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First Penning trap mass measurement of 36 Ca

Background: Isobaric quintets provide the best test of the isobaric multiplet mass equation (IMME) and can uniquely identify higher order corrections suggestive of isospin symmetry breaking effects in the nuclear Hamilto nian. The Generalized IMME (GIMME) is a novel microscopic interaction theory that predicts an extension to the quadratic form of the IMME. Only the A = 20, 32 T = 2 quintets have the exotic T z = –2 member ground state mass determined to high-precision by Penning trap mass spectrometry. Purpose: To establish A = 36 as the third high-precision T = 2 isobaric quintet with the T z = –2 member ground state mass measured by Penning trap mass spectrometry and provide the first test of the predictive power of the GIMME. Method: Here, a radioactive beam of neutron-deficient 36 Ca was produced by projectile fragmentation at the National Superconducting Cyclotron Laboratory. The beam was thermalized and the mass of 36 Ca + and 36 Ca 2+ measured by the Time of Flight - Ion Cyclotron Resonance method in the LEBIT 9.4 T Penning trap. Results: We measure the mass excess of 36 Ca to be ME= –6483.6(56) keV, an improvement in precision by a factor of 6 over the literature value. The new datum is considered together with evaluated nuclear data on the A = 36, T = 2 quintet. We find agreement with the quadratic form of the IMME given by isospin symmetry, but only coarse qualitative agreement with predictions of the GIMME. Conclusion: A total of three isobaric quintets have their most exotic members measured by Penning trap mass spectrometry. The GIMME predictions in the T = 2 quintet appear to break down for A = 32 and greater.

20 ≤ A ≤ 38↗

Progress Update on the MUSIC Critical Benchmark

The Measurement of Uranium Subcritical and Critical (MUSiC) experiment was carried out from December 2020 through April 2021 at the National Criticality Experiments Research Center (NCERC). This measurement campaign featured bare configurations of the Rocky Flats highly-enriched uranium (HEU) shells, with each configuration having different numbers of these shells. The goal of the experiment was to test multiple neutron multiplicity detectors and measurement methods for a large range of neutron multiplication values. The large range of multiplications allows researchers to see when the combination of detectors and methods break down as the configurations reach the delayed supercritical window. The critical configurations were the extreme end of the multiplication range in MUSIC configurations. A critical benchmark in the International Criticality Safety Benchmark Evaluation Project (ICSBEP) Handbook is planned to help further validate nuclear data. Even though there are many benchmarks focusing on the fast spectrum for highly-enriched uranium, an additional benchmark that is well documented and up to the modern standard of the handbook would be a welcome addition. Given that there are no other materials such as moderators or significant reflectors, and its similarity to Lady Godiva, it is possible that this could be very useful for validation of 235 U nuclear data in the future.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Measurement of U 238 ( n , n ' γ ) cross section data and their impact on reaction models

A better knowledge of (n,xn) reaction cross sections is important for both reaction modeling and energy applications. This article focuses on inelastic scattering of neutrons off 238 U for which improvements are needed to better constrain evaluations and solve inconsistencies in nuclear power reactor calculations. A new precise measurement of (n,xnγ) reaction cross sections on 238 U has been performed at the GELINA (Geel Electron LINear Accelerator) neutron facility operated by EC-JRC-Geel (Belgium) with the GRAPhEME (GeRmanium array for Actinides PrEcise MEasurements) setup. The prompt γ-ray spectroscopy method coupled to time-of-flight measurements is used to extract (n,xnγ) cross section values which can be further combined to infer the total neutron inelastic scattering cross section. Cross section data for 18 γ transitions (five never measured before) are presented and compared to the data in the literature. Here, emphasis is especially given to the uncertainty determination to produce partial cross section data as accurate as possible. Due to intrinsic limitations of the experimental method, the use of additional nuclear structure information coupled with theoretical modeling is required to determine the total (n, n') cross section over the whole neutron energy range. We have investigated modeling aspects of the 238 U(n,n'γ) cross sections related to the description of compound nucleus and preequilibirum mechanisms as well as the discrete part of nuclear structure. Through comparison between experimental and calculated (n,n'γ) cross sections, we pinpoint inaccuracies in the description of specific reaction mechanisms and challenge recently implemented models. This helps improving the whole modeling of the (n, n') reaction.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Improving High-Energy Particle Detectors with Machine Learning

