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At least 145 records · Page 8

Miniature Crack or Damage Detection on Cable Insulation and Jacket Using Conformal Surface Wave Reflectometry

This letter introduces the study and application of a conformal surface wave launcher array to detect miniature insulation and/or jacket damage on unshielded cables. Here simulation and experimental results are presented that demonstrate that with the proposed concept very small instances of damage at various distances along power cables can be detected. Effects of damage detection feasibility in the presence of other cables in proximity and for cables containing semiconducting screen are also presented.

42 ENGINEERING↗

Optical Fiber Sensor with a Hydrophobic Filter Layer for Monitoring Hydrogen under Humid Conditions

Real-time and remote monitoring of hydrogen concentration in underground hydrogen storage reservoirs is crucial to maintaining the integrity and safety of the storage facilities. High humidity in the underground deposits interferes with hydrogen sensors, introducing inaccuracy into the hydrogen sensing measurements. A hydrophobic filter layer over a hydrogen sensing layer on an optical fiber hydrogen sensor was devised to minimize the impact of the humidity on the sensor. The hydrogen sensor coated with a hydrophobic filter layer demonstrated a significant improvement in reliable hydrogen sensing under high humidity conditions (99% RH) without severe baseline drift and reduction of transmission intensity. Finally, the optical fiber hydrogen sensor revamped with the filter layer would enable the reliable measurement of hydrogen concentration under the humid conditions expected in subsurface hydrogen storage facilities.

08 HYDROGEN↗

Y-12 Groundwater Protection Program Monitoring Well Inspection and Maintenance Plan

This plan describes the systematic approach for: inspecting the physical condition of monitoring wells at Y-12, determining maintenance needs that extend the life of a well, and identifying those wells that no longer meet acceptable monitoring well design or well construction standards and require plugging and abandonment. The inspection and maintenance of groundwater monitoring wells is one of the primary management strategies of the Y-12 Groundwater Protection Program (GWPP) Management Plan, that is, the “proactive stewardship of the extensive monitoring well network at Y-12" (Consolidated Nuclear Security, L.L.C. [CNS], 2018). Effective stewardship, and a program of routine inspections of the physical condition of each monitoring well, ensures that representative water-quality samples and hydrologic data are obtained from the well network and protects the subsurface environment. In accordance with the Y-12 GWPP Monitoring Optimization Plan (MOP) for Groundwater Monitoring Wells at the Y-12 National Security Complex, Oak Ridge, Tennessee (CNS, 2017), the status designation (active or inactive) for each well determines the scope and extent of well inspections and maintenance activities. This plan, in conjunction with the above document, formalizes the GWPP approach to focus available resources on monitoring wells which provide the most useful data, and for that reason the GWPP inspects and performs maintenance on the wells sampled by the GWPP. This plan applies to groundwater monitoring wells installed at Y-12 and the related waste management facilities located within the three hydrogeologic regimes: (1) the Bear Creek Hydrogeologic Regime (Bear Creek Regime), (2) the Upper East Fork Poplar Creek Hydrogeologic Regime (East Fork Regime), and (3) the Chestnut Ridge Hydrogeologic Regime (Chestnut Ridge Regime). The Bear Creek Regime encompasses the section of Bear Creek Valley (BCV) immediately west of Y-12. The East Fork Regime encompasses most of the Y-12 process, operations, and support facilities in BCV west of Scarboro Road. The Chestnut Ridge Regime is directly south of Y-12 and encompasses a section of Chestnut Ridge that is bounded to the west by a surface drainage feature (Dunaway Branch, located immediately west of Industrial Landfill II) and by Scarboro Road to the east. The GWPP maintains an extensive database of geographic and construction details and related information for the monitoring wells in each hydrogeologic regime in the Updated Subsurface Database for Bear Creek Valley, Chestnut Ridge, and Parts of Bethel Valley on the U.S. DOE Oak Ridge Reservation (CNS, 2019). A detailed description of the hydrogeologic framework at Y-12 can be found in the GWPP Management Plan (CNS, 2018).

