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At least 451 records · Page 25

Demonstration of TOFFEE: A Response Uncertainty Quantification Tool

A key characteristic in neutron transport is nuclear data. Cross-section uncertainty is not used in MCNP6.3 to propagate response uncertainty without external analysis. Here, the TOol For Fast Error Estimation (TOFFEE) is a Python-based code developed to automate the propagation of cross-section uncertainty for MCNP evaluations. TOFFEE implements the sandwich rule to calculate the uncertainty from cross sections with sensitivity coefficients from MCNP6.3 and ENDF/B covariance data. In this paper, TOFFEE has been tested with benchmark experiments, and it has been compared to the uncertainty quantification capabilities of Sampler and TSUNAMI, within SCALE, to verify the application’s capabilities.

97 MATHEMATICS AND COMPUTING↗

Final Search for Short-Baseline Neutrino Oscillations with the PROSPECT-I Detector at HFIR

The PROSPECT experiment is designed to perform precise searches for antineutrino disappearance at short distances (7–9 m) from compact nuclear reactor cores. This Letter reports results from a new neutrino oscillation analysis performed using the complete data sample from the PROSPECT-I detector operated at the High Flux Isotope Reactor in 2018. The analysis uses a multiperiod selection of inverse beta decay neutrino interactions with reduced backgrounds and enhanced statistical power to set limits on electron neutrino disappearance caused by mixing with sterile neutrinos with 0.2–20 eV 2 mass splittings. Inverse beta decay positron energy spectra from six different reactor-detector distance ranges are found to be statistically consistent with one another, as would be expected in the absence of sterile neutrino oscillations. The data excludes at 95% confidence level the existence of sterile neutrinos in regions above 3 eV 2 previously unexplored by terrestrial experiments, including all space below 10 eV 2 suggested by the recently strengthened Gallium Anomaly. The best-fit point of the Neutrino-4 reactor experiment’s claimed observation of short-baseline oscillation is ruled out at more than 5 standard deviations.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Product Consistency Test Results for the High-Chromium Matrix Glasses

This report provides chemical analysis of a series of Product Consistency Test (PCT) leachates from simulated nuclear waste glasses. The resulting data will be used in the development of improved property/composition models. For some of the glass leachates, minor scatter among the triplicate values of some analytes was observed. For other leachates, there were more significant differences among the triplicate values. A review of the PCT data noted that there was little difference between the normalized values on the basis of targeted or measured glass composition. Several of the study glasses, both quenched and canister centerline cooled, have NC i values that are greater than the Hanford Tank Waste Treatment and Immobilization Plant immobilized low-activity waste constraint of 4 g/L for B, Na, and Si. For many of the study glasses, heat treatment had only a marginal impact on the NC i values. The samples of the Environmental Assessment (EA) reference glass included with each PCT set had inconsistent NC i values, although some degree of variation in NC i values for the EA glass is typical. The release rates for boron and sodium were highly correlated for the study glasses, while for the other analytes, less correlation was observed.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Product Consistency Test Results for the LXC-Series Glasses

This report provides chemical analysis of a series of Product Consistency Test (PCT) leachates from simulated nuclear waste glasses. The resulting data will be used in the development of improved property/composition models. For some of the glass leachates, minor scatter among the triplicate values of some analytes was observed. For other leachates, there were more significant differences among the triplicate values. A review of the PCT data noted that there was little difference between the normalized values on the basis of targeted or measured glass composition. Several of the canister centerline cooled study glasses have NC i values that are greater than the Hanford Tank Waste Treatment and Immobilization Plant immobilized low-activity waste constraint of 4 g/L for B and Na. The results of these glasses will help ensure the ability of advanced glass performance models to appropriately predict acceptable compositions. For many of the study glasses, heat treatment had only a marginal impact on the NC i values. The samples of the Environmental Assessment (EA) reference glass included with each PCT set had generally consistent NC i values. The release rates for boron and sodium, and for sodium and silicon were highly correlated for the study glasses, while for the other analytes, less correlation was observed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Automated qualification data tool for high temperature metallic materials

