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At least 1,585 records · Page 88

A Multi-Tier Autonomous Aerial Architecture for Wildfire Detection, Characterization, and Communication in Infrastructure-Denied Environments

Wildfire response depends on how fast an ignition can be confirmed and located, especially in remote regions where ground-based communication and monitoring may be limited. Geostationary sensors provide frequent observations but at kilometer-scale resolution, which is too coarse to resolve small fires in remote terrain. Ground camera networks require sightlines and infrastructure that back-country areas lack. To address these limitations, this work proposes a Multi-Tier Autonomous Wildfire Intelligence System that combines wide-area monitoring with targeted, high-resolution sensing. A solar-powered high-altitude long endurance (HALE) platform operating at approximately 60,000 ft provides persistent wide-area thermal and optical surveillance, running onboard edge inference to screen candidate ignitions and reduce false positives and downlink bandwidth. When a candidate ignition is detected, low-altitude uncrewed aircraft systems (UAS) can be deployed to conduct localized observations, including high-resolution imaging and atmospheric measurements such as wind and plume observation. By combining persistent detection with local sensing, the proposed architecture is designed to provide first responders with timely, high-resolution information about fire location and behavior to aid in emergency decision making.

Wildfire management, UAS, drones↗

Lithium-Ion Battery Diagnostics Using Electrochemical Impedance via Machine-Learning

Diagnosing battery states such as health, state-of-charge, or temperature is crucial for ensuring the safety and reliability of electrochemical energy storage systems. While some states, such as temperature, may be measured using cheap sensors, accurate diagnosis of battery health metrics usually requires time-consuming performance measurements, making them infeasible for use in real-world operation. These health metrics can be measured during lab-testing and then estimated on-line using predictive life models or via state observer algorithms such as Kalman filters, but these predictive methods should be supplemented by actual measurement of battery health whenever possible to ensure reliability. Rapid measurement of battery health may be done by various types of fast diagnostic techniques such as electrochemical impedance spectroscopy (EIS), which can be performed in only a few minutes and require only a fraction of the energy and power needed for a full charge and discharge measurement. But there is a substantial challenge for estimating battery health using EIS data, as EIS is sensitive to cell temperature, state-of-charge, current, and resting time in addition to health. Thus, utilizing EIS data to predict battery capacity requires correcting for all these additional variables, a task that is extremely difficult to handle analytically. This talk utilizes machine-learning methods to estimate the effectiveness of battery capacity prediction from EIS data, leveraging a data set of hundreds of EIS measurements recorded at varying temperature and state-of-charge throughout a 500-day aging study of 32 commercial, large-format NMC-Graphite lithium-ion batteries. Using EIS as input to machine-learning models is complicated by the nonlinear response of impedance to battery health, temperature, and state-of-charge, as well as the collinearity between the impedance response at neighboring frequencies, which can easily lead to overfit models. To train robust models, features from EIS data need to be extracted from the data or some subset of critical frequencies selected. Many approaches for extracting and selecting features from EIS data from electrochemical analysis and machine-learning fields were identified for analysis: using the entire raw spectra; selection of one, two, or many frequencies from the entire spectra; selecting interesting points from the EIS measurement using domain knowledge; fitting EIS with an equivalent-circuit model; calculating statistics on the raw impedance values; and reducing the dimensionality of the data using unsupervised linear (principal component analysis) and non-linear (uniform manifold approximation and projection) methods. These approaches were rigorously compared using a machine-learning pipeline approach, training linear, Gaussian process, and random forest regression models and quantifying performance using cross-validation as well as a held-out test set. An artificial neural network model trained on the raw spectra was also tested. Promising pipelines were fine-tuned via Bayesian hyperparameter optimization using cross-validation loss and training with class-specific weights to counter data set imbalance. The most reliable method for utilizing impedance in this work was the selection of two optimal frequencies through an exhaustive search, resulting in about 2% mean absolute error on test data for both Gaussian process and random forest model architectures. Interrogation of a variety of models reveals critical frequencies of 100 Hz and 103 Hz for this data set, though the optimal set of frequencies is not necessarily intuitive, i.e., the best performing models are not simply those that use impedance at frequencies that have the highest correlation to the relative discharge capacity. The best performing model is an ensemble model, which is able to predict battery capacity with 1.9% mean absolute error for unseen cells using impedance recorded at a variety of temperatures and states-of-charge.

battery↗

Electrification Analysis: All Aboard America!

