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At least 523 records · Page 29

FRAM Isotopic Analysis of High-Resolution CZT Data [Slides]

Abstract: H3D Inc. introduced a new type of CZT detectors with resolution several times better than that of a typical CZT; The current FRAM v.6.1 can analyze uranium spectra with minimal modification of the parameter sets and get acceptable results; The exceptionally large high-energy tail of the peaks makes it difficult to achieve good uranium results and impossible to successfully analyze plutonium spectra; The FRAM code needed to be modified to better fit the high-energy tail of the peaks to analyze plutonium data and to get better uranium analysis results.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Small Nuclear Reactors for Maritime Ports

Maritime ports are entering a period of sharply rising electricity demand as operations are electrified, shore power adoption grows, and energy-intensive industries expand near ports. This report evaluates the feasibility of small nuclear reactors at U.S. ports, which could offer stable baseload power and reduced dependence on regional grids. The report describes the current state of advanced reactor technologies and other factors important for future deployment such as safety and operations, siting requirements, regulatory environments and policy, and other co-benefit considerations. A structured evaluation across a diverse group of U.S. ports highlights the wide variation in feasibility. Fifteen ports were analyzed through port interviews and data collection to assess the port-specific conditions that most impact advanced reactor deployment. The analysis found that the most feasible ports for deployment have favorable geotechnical stability, supportive regulatory environments, and substantial energy loads in a grid-constrained environment. Additionally, an initial reactor size matching was done for the ports based on their reported energy consumption across different modes of operation. However, further analysis and detailed data will be required in the future to determine the optimal reactor-port matching. The economic viability to adopt this technology will be dictated by competitive cost of nuclear-generated electricity compared to other alternatives. Overall, small nuclear reactors present a promising but highly site-dependent pathway for ports seeking resilient, high-capacity energy solutions that support future energy demands. This report identifies key areas for future research and highlights ports that warrant further evaluation to assess the viability of small nuclear reactor implementation. By establishing these priorities, the analysis provides support for the development of informed strategies for potential advanced nuclear technology deployment. The inclusion of ports in this report does not imply their endorsement of nuclear energy generation, and the authors are grateful for the information, expertise, and perspectives they contributed.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Strain gauge for testing microreactor hexagonal core blocks in the Single Primary Heat Extraction and Removal Emulator

To support the development and deployment of microreactor technologies, experiments that help verify and validate reactor systems and components are performed at non-nuclear test facilities. The Single Primary Heat Extraction Removal Emulator at Idaho National Laboratory is one of these test facilities and was used to monitor a test article that has a prototypic geometry of a heat-pipe cooled microreactor core block. To collect crucial temperature and strain data during testing, temperature and strain sensing fiber optics were embedded to the surface of the test article using an ultrasonic additive manufacturing technique. To support and provide benchmark strain data for the embedded sensors, a commercial resistive strain gauge was attached. This report will discuss the results from the deployment of the commercial strain gauge which includes the setup/attachment strategies, data acquisition, and analysis of the strain data.

36 MATERIALS SCIENCE↗

Empirical radius formulas for canonical neutron stars from bidirectionally selecting features of equations of state in extended Bayesian analyses of observational data