54 ENVIRONMENTAL SCIENCES↗

Monitoring and modeling hydrologic conditions in Ukraine for hydropower generation

Study region: The Dnieper and Dniester Rivers of Ukraine. Study focus: The ongoing conflict in Ukraine has caused disruptions to electricity generation, of which hydroelectric sources contribute approximately 9 % to the country’s needs. With the takeover of the Zaporizhzhia nuclear power plant by enemy forces, the loss of the Kakhovka hydroelectric dam, and the future impacts of the conflict on electricity generation unclear, it may be valuable for the Ukrainian government to better understand how it could leverage hydroelectric power sources in the near future. Unfortunately, measurements of river discharge throughout Ukraine ceased data collection in the late 1980’s to early 1990’s. To address this data gap, we developed a protocol that combined satellite-based time-series measurements of river width at seven locations throughout Ukraine from 2013 to 2023 with reanalysis data, climate-model predictions, and hydrologic models to both provide a means of monitoring a proxy for near-real-time discharge and also predict near-term (i.e., 2023–2030) hydrologic patterns for the region. New hydrological insights for the region: We ran new algorithms on 144 WorldView-2 and WorldView-3 satellite images to map rivers and extract width, one of which was validated against river gauge data located along the same river but in a neighboring country. Hydrologic models using two climate scenarios found minimal change in annual discharge at all sites, but magnitude and timing of peak discharge showed a moderate trend. The results suggest that hydropower is underutilized in Ukraine.

13 HYDRO ENERGY↗

Laser ablation spectrometry for studies of uranium plasmas, reactor monitoring, and spent fuel safety

Nuclear security is one of the defining challenges of our time. Nuclear threats range from deliberate dispersal of radioactive material to contaminate the vital infrastructure to diversion and smuggling of special nuclear material for clandestine nuclear programs and nuclear terrorism, respectively. There is an associated need to develop and sustain the nuclear forensics capabilities, which requires the understanding of complex processes that occur in plasmas of nuclear materials. The area of nuclear safety has seen a resurgence of public interest, and there is a concomitant need to safely store used nuclear fuel and detect structural material failure in nuclear power systems, especially in innovative reactor designs envisioned for future adoption. Laser-produced plasmas are complicated extreme environments that can generate intense and rich, highly specific signatures of nuclear and radiological materials, which can then be explored in a wide range of applications. They include interdiction and rapid detection of nuclear materials, including their isotopic composition, detection over long distances, laboratory simulation of weapons effects, monitoring the condition of structural materials in dry cask storage containers, and novel instrumentation for nuclear power systems. We present a compilation of recent representative examples of the application of laser spectroscopy, and laser-induced breakdown spectroscopy in particular, to nuclear safety and security problems. A case is made that spectroscopic techniques based on laser-produced plasmas offer complementary, and sometimes unique, capabilities that motivate the continued exploration of their efficient production and understanding of the signatures they produce

(020.3260) Isotope shifts, (140.3440) Laser-induce↗

Hanford Tank Vapors in Worker Breathing Zones - Source, Dispersion, and Receptor Data - 20373

A wide range of organic and inorganic chemicals from historical Hanford Site processes are now stored in 177 underground storage tanks at the Hanford tank farms. Workers at the Hanford tank farms have expressed concerns about chemical vapor exposures for many years. During the spring of 2014, worker reports of chemical odors and/or symptoms prompted the development of the Savannah River National Laboratory Hanford Tank Vapor Assessment Team (TVAT) and their resulting independent assessment and recommendations concerning tank farm worker reports of vapors. The Tank Vapor Assessment report included a hypothesis that 'vapors coming out of tanks in high concentration (bolus) plumes sporadically intersected with the breathing zones of workers, resulting in brief but intense exposures to some workers.' The focus of this effort is to present current knowledge to describe the mechanisms by which workers may experience short duration vapor concentrations above background in the tank farms environment. The TVAT hypothesis that workers have experienced concentrations approaching 80% of the tank headspace up to 3 meters (10 feet) from tank sources is not supported by sampling data or modeling results. Modeling indicates that concentrations are quickly reduced from the source, and that the upper end of predicted concentrations at worker breathing zones are a factor of 10 or more lower than source concentrations. Area measurements corroborate the fact that worker breathing zone concentrations are 10 to 100 times lower than source concentrations, and events with elevated concentrations are rare. These reduced vapor concentration levels may result in detectable odors or irritation, depending on a worker's specific odor threshold and sensitivity to the chemical species. Short-duration vapor events may be mitigated by evaluating daily atmospheric conditions in conjunction with planned tank farm activities. Monitoring changing conditions related to tank vapors concentrations at the source and within worker breathing zone is also an important step to protect workers from short duration elevated concentration events. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Selection of Components for the Remote, Canister-Monitoring System