This one-page highlight details the key takeaways from a project that utilized NREL's Fleet Research, Energy Data, and Insights (FleetREDI) data analysis pipeline, an electrification analysis for the Bustang motorcoach fleet operated by All Aboard America! Holdings Inc. (AAA). NREL installed logging devices and collected operational data on nine 40-foot Bustang motorcoaches operating on fixed routes from May 2022 through August 2022. The analysis determined that partial fleet electrification may be feasible with electrified motorcoach options currently on the market. While this fleet faces significant challenges to electrification given current market options due to demanding range requirements and relatively limited charging opportunities, vehicles operating on the shorter, lower-grade routes along the I-25 corridor show more immediately available electrification potential. Increases in available battery capacity and the availability of fast-charging locations along I-70 routes are likely critical for electrification of the full fleet.

AAA↗

Three-dimensional Skyrme Hartree-Fock-Bogoliubov solver in coordinate-space representation

The coordinate-space representation of the Hartree-Fock-Bogoliubov theory is the method of choice to study weakly bound nuclei whose properties are affected by the quasiparticle continuum space. To describe such systems, we developed a three-dimensional Skyrme-Hartree-Fock-Bogoliubov solver HFBFFT based on the existing, highly optimized and parallelized Skyrme-Hartree-Fock code Sky3D. The code does not impose any self-consistent spatial symmetries such as mirror inversions or parity. The underlying equations are solved in HFBFFT directly in the canonical basis using the fast Fourier transform. To remedy the problems with pairing collapse, we implemented the soft energy cutoff and pairing annealing. The convergence of HFB solutions was improved by a sub-iteration method. The Hermiticity violation of differential operators brought by Fourier-transform-based differentiation has also been solved. Furthermore, the accuracy and performance of HFBFFT were tested by benchmarking it against other HFB codes, both spherical and deformed, for a set of nuclei, both well-bound and weakly-bound.

3D coordinate-space representation↗

Cascading RF deflectors in compact beam spreader schemes

This study describes beam distribution schemes based on transverse electric field radio-frequency deflectors (RFD) as fast-switching devices and provides numerical relationships between their respective frequencies and phases. The adoption of compact transverse deflecting cavities represents an ideal solution for the design of high repetition rate ( > 1 MHz), compact beam distribution systems. While directly applicable to modern FEL facilities, this approach also provides opportunities for expanding existing beam delivery systems with additional experimental areas simultaneously feeding multiple beamlines. We derive the formalism for cascading RFDs by adopting the proper choice of deflector frequencies which can generate a large variety of beam switch yard topologies. Finally, we present for reference a potential application operating at an rf frequency of 325 MHz with the comparison of three possible distinct compact rf deflectors: a superconducting rf-dipole, a normal conducting rf-dipole, and a normal conducting 4-rod design.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Impacts of uncertain feedstock quality on the economic feasibility of fast pyrolysis biorefineries with blended feedstocks and decentralized preprocessing sites in the Southeastern United States

Abstract This study performs techno‐economic analysis and Monte Carlo simulations (MCS) to explore the effects that variations in biomass feedstock quality have on the economic feasibility of fast pyrolysis biorefineries using decentralized preprocessing sites (i.e., depots that produce pellets). Two biomass resources in the Southeastern United States, that is, pine residues and switchgrass, were examined as feedstocks. A scenario analysis was conducted for an array of different combinations, including different pellet ash control levels, feedstock blending ratios, different biorefinery capacities, and different biorefinery on‐stream capacities, followed by a comparison with the traditional centralized system. MCS results show that, with depot preprocessing, variations in the feedstock moisture and feedstock ash content can be significantly reduced compared with a traditional centralized system. For a biorefinery operating at 100% of its designed capacity, the minimum fuel selling price (MFSP) of the decentralized system is $3.97–$4.39 per gallon gasoline equivalent (GGE) based on the mean value across all scenarios, whereas the mean MFSP for the traditional centralized system was $3.79–$4.12/GGE. To understand the potential benefits of highly flowable pellets in decreasing biorefinery downtime due to feedstock handling and plugging problems, this study also compares the MFSP of the decentralized system at 90% of its designed capacity with a traditional system at 80%. The analysis illustrates that using low ash pellets mixed with switchgrass and pine residues generates a more competitive MFSP. Specifically, for a biorefinery designed for 2,000 oven dry metric ton per day, running a blended pellet made from 75% switchgrass and 25% pine residues with 2% ash level, and operating at 90% of designed capacity could make an MFSP between $4.49 and $4.71/GGE. In contrast, a traditional centralized biorefinery operating at 80% of designed capacity marks an MFSP between $4.72 and $5.28.