Significant advancement in Bayesian inference of nuclear equation of state (EOS) from gravitational wave and x-ray observations of neutron stars (NSs) has been made by the nuclear astrophysics community especially since GW170817. By extending the traditional Bayesian analysis which normally ends at presenting the marginalized posterior probability distribution functions (PDFs) of individual EOS parameters and their correlations (or sometimes only the Pearson correlation coefficients which are only reliably useful when the variables are linearly correlated while they are actually often not), we search for a data-driven and robust empirical formula for the radius 𝑅 1.4 of canonical NSs in terms of the characteristic EOS parameters (features). We also identify the single most important but currently poorly known EOS parameter for determining the 𝑅 1.4 . Using three regression-model-building methodologies: bidirectional stepwise feature selection, least absolute shrinkage selection operator (LASSO) regression, and neural network regression on a large set of posterior EOSs and the corresponding 𝑅 1.4 values inferred from earlier comprehensive Bayesian analyses of NS observational data, we systematically and rigorously develop the most probable 𝑅 1.4 formulas with varying statistical accuracy and technical complexity. Here, the most important EOS parameters for determining 𝑅 1.4 are found consistently in each of the feature selection processes to be (in order of decreasing importance): curvature 𝐾 sym , slope 𝐿, skewness 𝐽 sym of nuclear symmetry energy, skewness 𝐽 0 , incompressibility 𝐾 0 of symmetric nuclear matter, and the magnitude 𝐸 sym ⁡(𝜌 0 ) of symmetry energy at the saturation density 𝜌 0 of nuclear matter.

Bayesian methods↗

Tracking Robot Location for Non-Destructive Evaluation of Double-Shell Tanks

(1) Background: Non-destructive evaluation of double-shell nuclear-waste storage tanks at the U.S. Department of Energy’s Hanford site requires a robot to navigate a network of air slots in the confined space between primary and secondary tanks. Situational awareness, data collection, and data interpretation require continuous tracking of the robot’s location. (2) Methods: Robot location is continuously monitored using video image analysis for short distances and laser ranging for absolute location. (3) Results: The technique was demonstrated in our laboratory using a mockup of air slot and robot. (4) Conclusions: Location tracking and display provide decision support to inspectors and lay the groundwork for automated data collection.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Common-Cause Component Group Modeling Issues in Probabilistic Risk Assess

Common cause failures (CCFs) have been recognized as significant risk contributors in probabilistic risk assessments (PRAs) for commercial nuclear power plants (NPPs) since 1980s. A series of reports including those of United States Nuclear Regulatory Commission (NRC) regulations (NUREGs) have been published from late 1980s to early 2000s to provide guidelines for performing CCF event data analysis and modeling CCF in PRA. However, there are still some issues existed in CCF modeling and CCF parameter estimations. One of such issues is the modeling of multiple common-cause component group (CCCG) for the same component in a PRA model. This paper exams the CCCG definition and the requirements from the PRA standard, investigates the CCCG modeling practices and issues existing in PRAs, and presents systematic approaches and guidelines to model CCCG in PRA properly and consistently.

99 GENERAL AND MISCELLANEOUS↗

Quick Look Report of Godiva U233 shot March 2022 Data Collection Activities

This report discussing the March 2022 irradiation of U233 on the Godiva critical assembly using burst mode and subsequent analysis of the fission products starting at 65 minutes post irradiation, and ending 12 days later. The Short-Lived Fission Product Yield (SLFPY) project is one of many efforts under the Nuclear Physics Multi-Lab and related Venture Project. The objective of the SLFPY project is to provide improved measurements of fission product yields for select nuclides. The SLFPY project consists of measurement and analysis campaigns. To produce fission data, samples of actinide material are irradiated in a high-flux neutron environment. These samples are quickly placed in front of a detection system where both gamma singles and coincidence spectra are collected as a function of time. Gamma spectroscopy is performed on the irradiated material on site near the irradiation facility, starting as soon as feasible after the irradiation and continuing for 7 days or longer. Following the data collection, time-dependent fission yield analyses are performed using gamma-ray spectroscopy. This document summarizes the measurement campaign performed March 21 - April 4, 2022 where sub-gram quantities of 233 U nitrate (UO 2 (NO 3 ) 2 ) were irradiated in the Godiva reactor. The Godiva burst #2076 conducted under experiment IER 504 had a temperature change of +156 degrees Celsius, lasted 13.32 microseconds, and had a reactivity of $\$$1.089. The targets consisted of uranium oxide solution deposited in a quartz tube and packed with quartz wool. The flame-sealed quartz ampoules were used to contain the uranium samples for the irradiation and count activities. On March 22, 2022, at 10:27:00 a.m. the three uranium ampoules, along with a witness foil pack, were irradiated in the Godiva critical assembly using burst mode operations.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Probing the influence of ion-pairing on ligand-field excited-state dynamics

