produce no persistent waste. This approach could enable a >100× increase in information density over current solutions for precision farming of row and other crops, and lead to significant reductions in input energy use and provide increased yield for biofuel crops. Over the course of this project the team at the University of Colorado Boulder, University of California Berkeley, and Colorado State University/Kansas State University investigated a wide range of printable biodegradable electronic materials and sensor designs for determining soil moisture and soil nitrate concentration. These efforts expanded the available materials set for printed soil degradable electronic materials, particularly for conductors, enabling high conductivity and stability. Printed soil moisture and nitrate sensors with suitable sensitivity and selectivity were developed and characterized. Low power and passive wireless electronic systems were integrated with the soil sensors, and testing was carried out with completed sensors to understand their functionality under agricultural conditions. Additionally, other sensor types enabled by the biodegradable materials set created during this project, such as soil microbial activity sensors, were also developed and demonstrated. Project outputs include 10 peer reviewed publications, 4 patent applications, 21 technical presentations, 3 PhD thesis, 10 media reports, 8 additional grants worth over $\$$6M, and the formation of 3 start-up companies.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Extending Sensor Calibration Intervals in Nuclear Power Plants

Currently in the USA, sensor recalibration is required at every refueling outage, and it has emerged as a critical path item for shortening outage duration. International application of calibration monitoring, such as at the Sizewell B plant in UK, has shown that sensors may operate for eight years, or longer, within calibration tolerances. Online monitoring can be employed to identify those sensors which require calibration, allowing for calibration of only those sensors which need it. The US NRC accepted the general concept of online monitoring for sensor calibration monitoring in 2000, but no plants have been granted the necessary license amendment to apply it. This project addresses key issues in advanced recalibration methodologies and provides the science base to enable adoption of best practices for applying online monitoring, resulting in a public domain standardized methodology for sensor calibration interval extension. Research to develop this methodology will focus on three key areas: (1) quantification of uncertainty in modeling techniques used for calibration monitoring, with a particular focus on non-redundant sensor models; (2) accurate determination of acceptance criteria and quantification of the effect of acceptance criteria variability on system performance; and (3) the use of virtual sensor estimates to replace identified faulty sensors to extend operation to the next convenient maintenance opportunity.

Calibration Extension↗

Electron beam diagnostic system using computed tomography and an annular sensor

A system for analyzing an electron beam including a circular electron beam diagnostic sensor adapted to receive the electron beam, the circular electron beam diagnostic sensor having a central axis; an annular sensor structure operatively connected to the circular electron beam diagnostic sensor, wherein the sensor structure receives the electron beam; a system for sweeping the electron beam radially outward from the central axis of the circular electron beam diagnostic sensor to the annular sensor structure wherein the electron beam is intercepted by the annular sensor structure; and a device for measuring the electron beam that is intercepted by the annular sensor structure.

47 OTHER INSTRUMENTATION↗