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At least 217 records · Page 12

Xenon Detection Using Double-Pulse Laser-Induced Breakdown Spectroscopy

Laser-induced breakdown spectroscopy has been proposed as a diagnostic tool for fuel failure monitoring in helium-cooled fast reactor designs. Here, we show preliminary results which indicate that using double-pulse laser induced breakdown spectroscopy, a sub-ppm sensitivity for xenon in a helium ambient can be achieved. We additionally propose future studies which could help elucidate the mechanisms which lead to the observed signal enhancement.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Streaming Analytics for Anomaly Detection in Large-Scale Data

Anomalous behavior poses serious risks to assured performance and reliability of complex, high-consequence systems. For spaceborne assets and their state-of-health (SOH) telemetry, the challenges of high-dimensional data of varying data types are compounded by computational limitations from size, weight, and power (SWaP) constraints as well as data availability. Automated anomaly detection methods tend to perform poorly under these constraints, while current operational approaches can introduce delays in response time due to the manual, retrospective processes for understanding system failures. As a result, presently deployed space systems, and those deployed in the near future, face situations where mission operations might be delayed or only be able to operate under degraded capabilities. Here, we examine a near-term lightweight solution that provides real-time detection capabilities for rare events and assess state-of-the-art anomaly detection techniques against real SOH telemetry from space platforms. This report describes our methodology and research, which could support more automated capabilities for comprehensive space operations as well as for other resource-constrained edge applications.

97 MATHEMATICS AND COMPUTING↗

Physics-informed neural networks for identification of material properties using standing waves

A metallic structure in its initial stage of failure involves plastic deformation or environmental degradation that changes the elastic modulus and density. This work presents the detection of change in wave velocity (a function of elastic modulus and density) as a system identification problem. A physics-informed neural network (PINN) is proposed to solve the system identification problem. The PINN takes the spatial coordinates of scanning locations and time as inputs and provides the displacement and wave velocity as outputs. The governing partial differential equation of standing waves in a rod is incorporated into the neural network as physics in the form of a loss function. The wave velocity vector is randomly initiated. During the training of the network, physics is used to determine and update the wave velocity target vector from the network’s displacement predictions. The measured data, comprising sparse displacement response on the rod structure, are used to train the PINN. The wave velocity at the sparse locations on the rod is learned from the predicted displacements during the training. Using the predictions of the trained network, the response of free vibration or material property variation can be reconstructed at unscanned locations on the structure to obtain high-resolution maps for full-field imaging to detect and localize the changes caused by plastic deformation. The PINN’s sparse scanning and simultaneous prediction capability during training can lead to high scanning and data-processing speeds. This capability yields a nondestructive evaluation system that can predict the presence of degraded material locations as the structural vibrations are scanned and processed in real time.

Rathod, Vivek↗

Influence of local river hydraulics on Kootenai River white sturgeon ( Acipenser transmontanus ) habitat selection during four spawning years, 2017–2020

Understanding fine-scale habitat selection of endangered Kootenai River white sturgeon ( Acipenser transmontanus) is an important component for monitoring and recovery efforts. Fine-scale habitat selection and quantifying temporal changes in suitable habitat contributes to the work of addressing recruitment failure within the Kootenai River population. Habitat suitability indices were developed using over 96 000 acoustic telemetry sturgeon detections and two-dimensional hydrodynamic model simulations near Bonners Ferry, Idaho, USA. The selected habitat was assessed to develop habitat suitability indices for sturgeon; females undergoing spawn migrations and non-spawners. The most frequented locations were 8–9 m deep and water velocities of 0.3–0.7 m·s −1 . These observations suggest sturgeon with different spawning capabilities selected similar habitat. Weighted usable area was calculated to understand temporal variability in habitat quality, which showed a positive relationship with increases in flow. Results help understand the habitat limiting factors in regulated hydrologic regimes; provide biologists insight for monitoring efforts in discrete habitat conditions; guidance for water managers and the regulation of upstream water resources; and guidance to restoration practitioners for in-stream structure designs.