Exploration of the photophysical and photochemical properties of transition metal complexes has driven ground-breaking advancements in solar energy conversion technologies, including photoredox catalysis. While significant research has been devoted to understanding excited state properties of second- and third-row transition metal complexes, earth-abundant first-row metal complexes have received comparatively little attention in this context until very recently. In particular, the role of ion-pairing – which has been identified as a potentially significant factor for Ir(III)-based photosensitizers – has not been examined with regard to its influence on the ligand-field excited states that dominate much of first-row photophysics. A key challenge in studying ion-pair interactions lies in quantifying the extent and nature of ion-pairing, particularly in non-aqueous media where the vast majority of photophysical studies are performed. Cobalt(III) polypyridyl complexes provide an attractive platform to address such questions due to their demonstrated potential for applications in photoredox catalysis involving ligand-field excited states. In the present study, we prepared a cobalt(III) polypyridyl complex, [Co(4,4′-OMebpy) 3 ](BAr F 4 ) 3 (where 4,4′-OMebpy is 4,4′-dimethoxy-2,2′-bipyridine and BAr F 4 is tetrakis(3,5-bis(trifluoromethyl)-phenyl)borate) to probe ion-pairing in non-aqueous solutions. Specifically, analysis of data acquired from both variable-temperature diffusion ordered spectroscopy (DOSY) NMR and 1-D rotating-frame nuclear Overhauser effect (ROE) experiments allowed us to identify and differentiate between solvent-separated ion pairs in high-dielectric media and contact ion pairs in a low-dielectric solvent. Time-resolved absorption spectroscopy was then used to measure ground-state recovery dynamics under these varying conditions of ion-pairing, the results of which revealed an increase in excited-state lifetime for contact ion-pairs that we suggest arises from a reduction in outer-sphere reorganization energy relative to conditions which favored solvent-separated ion pairs. We believe this study demonstrates that one can leverage broadly available NMR-based methods to understand ion-pairing in non-aqueous solutions, which in turn can provide a microscopic picture of intermolecular interactions that can impact the photophysical properties of transition metal-based chromophores.

Ghosh, Atanu [Michigan State University, East Lans↗

Get on the BAND Wagon: a Bayesian framework for quantifying model uncertainties in nuclear dynamics

In this paper, we describe the Bayesian Analysis of Nuclear Dynamics (BAND) framework, a cyberinfrastructure that we are developing which will unify the treatment of nuclear models, experimental data, and associated uncertainties. We overview the statistical principles and nuclear-physics contexts underlying the BAND toolset, with an emphasis on Bayesian methodology's ability to leverage insight from multiple models. In order to facilitate understanding of these tools we provide a simple and accessible example of the BAND framework's application. Four case studies are presented to highlight how elements of the framework will enable progress on complex, far-ranging problems in nuclear physics. By collecting notation and terminology, providing illustrative examples, and giving an overview of the associated techniques, this paper aims to open paths through which the nuclear physics and statistics communities can contribute to and build upon the BAND framework.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Deuterium supersaturated surface layer in tungsten: ion energy dependence