This report documents the selection of components as part of the efforts initiated to develop a remote, canister-monitoring system (RCMS) for determining and monitoring environmental conditions within dry fuel storage canisters containing aluminum clad spent nuclear fuel (ASNF) at the Idaho National Laboratory (INL). These efforts are in support of Department of Energy Office of Environmental Management (DOE-EM) investigations into technical issues associated with extended dry storage (50+ years) of ASNF. The capability to establish and monitor the performance of ASNF in situ provides the opportunity to (1) evaluate the appropriate technologies for monitoring, (2) collect canister environment conditions as soon as possible, (3) verify and validate current laboratory-based study results and analytic modeling approaches, and (4) potentially identify additional dry storage options for ASNF at the INL site. The improved understanding of ASNF behavior gained by performing this work would also contribute to the safety basis for extended dry storage in current and future configurations as well as to provide information for future transportation, conditioning, and disposal of ASNF. The parameters to be monitored by the RCMS include temperature, relative humidity, hydrogen gas concentration and radiation environment (dose). Components are selected based on the expected environmental conditions within the canister and fuel storage area, and the desired performance of the RCMS. Several of these components have been purchased and received. Future activities include component testing and calibration, software development for operation of the integrated sensor module and fabrication of a representative test volume. The results of these tests and changes to desired performance characteristics will inform subsequent activities.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Automatic Calibration and Health Monitoring of Infrastructure Sensors

Smart transportation infrastructure relies on networks of heterogeneous sensors - cameras, radars, and lidars - continuously monitoring traffic conditions. However, executing the initial spatial calibration of multiple sensors and the subsequent health monitoring presents significant operational challenges. Environmental factors, mechanical vibrations, and gradual drift cause spatial misalignment, degrading fusion performance and tracking accuracy. Traditional calibration approaches require manual intervention with specialized targets or survey equipment, resulting in service interruptions and high maintenance costs. This work presents an automated framework for initial calibration and continuous health monitoring without human intervention or service disruption. Our approach addresses two critical problems: (1) detecting when sensors become miscalibrated during operation, and (2) automatically re-establishing spatial alignment using only operational traffic data. The health monitoring component analyzes measurement innovations - differences between sensor observations and predicted object states - to detect systematic biases indicative of calibration drift. By computing bias magnitude, directional consistency, and rejection rates, the system identifies miscalibrations as small as 0.5 meters. Unlike traditional methods requiring known calibration targets, our diagnostic operates continuously on live traffic observations, enabling early detection before fusion quality degrades. The automatic recalibration algorithm leverages overlapping sensor fields-of-view and temporal correlation of vehicle observations. Using graph-based optimization, the system automatically discovers which sensor pairs observe common regions, estimates pairwise spatial transformations using RANSAC-based robust estimation, and jointly optimizes all sensor poses through bundle adjustment. The framework handles practical deployment challenges, including different sensor sampling rates (1-10 Hz), varying installation positions, unknown orientations, and limited overlap regions (>10%). When approximate sensor positions are available from installation surveys (+/-1m accuracy), the algorithm additionally estimates sensor orientations, refining both position and rotation to sub-meter and sub-degree accuracy. We validate the framework on multi-hour traffic datasets from six heterogeneous sensors with sampling rates ranging from 1 Hz to 10 Hz. Results demonstrate successful calibration even with sparse overlap (<20%) and automatic detection of miscalibrations exceeding 0.8 meters. This work enables a "deploy-and-forget" sensor infrastructure that maintains calibration autonomously, reducing maintenance costs while improving tracking accuracy. The techniques generalize beyond transportation to any multi-sensor monitoring application requiring robust spatial alignment, including smart cities, industrial monitoring, and surveillance systems.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Online Monitoring System for Concrete Structures Affected by Alkali-Silica Reaction

