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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 415 records · Page 23
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Ambient field seismology in critical zone hydrological sciences

Passive ambient noise monitoring is an emerging tool in environmental seismology, leveraging the ambient seismic field to assess temporal variations in shallow subsurface properties. This review focuses on the potential and challenges of using scattered coda waves from noise correlation functions to monitor critical zone dynamics. The sensitivity of seismic velocities to various environmental factors, including precipitation, snowmelt, atmospheric pressure, and groundwater fluctuations, underscores the method’s versatility. While coda waves excel in detecting subtle changes due to their scattered nature, ballistic waves provide higher spatial resolution, albeit with challenges in source stability. Advances in seismic sensing, including distributed acoustic sensing and low-cost geophone networks, have enabled high-resolution monitoring of hydrological processes, subsurface deformation, and seismic hazards. Integrating seismic data with hydrological models provides insights into water storage, pore pressure changes, and soil moisture dynamics. However, limitations in spatial resolution, calibration with ground truth data, and coupled effects between environmental factors remain key challenges. This review emphasizes the importance of interdisciplinary approaches in refining methodologies, enhancing sensor deployments, and addressing data gaps. Passive seismic monitoring offers opportunities to understand critical zone processes and their broader impacts on seismic hazards and environmental sustainability.

58 GEOSCIENCES↗
DOE OSTI2022

Automated cryogenic refilling system

An improved system and method for the automated refilling of cryogenic helium is provided. In one embodiment, the system includes a dewar in fluid communication with a liquid helium cryostat through a cryogen transfer line. A controller regulates operation of a three-way valve to pre-cool the transfer line and to cause gaseous helium to flow to the dewar and force liquid helium through the transfer line into the cryostat. The controller is coupled to the output of a cryogenic level sensor, such that the controller regulates the helium liquid level within the cryostat. During filling cycles, the dewar liquid level is also monitored by the cryogenic level sensor and an alarm sounds if the dewar liquid level is undesirably low. Between filling cycles, the controller is operable to ventilate the dewar through a solenoid vent valve in fixed time intervals to ensure the dewar pressure is sufficiently low so as to not bleed liquid helium into the cryostat.

Ruiz-Rodriguez, Mariano M.↗
DOE OSTI2024

Identifying Controlling Variables for Mercury Vapors in Alpha-4 at Y-12: Two Year Data Collection Update

Multiple sensor packages were deployed at Alpha-4 by SRNL, in collaboration with United Cleanup Oak Ridge LLC (UCOR), to monitor mercury vapor concentrations and meteorological parameters. These sensors collected data, inside and outside of the legacy-use facility, for approximately two years. Though data gaps still exist, particularly in colder months, several controlling variables were identified that govern mercury vapor concentrations within Alpha-4. Temperature, barometric pressure gradients, humidity, and wind speed have been identified as controlling variables. A strong positive correlation was seen between mercury vapor concentrations and temperature which generally followed diurnal fluctuations. Temperatures below approximately 10 degrees Celsius did not show any spikes above the PEL, indicating more work can be performed at any time during the winter months – more data should be collected to confirm consistency in this finding. Additionally, spikes in mercury vapor concentrations above that of the permissible exposure limit (PEL; 100 µg/m 3 ) occurred primarily in late afternoon or evening/overnight hours (between 3 PM and 6 AM), which suggests D&D operations might be best scheduled during morning or daytime hours prior to the late afternoon. However, a limited number of spikes did occur outside of the identified window, although this may be attributed to disturbances in air flow and mercury vapor release from work activities performed inside of the Alpha-4 building. The analysis conducted allows for a strong predictive capability for estimating mercury vapor concentrations based upon accurate meteorological parameters. Still, additional data collection, particularly in the winter months, could help to strengthen the predictive power and validate the identified data trends. Further, increased temporal resolution could also help to better characterize the incipient stages of the increases and decreases in the mercury vapor concentration. Continued monitoring support by SRNL at Y-12 is underway at Alpha-4 to further close remaining data gaps and support deactivation and decommissioning work. Within a collaborative effort with UCOR, the SRNL team is collecting mercury vapor data to study the efficacy of a novel mercury suppressant, FerroBlack® which was recently deployed at Alpha-4. In addition, modifications to the current monitoring setup to increase measurement resolution is also being investigated.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Streamflow measurements from four sites on the Tuolumne River in Yosemite National Park from Water Years 2002 to 2021

