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At least 235 records · Page 13

Feasibility Study for Disposal Control Rod Assemblies Using UNF-ST&DARDS As-Loaded Zion Dual Purpose Cask Models

This report documents an initial evaluation to support future use of disposal control rod assemblies (DCRAs) for post-closure criticality control in dual purpose canisters (DPCs). The work described herein is an extension of previous efforts performed by Walker using inputs generated by the Used Nuclear Fuel-Storage, Transportation & Disposal Analysis Resource and Data System (UNFST&DARDS) for the Zion site DPCs with as-loaded isotopic compositions. The results of this analysis demonstrate that there are multiple pathways to using DCRA for post-closure criticality control. Various configurations of DCRA material, diameter, number of rods per DCRA, and number and location of DCRAs within a DPC were shown to be effective in varying degrees for the set of DPCs analyzed by Walker. Because of the variations in DPC as-loaded isotopic compositions considered in an array of DCRA parametric sweeps, it can be concluded that a DPC-specific methodology is feasible (i.e., a one-size-fits-all approach may not be needed). Instead, the utility program created for this work can be expanded to develop capabilities to provide DPC-specific DCRA arrangements to limit cost and weight and to allow for operational considerations.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Machine learning for ultrasonic nondestructive examination of welding defects: A systematic review

Recent years have seen a substantial increase in the application of machine learning (ML) for automated analysis of nondestructive examination (NDE) data. One of the applications of interest is the use of ML for the analysis of data from in-service inspection of welds in nuclear power and other industries. These types of inspections are performed in accordance with criteria described in the ASME Boiler and Pressure Vessel Code and require the use of reliable NDE techniques. The rapid growth in ML methods and the diversity of possible approaches indicate a need to assess the current capabilities of ML and automated data analysis for NDE and identify any gaps or shortcomings in current ML technologies as applied to the automated analysis of NDE data. In particular, there is a need to determine the impact of ML on the NDE reliability. This paper discusses the findings from a literature survey on the current state of ML for the automated analysis of data from ultrasonic NDE of weld flaws. It discusses an overview of ultrasonic NDE as used for weld inspections in nuclear power and other industries. Herein, data sets and ML models used in the literature are summarized, along with a generally applicable workflow for ML. Findings on the capabilities, limitations and potential gaps in feature selection, data selection, and ML model optimization are discussed. The paper identified several needs for quantifying and validating the performance of ML methods for ultrasonic NDE, including the need for common data sets.

36 MATERIALS SCIENCE↗

ORNL Neutron Cross Section Measurements of 90 Zr

Nuclear criticality modeling and simulations rely on the quality of the existing evaluated nuclear data libraries such as Evaluated Nuclear Data File (ENDF)/B, the Joint Evaluated Fission and Fusion (JEFF) nuclear data library, or the Japanese Evaluated Nuclear Data Library (JENDL). In some cases, the cross-section evaluations of those libraries were found to be deficient in describing criticality benchmarks accurately. More than two decades ago, the US Nuclear Criticality Safety Program (NCSP) established a Nuclear Data (ND) task which encompassed experiments and evaluations. In response to this, the Oak Ridge National Laboratory (ORNL) formed a Nuclear Criticality and Data group which performed ND experiments, data analysis, and evaluations to produce ENDF files for the ND libraries as identified in the NCSP Five-Year Plan. Before being submitted to the ENDF library, files were processed and tested for performance by running benchmark calculations. This procedure was centralized in the ORNL group and is now often referred to as the ND pipeline. NCSP collaborates with the Joint Research Center (JRC) of the European Commission in Geel, Belgium, to perform high-resolution neutron-induced cross section measurements at the Geel Linear Accelerator (GELINA). The objective is to address emerging ND problems in criticality calculations. Difficulties with ND include insufficient neutron energy range, missing covariances, and previously unrecognized inaccuracies with experiments. New neutron total and capture cross sections of 90 Zr in the neutron energy range from 100 eV to several hundred keV were recently performed. These measured data will be used, together with existing high-resolution transmission data from a metallic 90 Zr sample, to improve representation of the cross sections.