09 BIOMASS FUELS↗

Initial Core Physics and Safety Analyses Supporting the Versatile Test Reactor

The Versatile Test Reactor (VTR) is a proposed integrated facility for investigations into the behavior of fuels and materials subjected to high, fast neutron fluxes prototypical of fast reactor environments. Detailed design of the reactor is currently being performed by a group of U.S. National Laboratories, including Argonne National Laboratory. The current design of the reactor is a 300 MW sodium-cooled pool-type fast reactor fueled with ternary U-20Pu-10Zr metallic fuel. This report documents reactor core physics and preliminary safety analyses that have been performed. The reference VTR core has 313 assembly positions, 66 of which contain fuel assemblies. The remaining assembly positions are loaded with reflector, shield, control rod duct, and test assemblies. Ten positions are available in the reference design for experimental or test assemblies, however the VTR will support test assemblies in any position in the core for alternate core loadings. The performance of the reference VTR core has been assessed for an assumed equilibrium cycle. The core power distribution and reactivity feedback coefficients have been calculated. Preliminary assessments of the reactivity coefficients have shown that each of them results in a negative reactivity change for increasing temperatures. Safety analysis of a VTR layout has been performed using the SAS4A/SASSYS-1 fast reactor safety analysis code. A model has been developed to represent the current core design and a reference heat transport system design. The model has been used to simulate and perform analysis of protected and unprotected loss of heat sink, station blackout, and transient overpower accident scenarios. These scenarios represent the three main ways to perturb the reactor core, through changes to the core inlet temperature, mass flow rate, or reactivity insertions and are credible bounding scenarios for the evaluated transient categories. The results of these simulations have been assessed against simplified criteria for Anticipated Operational Occurrences for the protected transients and for Beyond Design Basis Events for the unprotected transients. Because the primary heat transport system is able to transition quickly and effectively to natural circulation and because the shutdown heat removal system provides sufficient heat rejection capability, large margins for all criteria were predicted for all protected transients. Large margins were also predicted for the unprotected loss of heat sink and station blackout transients due to the strong negative reactivity feedbacks generated by the core. Because of the high power density in the reactor, smaller fuel melting margins are predicted for the unprotected transient overpower accident.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Enabling Secure and Resilient XFC: A Software/Hardware-Security Co-Design Approach

Extremely fast charging (XFC) has the potential to reduce the charging time of battery electric vehicles (BEV) to be equivalent to the filling time of internal combustion engine vehicles (ICEV), thus eliminating one of the few advantages ICEV still poses for light- and heavy-duty vehicles. Enabling XFC will, however, require coordination and cooperation between the grid, charging stations, and the vehicles themselves, which leads to an inevitable increase in the attack surface for all systems combined. In securing the overall system, we must not only embrace traditional cybersecurity, which is chiefly concerned with communications and the operation of digital systems, but also cyber-physical systems security as the proper operation of XFC is critically dependent on systems’ abilities to know about (sense) and interact with (actuate) the physical world. The project team consists of academic and industry researchers with backgrounds in cybersecurity, cyber-physical systems security, learning in adversarial environments, transportation security, grid security and resilience, wireless power transfer, converter design, and battery management systems.