Abstract Properties of deuterium (D) supersaturated surface layers (DSSLs) formed in tungsten (W), such as thickness, internal microstructures, and D retention, are experimentally investigated as a function of the incident ion energy, E i . W samples were exposed to D plasmas in the PISCES-A linear plasma device in a range of E i ∼ 45–175 eV, while other plasma exposure parameters were fixed: sample temperature, T s , ∼423 K, ion flux, Γ i , ∼1.2 × 10 21 m −2 s −1 , and fluence, Φ i , ∼3.0 × 10 24 m −2 . High-resolution, cross-sectional, transmission electron microscopy observations confirm that (1) a DSSL forms even at the lowest E i ∼ 45 eV, (2) the DSSL thickness, Δ t DSSL , is found to decrease with decreasing E i from ∼11–12 nm at E i ∼ 175 eV to ∼5–6 nm at ∼45 eV, and to agree with approximately the maximum implantation depth calculated using SDTrimSP, and (3) high-density D nanobubbles with a diameter of ∼1 nm or less exist inside the DSSL, which is deemed to validate a theory-predicted vacancy stabilization process due to trapping of a solute D atom(s). Utilizing a D areal density of ∼4.2 × 10 19 m −2 in the first 14 nm from the surface at E i ∼ 75 eV from nuclear reaction analysis and the measured E i dependence of Δ t DSSL , our previous laser-induced breakdown spectroscopy data is updated: both dynamic and static D retention increase with decreasing E i , and the D/W atomic fraction during plasma exposure reaches ∼0.3 at E i ∼ 45 eV. A possible DSSL formation mechanism is proposed.

Physics↗

Low Activity Tritium Detection in CCDs Using Deep Learning Techniques

Here, this study explores the use of charge-coupled devices (CCDs) for detecting low-energy beta particles from tritium decay - a critical signal for nuclear safety, nuclear nonproliferation, and environmental monitoring. We employ a dual approach utilizing both measured CCD data and detailed Geant4 simulations. Our analysis compares classical techniques with advanced deep learning methods, including convolutional neural networks (CNNs), autoencoders trained exclusively on tritium data, and preliminary studies on boosted decision trees (BDTs). The CNN, trained on mixed signal/background datasets, demonstrates superior classification performance, while the autoencoder shows the potential of unsupervised, background-agnostic strategies when background characteristics are poorly defined. These results highlight the excellent sensitivity achievable thanks to the background rejection made possible by information-rich CCD data, paving the way for improved portable tritium monitoring.

Autoencoder↗

Thermal scattering law for structure-dependent-Doppler broadening in FLASSH

Traditional Doppler broadening methods assume that target nuclei velocities follow a Maxwell-Boltzmann distribution which inherently assumes that the atoms are a free gas or that their velocities are independent of each other. This approximation is reasonable at high target temperatures and high neutron energies. However, nuclei are not independent: the lattice temperature and chemical binding will define the atomic motion. The thermal scattering law (i.e., TSL or S(α,β)) is a material property which describes the chemical binding and temperature response in terms of available momentum and energy states. In the thermal energy range, this TSL will define the thermal scattering cross sections. In the resonance region, the TSL offers a first-principles description of the probability distribution function for the velocity of the target nuclei. Using the TSL in Doppler broadening captures the structure of the material consistently from the thermal range into the resonance cross sections. In this work, both traditional free-gas and precise TSL Doppler broadening methods for resonance cross section evaluation have been implemented within the Full Law Analysis Scattering System Hub (FLASSH). This framework provides a generalized formulation for evaluating low-lying resonance data and streamlines nuclear data processing methods. TSL data generated using ab initio lattice dynamics (AILD) can be used to broaden cross section libraries in ENDF format for high-fidelity input into reactor physics calculations. These capabilities are demonstrated for the lowest absorption resonances of {sup 238}U in UO{sub 2}, UC and UN. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

A Discussion of Strength Reduction Factor Development for Thermal Aging Effect on Nuclear Structural Alloys