97 MATHEMATICS AND COMPUTING↗

Enhanced Component Performance Study: Emergency Diesel Generators 1998–2018

This report presents an enhanced performance evaluation of emergency diesel generators (EDGs) at U.S. commercial nuclear power plants. This report evaluates component performance over time using (1) Institute of Nuclear Power Operations (INPO) Consolidated Events Database (ICES) data from 1998 through 2018 and (2) maintenance unavailability (UA) performance data from Mitigating Systems Performance Index (MSPI) Basis Document data from 2002 through 2018. The objective is to show estimates of current failure probabilities and rates related to EDGs, trend these data on an annual basis, determine if the current data are consistent with the probability distributions currently recommended for use in NRC probabilistic risk assessments, show how the reliability data differ for different EDG manufacturers and for EDGs with different ratings; and summarize the subcomponents, causes, detection methods, and recovery associated with each EDG failure mode. Engineering analyses were performed with respect to time period and failure mode without regard to the actual number of EDGs at each plant. The factors analyzed are: sub-component, failure cause, detection method, recovery, manufacturer, and EDG rating. A statistically significant increasing trend was identified in the frequency of FTLR demands for emergency power system (EPS) and high pressure core spray (HPCS) EDGs and a statistically significant decreasing trend was identified in the frequency of run > 1H hours for EPS and HPCS EDGs.

99 GENERAL AND MISCELLANEOUS↗

Review of multi-faceted morphologic signatures of actinide process materials for nuclear forensic science

Particle morphology is an emerging signature that has the potential to identify the processing history of unknown nuclear materials. Using readily available scanning electron microscopes (SEM), the morphology of nearly any solid material can be measured within hours. Coupled with robust image analysis and classification methods, the morphological features can be quantified and support identification of the processing history of unknown nuclear materials. The viability of this signature depends on developing databases of morphological features, coupled with a rapid data analysis and accurate classification process. With developed reference methods, datasets, and throughputs, morphological analysis can be applied within days to (i) interdicted bulk nuclear materials (gram to kilogram quantities), and (ii) trace amounts of nuclear materials detected on swipes or environmental samples. In conclusion, this review aims to develop validated and verified analytical strategies for morphological analysis relevant to nuclear forensics.

36 MATERIALS SCIENCE↗

The Relationship Between Dose Rate and Decay Heat for Spent Nuclear Fuel Casks

Decay heat and dose rate are two important limits used for determining the allowable contents of spent fuel (SNF) in dry storage systems and transportation packages. While the decay heat limit is used to maintain fuel cladding integrity and ensure retrievability, dose rates are used to demonstrate compliance with regulatory requirements on radiation protection. Because both dose rate and decay heat result from decay of radioisotopes in SNF, this study is an attempt to examine the relationship between dose rate and decay heat for a given cask design. Dose rates were evaluated for 198 cask configurations, that include various SNF system designs (e.g., storage, transfer, transport), SNF characteristics (e.g., fuel types, burnup, cooling time), and loading maps (e.g., uniform loading, zone loading), while a constant decay heat was maintained. The decay heat was calculated using US Nuclear Regulatory Commission (NRC) Regulatory Guide (RG) 3.54, Revision 2, and verified using ORIGEN sequence within SCALE code system. The ORIGEN outputs were used as source terms in the dose analysis using 198 different configurations. A computer script was developed to calculate the cooling time necessary to achieve a given decay heat for a given enrichment, assembly average burnup, assembly mass, and in-core history using a rootfinder algorithm. Initially the computer script was developed to provide cooling time and burnup calculations directly to the analysis of dose rates and decay heats, so a comparison between Used Nuclear Fuel-Storage Transportation and Disposal Analysis Resource Data System (UNF-ST&DARDS) results and RG3.54 data was made; results are included in the appendix to this document. However, an iterative approach was used to compute cooling time, and its accuracy did not depend on the results of the RG3.54r2 algorithm, although the algorithm was still used. The results of the evaluation presented herein clearly demonstrate that a given decay heat does not correspond to a unique dose rate for a variety of cask and package designs. There is no clear pattern to develop a correlation between decay heat and the source terms. Depending on burnup, enrichment, cask type, and loading pattern, dose rates varied for the exact same decay heat—in some cases by 400% for a given cask. For cases in which decay heat was held constant through selection of the appropriate cooling time, dose rates would decrease with increasing burnup, and in other cases, dose rates would increase. The large variation in dose rates for a constant decay heat indicates that casks loaded based on decay heat—that is allowing any burnup, cooling time, and enrichment combinations that yield the qualified decay heat limit(s) —cannot ensure that an Independent Spent Fuel Storage Installation or a spent fuel transportation package will meet the regulatory limits set forth by the respective regulations, i.e., 10 CFR 72 or 10 CFR 71.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Gaussian Process Optimization of Sensitivity-Based Similarity Metrics between New Nuclear Applications and New/Existing Benchmarks [Slides]