This report presents a comprehensive study of developing ultrasonic wave and acoustic emission (AE) techniques for long-term monitoring of alkali-silica reaction (ASR) development in concrete. Small, medium, and full-scale concrete specimens were cast, conditioned, and monitored for various periods, from at least one year to 2.4 years. The reactive concrete specimens contain coarse or fine reactive aggregates to study the effects of different types of reactive aggregates. Confinements were also designed to simulate the 2-dimensional confinement effects of reinforcement in the shield building of nuclear power plants. The concrete specimens were stored in a environmental chamber with high humidity and high temperature to accelerate the ASR development. The ultrasonic monitoring data shows high sensitivity to ASR development and could detect cracking initiation well before visible surface cracks occurred. However, the linear ultrasonic analysis based on wave velocity is strongly affected by temperature variation. Therefore, a nonlinear ultrasonic method was proposed to measure thermally induced nonlinear acoustic responses of concrete (thermal modulation of ultrasonic wave). The measured nonlinear acoustic parameter shows a high correlation with ASR expansion across specimens with different reactive aggregates and confinement conditions. The same conclusion was obtained from nonlinear resonance tests on small concrete prisms. Compared to the linear acoustic methods, the nonlinear tests show high sensitivities to ASR damage from internal microcracking initiation at the early stage to visible cracks at the late stage of ASR. The attributes of the thermal modulation of nonlinear ultrasonic method include high sensitivity, immunity to temperature effects, and strong correlation with ASR expansion, which demonstrate great potentials of the nonlinear ultrasonic method for diagnosis of ASR damage and prediction of concrete deterioration process. Acoustic emission is a passive sensing technique for damage assessment, and access to only one surface is needed even for thick and heavily reinforced elements such as the walls utilized for nuclear shield building. Additionally, relatively few sensors are required to monitor the progression of the damage process. Results indicate that the AE data can be related to the damage rating index, which is a petrography-based means of assessing damage due to ASR in reinforced concrete. Furthermore, AE is capable of detecting ASR damage long before surface cracking is visually noticeable. Boundary conditions play in important role in the progression of ASR damage and differences in boundary conditions are reflected in the AE data. Entropy based data assessment methods provide a means to assess the damage state, and convolutional neural network based data assessment provided a means to assess the damage state in real-time. Results indicate that artificial neural network models may be used as a means to predict volumetric expansion based on AE data.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Open data sets for assessing photovoltaic system reliability

Photovoltaic (PV) systems have become a cornerstone of renewable energy strategies, particularly due to the significant reduction in solar power costs over the past decade. However, the long-term reliability of PV installations presents a persistent challenge, requiring the development of advanced monitoring and predictive maintenance strategies. A wide range of data types is used to evaluate the health of PV systems, including environmental conditions, electrical performance, and inspection imagery. These data enable methodologies such as machine learning (ML) models for lifetime prediction and computer vision techniques for defect detection. However, the acquisition of high-quality and comprehensive data is difficult, particularly in terms of long-term consistency and data variety. Publicly available data sets serve as valuable resources for addressing these challenges, but they often suffer from fragmentation and are difficult to access. This paper presents a comprehensive review of existing open-source data sets related to PV degradation, analyzing their features, functionalities, and potential applications. We categorize these data sets based on the specific aspects of PV system information they cover, such as environmental conditions, operational monitoring, image inspection and module materials, and propose relevant tools and ML models for processing them. In addition, we propose practices for future data collection and usage, while also discussing potential directions in data-driven research. Our aim is to enhance data utilization and publication among researchers and industry professionals, promoting a deeper understanding of the role of data in enhancing the performance and durability of PV systems.

