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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

Effects of electrostatic discharge on three cryogenic temperature sensor models

Cryogenic temperature sensors are not usually thought of as electrostatic discharge (ESD) sensitive devices. However, the most common cryogenic thermometers in use today are thermally sensitive diodes or resistors - both electronic devices in their base form. As such, they are sensitive to ESD at some level above which either catastrophic or latent damage can occur. Instituting an ESD program for safe handling and installation of the sensor is costly and it is desirable to balance the risk of ESD damage against this cost. However, this risk cannot be evaluated without specific knowledge of the ESD vulnerability of the devices in question. This work examines three types of cryogenic temperature sensors for ESD sensitivity - silicon diodes, Cernox(trade mark, serif) resistors, and wire wound platinum resistors, all manufactured by Lake Shore Cryotronics, Inc. Testing was performed per TIA/EIA FOTP129 (Human Body Model). Damage was found to occur in the silicon diode sensors at discharge levels of 1,500 V. For Cernox(trade mark, serif) temperature sensors, damage was observed at 3,500 V. The platinum temperature sensors were not damaged by ESD exposure levels of 9,900 V. At the lower damage limit, both the silicon diode and the Cernox(trade mark, serif) temperature sensors showed relatively small calibration shifts of 1 to 3 K at room temperature. The diode sensors were stable with time and thermal cycling, but the long term stability of the Cernox(trade mark, serif) sensors was degraded. Catastrophic failure occurred at higher levels of ESD exposure.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2015

The resilient hybrid fiber sensor network with self-healing function

This paper presents a novel resilient fiber sensor network (FSN) with multi-ring architecture, which could interconnect various kinds of fiber sensors responsible for more than one measurands. We explain how the intelligent control system provides sensors with self-healing function meanwhile sensors are working properly, besides each fiber in FSN is under real-time monitoring. We explain the software process and emergency mechanism to respond failures or other circumstances. To improve the efficiency in the use of limited spectrum resources in some situations, we have two different structures to distribute the light sources rationally. Then, we propose a hybrid sensor working in FSN which is a combination of a distributed sensor and a FBG (Fiber Bragg Grating) array fused in a common fiber sensing temperature and vibrations simultaneously with neglectable crosstalk to each other. By making a failure to a working fiber in experiment, the feasibility and effectiveness of the network with a hybrid sensor has been demonstrated, hybrid sensors could not only work as designed but also survive from destructive failures with the help of resilient network and smart and quick self-healing actions. The network has improved the viability of the fiber sensors and diversity of measurands.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

Review of the gas breakdown physics and nanomaterial-based ionization gas sensors and their applications

Ionization gas sensors are ubiquitous tools that can monitor desired gases or detect abnormalities in real time to protect the environment of living organisms or to maintain clean and/or safe environment in industries. The sensors’ working principle is based on the fingerprinting of the breakdown voltage of one or more target gases using nanostructured materials. Fundamentally, nanomaterial-based ionization-gas sensors operate within a large framework of gas breakdown physics; signifying that an overall understanding of the gas breakdown mechanism is a crucial factor in the technological development of ionization gas sensors. Moreover, many studies have revealed that physical properties of nanomaterials play decisive roles in the gas breakdown physics and the performance of plasma-based gas sensors. Based on this insight, this review provides a comprehensive description of the foundation of both the gas breakdown physics and the nanomaterial-based ionization-gas-sensor technology, as well as introduces research trends on nanomaterial-based ionization gas sensors. The gas breakdown is reviewed, including the classical Townsend discharge theory and modified Paschen curves; and nanomaterial-based-electrodes proposed to improve the performance of ionization gas sensors are introduced. The secondary electron emission at the electrode surface is the key plasma–surface process that affects the performance of ionization gas sensors. Finally, we present our perspectives on possible future directions.

nanomaterial-based gas breakdown characteristics↗
DOE OSTI2024

Design Optimization and Measurement Uncertainty of an Electromagnetic Level Sensor for Liquid Metal Reactors