This report describes a framework for storing, processing, and displaying qualification data for high temperature mechanical properties. The framework automates the process of generating design data from mechanical test results, for example for a data qualification report for the ASME Boiler \& Pressure Vessel Code. The framework has three parts: a data storage model with common formats for several types of typical mechanical property tests, a backend based on the \pycreep Python library for correlating and extrapolating the data to generate design material properties and allowable stresses, and a demonstration user interface for displaying, sorting, and filtering the data and exploring different options for modeling the design mechanical properties. The report discusses the options available for data processing, with illustrations from real test data on Alloy 617, Alloy 709, Alloy 740H, and Laser-Powder Bed Fusion 316H. The framework is complete for ASME type data analysis and will be used to store test data generated by the Department of Energy, Office of Nuclear Energy, Advanced Materials and Manufacturing Technologies sponsored qualification programs. Future work could extend the tool to other types of material properties and/or expand the demo user interface to make it accessible across the AMMT program.

36 MATERIALS SCIENCE↗

Nuclear Software Validation for 7% Enriched UO 2 Fuel Lattices

This analysis performs validation for the Virtual Environment for Reaction Application’s (VERA’s) neutronics codes MPACT and Shift against measured data from the Seven Percent Critical Experiment (7uPCX) at Sandia National Laboratory. The benchmarking supports the future application of VERA for analysis of high-assay low-enriched uranium (HALEU) fuel in commercial pressurized water reactors (PWRs). VERA demonstrates very good agreement with measured data, and the deterministic code MPACT also agrees very well with higher-fidelity stochastic methods KENO-VI and Shift in both total neutron flux and fission rate distribution comparisons. Despite some significant differences between the 7uPCX and existing commercial PWRs that challenge the neutron cross section data and transport solver methods used by MPACT, all of the results are excellent. The agreement increases the confidence in the applicability and accuracy of VERA for reactor analysis of HALEU fuels in commercial reactors.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Using photoelectron spectroscopy to measure resonant inelastic X-ray scattering: a computational investigation

Resonant inelastic X-ray scattering (RIXS) has become an important scientific tool. Nonetheless, conventional high-resolution (few hundred meV or less) RIXS measurements, especially in the soft X-ray range, require low-throughput grating spectrometers, which limits measurement accuracy. Here, the performance of a different method for measuring RIXS, i.e. photoelectron spectrometry for analysis of X-rays (PAX), is computationally investigated. This method transforms the X-ray measurement problem of RIXS to an electron measurement problem, enabling use of high-throughput, compact electron spectrometers. X-rays to be measured are incident on a converter material and the energy distribution of the resultant photoelectrons, the PAX spectrum, is measured with an electron spectrometer. A deconvolution algorithm for analysis of such PAX data is proposed. It is shown that the deconvolution algorithm works well on data recorded with ~0.5 eV resolution. Additional simulations show the potential of PAX for estimation of RIXS features with smaller widths. For simulations using the 3d levels of Ag as a converter material, and with 10 5 simulated detected electrons, it is estimated that features with a few hundred meV width can be accurately estimated in a model RIXS spectrum. For simulations using a sharp Fermi edge to encode RIXS spectra, it is estimated that one can accurately distinguish 100 meV FWHM peaks separated by 45 meV with 10 5 simulated detected electrons that were photoemitted from within 0.4 eV of the Fermi level.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Dynamic responses of submerged components in advanced reactors: experimental and numerical studies

The seismic design of an advanced nuclear reactor must consider the interaction of vessel internal components with the surrounding coolant: fluid–structure interaction (FSI). Available analytical solutions for FSI of submerged components do not accommodate multiple-component, intense seismic inputs and complex reactor and internal geometries. Physical testing of reactor vessels and internals to inform seismic design is impractical and cost-prohibitive, leaving the use of verified and validated, robust numerical models as the only plausible option for analysis and design. Physical data that could be used for validating such numerical models for multi-component shaking are not available. This article describes an experimental program performed on a 6-degree-of-freedom earthquake simulator to generate data that could support validation of seismic FSI numerical models for submerged components in commercial finite element codes. A scaled model of a base-supported reactor vessel with simplified representations of submerged internals was tested to generate submerged-component response histories for a range of seismic inputs. The generated data were used to validate numerical models in the finite element code LS-DYNA. Numerical models were validated for calculation of hydrodynamic pressure responses on internals, in-water frequencies of internals, and acceleration responses of internals. The generated data and the analysis recommendations could aid engineering analysts designing submerged components and systems for seismic effects.