Dudunake, Taylor J. (ORCID:0000000176502419)↗

Regional Characteristics of Observable Foreshocks

Abstract Measures of foreshock occurrence are systematically examined using earthquake catalogs for eight regions (Italy, southern California, northern California, Costa Rica, Onshore Japan, Alaska, Turkey, and Greece) after imposing a magnitude ≥3.0 completeness level. Foreshocks are identified using three approaches: a magnitude-dependent space + fixed-time windowing method, a nearest-neighbor clustering method, and a modified magnitude-dependent space + variable-time windowing method. The method with fixed-time windows systematically yields higher counts of foreshocks than the other two clustering methods. We find similar counts of foreshocks across the three methods when the magnitude aperture is equalized by including only earthquakes in the magnitude range M*−2≤ M< M*, in which M* is the mainshock magnitude. For most of the catalogs (excluding Italy and southern California), the measured b-values of the foreshocks of all region-specific mainshocks are lower by 0.1–0.2 than b-values of respective aftershocks. Allowing for variable-time windows results in relatively high probabilities of having at least one foreshock in Italy (∼43%–56%), compared to other regional catalogs. Foreshock probabilities decrease to 14%–41% for regions such as Turkey, Greece, and Costa Rica. Similar trends are found when requiring at least five foreshocks in a sequence to be considered. Estimates of foreshock probabilities for each mainshock are method dependent; however, consistent regional trends exist regardless of method, with regions such as Italy and southern California producing more observable foreshocks than Turkey and Greece. Some regions with relatively high background seismicity have comparatively low probabilities of detectable foreshock activity when using methods that account for variable background, possibly due to depletion of near-failure fault conditions by background activity.

Geochemistry & Geophysics↗

Characterization of Rare-earth Doped Thermal Barrier Coatings for Phosphor Thermometry

Thermal Barrier Coatings have been extensively used to protect and insulate the metallic components in turbine engines from extreme environments to achieve higher turbine inlet temperatures, resulting in an increase in combined engine cycle efficiency, lowering NOx emissions and fuel consumption. Additionally, as the major failure mechanisms determining lifetime are thermally activated during engine operation, uncertainty in temperature measurements affects lifetime prediction. Early detection of Thermal Barrier Coatings spallation symptoms, associated with local delamination induced temperature changes, can reduce forced engine outages. Further improvements are envisioned with the development of more reliable measurement techniques. For this purpose, Phosphor Thermometry has been considered a promising method for precision monitoring of turbine blade coatings that contain embedded phosphor dopants. In this work, a modified four-flux Kubelka-Munk model for luminescent rare-earth doped Thermal Barrier Coating configurations supported the design and the fabrication of viable sensing coatings for potential industrial implementation. Phosphor Thermometry instrumentation was developed with the objective of expanding capabilities of the technique, using a synchronized acquisition method on sensing coatings. Experiments on an innovative Erbium-Europium co-doped Yttria-Stabilized Zirconia coating have demonstrated the effectiveness of this advanced Phosphor Thermometry instrument with enhanced sensitivity and extended temperature range. Delamination progression monitoring was achieved for the first time using a Thermal Barrier Coating configuration subjected to indentation that includes a thin luminescent layer deposited on the surface and associating the multi-layer configuration with a predictive model that evaluates the advancement of the degradation of the coatings. To further ensure the integrity of the phosphor doped coatings, synchrotron X-ray diffraction was performed to characterize the specific residual strains and thermal expansion of the materials, determining mechanical robustness and compatibility with state-of-the-art Thermal Barrier Coatings. The outcomes of this work pave the way for in-situ temperature measurements on phosphor-doped turbine blade coatings with increased performance and accuracy.