Here, this article describes the design and operation of a prototype mutual inductance level sensor (MILS) and the development and validation of a finite-element analysis (FEA) model describing its behavior. The MILS was designed for use in liquid sodium up to temperatures of 650 °C in the Mechanisms Engineering Test Loop (METL) at Argonne National Laboratory (ANL). Preliminary testing was performed in a room temperature test stand with aluminum acting as an analog for the sodium to better understand sensor performance and provide accurate code validation data. This experimental data, along with material properties found in literature, were used to validate an FEA model in ANSYS Maxwell. The validated ANSYS Maxwell model was used to examine the performance of the MILS in various environments and under various operating conditions. Simulations suggest the following: The MILS will perform adequately in liquid sodium and liquid lead at temperatures up to 650 °C . The temperature dependence of electrical conductivity imposes a temperature dependence on the sensor that requires proper compensation. The MILS signal sensitivity is maximized when mutual inductance between sensor coils is maximized, and sensor geometry should be selected to account for this factor. The operating frequency of the MILS can be optimized and is dependent on process fluid material, operating temperature, and materials/geometry of sensor system. Finally, the use of a stainless-steel isolating thimble does not adversely affect the sensor signal. The primary sources of error for this MILS system are the accuracy of the calibration standard against which the sensor is calibrated, and the temperature dependence of the sensor. This work contains all the necessary details to recreate the FEA model and results. This model can be used to optimize the performance of a MILS in any operating environment to read any electrically conductive working fluid.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2011

A wireless sensor tag platform for container security and integrity

Cargo containers onboard ships are widely used in the global supply chain. The need for container security is evidenced by the Container Security Initiative launched by the U.S. Bureau of Customs and Border Protection (CBP). One method of monitoring cargo containers is using low power wireless sensor tags. The wireless sensor tags are used to set up a network that is comprised of tags internal to the container and a central device. The sensor network reports alarms and other anomalies to a central device, which then relays the message to an outside network upon arrival at the destination port. This allows the port authorities to have knowledge of potential security or integrity issues before physically examining the container. Challenges of using wireless sensor tag networks for container security include battery life, size, environmental conditions, information security, and cost among others. PNNL developed an active wireless sensor tag platform capable of reporting data wirelessly to a central node as well as logging data to nonvolatile memory. The tags, operate at 2.4 GHz over an IEEE 802.15.4 protocol, and were designed to be distributed throughout the inside of a shipping container in the upper support frame. The tags are mounted in a housing that allows for simple and efficient installation or removal prior to, during, or after shipment. The distributed tags monitor the entire container volume. The sensor tag platform utilizes low power electronics and provides an extensible sensor interface for incorporating a wide range of sensors including chemical, biological, and environmental sensors.

36 MATERIALS SCIENCE↗
DOE OSTI2015

TU-AB-201-03: A Robot for the Automated Delivery of An Electromagnetic Tracking Sensor for the Localization of Brachytherapy Catheters

Purpose: To present a programmable robotic system for the accurate and fast deployment of an electromagnetic (EM) sensor for brachytherapy catheter localization. Methods: A robotic system for deployment of an EM sensor was designed and built. The system was programmed to increment the sensor position at specified time and space intervals. Sensor delivery accuracy was measured in a phantom using the localization of the EM sensor and tested in different environmental conditions. Accuracy was tested by measuring the distance between the physical locations reached by the sensor (measured by the EM tracker) and the intended programmed locations. Results: The system consisted of a stepper motor connected to drive wheels (that grip the cable to move the sensor) and a series of guides to connect to a brachytherapy transfer tube, all controlled by a programmable Arduino microprocessor. The total cost for parts was <$300. The positional accuracy of the sensor location was within 1 mm of the expected position provided by the motorized guide system. Acquisition speed to localize a brachytherapy catheter with 20 cm of active length was 10 seconds. The current design showed some cable slip and warping depending on environment temperature. Conclusion: The use of EM tracking for the localization of brachytherapy catheters has been previously demonstrated. Efficient data acquisition and artifact reduction requires fast and accurate deployment of an EM sensor in consistent, repeatable patterns, which cannot practically be achieved manually. The design of an inexpensive, programmable robot allowing for the precise deployment of stepping patterns was presented, and a prototype was built. Further engineering is necessary to ensure that the device provides efficient independent localization of brachytherapy catheters. This research was funded by the Kaye Family Award.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2011

Sensitivity enhancement of grating interferometer based two-dimensional sensor arrays using two-wavelength readout