Regions with remote and complex terrain experience spatially varying streamflow patterns, but are often poorly sampled due to difficult access. This data package includes streamflow measurements collected using low-visibility and low-impact installations at four sites on the Tuolumne River in Yosemite National Park, for water years 2002 to 2021. The resulting data set offers a unique opportunity to explore hydrologic processes in complex terrain.This data package contains half-hourly recordings of unvented pressure, vented pressure, and water temperature are measured and used to estimate discharge and stage height. Discharge flags provide insight into data anomalies. This dataset is formatted in accordance with ESS-Dive's Hydrologic Monitoring and File Level Metadata Formats. It contains the following files:1) Folder containing four csv files of time series streamflow measurements (unvented pressure, vented pressure, estimated discharge, water temperature, stage height, and discharge flag) from four locations on the Tuolumne River2) Data dictionary (dd.csv) containing units, definitions, human readable column names, and data type for all column headers throughout the dataset3) File-level metadata (FLMD.csv) containing metadata for files contained in the dataset4) Installation methods (InstallationMethods.csv) containing metadata on sensor installation

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Descriptor: High Temporal Resolution Meteorological Data at Oak Ridge Reservation (ORR-HiResMet)

Access to continuous, quality assessed meteorological data is critical for understanding the climatology and atmospheric dynamics of a region. Research facilities like Oak Ridge National Laboratory (ORNL) rely on such data to assess site-specific climatology, model potential emissions, establish safety baselines, and prepare for emergency scenarios. To meet these needs, on-site towers at ORNL collect meteorological data at 15-minute and hourly intervals. However, data measurements from meteorological towers are affected by sensor sensitivity, degradation, lightning strikes, power fluctuations, glitching, and sensor failures, all of which can affect data quality. To address these challenges, we conducted a comprehensive quality assessment and processing of five years of meteorological data collected from ORNL at 15-minute intervals, including measurements of temperature, pressure, humidity, wind, and solar radiation. The time series of each variable was pre-processed and gap-filled using established meteorological data collection and cleaning techniques, i.e., the time series were subjected to structural standardization, data integrity testing, automated and manual outlier detection, and gap-filling. The data product and highly generalizable processing workflow developed in Python Jupyter notebooks are publicly accessible online. As a key contribution of this study, the evaluated 5-year data will be used to train atmospheric dispersion models that simulate dispersion dynamics across the complex ridge-and-valley topography of the Oak Ridge Reservation in East Tennessee.

Steckler, Morgan R. [Oak Ridge National Laboratory↗
DOE OSTI2020

Artificial illumination identification from an unmanned aerial vehicle

Artificial illumination identification within images is a useful tool for many applications. Performing such identification allows for an estimation of the illumination source spectrum, which in turn can be used for additional applications ranging from spectral detection and exploitation to statistics about nighttime light usage. Illumination identification has been performed in laboratory settings but not from an unmanned aerial vehicle (UAV) platform. Here, we test the feasibility of using a UAV and commercial off-the-shelf multispectral imaging sensor to perform such artificial illumination identification through linear discriminant analysis using nighttime UAV images. The results are very promising, showing source classification accuracies of 83.3%, 92.3%, 100%, and 100% for the incandescent, light-emitting diode, high pressure sodium, and metal halide illumination sources, respectively. We show that the information gained from the source identification can be further used to inform additional analysis, such as spectral identification. The high resolution of UAV imaging techniques combined with the knowledge of the illumination source can lead to better exploitation of such nighttime data for many applications.

42 ENGINEERING↗
DOE OSTI2025

Advancing 1D thermo-hydraulic tools for large cryogenic facilities

The Cryogenic Division at Fermilab develops large-scale cryogenic systems for particle accelerators and superconducting magnet test facilities. To support design and diagnostics, a Python-based code was created to calculate pressure drops in components such as valves and pipes. This paper presents recent enhancements to the code, including new heat transfer functions that improve the accuracy of thermal and hydraulic predictions. The first application models pressure and temperature changes in Proton Improvement Plant PIP-II relief pipes, aiding pipe sizing and protecting relief valves. The second example analyses heat load evolution in a pipe carrying sub-atmospheric helium, helping interpret temperature sensor data and understand gas return behavior to cold compressors. These improvements significantly expand the tool's capabilities, offering a practical resource for designing and troubleshooting cryogenic systems under dynamic thermal and flow conditions.