In consideration of structural alloy property deterioration during long-term exposure to elevated temperatures, the yield and ultimate tensile strength reduction factors are provided in the Boiler and Pressure Vessel Code Section III for nuclear reactor component design and operation analysis. Because the Gen IV reactor requirement of 40 ~ 60 years of service life makes it difficult to acquire such long exposure test data for developing the reduction factors, they must be derived from test data with relatively short exposure by predictive methods considered to be reasonably reliable. A novel approach with a physically-based model has recently been proposed for application to development of reduction factors for 9Cr-1Mo-V. In the model, contributors to the tensile strength are first identified and related to definite microstructural features of the alloy, then some physically-based methods are employed to simulate the microstructural evolution, and finally the model is assembled with test-data-calibrated parameters to generate the yield and ultimate tensile strength reduction factors covering elevated temperature exposure for up to 57 years. The approach is undoubtedly a trailblazing development that will, if proven reliable, lead to a paradigm shift in predicting thermal aging behavior of many other alloys. Its debut application to Section III, however, concerns nuclear safety and naturally warrants objective, impartial, and thorough technical scrutiny. In the present paper, the novel and conventional approaches are discussed. Necessary improvements to the novel approach are recommended for its application to nuclear structural component design and analysis, and for its potential expanded use to other alloys.

Ren, Weiju↗

Responsible Artificial Intelligence for Insider Threat Mitigation

This report examines the application of artificial intelligence (AI) technologies for insider threat mitigation (ITM) programs in nuclear security facilities. Insider threat detection presents unique challenges due to the subtle and adaptive nature of these threats, the complex signatures involved, and the scarcity of available data for analysis. Traditional human-centered approaches, while essential, face limitations in processing large amounts of data continuously and detecting subtle patterns across multiple systems. AI technologies can potentially address these limitations by providing 24/7 monitoring capabilities, identifying complex patterns that might escape human observation, and offering consistent application of security criteria. However, the deployment of AI in nuclear security contexts introduces significant new risks, including workflow disruption, expanded attack surfaces, potential for misuse, and ethical concerns regarding privacy, fairness, transparency, safety, and security. The high-consequence nature of nuclear security decisions demands careful consideration of these risks and systematic approaches to their mitigation.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

Validation and Independent Uncertainty Analysis of the MIX-SOL-THERM-003 ICSBEP Benchmark

The International Criticality Safety Benchmark Evaluation Project (ICSBEP) was started in 1992 by the United States Department of Energy and later in 1995 became an international project with contributions from 22 countries. The project is now organized by the OECD (Organisation for Economic Co-operation and Development) Nuclear Energy Agency (NEA). In its most recent iteration, the ICSBEP handbook contains over five thousand evaluations of critical, near-critical, and subcritical experiments conducted in facilities all around the world. These benchmarks serve as valuable information for criticality safety engineers who can use them to validate calculation techniques and establish minimum subcritical margins for operations with fissionable materials. The benchmarks in the handbook are categorized by their fissile material composition, material form (oxide, solution, or metal), and fission energy spectra. This is especially useful for those looking for benchmarks similar to a system they are working on to compare methods and identify trends. The ICSBEP Handbook Uncertainty Guide is document outlining recommended practices and methods for determining uncertainties in these benchmarks. Quantifying these uncertainties thoroughly is crucial as it allows a higher degree of confidence that data used from them is valid and relevant. The guide stresses the importance of a thorough and well documented uncertainty analysis when evaluating an experiment. All measured values of a system, whether they be dimensions or material compositions, have a certain amount of uncertainty associated with them and can be analyzed one by one to determine their effects on the system. Many evaluated benchmarks in the handbook present this in detail, however some do not, mostly earlier evaluations performed in the 1990’s and early 2000’s. Recently at Los Alamos National Laboratory (LANL), the Nuclear Criticality Safety Division (NCSD) of LANL has been validating MCNP6.2 ® input files of criticality benchmarks for use by Whisper, a criticality safety code developed at LANL. This effort is also part of the OECD NEA Working Party on International Nuclear Data Evaluation Co-operation (WPEC) Subgroup 45, also known as Validation of Nuclear Data Libraries (VaNDaL). The goal of VaNDaL is to compile a set of validated simulation inputs for use in validating nuclear data and simulation codes. As part of these efforts, one of the benchmarks reviewed was the MIX SOL-THERM-003 ICSBEP benchmark. This paper provides an independent uncertainty analysis of this benchmark experiment.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Real-Time Automated pH Control within Batch Processes Relying on Raman pH Measurement