This presentation discusses Nuclear Criticality Safety (NCS) and how designing safe, new nuclear criticality experiments requires expert judgement, which could take years of experience. Sensitivity/uncertainty (S/U) analysis can be utilized by less experienced individuals to conservatively estimate uncertainties in important parameters, such as k eff , in newly proposed nuclear experiments. The presentation poses the question of how this analysis can be performed and states that the answer lies in matching new nuclear experiments with existing benchmark experiments using similarity metrics. By increasing the criticality safety of the application in this work, higher mass limits could be used in PF-4 operations. Additionally, the presentation discusses MCNP6.2®, Whisper-1.1, the software that can be used in this analysis. Also discussed is the fact that International Criticality Safety Benchmark Evaluation Project (ICSBEP) benchmarks rarely match new nuclear applications and that there are significant differences in given set of materials and/or geometry. If there are no benchmarks that match the application, the presentation discusses the possibility of creating new benchmarks. In conclusion, this work presents a Gaussian process (GP) optimization scheme that was used to generate new benchmarks with the highest sensitivity-based similarity metrics to user-defined nuclear applications. The Gaussian process optimization successfully designed 3 new experimental benchmarks that were highly correlated to the application of interest and had k eff values near critical. Optimization over c k,i-r has shown that investigating specific isotope reactions for different applications is crucial to designing benchmark experiments. Partial contribution from Pu dominates c k similarity metric. Future work includes testing new stand-alone similarity metrics or new combinations of similarity metrics as the design criterion of this optimization – design criterion is application dependent.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Positron annihilation spectroscopy of defects in nuclear and irradiated materials- a review

Positron is the only probe that can detect individual atomic vacancies and small and large vacancy clusters induced by irradiation with remarkable sensitivity, providing information about their size, concentration, and chemical environment. The focus of this review article is to provide guidance to facilitate applications of positron annihilation spectroscopy (PAS) in irradiation-induced defect studies to advance the development of new radiation-tolerant materials. The principle of PAS, its techniques, and data analysis methods are described. PAS studies of defects in nuclear and irradiated materials are reviewed and discussed in depth. Future developments to advance PAS applications in nuclear materials research and studies of materials under extreme environments are presented.

Atomic scale defects↗

SAGIPS: A scalable Framework for scidac quantom

As part of the Scientific Discovery through Advanced Computing (SciDAC) program, the Quantum Chromodynamics Nuclear Tomography (QuantOM) project aims to analyze data from Deep Inelastic Scattering (DIS) experiments conducted at Thomas Jefferson National Accelerator Facility and the upcoming Electron Ion Collider. The DIS data analysis is performed on an event level by taking into leveraging nuclear theory models and accounting for experimental conditions. In order to efficiently run multiple analyses under varying conditions, a composable workflow was designed where each section (theory, experiment, objective minimization, etc.) has its own dedicated module. This presentation gives an overview over of the current status of this workflow, highlights present and future challenges, and highlights possible extensions to other projects with similar requirements.

Lersch, Daniel [Thomas Jefferson National Accelera↗

Analysis of human performance differences between students and operators when using the Rancor Microworld simulator

Here, from within the umbrella of the Simplified Human Error Experimental Program (SHEEP) framework, this paper analyzes human performance differences between professional and student operators when using a simplified simulator (i.e., Rancor Microworld). This paper represents a crucial step in understanding the fidelity of the simplified simulators and student operators within the SHEEP study. This paper explores a randomized factorial experimental design that features two independent variables: participant type and event class. Six human performance measurements are considered in the experiment. The experiment is conducted using 20 professional reactor operators employed at actual nuclear power plants (NPPs), along with 20 trained students. The experimental data are analyzed via statistical analysis methods. Finally, this paper examines the differences in human performance between actual operators and students when using Rancor Microworld.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

End-to-End Pipeline for Trigger Detection on Hit and Track Graphs

There has been a surge of interest in applying deep learning in particle and nuclear physics to replace labor-intensive offline data analysis with automated online machine learning tasks. This paper details a novel AI-enabled triggering solution for physics experiments in Relativistic Heavy Ion Collider and future Electron-Ion Collider. The triggering system consists of a comprehensive end-to-end pipeline based on Graph Neural Networks that classifies trigger events versus background events, makes online decisions to retain signal data, and enables efficient data acquisition. Here, the triggering system first starts with the coordinates of pixel hits lit up by passing particles in the detector, applies three stages of event processing (hits clustering, track reconstruction, and trigger detection), and labels all processed events with the binary tag of trigger versus background events. By switching among different objective functions, we train the Graph Neural Networks in the pipeline to solve multiple tasks: the edge-level track reconstruction problem, the edge-level track adjacency matrix prediction, and the graph-level trigger detection problem. We propose a novel method to treat the events as track-graphs instead of hit-graphs. This method focuses on intertrack relations and is driven by underlying physics processing. As a result, it attains a solid performance (around 72% accuracy) for trigger detection and outperforms the baseline method using hit-graphs by 2% higher accuracy.