Diffraction gratings integrated with microelectromechanical systems (MEMS) sensors offer displacement measurements with subnanometer sensitivity. However, the sensitivity of the interferometric readout may drop significantly based on the gap between the grating and the reference surface. A two-wavelength (2-{lambda}) readout method was previously tested using a single MEMS sensor for illustrating increased displacement measurement capability. This work demonstrates sensitivity enhancement on a sensor array with large scale parallelization ({approx}20,000 sensors). The statistical representation, which is developed to model sensitivity enhancement within a grating based sensor array, is supported by experimental results using a thermal sensor array. In the experiments, two lasers at different wavelengths (633 and 650 nm) illuminate the thermal sensor array from the backside, time-sequentially. The diffracted first order light from the array is imaged onto a single CCD camera. The target scene is reconstructed by observing the change in the first diffracted order diffraction intensity for both wavelengths. Merging of the data from two measurements with two lasers was performed by taking the larger of the two CCD measurements with respect to the reference image for each sensor. {approx}30% increase in the average sensitivity was demonstrated for a 160x120 pixel IR sensor array. Proposed architecture is also applicable to a variety of sensing applications, such as parallel biosensing and atomic force microscopy, for improved displacement measurements and enhanced sensitivity.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2018

AOI [3]: Smart Refractory Sensor Systems for Wireless Monitoring of Temperature, Health, and Degradation of Slagging Gasifiers

The objective of the work was to develop refractory “smart bricks”, which would contain embedded temperature, strain/stress, and spallation sensors throughout the volume of highchromia (-Cr 2 O 3 ) refractory brick. The proposed work included work to interconnect the sensors to the reactor exterior, where the sensor signals may be processed by low-power electronics and transmitted wirelessly to a central processing hub. The data processing and wireless transmitter hardware was specifically designed to be isolated (with low power consumption) and to be adaptable to future implementation of energy-harvesting strategies for extended life. Finally, the collected data was incorporated into a model to estimate refractory degradation, a technique that could help monitor the health of the refractory in real-time. The long-term goal of this program was to demonstrate high-temperature, wireless sensor arrays for in situ three-dimensional (3-D) refractory monitoring or mapping for slagging gasification systems. The research was in collaboration with HarbisonWalker International (HWI) Technology Center in West Mifflin, PA. HWI is a leading developer and manufacturer of ceramic refractory products for high-temperature applications. The work completed focused on the following areas: 1) Investigation of the chemical stability, microstructural evolution, grain growth kinetics, degree of homogeneity (quantitative image analysis), and electrical properties of refractory oxide-silicide composites at temperatures between 750-1450ºC; 2) Fabrication of silicide-alumina composite and oxide thermocouples and thermistor preforms and the development of techniques to embed them into high-chromia refractory bricks to form “smart bricks”; 3) Utilization of commercial off-the-shelf discrete components to prototype circuits for interfacing between smart brick sensors and the wireless sensor network. The prototypes were then used to design an integrated circuit for thermistor, thermocouple, and capacitive-based smart brick sensor interfacing; 4) Interfacing of the smart bricks with embedded sensors with wireless motes thus yielding a complete signal chain. This end-to-end data collection system was tested on a furnace heated to 1350°C; 5) Development of a slag penetration model and a nonlinear unknown input filter for the data from the embedded sensors for estimating temperature and extent of slag penetration.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2019

Status of Mock-up and Integration for Ultrasonic Deformation Sensor for TREAT Experiments

Fuel deformation (both axial and radial) information provides insights into fuel performance and failure limits. Traditionally, fuel deformation has been quantified using post-irradiation examinations due to the lack of an appropriate sensor for monitoring deformation in situ. Recent developments in sensor and instrumentation design have led to the use of linear variable differential transducers (LVDT) for monitoring axial strain in fuel during irradiation. Size and operational constraints limit the use of LVDT sensors for radial deformation monitoring, and alternatives are needed. One possible alternative to LVDT sensors is an ultrasonic sensor. Ultrasonic sensors monitor the interaction of high-frequency stress waves with the test object. The resulting response may be analyzed to determine the properties of the material, including stress, strain, microstructure, presence of defects, and the elastic constants. While ultrasonic measurements have been successfully applied for monitoring strain in a number of applications, their use for in-core measurements has been limited. Largely, the limitations are due to the challenges associated with designing sensors that can operate under typical in-core conditions. This report documents progress to date toward planning, construction, and testing of a mock-up test capsule/facility to be used for in-lab testing of ultrasonic displacement sensor designs and toward integration of the sensor into prototypic TREAT experiment designs.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