14 SOLAR ENERGY↗

Embedded sensors integrated into critical components for in situ health monitoring of steam turbines

Operational flexibility is desired in today’s coal-fired power plants to balance power grids by compensating for the variable electricity supply from renewable energy sources and distributed gensets. This demanding requirement accelerates materials degradation and makes in-situ health monitoring essential. Life monitoring of components and subsystems is thus seen as essential in assessing material and mechanical behavior to estimate system reliability, move to a conditionbased maintenance strategy and determine time to failure of the units in their actual operating conditions. Vibration monitoring can be exploited for blade tip timing to measure blade vibration amplitude and tip clearance to detect any deterioration taking place in the condition of steam turbine blades. A failure of a rotating blade can lead to severe turbine damage followed by extensive repairs and loss of power production. A blade vibration monitoring system can help early detection of abnormal blade vibration behavior. In conjunction with a health monitoring system, the vibration characteristics can be analyzed to support a pro-active maintenance and inspection schedule. While the feasibility of this inspection technique has been amply demonstrated, there is a need to install induction probes to magnetize the blade for signal output. Siemens, in partnership with Raytheon Technologies Research Corporation (RTRC), proposes a holistic approach to develop embedded sensors to utilize radio frequency for not only coupling to sensors, but as the sensing modality. The goal of this project is to “embed” the novel sensing approach by using either additively manufactured or extruded waveguides on rotating blades for recording, evaluation and monitoring of blade vibrations in Low Pressure turbines, with applications extending to aero engines

01 COAL, LIGNITE, AND PEAT↗

Evaluation of Digital Twin Modeling and Simulation

A digital twin has intelligent modules that continuously monitor the condition of the individual components and the whole of a system. Digital twins can provide nuclear power plants (NPP) operators an unprecedented level of monitoring, control, supervision, and security by contributing a greater volume of data for more comprehensive data analysis and increased accuracy of insights and predictions for decision making throughout the entire NPP lifecycle. NPP operators and managers have historically relied on limited, second hand or incomplete data. With proper implementation, digital twins can provide a central hub of all intel that allows for a multidisciplinary view of an NPP. This equips operators and managers with the ability to have more information, context, and intel that can be used for greater granularity during planning and decision making. Digital twins can be used in many activities as the technology has many different concepts surrounding it. From the various definitions of a digital twin within the industry, digital twins can be differentiated by levels of integration/automation. The three main models include digital model, digital shadow, and digital twin. Digital twins offer many potential advancements to the nuclear industry that could reduce costs, improve designs, provide safer operation, and improve their overall security.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Vibration Analysis - Presented to the MMWG Predictive Maintenance User’s Group [Slides]

Vibration Analysis monitors the condition of rotating equipment by focusing on the mechanical vibration the equipment transmits. For very little investment (a few thousands) you can protect millions of dollars of assets. Vibration Analysis is used to monitor fans, pumps, motors, compressors, chillers, and fixed structures. It is used to detect bearing problems, belt problems, bent shaft, misalignment, oil whirl, resonance, cavitation, recirculation, gear problems, mechanical looseness, sheave problems, unbalance, and some electrical problems including broken rotor bars and loose stators.

42 ENGINEERING↗

Is satellite Sun-Induced Chlorophyll Fluorescence more indicative than vegetation indices under drought condition?

Droughts represent one of the most severe abiotic stress factors that could result in great crop yield loss. Numerous vegetation indices have been proposed for monitoring the vegetation condition under stress and assessing drought impacts on yield loss. However, the understanding and comparison between traditional vegetation indices (VIs) and the newly emerging satellite Sun-Induced Chlorophyll Fluorescence (SIF) for monitoring vegetation condition is still limited especially under drought stress and at multiple spatial scales. In this study, the potential of satellite observation SIF for monitoring corn response to drought was investigated based on the 2012 drought in the US Corn Belt. The standardized precipitation evapotranspiration index (SPEI) was used here to quantify drought. We found that all SPEI were above –1, except for July (–1.27), August (–1.39) and September (–1.14) in 2012, indicating the severity of this drought. We examined the relationship between satellite measurements of SIF, SIF yield , VIs (e.g., NDVI and EVI) and SPEI. Results indicated that SIF yield was sensitive to drought and SIF captured the stress more accurately both at the regional and state scales for the US Corn Belt. Quantitatively, SIF yield had a high correlation with SPEI (r = 0.987, p < 0.05) over the entire Corn Belt, and it indicated losses in response to drought approximately one month earlier than SIF/NDVI/EVI. Furthermore, our results demonstrated that SIF could be trusted as an effective indicator to study the relationship between GPP (R 2 ≥ 0.8664, p < 0.01) under drought conditions across the Corn Belt. Finally, this study highlighted the advantage of using satellite SIF observations to monitor the drought stress on crop growth especially GPP at regional scale.