Beckwith, R. [Fermilab]↗
DOE OSTI2022

Cubic-meter scale laboratory fault re-activation experiments to improve the understanding of induced seismicity risks

Abstract To understand fluid induced seismicity, we have designed a large-scale laboratory experiment consisting of a one-cubic-meter sandstone with an artificial fault cut and fluid-injection boreholes. The sandstone block is assembled in a true triaxial loading frame and equipped with 38 piezoelectric sensors to locate and characterise acoustic emission events. The differential stress on the artificial fault is increased in stages to bring it towards a critically stressed state. After each stage of differential stress increase, fluids are injected at low pressures through boreholes to test the potential of fault re-activation. In addition, a high-pressure injection was conducted that created a hydraulic fracture from the injection borehole towards the artificial fault. The newly generated fluid pathway resulted in an activation of the complete block through a stick–slip movement. We compare acoustic emission measurements from the laboratory experiment with seismicity observations from the field-scale CO 2 injection at Decatur, Illinois, U.S., and conclude that the existence of fluid pathways plays a decisive role for the potential of induced seismicity.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

Impact of Time Dependent Reactor and Sensor Physics on Core Power Synthesis

Online synthesis of the power distribution is critical in the operation and control of nuclear power reactors to ensure that the core is operating within safety margins, and to provide essential knowledge associated with the burnup of the fuel. In light water reactors (LWRs), power synthesis is achieved by using some a priori knowledge of the state of the reactor core and updating based on the signals coming from in-core sensors—namely, self-powered neutron detectors (SPNDs). This report aims to study the effects of fuel burnup and sensor degradation on the ability to accurately synthesize the power distribution in a LWR. Several modeling tools were used to simulate power synthesis based on the responses of SPNDs, with emitters made out of Rh or V. A representative pressurized water reactor low-enriched uranium (LEU) core was modeled using the Polaris/Purdue Advanced Reactor Core Simulator (PARCS) approach. The Monte Carlo N-Particle Transport 6 (MCNP6) code was used, as well, to calculate response functions between different segments of fuel to individual SPNDs; this is a crucial parameter for power synthesis. The Oak Ridge Isotope GENeration (ORIGEN) package in the Standardized Computer Analyses for Licensing Evaluation (SCALE) code was used to model the time-dependent isotopic transmutation in the SPND emitters. All these data were fed into a custom code that enacted the point-based iterative (PBI) method to simulate power synthesis. Developmental work was also performed on high-fidelity SPND models in the GEometry ANd Tracking 4 (Geant4) code, which enables higher-accuracy modeling of the current responses from SPNDs. In this work, five sets of time-dependent power synthesis test cases were conducted. In these test cases, systematic changes in the input conditions enabled an analysis of the effect of (1) slightly inaccurate a priori power distribution assumptions with respect to fuel burnup, (2) highly inaccurate a priori assumptions with respect to fuel burnup (such that burnup is not included in the a priori assumed distribution), and (3) differences between Rh and V SPNDs in terms of downstream consequences of the transmutation in the emitters. The authors discovered that one may permissibly have slightly inaccurate a priori assumptions of the fuel burnup (such that the level of burnup may be slightly under- or over-approximated by the accumulated burnup in approximately 9.3 full power days), but to not account for burnup at all in the a priori assumption leads to severe levels of error, approaching 25% at maximum. The authors also discovered that V SPNDs are extraordinarily robust in the low-enriched uranium fuel cycle considered in this modeling work, whereas Rh SPNDs undergo significant transmutation that can result in large errors in the synthesized power distribution.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2023

SATS Enhanced Capabilities and Demonstration of Improved Ramp Rates for In-Cell Testing