33 ADVANCED PROPULSION SYSTEMS↗

NASA Tech Briefs, March 2013

Topics covered include: Remote Data Access with IDL Data Compression Algorithm Architecture for Large Depth-of-Field Particle Image Velocimeters Vectorized Rebinning Algorithm for Fast Data Down-Sampling Display Provides Pilots with Real-Time Sonic-Boom Information Onboard Algorithms for Data Prioritization and Summarization of Aerial Imagery Monitoring and Acquisition Real-time System (MARS) Analog Signal Correlating Using an Analog-Based Signal Conditioning Front End Micro-Textured Black Silicon Wick for Silicon Heat Pipe Array Robust Multivariable Optimization and Performance Simulation for ASIC Design; Castable Amorphous Metal Mirrors and Mirror Assemblies; Sandwich Core Heat-Pipe Radiator for Power and Propulsion Systems; Apparatus for Pumping a Fluid; Cobra Fiber-Optic Positioner Upgrade; Improved Wide Operating Temperature Range of Li-Ion Cells; Non-Toxic, Non-Flammable, -80 C Phase Change Materials; Soft-Bake Purification of SWCNTs Produced by Pulsed Laser Vaporization; Improved Cell Culture Method for Growing Contracting Skeletal Muscle Models; Hand-Based Biometric Analysis; The Next Generation of Cold Immersion Dry Suit Design Evolution for Hypothermia Prevention; Integrated Lunar Information Architecture for Decision Support Version 3.0 (ILIADS 3.0); Relay Forward-Link File Management Services (MaROS Phase 2); Two Mechanisms to Avoid Control Conflicts Resulting from Uncoordinated Intent; XTCE GOVSAT Tool Suite 1.0; Determining Temperature Differential to Prevent Hardware Cross-Contamination in a Vacuum Chamber; SequenceL: Automated Parallel Algorithms Derived from CSP-NT Computational Laws; Remote Data Exploration with the Interactive Data Language (IDL); Mixture-Tuned, Clutter Matched Filter for Remote Detection of Subpixel Spectral Signals; Partitioned-Interval Quantum Optical Communications Receiver; and Practical UAV Optical Sensor Bench with Minimal Adjustability.

Source record↗

Overview of the ICRF heating system in SPARC

Ion Cyclotron Range of Frequencies (ICRF) heating is a critical system for the SPARC mission of demonstrating net positive fusion gain. In the first campaign, 20 MW of installed power at 120 MHz will be supplied to 10 four-strap antennas, arranged in poloidal pairs. The matching network is designed to accommodate for a range of loading conditions and a fast controller adjusts the matching during a pulse with frequency modulation of ±1 MHz. For the main L-mode scenario of the first experimental campaign, the power coupling and absorption is analysed in this work. Several feeding schemes are compared and limits on the amount of the total coupled power are evaluated. Coupling of the full 20 MW power is possible well within the limit of the peak electric field in the transmission line of 15 kV/cm. The 3 He minority and 2 nd harmonic T heating scheme is validated in full-wave modelling to be efficient for heating plasma in the SPARC L-mode Q>1 scenario, with dominant ion heating and efficient single-pass absorption. A range of ICRF wave parameters and minority concentration would be suitable for operation and allow tailoring the heating properties for plasma conditions and experimental objectives.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Quench protection analysis of the Mu2e production solenoid

The Muon-to-Electron conversion experiment (Mu2e), under development at Fermilab, seeks to detect direct muon to electron conversion to provide evidence for a process violating muon and electron lepton number conservation that cannot be explained by the Standard Model of particle physics. The Mu2e magnet system consists of three large superconducting solenoids. In case of a quench, the stored magnetic energy is extracted to an external dump circuit. However, because of the fast current decay, a significant fraction of the energy dissipates inside of the cryostat in the coil support shells made of structural aluminum, and in the radiation shield. A 3D finite-element model of the complete cold-mass was created in order to simulate the quench development and understand the role of the quench-back. The simulation results are reported at the normal and non-standard operating conditions.