Engineering↗

Inferring small-sample-reactivity worth from oscillation experiment with auto-corrected local flux

To estimate reactivity changes as a function of time from the signal of detectors count rates, one usually uses point kinetic equations. However, when detectors are located inside the core, it is often necessary to compute a correction factor to account for the flux-shape deformation (i.e. the change of detector efficiency that may have been induced by neutron absorbers movements). Various simulation methods have been developed depending on transients observed. They range from the resolution of static equations up to full-time-dependent neutron transport in 3D. However, those methods require high computational-cost calculations of local reaction rates that rely on nuclear data evaluations. Therefore, a 'measured' reactivity is never determined through pure measurements. Taking advantage of the known oscillation movement of a small sample at the center of the MINERVE reactor, the innovative algorithm presented in this paper derives the correction factor needed to get no time drift on reactivity steps. Derived correction factors are in good agreement with those obtained independently with TRIPOLI-4 through sensitivity analysis. Low sensitivity to the sample composition and moderate sensitivity to the detectors position reinforce the reliability of those results. This application paves the way to almost pure nuclear data reactivity measurements. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Multilabel proportion prediction and out-of-distribution detection on gamma spectra of short-lived fission products

In the machine learning problem of multilabel classification, the objective is to determine for each test instance which classes the instance belongs to. In this work, we consider an extension of multilabel classification, called multilabel proportion prediction, in the context of radioisotope identification (RIID) using gamma spectra data. We aim to not only predict radioisotope proportions, but also identify out-of-distribution (OOD) spectra. We achieve this goal by viewing gamma spectra as discrete probability distributions, and based on this perspective, we develop a custom semi-supervised loss function that combines a traditional supervised loss with an unsupervised reconstruction error function. Our approach was motivated by its application to the analysis of short-lived fission products from spent nuclear fuel. In particular, we demonstrate that a neural network model trained with our loss function can successfully predict the relative proportions of 37 radioisotopes simultaneously. The model trained with synthetic data was then applied to measurements taken by Pacific Northwest National Laboratory (PNNL) to conduct analysis typically done by subject-matter experts. Here, we also extend our approach to successfully identify when measurements are OOD, and thus should not be trusted, whether due to the presence of a novel source or novel proportions.

Anomaly detection↗

Development of a Neutron List Mode Collar (LMCL) and a List Mode Response Matrix Analysis Concept

This report was prepared for the Safeguards Program of the US Department of Energy’s (DOE’s) National Nuclear Security Administration (NNSA), Office of Defense Nuclear Nonproliferation Research and Development (DNN R&D). The report presents the development of the neutron nondestructive assay system, the List Mode Collar (LMCL) for the project OR16-List Mode for Collar-PD1La “List Mode Response Matrix for Advanced Correlated Neutron Analysis for Nuclear Safeguards.” The new list mode electronics developed under this project, and a spatial analysis concept called the List Mode Response Matrix are also described in this report. Analysis algorithms based on classification methods are published in a separate report. This research addresses the need to expand the capabilities of current nondestructive assay systems used for nuclear safeguards applications and considers the sustainability of safeguards technologies by the development of a “retrofit” concept using electronics based on modern standards. Furthermore, employing list mode data acquisition enabled the development of a spatial analysis concept and empirical measurement of a spatial response not previously used for safeguards neutron counting applications or measured in a traditional neutron collar detector and, therefore, provides new capability.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Sensitivity Study of Multiscale and Phenomenological Elasto-Viscoplastic Grade 91 Material Models for Component-Scale Response