This report presents the development of the second-generation Severe Accident Test Station, referred to as SATS 2.0. SATS 2.0 represents a major advancement in addressing critical research needs for the United States nuclear industry, particularly in relation to fuel fragmentation, relocation, and dispersal (FFRD) concerns associated with the nuclear industry’s goal to extend fuel burnup beyond a peak rod average of 62 GWd/tU. The central objective of SATS 2.0 was the deployment a new furnace capable of achieving heating rates up to 100°C/s. This achievement addresses critical capability gaps, enabling assessment of prioritized research objectives established by the Electric Power Research Institute’s (EPRI) Collaborative Research on Advanced Fuel Technologies (CRAFT) working group. These research objectives are directly related to high-burnup loss-of-coolant accident (LOCA) conditions and the effects of prolonged exposure to elevated temperatures, both of which are crucial to enhancing nuclear safety and efficiency. The SATS 2.0 system builds upon prior experience with the original SATS system, which focused on evaluating accident-tolerant fuel (ATF) cladding concepts during accident conditions. However, the new system not only expands upon prior core capabilities by achieving higher heating rates with a better furnace but also plans to incorporate novel auxiliary systems to create a versatile platform for addressing current research needs. For example, a system was developed for the quantification and characterization of fission gas released during high-temperature transients. Additionally, in situ measurement capabilities were developed, such as digital image correlation which enabled the real-time capture of strain related to balloon and burst events and fiber-optic sensors that allowed for high-fidelity characterization of temperature gradients. Demonstration tests of the new 12-lamp furnace achieved heating rates up to 120°C/s. Notably, SATS 2.0 demonstrated its capacity to simulate LOCA burst tests at different pressures, yielding burst data that align with historical empirical models. Moreover, the system exhibited its capability to simulate complex conditions observed in anticipated operational occurrences, while effectively mitigating temperature overshoots. These accomplishments mark significant progress toward overcoming FFRD challenges and advancing the United States nuclear industry's safety basis and technical capabilities for extended burnup.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

EVALUATION OF OPERATION TEMPERATURES UNDER NATURAL CONVECTION HELIUM FLOW IN A CONFINED CAVITY

The Spallation Neutron Source (SNS) is a high-power accelerator-based pulsed neutron source led by Oak Ridge National Laboratory (ORNL) to achieve high fluxes of neutrons for scientific experiments. Active and passive cooling of the systems and parts forming the SNS have been considered to warrant the safe operation of the facility. The diverse cooling systems make use of conjugated heat transfer mechanisms to provide a stable operation temperature for all components in the machine. Thermal power deposited into stainless-steel piping lines due to particle radiation may reach values of up to 1.2 W/cc in the regions located closer to the center of the lower IRP. These energy deposition levels, in not actively cooled components, such as the transfer-line-outer-vacuum-layer may increase the temperature of the component beyond design requirement limitations. The evaluation of the operation temperatures for the former components relies in the assumption that a low-pressure helium atmosphere provides enough heat removal capacity based on natural convection phenomena. In this work, the evaluation of steady state temperatures in components such as the CMS transfer lines has been evaluated using computational fluid dynamics (CFD), analytical correlations and experimental measurements. The companion experiments were conducted in a closed helium system at pressures varying from 1.1 to 1.5 bar. A copper rod was affixed horizontally between viewing windows and heated at constant power, and measurements were made of both the rod temperature and ambient temperature via a system fiberoptic distributed temperature sensors and RTDs. It was found that the measured heat transfer coefficients agree well with the predictions of Churchill and Chu correlations across the range of cases considered. Additionally, the ambient helium volume above the rod was imaged via background oriented schlieren (BOS), and these data was used to determine the line-averaged density gradients in this region. These gradients were compared to simulation data to validate the predictions of natural convection simulations.

Dominguez-Ontiveros, Elvis [ORNL] (ORCID:000000018↗
DOE OSTI2020

Distributed Acoustic Sensing as a Distributed Hydraulic Sensor in Fractured Bedrock

Distributed acoustic sensing (DAS) was originally intended to measure oscillatory strain at frequencies of 1 Hz or more on a fiber optic cable. Recently, measurements at much lower frequencies have opened the possibility of using DAS as a dynamic strain sensor in boreholes. A fiber optic cable mechanically coupled to a geologic formation will strain in response to hydraulic stresses in pores and fractures. A DAS interrogator can measure dynamic strain in the borehole, which can be related to fluid pressure through the mechanical compliance properties of the formation. Because DAS makes distributed measurements, it is capable of both locating hydraulically active features and quantifying the fluid pressure in the formation. We present field experiments in which a fiber optic cable was mechanically coupled to two crystalline rock boreholes. The formation was stressed hydraulically at another well using alternating injection and pumping. The DAS instrument measured oscillating strain at the location of a fracture zone known to be hydraulically active. Rock displacements of less than 1 nm were measured. Laboratory experiments confirm that displacement is measured correctly. These results suggest that fiber optic cable embedded in geologic formations may be used to map hydraulic connections in three-dimensional fracture networks. A great advantage of this approach is that strain, an indirect measure of hydraulic stress, can be measured without beforehand knowledge of flowing fractures that intersect boreholes. The technology has obvious applications in water resources, geothermal energy, CO 2 sequestration, and remediation of groundwater in fractured bedrock.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Tethered Balloon System Ozone Profiles during CoURAGE Summer Intensive Operational Period Field Campaign Report