43 PARTICLE ACCELERATORS↗

Development of frequency modulated continuous wave reflectometer for electron density profile measurement on the HL-2A tokamak

The frequency modulated continuous wave reflectometer was developed for the first time on the HL-2A tokamak. The system utilizes a voltage controlled oscillator and an active multiplier for broadband coverage and detects as heterodyne mode. Three reflectometers have been installed and operated in extraordinary mode polarization on HL-2A to measure density profiles at low field side, covering the Q-band (33–50 GHz), V-band (50–75 GHz), and W-band (75–110 GHz). For density profile reconstruction from the phase shift of the probing wave, a corrected phase unwrapping method is introduced in this article. The effectiveness of the method is demonstrated. The density profile behavior of a fast plasma event is presented and it demonstrates the capability of the reflectometer. These diagnostics will be contributed to the routine density profile measurements and the plasma physics study on HL-2A.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Impacts of Providing Inertial Response on Dynamic Loads of Wind Turbine Drivetrains

There has been growing demand from the power industry for wind power plants to support power system operations. One such requirement is for wind turbines to provide ancillary services in the form of inertial response. When the grid frequency drops, it is essential for wind turbine generators (WTGs) to inject kinetic energy stored in their inertia into the grid to help arrest the frequency decline. However, the impacts of inertial response on the structural loads of the wind turbine have not been given much attention. To bridge this gap, this paper utilizes a holistic model for both fixed-speed and variable-speed WTGs by integrating the aeroelastic wind turbine model in FAST, developed by the National Renewable Energy Laboratory, with the electromechanical drivetrain model in SimDriveline and SimPowerSystems.

17 WIND ENERGY↗

Model-Based Detection of Coordinated Attacks (DCA) in Distribution Systems

The fast-paced growth in digitization of smart grid components enhances system observability and remote-control capabilities through efficient communication. However, enhanced connectivity results in heightened system vulnerability towards cybersecurity risks in the cyber-physical power system. Coordinated cyber-attacks (CCA), when undetected, lead to system-wide impact in terms of large disturbances or widespread outages. Detecting CCA in the cyber layer is critical to thwart cyber-attacks in real-time before the attack impacts the physical system. The challenge of locating CCA stems from the complex grid dynamics, making it difficult to distinguish between normal operational variations and cyber-attack impact. CCA often employs multiple attack vectors targeting geographically distributed components, further complicating CCA identification. Existing research in intrusion detection is primarily focused on the transmission network and limited to detecting individual attacks. In this paper, a novel proactive DCA strategy is proposed for early detection of CCA by establishing correlations among distinct attack events through model-based reinforcement learning that utilizes abductive reasoning to conclude the attacker goal. The solution includes understanding the system model, learning the system dynamics, and correlating individual cyber-attacks to extract the attacker’s objective. The developed learning algorithm identifies the most probable attack path to reach the attacker’s objective by predicting the next attack steps. A DNP3-based cyber-physical co-simulation testbed is developed to test the proposed algorithm using the IEEE 13-node test feeder.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Design and Prototyping of a Novel Toroidal Magnet System for MOLLER Experiment at Jefferson Lab

The Thomas Jefferson National Accelerator Facility (JLab) has designed a unique spectrometer system to measure the weak interaction between electrons. The experiment— Measurement of Lepton-Lepton Electroweak Reaction (MOLLER)—requires leveraging the recent 12 GeV electron beam upgrade and will run in JLab for three years. Focusing the signal for the MOLLER experiment requires five water-cooled toroidal magnets, each with unique geometry and with 7-fold symmetry. The five magnets operate in a vacuum and provide the magnetic field required to separate the incident beam electrons scattered from the target electrons (Møller scattering) and protons (elastic e-p scattering) in a liquid hydrogen target. The conceptual design was developed by the MOLLER Collaboration and was given to JLab in the form of amp turns and physical location, with additional physics requirements. This article presents prototyping of the coils and magnet support system and discusses the lessons learned during the process along with the plans for full magnet testing and installation. The JLab Magnet Group along with the MOLLER Collaboration developed the specification document that includes keep out zones to design the set of magnets. JLab contracted the design of the first toroid magnet (TM0) of the magnet system to Massachusetts Institute of Technology. The other four toroid magnets (TM1 through TM4) have been designed by JLab and are in the process of fabrication and assembly. Prototype coils of TM1-TM4 were fabricated by Everson-Tesla Incorporated, PA (USA). Finally, this article presents the unique challenges of the design, alignment, high current density, operating range, high radiation dose, and vacuum environment.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Agent-Based Coordination Scheme for PV Integration (ABC4PV)