Description of Sensor Assignment Optimization Method as Deployed on a Multi-Node Cluster

Data analytic methods are being developed to address the problem of how to assign a sensor set in a nuclear facility such that a requisite level of process monitoring capability is realized and that the sensor set is sufficiently rich to determine the status of the individual sensors with respect to need for calibration. There is an awareness in the nuclear industry that data analytics combined with rich sensor sets represent a means to improve operations and reduce costs. In the industry the calibration problem has been previously approached as an empirical data-driven problem with several methods having been developed. However, the experience of the utilities over the past ten years with these methods indicates that the absence of physics-based information renders the data-driven approach less reliable. Complicating factors such as the inherent variability of operation (both equipment alignment and operating condition) can confound a pure data-driven approach while there are no rigorous guidelines for determining what constitutes an adequate sensor set. The solution under development to overcome these shortcomings supplements the data analytic method with process information in a so-called process-constrained data-analytic approach. Simple balance equations are written for generic components (e.g., mechanical pump, valve, and heat exchanger). These do not require a priori knowledge of process parameters, such as heat transfer coefficients or friction factors. All that is needed on the part of the utility user is to identify the components and how they are connected. This report describes the development of a parallel computing capability for determining the optimal sensor set. The optimal sensor set problem suffers from the curse of dimensionality. Computation time increases exponentially as the size of the system grows. To overcome this difficulty a pre-conditioner algorithm is developed to find an approximate solution close the actual solution. This serves as a seed for the full-blown algorithm and acts to constrain the space that must searched. The optimization algorithms are described and the implementation on a parallel computing platform is described. The application of the method to a use case we are solving in collaboration with our utility partner served to illustrate how the default sensor set in a nuclear plant may not provide sufficient coverage to infer sensor calibration status.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Passive Wireless Sensors for Realtime Temperature and Corrosion Monitoring of Coal Boiler Components Under Flexible Operation (Final Technical Report)

Researchers at West Virginia University (WVU) propose to demonstrate inexpensive wireless, high-temperature sensors for real-time monitoring of the temperature and corrosion of metal components, which are commonly used in coal-fired boilers. This study presents the development of cost-effective wireless high-temperature sensors for real-time temperature and corrosion monitoring in coal-fired boilers' metal components. The focus is on fabricating and evaluating chipless radio-frequency identification (RFID) sensors capable of operating between 25-1300 ºC. Efforts were directed towards designing passive RFID sensor and interrogator antenna with a broad frequency range, optimizing a microstrip patch antenna sensor integrated into a "peel-and-stick" format for efficient application to various metal specimens without altering their geometry. Additionally, this research aimed to assess the sensor responses under accelerated high-temperature conditions, correlating corrosion and cracking mechanisms with sensor data. An investigation of through-wall data acquisition techniques was also planned, facilitating unobtrusive monitoring of sensor responses housed within metal enclosures. Ultimately, this work sought to establish a robust passive wireless sensor system for the continuous health monitoring of metal components in operational settings, thereby contributing to enhanced safety and efficiency in coal-fired power plants.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2012

Fiber Loop Ringdown Sensor for Potential Real-Time Monitoring of Cracks in Concrete Structures: An Exploratory Study

A fiber loop ringdown (FLRD) concrete crack sensor is described for the first time. A bare single mode fiber (SMF), without using other optical components or chemical coatings, etc., was utilized to construct the sensor head, which was driven by a FLRD sensor system. The performance of the sensor was evaluated on concrete bars with dimensions 20 cm × 5 cm × 5 cm, made in our laboratory. Cracks were produced manually and the responses of the sensor were recorded in terms of ringdown times. The sensor demonstrated detection of the surface crack width (SCW) of 0.5 mm, which leads to a theoretical SCW detection limit of 31 μm. The sensor’s response to a cracking event is near real-time (1.5 s). A large dynamic range of crack detection ranging from a few microns (μm) to a few millimeters is expected from this sensor. With the distinct features, such as simplicity, temperature independence, near real-time response, high SCW detection sensitivity, and a large dynamic range, this FLRD crack sensor appears promising for detections of cracks when embedded in concrete.