During the summer IOP, the small ARM field campaign CRGTBSO3 collected measurements to gain an improved understanding of differences between the atmospheric composition in and just above the marine layer at the CoURAGE TBS site near the eastern shore of Chesapeake Bay. CRGTBSO3 included guest instrumentation with ozone (O 3 ) profile measurements on the TBS and surface O3 and meteorological measurements at the TBS site. An En-Sci 2Z electrochemical cell (ECC) ozonesonde (Komhyr 1969, 1986, Witte et al. 2018) was included on the TBS. The ozonesonde was connected to an InterMet iMet-4RSB radiosonde, and the overall data collected included vertical profiles of ozone, relative humidity, temperature, pressure, and altitude. The CRGTBSO3 iMet-4 radiosonde data is identical to that of the iMet in the Tethered Balloon System Merged Data Product (TBSMERGED; Gaustad and Dexheimer 2025). The TBSMERGED data product also includes meteorological data from a different sensor, the iMet XQ2. In some cases, the iMet XQ2 relative humidity (RH) data may be more accurate than the iMet-4, such as for some instances when the iMet-4 RH data stays at 100% for an extended period throughout a profile.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

JHTDB-wind: a web-accessible large-eddy simulation database of a wind farm with virtual sensor querying

This paper introduces JHTDB-wind (https://turbulence.idies.jhu.edu/datasets/windfarms, last access: 11 November 2025), a publicly accessible database containing large-eddy simulation (LES) data from wind farms. Building on the framework of the Johns Hopkins Turbulence Database (JHTDB), which hosts direct numerical simulation (DNS) and some LES datasets of canonical turbulent flows, JHTDB-wind stores the 4D space–time history of the flow and provides users the ability to access and query the data via a web-based virtual sensor interface. The initial dataset comprises LES results from a large wind farm with 10×6 turbines, modeled using a filtered actuator line method, under conventionally neutral atmospheric conditions. These data comprise 1 h (hour) of flow field data (velocity, pressure, potential temperature deviation, subgrid-scale (SGS) eddy viscosity, and turbine forces, approximately 15 TB (terabytes) and wind turbine data – including both turbine-level operational quantities and blade-level aerodynamic quantities (approximately 1.3 TB) – stored in Zarr and Parquet formats, respectively. Data retrieval is facilitated by the giverny Python package, allowing remote users to query the database in Python or MATLAB (C and Fortran support are available for flow field data). This paper details the simulation setup and demonstrates data access through examples that analyze wind farm flow structures and turbine performance. The framework is extensible to future datasets, including the JHTDB-wind diurnal cycle simulation analyzed in Xiao et al. (2025).

17 WIND ENERGY↗
DOE OSTI2025

Leveraging artificial intelligence and advanced food processing techniques for enhanced food safety, quality, and security: a comprehensive review

Artificial intelligence is emerging as a transformative force in addressing the multifaceted challenges of food safety, food quality, and food security. This review synthesizes advancements in AI-driven technologies, such as machine learning, deep learning, natural language processing, and computer vision, and their applications across the food supply chain, based on a comprehensive analysis of literature published from 1990 to 2024. AI enhances food safety through real-time contamination detection, predictive risk modeling, and compliance monitoring, reducing public health risks. It improves food quality by automating defect detection, optimizing shelf-life predictions, and ensuring consistency in taste, texture, and appearance. Furthermore, AI addresses food security by enabling resource-efficient agriculture, yield forecasting, and supply chain optimization to ensure the availability and accessibility of nutritious food resources. This review also highlights the integration of AI with advanced food processing techniques such as high-pressure processing, ultraviolet treatment, pulsed electric fields, cold plasma, and irradiation, which ensure microbial safety, extend shelf life, and enhance product quality. Additionally, the integration of AI with emerging technologies such as the Internet of Things, blockchain, and AI-powered sensors enables proactive risk management, predictive analytics, and automated quality control. By examining these innovations' potential to enhance transparency, efficiency, and decision-making within food systems, this review identifies current research gaps and proposes strategies to address barriers such as data limitations, model generalizability, and ethical concerns. These insights underscore the critical role of AI in advancing safer, higher-quality, and more secure food systems, guiding future research and fostering sustainable food systems that benefit public health and consumer trust.