Renewables and especially photovoltaics (PV) have benefitted significantly from a host of incentives and policies targeted toward enhanced integration and adoption of specific energy technologies. However, with the push to move forward into a subsidy-free market framework, behind-the-meter residential PV applications have generally struggled to retain their value (unlike utility scale and commercial projects) [1]. This project focused on developing control-theoretic solutions aimed at improving the integration and interaction of behind-the-meter residential PV with other distribution system assets (controllable and non-controllable) to enhance the integrated value of residential PV. To this end, a suite of decentralized control methodologies have been developed to enable effective coordination and control of behind-the-meter residential load customers’ PV, battery storage systems (BSS), controllable loads and other similar assets within a distribution feeder. This interaction aims at procuring energy savings and, thus, energy bill savings. The main source of savings is drawn from reducing the effect of demand charge pricing and is realized at the feeder level, assuming community level interaction and management among the aforementioned assets. Optimal control of the assets is implemented with a distributed optimization methodology, leveraging consensus-based algorithms. The results gathered from the optimal control simulations demonstrates that the savings can be duly achieved and the algorithm decision times (to dynamically control asset set points, for example) are fast. As for the overall efficiency of PV+BSS systems, to procure energy savings from curtailment of the demand charge pricing effects, the optimal control is set up so as to minimize the variance of the load for all customers, throughout a feeder and throughout time in a rolling horizon scheduling with model predictive control. The control takes into account inter-temporal electrochemical storage (battery) degradation costs: specifically, we have developed a long-term lifetime model for the BSS that weighs in the effect of the degradation factor in the dispatch formulations, thus, a considerable operating cost that affects energy decision making. The levelized cost of energy (LCOE – redefined for the purpose of quantifying asset integration effectiveness through the customers’ energy cost) is shown to be below the threshold set for the combined PV+BSS topology of $ 0.14/kWh for multiple cases of PV penetration all the way up to 50%, provided that a policy of shared ownership of and savings is in place. Further, the LCOE calculated for the case before the deployment PV+BSS systems is also achievable, i.e. the deployment of PV+BSS, if planned and scheduled optimally. will have no effect on customers’ energy costs. From the control methodology viewpoint, the developed consensus-based algorithms are shown to converge for a wide range of problem cases (spanning normal operating scenarios and contingencies), guaranteeing dispatch solutions under forecasting errors, communication break-downs and cyber-security attacks. The proposed control solutions are scalable and real-time implementable, with dispatch computations and device set-point updates converging in less than 2s in most practical instances of the above events.

14 SOLAR ENERGY↗

ICRF antenna matching systems with ferrite tuners for the Alcator C-Mod tokamak

Real-time fast ferrite tuning (FFT) has been successfully implemented on the ICRF antennas on Alcator C-Mod. The former prototypical FFT system on the E-port 2-strap antenna has been upgraded using new ferrite tuners. A new FFT system with two ferrite tuners and one fixed-length stub has been installed on the transmission line of the D-port 2-strap antenna. These two systems are able to achieve and maintain the reflected power to the transmitters to less than 1% in real time under almost all plasma conditions and help ensure reliable high power operation of the antennas. The loading insensitivity feature vs. plasma conditions of the innovative field-aligned (FA) 4-strap antenna on the J-port allows us to significantly improve the matching by installing a carefully designed stub on each of the two transmission lines. The reduction of the RF voltages in the transmission lines has enabled the J-port FA antenna to deliver 3.7 MW RF power to plasmas out of 4 MW source power. The matching on the J-port antenna can be further improved by adding a single ferrite tuner under real-time control on each transmission line and this scheme will be implemented in the near future.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

In-Sodium Testing of a Prototype Thermoacoustic Power Sensor for Sodium-Cooled Fast Reactors