Fouliard, Quentin↗

Minimum Detectable Quantity Calculation for Radiation Portal Monitors

The minimum detectable quantity of a radiation portal monitor is the smallest amount of radioactive material that can be detected passing through the monitor (with a specified detection probability). The minimum detectable quantity is a function of many factors, including isotope, velocity, distance between pillars, height of portal and vehicle, source distribution and position, background radiation, background suppression, detector volume and positions, detector efficiency, decision metrics and algorithms, the presence of NORM (naturally occurring radioactive material), and alarm thresholds. Experimentally testing a radiation portal monitor to failure for all combinations of these factors is extremely time-consuming and often cost prohibitive. This document outlines a straightforward method for quickly estimating the minimum detectable quantity for moving sources over a large variety of conditions with a minimal number of static measurements. The document also describes a proof of concept software application that the International Atomic Energy Agency has designed based on the described method that can be used by Member States to estimate a monitor’s minimum detectable quantity.

Blessinger, Christopher S.↗

Disk Failure Dataset from the Campaign Storage System

This dataset consists of 1,389 disk (HDD) failure events collected from the Campaign storage system at LANL. The Campaign system supported various compute platforms throughout its lifespan, including Cielo, Fire, Ice, and notably, the Trinity supercomputer. Each recorded event includes its detection timestamp (in ISO 8601 format) and details such as its location within the storage system—rack, enclosure, and drive slot number. The data, spanning from May 4, 2021, to July 25, 2023 (2 years, 2 months, and 22 days), represents failure events from the terminal years of Campaign's operational period, accounting for 26% of its total operational time.

97 MATHEMATICS AND COMPUTING↗

Improvements of pre-emptive identification of particle accelerator failures using binary classifiers and dimensionality reduction

In this paper we look at the properties of the Spallation Neutron Source (SNS) Differential Beam Current Monitor (DCM) data and various methods of data transformation to improve pre-emptive detection of machine trips. In this study, the foundation of the approach is the analysis of new underlying data and understanding various properties with the goal of faster classification, higher precision and higher recall with the aim to reduce false positives as low as required. The result of the research presented in this paper are a binary classifier capable of predicting accelerator failures with millisecond classification time, 96% precision, 58% true positive and 0% false positive rate and optimization techniques enabling real-time implementations.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Enhanced Design of Radiation Tolerant High-Temperature Structural Health Monitoring Sensors

Acoustic emission sensors are vital in the nuclear industry for real-time structural health monitoring and early detection of material degradation. By capturing high-frequency stress waves emitted from defects like cracks, corrosion, or fatigue, acoustic emission sensors enable non-invasive monitoring of critical components such as reactor vessels, piping, and containment structures. This technology supports predictive maintenance, enhances safety, and ensures regulatory compliance by providing early warnings of potential failures. It is also instrumental in research, particularly in material testing reactors, where it is used to monitor the behavior of fuels and materials under irradiation, by allowing the detection of cracking or other acoustic signals in real time. This enables the evaluation of performance and accident behavior of advanced fuel concepts.

46 - INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AN↗

Paleotopography controls weathering of Cambrian-age profiles beneath the Great Unconformity, St. Francois Mountains, SE Missouri, U.S.A.