Microseconds after the Big Bang, the universe existed in a state called the quark-gluon plasma (QGP). To experimentally study its properties, the QGP is recreated in high-energy nuclear collisions at the LHC, and the particles produced from the QGP are reconstructed from their energy deposition in the ATLAS calorimeter. This requires both classifying the particles and calibrating their deposited energy. The objective of this project is to improve the reconstruction by using machine learning techniques, where the energy depositions of clusters of cells, formed by ATLAS topo-clustering methods, are treated as three-dimensional images when inputted to neural networks. This approach significantly improves the calibration of deposited energies when cross-validating while training, and models trained on idealized data predict the calibrated energies of particles in more complex data sets well. Additionally, implementation of a data generator using uproot allows the program to load input data into memory as needed while training or predicting, significantly reducing the amount of memory used. The data generator also allows for use of multiprocessing to speed up training and evaluating. This work illustrates that using machine learning methods for both classification and calibration has the potential to significantly improve particle reconstruction.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Evaluation of the Radioactive Material Released in the Harborview Research and Training Building and Some Implications for Emergency Response

On 2 May 2019, during the 137 Cs source recovery operation, a source capsule in a research irradiator containing approximately 77.1 TBq was breached. Based on a geometric reconstruction analysis of the damage to the capsule, approximately 46.3 GBq (0.04%) was impacted by the chop saw (grinder) inside a mobile hot cell on the loading dock at the University of Washington Harborview Research and Training (HRT) Building. A very small fraction of the material impacted, less than 1%, was released from the mobile hot cell and then to the rest of the HRT Building. The objectives of this project were to assess the accidental release of 137 CsCl and its implications related to emergency response methods and the ramifications of 137 CsCl transport. The phenomenology of this event was also compared with past alkali halide dispersal events. The vast number of measurements and samples collected by the remediation contractors, the Department of Energy’s Nuclear Emergency Support Team, and the small number of retrospective samples collected by the authors informed the analysis. The techniques included (1) autoradiography and electron microscopy of samples collected from the HRT Building and the irradiator, (2) 3D visualization of deposition on surfaces and within the ventilation system, and (3) a study of the damage to the source capsule to evaluate the Cs particle size and particle composition due to the grinding accident. Subsequently, the cesium contaminant transport through the numerous pathways in the building was reconstructed to assess the deposition on surfaces as a function of particle size. Furthermore, the implications for emergency response are relevant to data quality and management. A Data Quality Objective guides data collection methods so that they have appropriate accuracy and precision for the intended application. Recommendations were made with respect to the sample collection protocols and archiving of samples.

46 - INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AN↗

How can a diverse set of integral and semi-integral measurements inform identification of discrepant nuclear data? [Slides]

Importance of nuclear data to bias changed significantly when including diverse measurement sets. LLNL pulsed sphere measurements provided information for 9 Be nuclear data above 2 MeV and subcritical benchmarks provided information for 240 Pu nuclear data between 100 keV and 10 MeV. Pulsed sphere leakage spectra and neutron noise observables are differently sensitive to nuclear data compared to critical benchmarks. Leakage spectra are sensitive to nuclear data above 5 MeV. Count rate and Feynman Y are more sensitive to nuclear data. A change in bias can help evaluators identify discrepant nuclear data. In the future, EUCLID plans to perform RAFIEKI analysis with additional benchmark and measurement sets.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Testing to Evaluate Processes Expected to Occur during MSR Salt Spill Accidents