Nuclear fission is an energy source that can provide consistent power with very low associated carbon emissions. However, management of the used nuclear fuel is an important aspect of the application of nuclear power. Recycling of useful components from used fuel is an attractive option, but this involves chemical processing of the fuel. Possible chemical separation technologies that might be used in this regard are sensitive to solution pH. Raman spectroscopy is a promising technique for monitoring the pH of solutions in real time. Classical pH probes are too fragile to be used in the harsh environments encountered in nuclear fuel processing. Raman probes are robust and can withstand these harsh environments to track pH. Coupled with chemometric analysis, the demonstration of the use of Raman spectroscopy to track and predict the pH in carboxylate-buffered systems is made possible. Utilizing this spectroscopy in conjunction with Programmable Logic Controllers mimics industrial control systems used in many modern industrial settings. This showcases a pragmatic approach toward leveraging Raman spectroscopy and chemometric model outputs as inputs for a real-time control system. The model to predict pH created by chemometrics proved to be successful in tracking pH. The optimal pH for TALSPEAK extraction of lanthanides and actinides from aqueous solution is known to proceed in a narrow pH range of around pH = 2.8 ± 0.1. This study uses Raman optical monitoring and automated control to return and maintain solution pH within this range after acid or base perturbations move the solution pH well outside this region. Root-mean-square errors show that pH changes measured using Raman spectroscopy on the batch process solution are reliably measured and used to automatically correct and maintain solution pH. Measurement of solution pH tracks favorably with electrochemical pH probe comparison measurements. As a result, the ability to showcase Raman spectroscopy paired with chemometrics analysis acts as a durable, better alternative data source compared to traditional pH probes to optimize the separation efficiency in the used nuclear fuel processing.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Status Report on Characterization of High Burnup Fuel with Advanced Nondestructive Pulsed Neutron PIE

Characterizing irradiated or spent nuclear fuels with pulsed neutron techniques provides microstructural data such as phase fractions as well as crystallographic data, e.g. lattice parameters, from diffraction analysis. Diffraction characterization is complemented by spatially resolved mapping of isotope densities from energy-resolved neutron imaging, in particular neutron absorption resonance imaging, and overall bulk isotope assay with better sensitivity for minority isotopes from neutron absorption resonance spectroscopy without spatial resolution. Furthermore, after characterization at ambient condition, heating of irradiated or spent fuel will allow to characterize differences of e.g. lattice thermal expansion or phase transition temperature and kinetics compared to fresh fuel as well as enable the study of disappearance of irradiation defects. This data enables benchmarking of predictions of properties of irradiated fuels for which otherwise experimental data is sparse. The effort described here strives to characterize a section cut from a high-burnup fuel. Volumes smaller than entire fuel pellets or rodlets as proposed here, e.g. sections cut from a fuel pellet, to pave the way to characterize entire pellets or rodlets in the future.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Utilizing a Virtual Sodium-Cooled Fast Reactor Digital Twin to Aid in Diversion Pathway Analysis for International Safeguards Applications

We report digital twin technology has the potential to improve the effectiveness of international safeguards inspectors by providing a tool which can: first, perform an accurate diversion path analysis, identify their indicators, and required sensors to detect them; and second, monitor facilities in real-time using critical data streams that benefit from this safeguards-by-design approach. Safeguards inspectors are required to visit facilities and verify the nuclear material to ensure no diversion has taken place and detect misuse of the facility; however, this analysis and verification effort is time consuming, and with limited funding it is imperative that time spent at a nuclear facility is focused on key areas. A virtual digital twin of three prototypic sodium fast reactors was developed, where diversion and misuse scenarios were explored to determine how a digital twin could provide inspectors with an understanding of how proliferation may occur and where the most likely areas for proliferation would be. For each of the three reactors, an optimization algorithm was able to find core designs which would be difficult to detect via sensors alone; however, the use of a machine learning adapter provided by the digital twin was able to show general trends in where proliferation as likely to take place.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