ABSTRACT Precambrian (1.4 to 1.5 Ga) granite and rhyolite in the St. Francois Mountains at the northeast corner of the Ozark Plateau in Missouri has been altered down to a depth up to 8 meters below the Great Unconformity (the contact between Paleozoic sedimentary rock and underlying Precambrian). Petrographic, geochemical, and mineralogic data indicate that at least two events generated this alteration: 1) surficial weathering due to subaerial exposure of the granite before Cambrian burial—this material is preserved as a paleosol; and 2) alteration due to reaction with basinal fluids channeled along the unconformity from nearby sedimentary basins long after burial by Paleozoic strata. To assess the variation between surficial weathering and basinal fluid alteration, we measured and sampled for petrologic, geochemical, and mineralogic data in the rock at and just below the Great Unconformity at three paleoelevations. Whole-rock geochemical oxide and X-ray diffraction data indicate that K-metasomatism and highly crystalline illite occurred in each profile. The K increase reflects crystallization of authigenic feldspar and illite from basinal fluids that were channeled along the Great Unconformity during younger Paleozoic fluid-flow events. Each profile also exhibits an upward increase in altered feldspar crystals and highly crystalline kaolinite, and an upward decrease in Ca and Na. Such changes reflect soil formation due to reaction with meteoric water before Cambrian burial, indicating that the altered granite was a paleosol before Paleozoic basinal fluid-flow events. Notably, the paleosol at the highest paleoelevation displays the least amount of paleoweathering and the paleosol at the lowest displays the greatest amount of paleoweathering. These results demonstrate that not only can characteristics of the paleosol just below the Great Unconformity be recognized in the St. Francois Mountains, despite subsequent alteration, but also it is possible to detect variations in soil thickness that were controlled by slope steepness and, therefore, water availability and/or soil creep or failure. This spatial relationship is compatible with studies of modern soils which indicate that soil character varies with position on a slope.

Geology↗

SpecFIDLER User Manual: Software Version 2.4.0

The Spectroscopic Field Instrument for Detection of Low Energy Radiation (SpecFIDLER) allows response teams to detect and quantify plutonium contamination on the ground. Notional scenarios include dispersion from a weapon accident, or the launch failure of a space probe containing a radioisotope thermoelectric generator. Unlike other instruments, the thin-window sodium iodide detector is sensitive to the low-energy gamma rays emitted by plutonium isotopes. The system supports both mobile survey as well as stationary sampling. This manual provides information about installing, maintaining, and troubleshooting the SpecFIDLER. The scope of this document includes the physical hardware, software for data acquisition, and algorithms for data analysis. Recent changes to the software and algorithms aim to streamline the operation of the system.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

SpecFIDLER User Manual (Software V.2.5.0)

The Spectroscopic Field Instrument for Detection of Low Energy Radiation (SpecFIDLER) allows response teams to detect and quantify plutonium contamination on the ground. Notional scenarios include dispersion from a weapon accident, or the launch failure of a space probe containing a radioisotope thermoelectric generator. Unlike other instruments, the thin-window sodium iodide detector is sensitive to the low-energy gamma rays emitted by plutonium isotopes. The system supports both mobile survey as well as stationary sampling. This manual provides information about installing, maintaining, and troubleshooting the SpecFIDLER. The scope of this document includes the physical hardware, software for data acquisition, and algorithms for data analysis. Recent changes to the software and algorithms aim to streamline the operation of the system.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

SpecFIDLER User Manual (Software V.2.6.0)

The Spectroscopic Field Instrument for Detection of Low Energy Radiation (SpecFIDLER) allows response teams to detect and quantify plutonium contamination on the ground. Notional scenarios include dispersion from a weapon accident, or the launch failure of a space probe containing a radioisotope thermoelectric generator. Unlike other instruments, the thin-window sodium iodide detector is sensitive to the low-energy gamma rays emitted by plutonium isotopes. The system supports both mobile survey as well as stationary sampling. This manual provides information about installing, maintaining, and troubleshooting the SpecFIDLER. The scope of this document includes the physical hardware, software for data acquisition, and algorithms for data analysis. Recent changes to the software and algorithms aim to streamline the operation of the system.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

SpecFIDLER User Manual (Software V.2.3.0)

The Spectroscopic Field Instrument for Detection of Low Energy Radiation (SpecFIDLER) allows response teams to detect and quantify plutonium contamination on the ground. Notional scenarios include dispersion from a weapon accident, or the launch failure of a space probe containing a radioisotope thermoelectric generator. Unlike other instruments, the thin-window sodium iodide detector is sensitive to the low-energy gamma rays emitted by plutonium isotopes. The system supports both mobile survey as well as stationary sampling. This manual provides information about installing, maintaining, and troubleshooting the SpecFIDLER. The scope of this document includes the physical hardware, software for data acquisition, and algorithms for data analysis. Recent changes to the software and algorithms aim to streamline the operation of the system.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Fiber optic system for direct detection of CO 2 leakage in carbon storage wells (Abbreviated Final Report)