36 MATERIALS SCIENCE↗
DOE OSTI2017

On Efficient Deployment of Wireless Sensors for Coverage and Connectivity in Constrained 3D Space

Sensor networks have been used in a rapidly increasing number of applications in many fields. This work generalizes a sensor deployment problem to place a minimum set of wireless sensors at candidate locations in constrained 3D space to k-cover a given set of target objects. By exhausting the combinations of discreteness/continuousness constraints on either sensor locations or target objects, we formulate four classes of sensor deployment problems in 3D space: deploy sensors at Discrete/Continuous Locations (D/CL) to cover Discrete/Continuous Targets (D/CT). We begin with the design of an approximate algorithm for DLDT and then reduce DLCT, CLDT, and CLCT to DLDT by discretizing continuous sensor locations or target objects into a set of divisions without sacrificing sensing precision. Furthermore, we consider a connected version of each problem where the deployed sensors must form a connected network, and design an approximation algorithm to minimize the number of deployed sensors with connectivity guarantee. For performance comparison, we design and implement an optimal solution and a genetic algorithm (GA)-based approach. Extensive simulation results show that the proposed deployment algorithms consistently outperform the GA-based heuristic and achieve a close-to-optimal performance in small-scale problem instances and a significantly superior overall performance than the theoretical upper bound.

47 OTHER INSTRUMENTATION↗
DOE OSTI2017

EDGE COMPUTING AND CONTEXTUAL INFORMATION FOR THE INTERNET OF THINGS SENSORS

Interpreting sensor data require knowledge about sensor placement and the surrounding environment. For a single sensor measurement, it is easy to document the context by visual observation, however for millions of sensors reporting data back to a server, the contextual information needs to be automatically extracted from either data analysis or leveraging complimentary data sources. Data layers that overlap spatially or temporally with sensor locations, can be used to extract the context and to validate the measurement. To minimize the amount of data transmitted through the internet, while preserving signal information content, two methods are explored; computation at the edge and compressed sensing. We validate the above methods on wind and chemical sensor data (1) eliminate redundant measurement from wind sensors and (2) extract peak value of a chemical sensor measuring a methane plume. We present a general cloud based framework to validate sensor data based on statistical and physical modeling and contextual data extracted from geospatial data.

03 NATURAL GAS↗
DOE OSTI2021

High-Temperature Multi-Process Sensor Development and Demonstration at a Full-scale PC Combustion System

The main objective of this research program is to design, manufacture, and demonstrate a miniaturized, multi-process, monitoring system (mMPMS) for boiler condition management and easy system deployment to obtain a higher spatial resolution of wall conditions in utility boilers. This system will facilitate a Condition-Based Maintenance (CBM) philosophy that actively monitors the health of assets to predict and prevent failures and maximize availability and generating capacity at a reduced cost. CBM systems can provide boiler data that the advanced process control (APC) system can utilize for plant performance optimization, which is increasingly relevant as coal power plants shift from predominantly base-load operation to predominantly transient operation involving large load swings. The mMPMS is based on an electrochemical sensor that provides a real-time indication of the risk of damage to key locations in the radiant or convective section of a coal-fired boiler such as metal loss rates, heat flux, metal surface temperature, and deposit thickness. These indications can be utilized to optimize boiler performance as well as improve boiler availability in conjunction with corresponding operating conditions. This monitoring system was developed and tested in the high-temperature regions of a coal-fired utility boiler in this project but can be applied to many other industries and applications as well. The new sensor design, leveraging the existing electrochemical noise-based monitoring system, is small enough to be installed through the webbing of the waterwalls without the need for long shut-downs to bend tubes and to make it feasible to obtain high spatial resolution in the boiler. Data can be transferred to the plant distributed control system (DCS) and any other control system. The sensor body that houses the sensor assembly was designed to ensure good conductive contact with boiler tubes to ensure the sensor is held at an identical temperature to the tube surface temperature. The data acquisition and signal conditioning modules were redesigned into a small footprint with optimized cooling of the module. System software was developed specifically for the new signal conditioning module and is compatible with plant PLCs. After the preliminary testing at a pilot-scale facility, five mMPMS were installed at a full-scale pulverized coal-fired plant, Basin Electric Power Cooperative’s Leland Olds Unit 1. The systems were demonstrated over a 6-week period during typical operation. Sensor measurements of deposit thickness were validated during the demonstration and subsequently leveraged to determine sensor-based boiler cleaning strategies. These strategies have the benefit of reduced thermal stresses on boiler tubes from over-cleaning and improved boiler water management. At the end of the project, continued development of the sensor technology was carried out at PacifiCorp’s Hunter Station. REI leveraged the permanent installation of the mMPMS in Unit 3 made possible by DOE funding on a separate program. The work at Hunter Plant focused on application of machine learning and artificial intelligence-based models for integration of sensor signals into control and optimization of Hunter Unit 3 processes.