The ultimate goal of this project is to develop and demonstrate a thermoacoustic power sensor (TAPS) for Sodium-Cooled Fast Reactors (SFRs), with potential application also envisioned to other nuclear technologies such as Lead-Cooled Fast Reactors (LFRs), Molten Salt Reactors (MSRs), in addition to Light Water Reactors (LWRs). The project was led by Westinghouse Electric Company, LLC (Westinghouse) and carried out in collaboration with Argonne National Laboratory (ANL) and the University of Pittsburgh. A TAPS is a passive (self-powered), non-invasive (wireless) sensor envisioned for measuring key parameters, such as local temperature and neutron flux, in a nuclear reactor core. The sensor generates pressure waves (i.e., sound waves) with a frequency and amplitude dependent upon nuclear operating conditions (coolant temperature or power changes). The acoustic waves are able to travel through the core and associated structures, and reach to the sensor network placed outside and/or inside of the reactor vessel. These sensors require a very small amount of power which, during loss of power events, can be provided, for example, by harvesting gamma radiation energy, thus resulting in a monitoring system that can function both during normal operation and during loss of power events. Westinghouse and the University of Pittsburgh designed and fabricated TAPS prototypes for Argonne National Laboratory (ANL) to carry out in-sodium testing to evaluate the effects of sodium on the TAPS and the performance of the TAPS technique in sodium. Argonne received a TAPS prototype from Westinghouse, and the prototype was modified such that it can be installed into a test vessel and function in sodium at elevated temperature without potentially leaking. A water mockup test apparatus was constructed to validate proper working of the prototype. An instrumentation and control (I&C) system, running on the National Instruments (NI) LabView platform, was developed to: 1) operate both the water mockup test and the in-sodium test facility; and 2) process and analyze the received acoustic signals from an array of accelerometers and the Argonne sodium-submersible high-temperature acoustic sensor. The prototype was successfully tested in a water bath at different temperatures. Water mockup tests demonstrated that the TAPS prototype is working properly and its resonance frequency changes linearly with the coolant (water) temperature. A TAPS test apparatus was constructed and integrated with the upgraded Under-Sodium Viewing (USV) sodium test facility. The integrated USV-TAPS sodium test facility has been operational. The TAPS prototype and a high-temperature sodium-submersible acoustic sensor (SSAS) developed by Argonne were both installed inside the TAPS test vessel. Being operated within argon cover gas under ambient conditions, the TAPS prototype demonstrated that it was functioning properly with a resonance frequency at 1407.2 Hz, which was successfully detected by the accelerometers mounted on the external wall of the vessel and the high-temperature SSAS installed inside the vessel. After successfully transferring sodium into the vessel, in-sodium tests of the prototype were conducted. Tests of the TAPS prototype demonstrated that the resonance frequency of the TAPS changes linearly with respect to the temperature difference between the interior of the TAPS and bulk sodium. The early tests showed that the TAPS prototype could not establish a continuous and consistent resonance in sodium. The resonance diminished before the prototype reached its operating temperature. A signal postprocessor was added to the DAQ module latterly to isolate interferences, enhance signal conditioning, improve peak detection, and generate resonance frequency versus temperature plots. After testing in molten sodium and immersion at higher temperature for several weeks, the TAPS prototype was able to establish a continuous resonance. Performance evaluation of the TAPS prototype was then conducted in sodium. The tests included the investigation of 1) the effects of the temperature difference between the TAPS and bulk sodium, 2) the effects of sodium flowrate; and 3) the performance of the different sensor-receiver systems positioned inside or outside the vessel. Results of a test demonstrated that, with limited sodium circulation, a continuous and consistent resonance of the TAPS prototype was established occasionally. The tests also demonstrated that, because of the nature of detection principles and mounting methods, the high temperature SSAS is more affected by acoustic noise, while accelerometers are more affected by vibrations, in the test environment. It is unknown why the TAPS prototype only occasionally established a continuous and consistent resonance when the TAPS temperature reached its operating temperature in molten sodium, and why it ultimately failed to resonate at all. A failure modes assessment was conducted and a few potential causes of failure were identified. Different post in-sodium tests were conducted to obtain additional information potentially relevant to the cause of the failure. Nondestructive evaluation techniques are suggested to examine the internal integrity as well as the gas mixture of the prototype. If they prove inconclusive, the prototype should be cut open to conduct a thorough inspection of its internal integrity and determine the state of the gas mixture.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