54 ENVIRONMENTAL SCIENCES↗

Architecture and Component Selection for the Remote Canister-Monitoring System

This report documents the selected system architecture and components surveyed for the development of a remote, canister-monitoring system (RCMS) for determining and monitoring environmental conditions within dry fuel storage canisters containing aluminum-clad spent nuclear fuel (ASNF) at Idaho National Laboratory (INL). These efforts are in support of the Department of Energy Office of Environmental Management (DOE-EM) investigations into the technical issues associated with extended dry storage (50+ years) of ASNF. It is important to resolve questions regarding storage because the ATR is expected to continue producing approximately 100 elements of spent fuel per year for at least another twenty years. The parameters to be monitored by the RCMS include temperature, relative humidity, hydrogen gas concentration, and radiation environment (dose). Components are selected based on the expected environmental conditions within the canister and fuel storage area and the desired performance of the RCMS. Several of these components have been purchased and are currently undergoing component testing to confirm their suitability for use in delivering the RCMS. Additional components may be identified through the course of design and may be selected in the future. Furthermore, changing performance, interfacing, and compatibility requirements and the results of component testing may necessitate revisiting component selection.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Mercury Speciation During Vitrification of LAW

n this work, laboratory and engineering-scale tests were conducted that mimic the reactive environment of the Hanford Tank Waste Treatment and Immobilization Plant (WTP) low activity waste (LAW) melter and off-gas system in order to assess the speciation of mercury at select points in the processing system. The experimental protocols, test equipment, feed materials used, and rationale for testing are detailed in the Test Plan for this work. Particular attention was paid to the amount and speciation of mercury in submerged bed scrubber (SBS) solutions, which are intended to be recycled back to the melter feed at the WTP. Results are presented from detailed mercury analysis of these solutions using Environmental Protection Agency (EPA) Method 1630 and modifications to this method for dimethyl mercury and methyl mercury as well as EPA Method 1631 and modifications to this method for total, dissolved, elemental, suspended, and ionic mercury. Testing was conducted in two separate sets of experiments: (1) One set of tests (crucible-scale furnace tests) that involved heating small batches of mercury-spiked melter feed in crucibles to determine the amount of mercury retained in the glass and the species of mercury in the exhaust gases; (2) A second set of tests (DM10 melter tests) was planned that involved creating LAW melter plenum gas compositions using the DM10 melter system, injecting mercury into the off-gas stream, and passing that stream though a reactor that simulates various plenum gas conditions. Operational issues led to the need to use one of the VSL DM100 melters in place of the planned DM10 melter for these tests. The speciation of mercury after exposure to those conditions was monitored. In both sets of tests, the exhaust gases were run through a scrubber that was intended to mimic the LAW SBS in order to determine how much of the mercury exiting the melter would be retained in the primary off-gas system fluids and in what form. After passing through the SBS, the exhaust stream was analyzed to determine particulate, ionic, elemental, and total mercury passing downstream of the SBS. In tests employing gases derived from the DM100 melter that were spiked with elemental mercury, the processing system provided gas temperatures and residence times that are representative of the WTP LAW vitrification system in order to assess the effect of those conditions on mercury speciation. The Decontamination Factor (DF) across the system in the tests with mercury-spiked DM100 melter exhaust was determined using the analytical data from EPA Method 30B (Fluegas Adsorption Mercury Speciation (FAMS TM )) exhaust samples and the amount of mercury detected in the SBS solutions. Mercury species used in melter feed crucible scale tests were divalent (chloride and iodide), monovalent (chloride and fluoride), and elemental mercury. Individual tests included only a single form of mercury in the feed. The results for total mercury mass balances in the crucible tests are also presented.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