Advanced Sensors, Corrosion, Ash Deposition, Optim↗
DOE OSTI2015

Acoustic sensors for fission gas characterization: R and D skills devoted to innovative instrumentation in MTR, non-destructive devices in hot lab facilities and specific transducers for measurements of LWR rods in nuclear plants

First of all, we will present the main principle of the method. A piezoelectric transducer, driven by a pulse generator, generates the acoustic waves in a cavity that may be the fuel rod or a chamber connected to an instrumented rod. The composition determination consists in measuring the time of flight of the acoustic signal emitted. The pressure can be estimated by a calibration process, above the measurement of the amplitude of the signal. Two projects will then be detailed. The first project consists in the development of advanced instrumentation for in-pile experiments in Material Testing Reactor. It constitutes a main goal for the improvement of the nuclear fuel behavior knowledge. This acoustic method was tested with success during a first experiment called REMORA 3, and the results were used to differentiate helium and fission gas release kinetics under transient operating conditions. This experiment was lead at OSIRIS reactor (CEA Saclay, France). As a first step of the development program, we performed in-pile tests on the most sensitive component, i.e., the piezoelectric transducer. For this purpose, the active part of this sensor has been qualified on gamma and neutron radiations and at high temperature. Various industrial piezo-ceramics were exposed to a high activity Cobalt source for few days. The cumulated dose was ranged from 50 kGy up to 2 MGy. Next, these devices were placed inside a Material Test Reactor to investigate their reliability towards neutron fluence. The final fluence after 150 days of irradiation was up to 1.6.10{sup 21}n/cm{sup 2} (for thermal neutron). Irreversible variations have been measured. Next, a specific sensor has been implemented on an instrumented fuel rod and tested in the frame of a REMORA 3 Irradiation test. It was the first experiment under high mixed, temperature neutron and gamma flux. A first irradiation phase took place in March 2010 in the OSIRIS reactor and in November 2010 for the second step of the irradiation. The instrumented fuel rod incorporating the ultrasonic gas composition sensor was finally irradiated during 2 weeks in nominal conditions. Neutronics calculation will be performed in order to calculate the thermal and fast neutron fluence and the gamma dose absorbed by acoustic sensor. A first evaluation gives a thermal fluence about 4,5.10{sup 19} n/cm{sup 2}, a fast neutrons fluence about 4,5.1018 n/cm{sup 2} and a total gamma dose up to 0,25 MGy The maximal temperature during the irradiation test was about 150 C. Although the ultrasonic sensor appears to be damaged, the optimization of the electrical attack parameters and the development of a new signal processing maintain the measurement feasibility up the end of the irradiation campaign. It was the first time that the composition of fission gas has been monitored all along an irradiation experiment in a MTR, giving access to the gas release kinetics. New researches involve thick film transducers produced by screen-printing process in order to propose piezoelectric structures for harsh temperature and irradiation measurements. The second project consists in the development of a non-destructive device that can be directly applied on a LWR fuel rod. The problem to be solved relates to the measurement of the fission gas pressure and composition in a fuel rod using a non-destructive method. Fuel rod internal pressure is one of the safety criteria applied in nuclear power analyses. This criterion must be verified in order to avoid any fuel-cladding gap reopening risk and therefore any local clad ballooning. Apart from the safety implications, this parameter is also a fuel behaviour indicator and reflects the overall fuel performance in operation, but also during shipping and long-term storage. Rod internal pressure is one criterion amongst others, like cladding corrosion, against which the acceptable fuel burn-up limit is set. A sensor has been achieved in 2007. A full-scale hot cell test of the internal gas pressure and composition measurement by an acoustic sensor was conducted successfully between 2008 and 2010 on 5 high burn-up MOX fuel rods and 2 very high burn-up UO{sub 2} fuel rods in LECA Facility at Cadarache Centre. An improvement of this sensor has been proposed, allowing us to divide by two the uncertainty on the pressure measurement. In the case of hot-cell measurements, viscous liquid can be used to couple the sensor with the rod. For gas content with a pressure exceeding 15 bars and a 10% Xe/Kr ratio, such coupling may reduce relative acoustic method accuracy by ±7% for pressure measurement result and ±0.25 % for the assessment of gas composition. These results make it possible to demonstrate the feasibility of the technique on LWR fuel rods. The transducer and the associated methodology are now operational for non-destructive measurements in hot lab facilities and allow characterising the fission gas without puncturing the fuel rods. Up to now, any other non-destructive method can be proposed. A next step will be the development of an industrial application in a fuel storage pool in order to perform a large number of measurements on a fuel assembly in nuclear plants.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2019