Obtaining a license for a new nuclear reactor requires the identification and assessment of the potential consequences of specified accident scenarios, which are achieved using accident progression models. Those models need to be parameterized and validated using experimental data, but existing experimental data addressing processes relevant to molten salt reactor accidents are sparse. Specifically, experimental data that quantify the sensitives of important processes to the initial conditions of the spill, the ambient environment, and the containment features are needed to parameterize individual process models. Integrated experiments that simulate accident scenarios are also needed to provide data for model validation, but these experiments will require the use of proven methods to quantify the processes under evaluation. The overarching objectives of this work are to develop the methods for simulating the targeted processes, to determine the effectiveness of the methods in producing the data required for model development, to generate data that can be used to parameterize individual process models, and to provide key insights into the behavior of spilled molten salt that should be considered in models. Experimental methods were designed to quantify aspects of individual processes expected to occur during or after a molten salt spill accident that will affect the fate of spilled molten salt and the radionuclides within. These processes include 1) molten salt spreading and heat transfer, 2) molten salt flowing and freezing in tubing, 3) stainless steel corrosion kinetics in molten salt, and 4) molten salt splashing and aerosol generation. The initial tests described in this report were conducted using eutectic FLiNaK to demonstrate the test methods, the data that are generated, and the analyses of the data to derive values needed for modeling. The primary variables that were tested include initial salt temperature and the presence of volatile surrogate fission products (e.g., cesium and iodine). The developed methods are shown to be effective in quantifying the desired processes and can be applied to study more complex salt compositions of interest to molten salt reactor developers, a wide range of environmental conditions of interest to modelers, and additional variables relevant to salt spill accidents. The developed methods and insights gained from laboratory tests can also be incorporated in future large-scale integrated tests used to simulate molten salt spill accidents.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Quantifying the interstellar medium and cosmic rays in the MBM 53, 54, and 55 molecular clouds and the pegasus loop using Fermi-LAT gamma-ray observations

A study of the interstellar medium (ISM) and cosmic rays (CRs) using Fermi Large Area Telescope (LAT) data, in a region encompassing the nearby molecular clouds MBM 53, 54, and 55 and a far-infrared loop-like structure in Pegasus, is reported. By comparing the Planck dust thermal emission model with Fermi-LAT γ-ray data, it was found that neither the dust radiance (R) nor the dust opacity at 353 GHz (τ {sub 353}) was proportional to the total gas column density N(H{sub tot}) primarily because N(H{sub tot})/R and N(H{sub tot})/τ {sub 353} depend on the dust temperature (T {sub d}). The N(H{sub tot}) distribution was evaluated using γ-ray data by assuming the regions of high T {sub d} to be dominated by optically thin atomic hydrogen (H I) and by employing an empirical linear relation of N(H{sub tot})/R to T {sub d}. It was determined that the mass of the gas not traced by the 21 cm or 2.6 mm surveys is ∼25% of the mass of H I in the optically thin case and is larger than the mass of the molecular gas traced by carbon monoxide by a factor of up to 5. The measured γ-ray emissivity spectrum is consistent with a model based on CR spectra measured at the Earth and a nuclear enhancement factor of ≤1.5. It is, however, lower than local H I emissivities reported by previous Fermi-LAT studies employing different analysis methods and assumptions on ISM properties by 15%–20% in energies below a few GeV, even if we take account of the statistical and systematic uncertainties. The origin of the discrepancy is also discussed.

79 ASTRONOMY AND ASTROPHYSICS↗

Python Performance Prediction Package for the PGET instrument: User Guide

The Performance Prediction Package (PPP) is a software suite for generating radiation transport results, or leveraging existing transport results, to produce synthetic emission tomography measurements of spent nuclear fuel assemblies. Such synthetic data can be used to mimic specific measurements, and to systematically investigate detection capabilities. Possible uses for the tool include: • Instrument design • Predictive evaluation of observables prior to an inspection visit • Post-measurement assessment of measured data • Evaluation of unusual cases – closed containers with anomalous objects • Sensitivity studies for planning inspections • Sensitivity studies for diversion scenarios • Evaluation of analysis methods A scenario is defined with an assembly type, burnup, and cooling time; as well as assembly rotation angle and position relative to the PGET instrument. Pin-to-pin activity variations or a burnup gradient may be present, but in an inspection scenario these are unlikely to be specified. The measurement will specify a measurement time and a particular detector for detector response, and an optional empirical correction can further adjust the model to better mimic the measurement. The goal is to detect missing pins, or burnup anomalies consistent with a pin substituted with a fresh pin after partial burnup.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Classification of background suppression profiles for low background RPM data