The feasibility study focused on the development of new fiber for distributed chemical sensing that will allow direct detection of CO2 leakages in the environment. This is particularly important for monitoring well integrity for carbon capture and storage (CSS), which can provide early warning for an incoming well failure and potential CO2 leaking through it. We proposed Raman or IR interrogation within gas-filled Holey Fibers (HoFs) interleaved with Fiber Bragg Grating (FBG) sections, so that the location and concentration of the gases would be provided simultaneously. The methodology would overcome current roadblocks to using fiber optics for CO2 (and other gases) detection in wells with direct in-situ measurements of concentration along with other important parameters such as temperature and pressure. We were able to assess commercially available IR/Raman hollow core fiber and demonstrated detection of CO2 through them in our controlled environment setups at various pressure conditions. We have also established the ability of drilling precisely with fs-lases side holes to enable penetration of CO2 into the hollow core fiber and reduce diffusion rates. Open joint collars were also explored with double functionality: to obtain splice to solid core fiber critical for field deployment and create gas ingress locations. Both diffusion-only and pressurized fiber system have been constructed following COMSOL based semi-hybrid optical /fluidodynamics models. FBGs have been identified and procured and characterized. Along the work we leveraged internal modeling/design, photonics/laser characterization, optical fiber fabrication, and AM lab capabilities to design, develop and test in-house components or assemblies. Our results indicate the potential of HoF for CO2 downhole direct detection.

25 ENERGY STORAGE↗

Self-Sensing Composites via an Embedded 3D-Printed PVDF-MoS 2 Nanosensor for Structural Health Monitoring

Carbon fiber (CF)-reinforced epoxy composites are widely used in vehicle applications, where early damage detection is crucial for reliability and safety. To address this need, we developed a self-sensing epoxy/CF composite by embedding a PVDF-MoS 2 nanosensor via an embedded 3D printing method. By harnessing the intrinsic curing kinetics of epoxy, we tailored its rheological properties to optimize the embedded printing process, enabling precise and reliable support for sensor filaments without compromising the composite’s structural and functional integrity. Through comprehensive rheological and kinetic analysis, we established a quantitative relationship among curing temperature, conversion rate, and resulting yield modulus─defining a narrow processing window essential for successful sensor integration. Specifically, we identified that an epoxy yield modulus range of 180–294 Pa and a conversion rate below 10% are critical to support the PVDF-MoS 2 filament architecture. Here, this embedded 3D printing method produces complex and multimaterial PVDF-MoS 2 sensors within an epoxy matrix with minimal deformation and reduced postprocessing, which is scalable and adaptable for industrial applications. Under cyclic loading, the embedded sensors exhibited stable signals under constant loads and increased voltage signals in response to crack formation (17–35% higher) and catastrophic failure (1 order of magnitude higher), effectively capturing structural changes in real time. This study demonstrates the potential of PVDF-MoS 2 nanocomposite sensor materials for real-time structural health monitoring in epoxy–CF composite systems, enabling early detection of defects and stress anomalies, significantly reducing the risk of unexpected failures, and enhancing structural reliability.

PVDF-MoS2 sensor↗

Leveraging Gaussian Mixture Models for Detecting Anomalies in Time-Series Data

Test systems must be capable of classifying measured data as expected or anomalous in real time. Anomalous results may portend system failure, and, if undetected, may result in damage to the unit, test equipment, or potential harm to personnel. This report investigates the use of Gaussian Mixture Models (GMMs) as a clustering tool in classifying time-series data.

Wilke, Rudeger H.T. [Sandia National Laboratories ↗