Many advanced nuclear reactor concepts currently being developed are targeting higher operating temperatures relative to the current fleet of light water nuclear reactors, for efficiency gains and other operational considerations. The design of high temperature structural components with reliable long-term operational performance will depend on material models that accurately capture the inelastic deformation mechanisms active in these environments. In this work, we perform a detailed parameter sensitivity analysis of two unified elasto-viscoplastic Grade 91 material models capable of capturing long term high temperature creep deformation. The first model is a phenomelogical material model from the Nuclear Engineering Material Library (NEML) developed at Argonne National Lab. The NEML model parameters and their uncertainty were fit to a range of Grade 91 experimental data using Bayesian Markov Chain Monte Carlo analysis. The second model is a LAROMance data-driven surrogate material model developed at Los Alamos National Lab. The LAROMance model is fit to a large database of responses produced by a mechanistic crystal plasticity based polycrystal model. Parameters for the LAROMance surrogate material model reflect the pedigree of the Grade 91 microstructure. Both material models have been integrated into the Grizzly code, based on the open-source MOOSE multiphysics simulation framework, to simulate both the progression of aging mechanisms and the effects of that aging on nuclear power plant structures. Grizzly is used analyze a three-dimensional Grade 91 piping system to compare the long-term inelastic response predicted by these two fundamentally different models and assess the sensitivity of the material model input parameters on this quantity of interest.

42 ENGINEERING↗

Siting Analyses for Advanced Nuclear Advisors (Final CRADA Report)

This report summarizes siting evaluation assistance provided to Advanced Nuclear Advisors (ANA) under CRADA/NFE-25-10693 for suitability of advanced nuclear technologies to meet siting criteria from the Nuclear Regulatory Commission (NRC) and associated guidance documents including the Electric Power Research Institute (EPRI) siting guide and other proprietary datasets. Advanced Nuclear Advisors provided sites for reactor siting evaluations using the Oak Ridge – Siting Analysis for power Generation Expansion (OR-SAGE) tool. Individual data packages for each site are provided separately.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Real-time neutron multiplicity and source localization for criticality safety during fuel debris removal

Advancing neutron detection and analysis techniques for complex radiation environments is an ongoing focus in nuclear instrumentation and monitoring. This proposal presents research and development of a generalized real-time neutron monitoring and analysis system, applicable to any detector capable of producing time-tagged neutron count data. While the work is demonstrated using the Neutron Multiplication Analysis Detector (NoMAD), a modular 15-tube helium-3 (He-3) array, due to its availability, spatial resolution, and flexible deployment, the methods developed are extensible to other systems, including organic scintillators and fast digital detectors. This research investigates two complementary analytical techniques for real-time characterization of neutron emitting sources: neutron multiplicity estimation based on the Hage-Cifarelli formalism and spatial localization using supervised machine learning applied to spatial count rate patterns. These methods are designed to operate under dynamic, evolving conditions such as fuel debris retrieval or reactor startup, where neutron-emitting material geometries may be partially unknown or changing over time. By integrating statistical neutron emission data with spatial localization, this research aims to develop and evaluate methods for real time neutron monitoring, source characterization, and material verification. Key contributions include implementation of a low-latency data pipeline for continuous neutron multiplicity analysis, development and validation of machine learning models for spatial inference, and experimental evaluation of system performance under variable measurement conditions. The outcomes are intended to support applications in nuclear safeguards, verification, emergency response, and reactor startup.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

A Standardized Analysis Process Using Digital Image Correlation to Calculate In Situ Cladding Strain from Modified Burst Tests for Fuel Performance Code Validation