AI↗
DOE OSTI2025

Ultralow-temperature cryogenic transmission electron microscopy using a new helium flow cryostat stage

Advances in cryogenic electron microscopy have opened new avenues for probing quantum phenomena in correlated materials. This study reports the installation and performance of a new side-entry condenZero cryogenic cooling system for JEOL (Scanning) Transmission Electron Microscopes (S/TEM), utilizing compressed liquid helium (LHe) and designed for imaging and spectroscopy at ultra-low temperatures. The system includes an external dewar mounted on a vibration-damping stage and a pressurized, low-noise helium transfer line with a remotely controllable needle valve, ensuring stable and efficient LHe flow with minimal thermal and mechanical noise. Performance evaluation demonstrates a stable base temperature of 4.37 K measured using a Cernox bare chip sensor on the holder with temperature fluctuations within ±0.004 K. Complementary in-situ electron energy-loss spectroscopy (EELS) via aluminum bulk plasmon analysis was used to measure the local specimen temperature and validate cryogenic operation during experiments. The integration of cryogenic cooling with other microscopy techniques, including electron diffraction and Lorentz TEM, was demonstrated by resolving charge density wave (CDW) transitions in NbSe2 using electron diffraction, and imaging nanometric magnetic skyrmions in MnSi via Lorentz TEM. In conclusion, this platform provides reliable cryogenic operation below 7 K, establishing a low-drift route for direct visualization of electronic and magnetic phase transformations in quantum materials.

Charge density wave↗
DOE OSTI2025

A sensing material-free and simple readout MEMS sensor for detecting Helium

Abstract In this work, we report a method that enables a standard electrostatic MEMS device to perform complex sensing functionalities, such as detecting the presence of helium without a sensing material or a conditioning circuit. Helium is a noble, odorless, non-reactive gas that is very challenging to detect. It is used in critical applications such as storing nuclear fuel waste inside a dry cask. In these applications, its leakage from the dry cask may indicate the cask's safe operation's degradation. A departure from the common practice of exciting the MEMS around its mechanical resonance, the method is based on exciting the MEMS around its electrical resonance circuit. This method shows that the tiny difference between the air dielectric constant (1.00059) and helium (1.000067) corresponding to only a few Femtofarad level capacitances produces a 25 mV difference without a conditioning circuit. Simulation results confirmed those findings and explored the sensor response at different operation conditions. This method eliminates the need for a heated microstructure and the need for absorption material. This method is not limited to gas sensing. It can be applied to other sensing mechanisms, such as acceleration and pressure measurements, and eliminate the complex circuit to read small capacitance in these applications.

Mohaidat, Sulaiman↗
DOE OSTI2022

Online Lead/Water Heat Exchanger Sensor/System Feasibility-PNNL (Final Report)

On-line structural health corrosion monitoring in advanced lead fast reactor heat exchangers and molten salt reactor heat exchangers is desirable for detecting tube degradation prior to leaks that may allow mixing of heat exchanger fluids or release of radiological contamination beyond the design containment boundary. This program, On-Line Lead/Water Heat Exchanger Sensor/System Feasibility – PNNL 76092, demonstrates feasibility for an ultrasonic torsional wave mode sensor attached to the outside of a long (30.5-m) heat exchanger tube in the stagnant flow area where the tube joins a heat exchanger plenum and where it is possible to protect a sensor and cable from high-force flows. The sensor must be cable connected to a monitoring instrument near the heat exchanger. The sensor and cable management approach for periodic in-service inspection will be impractical to implement on existing heat exchangers; rather permanently mounted sensors must be installed in conjunction with heat exchanger fabrication. Previous work has shown low-temperature lead zirconate titanate (PZT) piezoceramic sensors are able to detect anomalies of interest in 3.0-m long tubes. These sensors have hereby been extended to a 30.5-m long tube more representative of commercial power heat exchanger designs. The program will continue to investigate higher temperature piezoelectric ceramics and long-term performance of high temperature adhesives and sealants and mechanical pressure coupling for 350-500 °C lead reactor environments and higher temperature (700 °C) molten salt environments.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