R and DE Robotic Sensor Intern Team: Remote 3D Mapping Overview

The Department of Energy (DOE) nuclear complex includes many hazardous and challenging environments that must be inspected remotely and routinely for structural integrity evaluation and long-term planning purposes. The H-Canyon Air Exhaust (HCAEX) Tunnel biannual inspection is an example of such an environment. Presently inspections are performed by teleoperated robotic crawlers provide low resolution video feedback to the structural engineers. Advanced sensors such as Lidar and panospheric hi-res cameras have the potential to provide additional valuable data in future inspections. UT-Austin Lidar work in support of an H-Canyon deployment began with the DOE EM sponsored H-Canyon Integrated Research Project. The R and DE Robotic Sensor intern team includes two of the UT-Austin Masters students working on Lidar development to facilitate the pulling of university developed solutions to the field. The goal of this project is to develop a suite of sensors that could be used to gather advanced data in future HCAEX tunnel inspections. Of particular interest is the ability to map the tunnel walls at an accuracy that will allow for the comparison of two scans performed at different time periods to estimate the concrete erosion rate. Additionally, the development of the 3D point cloud in the GPS denied environment is the first step in being able to collect and overlay other 3D data such as radiation mapping. Project specific goals include: - Design and develop 3D mapping sensor suite. Merge Lidar point cloud with high res camera images Incorporate Inertial Measurement Unit (IMU) to assist with positioning. - Develop sensor software and user GUI Sensor data collection and integration software User GUI for reach back system. - Test solution on crawler in tunnel test bed Use crawler base similar to H-Canyon planned crawler Design and build test bed simulating tunnel conditions. To facilitate rapid sensor integration, software coding and user GUI development, the Robot Operating System (ROS) was employed as the development platform. ROS is a set of open source software libraries and tools that assist with the building of robot applications. ROS includes drivers for many sensors, state-of-the-art algorithms, and powerful developer tools. Sensors selected for the summer intern solution included assessment as to whether they possessed ROS drivers and associated sample code. Additionally, the ROS 3D Robot Visualizer (rviz) tool has been employed.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2017

On-Line Monitoring to Detect Sensor and Process Degradation under Normal Operational Transients - 327

Calibration assessment of nuclear plant sensors and transmitters is currently performed through periodic maintenance actions during plant refueling outages. On-line monitoring (OLM) can be used to reduce the time and cost of this maintenance process by using empirical models to evaluate sensor calibration. The implementation of OLM can also mitigate human error associated with unnecessary maintenance on sensors operating within calibration tolerances. OLM has been studied and validated for plants under steady-state baseload operation, but the extension to load-following operation is not well-documented in the literature. Auto-associative kernel regression (AAKR) provides an error-corrected prediction of process sensor measurements for OLM through a weighted average of historic data. The current study evaluates the performance of AAKR for prediction under normal operational transients (such as expected under load-following operation). Performance of the AAKR model with two anomaly detection routines, error uncertainty limit monitoring (EULM) and sequential probability ratio test (SPRT), was evaluated for normal operation, sensor faults, and process degradation. The data used to develop and evaluate the OLM system were collected from a forced flow loop with temperature and flow sensors. Three models of well-correlated groups of sensors are trained to predict normal system behavior under planned transients. The anomaly detection routines are tested for sensor faults and process faults. The results of this experimental study suggest AAKR and an appropriate anomaly detection routine can be applied for sensor calibration and process fault detection under transient operation. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