Historical data collection on nuclear fuel cladding materials has focused on generating a statistically significant amount of data to assess the material and its failure behavior. Furthermore, data generated to support material model and failure criteria development were previously posttest evaluations, so a large number of tests was required to gain new understanding. A way to expedite this process is to develop techniques capable of generating large, high-fidelity data sets from a single test with lower uncertainty or quantified uncertainty. One such example of this approach is Oak Ridge National Laboratory’s use of modified burst tests (MBTs) to analyze the mechanical behavior and failure conditions of cladding during a simulated reactivity-initiated accident (RIA). Each test incorporates digital image correlation (DIC) analysis techniques that are used to assess the accumulated strain in situ, as well as eventual cladding failure. This work has been fruitful in defining strain-to-failure conditions for materials like silicon carbide (SiC) fiber–reinforced/SiC matrix composite tubes (SiC/SiC), iron-chromium-aluminum (FeCrAl) alloy tubes, and chromium-coated Zircaloy-4 tubes. However, there are numerous DIC software available, including open-source and proprietary software. The different DIC software use various algorithms to process images and calculate displacement values. Using these different software and algorithms can lead to varying results, and perhaps larger-than-expected uncertainties. In the present study, previously published MBT data encompassing a variety of test conditions were reanalyzed with two different DIC software to assess the variance in the calculated strain results. The data consisted of SiC/SiC, FeCrAl, and chromium-coated Zircaloy-4 tubes. Plots of the calculated strains during the transient revealed good agreement between the two DIC software. The average root-mean-square errors between the two software was 0.20% strain, which is slightly larger than a previously reported error value for these tests. In conclusion, this variance in results is low enough that this analysis method can be used for code validation.

Reactivity-initiated accident↗

Stability optimization of energetic particle driven modes in nuclear fusion devices: the FAR3d gyro-fluid code

The development of reduced models provide efficient methods that can be used to perform short term experimental data analysis or narrow down the parametric range of more sophisticated numerical approaches. Reduced models are derived by simplifying the physics description with the goal of retaining only the essential ingredients required to reproduce the phenomena under study. This is the role of the gyro-fluid code FAR3d, dedicated to analyze the linear and nonlinear stability of Alfvén Eigenmodes (AE), Energetic Particle Modes (EPM) and magnetic-hydrodynamic modes as pressure gradient driven mode (PGDM) and current driven modes (CDM) in nuclear fusion devices. Such analysis is valuable for improving the plasma heating efficiency and confinement; this can enhance the overall device performance. The present review is dedicated to a description of the most important contributions of the FAR3d code in the field of energetic particles (EP) and AE/EPM stability. FAR3d is used to model and characterize the AE/EPM activity measured in fusion devices as LHD, JET, DIII-D, EAST, TJ-II and Heliotron J. In addition, the computational efficiency of FAR3d facilitates performing massive parametric studies leading to the identification of optimization trends with respect to the AE/EPM stability. This can aid in identifying operational regimes where AE/EPM activity is avoided or minimized. This technique is applied to the analysis of optimized configurations with respect to the thermal plasma parameters, magnetic field configuration, external actuators and the effect of multiple EP populations. In addition, the AE/EPM saturation phase is analyzed, taking into account both steady-state phases and bursting activity observed in LHD and DIII-D devices. The nonlinear calculations provide: the induced EP transport, the generation of zonal structures as well as the energy transfer towards the thermal plasma and between different toroidal/helical families. Finally, FAR3d is used to forecast the AE/EPM stability in operational scenarios of future devices as ITER, CFETR, JT60SA and CFQS as well as possible approaches to optimization with respect to variations in the most important plasma parameters.

Alfv én Eigenmodes↗

Light Water Reactor Sustainability Program: Use of Time Distributions to Predict Operator Procedure Performance in Dynamic Human Reliability Analysis

The Human Unimodel for Nuclear Technology to Enhance Reliability (HUNTER) framework affords software capable of conducting human reliability analysis (HRA) using a dynamic approach built around operating procedures (OPs) from nuclear power plants (NPPs). Previous HUNTER reports document the development of this software tool, the coupling of HUNTER to the simulator code, the collection of operator performance data by using simulators to calibrate HUNTER models, and linking HUNTER to probabilistic risk assessment (PRA) software. The present report largely addresses two topics. The first is a new function in HUNTER called the HUNTER Procedure Performance Predictor (P3). HUNTER P3 uses HUNTER’s built in Monte Carlo tools featuring human performance variability to identify potential error traps in procedures. The second topic is time distribution analysis to generate time inputs for dynamic HRA. The current analysis was performed to investigate time distributions for task primitives, which are the minimum task unit of analysis used in dynamic HRA modeling. Using the time distribution data, the elapsed time for human actions in an extended loss of AC power (ELAP) scenario is then investigated. Time data and prediction are essential for modeling procedure performance.

99 GENERAL AND MISCELLANEOUS↗