Suppression of the ambient gamma background radiation by traffic structure and cargo is a well-understood and studied effect for deployed radiation portal monitors (RPM). For effective analysis of measured RPM profiles with the objective of inferring the spatial characteristics of radiation sources, it is important to account for the effects of background suppression. In this report we analyze background suppression for a test dataset from vehicle RPMs at a sample port and estimate the distributions of suppression amplitudes and shapes. Cluster analysis of standardized and normalized profiles is used to obtain the dominant suppression shapes in the sample field data. We determine that a large fraction of non-alarm RPM occupancies are represented by a small number of suppression shapes. This fraction increases when the signal-to-noise ratio of an occupancy profile is improved by the addition of signals for multiple RPM detectors located at the same height. The calculated suppression shapes from RPM data can be used along with source models in the process of spatial profile analysis both in the field or offline. This background suppression analysis is an important step in improving the effectiveness of the RPM profile analysis methodology which is currently being investigated and may lead to methods that reduce the number of secondary inspections as well as to decision support tools that aid operators in evaluating RPM data that do not contain spectral information.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Validation of Thermal Scattering Laws for Light Water at Elevated Temperatures with Diffusion Experiments

Light water is the most important neutron moderator in many reactor applications. Thermal neutron scattering kernels for H bound in H 2 O are represented by ENDF-format thermal scattering laws (TSLs) evaluated at discrete temperatures T . Nuclear data evaluations are conventionally validated utilizing a combination of critical benchmarks and experimental cross section data. Existing public critical benchmarks may be inadequate for testing water TSLs over the full range of T of interest in reactor applications, and experimental thermal scattering cross section data for water is sparse at elevated T . In this work, MC21 is used to simulate the decay of the equilibrium thermal neutron flux in light-water spheres of several radii. The fundamental-mode time eigenvalue $\mathcal{a}$ is calculated at 22 °C and 227 °C (at saturation pressure) for each sphere using three different H-H 2 O TSLs. Fitting $\mathcal{a}$ to a polynomial function of geometric buckling allows calculation of the thermal neutron diffusion length L . Extrapolation lengths are treated as a function of the transport mean free path and geometry. Experimental L data from 25 publications at 49 temperatures (from 10 °C to 295 °C), computed by several different time-dependent and space-dependent decay methods, is used to develop an empirical fit of L vs. T . The MC21-calculated L for the TSLs tested are within ±1% of the predicted values at 22 °C and 227 °C. This validation approach, which may be repeated at arbitrary T , constitutes an integral benchmark specific to and characterizing the detailed physics of the thermal scattering kernel applied.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Sensitivity Studies, Gap Analysis, and Benchmark Experiment Optimization for Reactor Physics and Criticality Safety Applications

Many new reactor designs, such as advanced reactors and micro reactors, have materials that lack nuclear data validation. This is also true for many other applications in criticality safety and global security. Both differential and integral experiments are needed to validate cross-section data. Without this, a user cannot have confidence in the predicted results of a radiation-transport code. This work describes an approach called ARCHIMEDES (Application Relevant Critical/Subcritical HEU/Pu-based Integral Measurements for Enhancing Data and Evaluating Sensitivities) to design new criticality experiments that have similar k eff cross-section sensitivities to an application of interest. This process involves simulations to generate cross-section sensitivities to a parameter of interest (such as k eff ), a gap analysis to determine which existing benchmarks are most similar to the application, and an experiment optimization. Recently, there has been a great deal of interest in the reactor physics community on advanced reactors, micro reactors, and accelerator driven systems (ADS). This work will apply the described method to specific examples in this area. The focus of this work will be on the sensitivity study and gap analysis, while future work will include experiment design.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Event Classifications on DNE2 Main Experiment Data using a Convolutional Neural Network Ensemble

The Dynamic Networks (DN) Experiment for FY24 (DNE2) is an experiment within DN with the goal of quantitatively evaluating the effectiveness of solutions developed so far by various researchers under the Low Yield Nuclear Monitoring (LYNM) program using a shared set of metrics and datasets. A key component of this experiment is the mimicking of a signature processing pipeline, and comparing currently accepted and standard-use processing methods to more state-of-the-art processes developed under DN. In this work, we focus specifically on the Event Characterization (EC) Focus Area (FA) of the pipeline, where a seismic event’s magnitude, yield and class are identified. We use Deep Learning (DL) to classify the type of events being processed as either earthquakes (EQs) or explosions (EXs) for three iterations of experiment datasets. The model is noticeably more confident and accurate in classifying explosions than earthquakes, reflecting a known shortcoming of the model, that being of a bias towards predicting explosions over earthquakes in the west coast due to training data biases.

97 MATHEMATICS AND COMPUTING↗

EXSAN: An Interactive Version of the Nuclear Cross Section Data Handbook - 25687

Neutron cross section measurements and data files have advanced significantly since 1989 when Los Alamos published 'A Nuclear Cross Section Data Handbook', a detailed compendium of point-wise cross section plots and pie charts of relative contributions of individual reactions to the total cross section for 129 isotopes. Other compendiums with similar data and analysis tools have also been published. The intent of this work is to develop a modern, open-source application for interactive exploration and analysis of Evaluated Nuclear Data File (ENDF) libraries that also allows users to create their own 'Nuclear Cross Section Data Handbooks'. EXSAN is an easy-to-use graphical user interface application for exploring ENDF photon and neutron cross sections developed in Python. In addition to interactive plotting, EXSAN includes methods for computing rank-order lists of cross section for any energy and calculating composite cross sections for isotopic and elemental compositions and additional batch automation features. (authors)

61 RADIATION PROTECTION AND DOSIMETRY↗

Technical Assessment of the Application of Digital Twin and Prognostic Tools for Condition Monitoring

This report was prepared for the U.S. Nuclear Regulatory Commission (NRC) to present use cases of the application of advanced technologies toward meeting the current and future regulatory requirements for maintenance and condition monitoring of structures, systems, and components (SSCs). The advanced technologies considered in this work, collectively referred to as digital twin (DT) technologies, are advanced sensors and instrumentation, data analytics, machine learning and artificial intelligence (ML/AI), and physics-based models. The report presents two use cases of reactor coolant pumps (RCPs) and heat pipes in nuclear power plants (NPPs) with technical and regulatory considerations and opportunities in using advanced technologies for conditional monitoring. Key findings from the exploration of these considerations are as follows: - Uncertainties in sensor data and model predictions must be rigorously addressed through validation and verification processes - Regulatory compliance is paramount, necessitating data driven models to be developed in line with existing codes and standards, as well as considering potential future guidelines for advanced reactors - Explainability and transparency in ML/AI models are essential for developing operator trust and regulatory review, including methods that enhance the interpretability of complex data-driven predictions - Condition monitoring programs must be evaluated for their effectiveness in reducing maintenance-preventable function failures (MPFF) and aligning with plant performance criteria - The deployment of advanced technologies for condition monitoring could lead to a transition from periodic to continuous monitoring, thereby optimizing maintenance schedules - Collaborative efforts between industry stakeholders, regulatory bodies, and technology developers are crucial for the successful adoption of advanced technologies for condition monitoring systems in nuclear facilities In summary, the introduction of advanced technologies into condition monitoring programs represents a significant leap forward in the domain of NPP maintenance. By harnessing the capabilities of advanced sensors, data analytics, and ML/AI, NPP operators can transition from a time-based to a condition-based maintenance approach. This shift can potentially enhance the reliability and safety of critical plant components while optimizing maintenance efforts and minimizing unnecessary outages. The NRC is continuing to explore the regulatory aspects of advanced technologies as part of inservice inspection and inservice testing (ISI and IST) programs by pursuing additional research in this technical area.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗

Applying Waveform Correlation to Aftershock Sequences Using a Global Sparse Network

Agencies that monitor for underground nuclear tests are interested in techniques that automatically characterize earthquake aftershock sequences to reduce the human analyst effort required to produce high-quality event bulletins. Waveform correlation is effective in detecting similar seismic waveforms from repeating earthquakes, including aftershock sequences. We report the results of an experiment that uses waveform templates recorded by multiple stations of the Comprehensive Nuclear-Test-Ban Treaty International Monitoring System during the first twelve hours after a mainshock to detect and identify aftershocks that occur during the subsequent week. We discuss approaches for station and template selection, threshold setting, and event detection that are specialized for aftershock processing for a sparse, global network. We apply the approaches to three aftershock sequences to evaluate the potential for establishing a set of standards for aftershock waveform correlation processing that can be effective for operational monitoring systems with a sparse network. We compare candidate events detected with our processing methods to the Reviewed Event Bulletin of the International Data Center to develop an intuition about potential reduction in analyst workload.

58 GEOSCIENCES↗

Ambient Ionization Mass Spectrometry Measurement of Aminotransferase Activity

A change in enzyme activity has been used as a clinical biomarker for diagnosis and is useful in evaluating patient prognosis. Current laboratory measurements of enzyme activity involve multi-step derivatization of the reaction products followed by quantitative analysis of these derivatives. This study simplified the reaction systems by using only the target enzymatic reaction and directly detecting its product. A protocol using paper spray mass spectrometry for identifying and quantifying the reaction product has been developed. Evaluation of the activity of aspartate aminotransferase (AST) was chosen as a proof-of-principle. The volume of sample needed is greatly reduced compared with the traditional method. Paper spray has a desalting effect that avoids sprayer clogging problems seen when examining serum samples by nanoESI. This very simple method does not require sample pretreatment and additional derivatization reactions, yet it gives high quality kinetic data, excellent limits of detection (60 ppb from serum), and coefficients of variation <10% in quantitation. .

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

MPACT Verification and Validation Manual (rev 1)

The MPACT code provides the capability to calculate the steady-state and transient reactor core neutron distribution for operating nuclear power plant (PWR) conditions across multiple fuel cycles. As required in the CASL SQA plan, it is the responsibility of UM and ORNL as joint owners of MPACT to ensure that verification and validation activities are performed and documented in a V&V manual with supporting publications and CASL technical reports which can be distributed for reference and distribution within VERA. This document provides the first revision of the MPACT verification and validation (V&V) manual and describes the current state of MPACT V&V and updates the framework for future MPACT V&V activities. During FY16, MPACT V&V activities in the areas of code verification have continued to mature and work has progressed on code error evaluation using the Method of Manufactured Solutions (MMS). Several specific tasks have also been completed to improve MPACT code verification to include tasks to improve the unit and regression test coverage. A joint UM/ORNL task was completed to develop standardize coding standards and workflow for the continued collaborative development of MPACT. During the past year, MPACT validation work has continued in both the areas of measured data from critical experiments as well as measured data from operating nuclear power plants. Preliminary work was also performed in FY16 on the use of post-irradiation examinations for evaluation and validation of the isotopic depletion capability in MPACT. Based on the results of V&V efforts this past year, the confidence level has increased in the ability of MPACT to model an operational Pressurized Water Reactor. Areas were identified which require increased emphasis during FY17 to include updating all the V&V problems with the new 51-group library, the completion of cycle 2 of the BEAVRS benchmark, initial validation for BWR applications, the addition of Uncertainty Quantification results into the benchmark results, and the completion of specific validation tasks for the CASL Challenge problems.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