97 MATHEMATICS AND COMPUTING↗

Resolved Resonance Region Evaluation of n+ 140,142 Ce [Slides]

ORNL has completed new resolved resonance region (RRR) evaluations for 140,142 Ce, which were carried out using Reich-Moore formalism instead of MLBW. Lack of integral measurements makes validation difficult, but difference from Kadonis values suggest more investigation of capture cross section are warranted. The complete file (with updated File2 & File32) was submitted to NNDC repository for inclusion in next release of ENDF. Sponsor report and journal publication are in progress.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Modeling Non-UO2 Fuel With UNF-ST&DARDS

The U.S. Department of Energy’s Used Nuclear Fuel-Storage, Transportation & Disposal Analysis Resource and Data System (UNF-ST&DARDS) provides an easy-to-use interface to analyze irradiated UO2 fuel by allowing all analysis to be performed within the software and being able to store and use dozens of fuel assembly, canister, and cask designs [1]. However, performing these same analyses with non-UO2 fuel, such as UN or U3Si2, requires more user intervention in the process. This work uses UN, UN-ZrO2, and U3Si2 fuel to demonstrate how to perform criticality analyses in the current versions of UNF-ST&DARDS and how a non-UO2 fuel will compare to UO2. This work is part of a larger effort that also includes shielding and thermal analyses, but they will not be discussed.

Ivanusa, Pavlo↗

Optimization Algorithm for Criticality Experiment Design Using Whisper

Many criticality experiments performed to aid in nuclear data evaluation are designed to maximize the sensitivity of the system’s effective neutron multiplication factor to a certain nuclide reaction pair over an energy region of interest. This is typically done by evaluating possible designs in a transport code such as MCNP and selecting the one with the highest desired sensitivity. A designer has many tools to try to maximize this sensitivity such as different moderators, reflectors, fuels, and geometries. This balancing act of identifying a critical and maximally sensitive system become very computationally expensive as more variables are added and higher precisions are desired. In order to identify these optimal configurations more efficiently a Particle Swarm Optimization (PSO) algorithm coupled with MCNP has been developed by Los Alamos National Laboratory (LANL). This algorithm has been used to design two upcoming criticality experiments that will be performed at the National Criticality Experiments Research Center (NCERC), located at the Nevada National Security Site, and operated by LANL, the only general-purpose critical experiments laboratory in the United States. PSO uses a population (swarm) of candidate solutions (particles) on a search space of dimensions such as moderator and reflector thicknesses or enrichments and concentrations. These particles move around the search space from generation to generation according to simple rules. Eventually, the swarm converges on the configuration that is both critical and maximally sensitive to a piece of nuclear data. PSO is well suited for criticality experiments as the algorithm is agnostic to the underlying physics, meaning it is effective on many different experimental setups. This algorithm has been modified to maximize the nuclear data similarity coefficient between an application case and an experiment aimed at replicating the application case using WHISPER, a nuclear criticality safety analysis tool. This allows for the efficient design of critical experiments informed by nuclear data sensitives.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Application of Principal Component Analysis to Electrochemical Reprocessing PM and NMAC

In this report, data from an electrorefiner (ER) for nuclear fuel reprocessing is evaluated for process monitoring (PM) conclusions. This data comes from tests performed at the Idaho National Laboratory in 2022. Multivariate approaches utilizing methods of Principal Component Analysis (PCA) is applied. This is based off established work in process monitoring for fault detection in industrial facilities. This report will discuss the background, methods, and results of the application and some of the conclusions and applications that can be drawn from them. PCA is applied to two different electrorefiner (ER) operations that occurred at Idaho National Laboratory between August and October 2022. The first operation occurred with little incident while the second had several noted faults in the equipment in operational logs. The data from the first run was used to train the data for “normal” operations and applied to both sets of data to determine when operations were in an “off-normal” condition and identify where the fault occurs through PCA. PCA was able to identify off-normal events and identify the cause for off-normal operations. These identified off-normal events matched with the events and their causes in the operational logs. However, small amounts of variance in the data led to false detection of “off-normal” events. Thus, careful selection of training data and a-posteriori conclusions based off operator assessments will both be required for application of PCA to PM applications. This work demonstrated that multivariate approaches and latent variables are applicable to pyroprocessing PM applications and can be further expanded in future work as quality variables such as salt concentration from sensors and sampling become available.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

A Comparison of As-loaded Dose Calculations to Measured Dose Rates

Demonstrating that the radiation dose fields surrounding spent nuclear fuel (SNF) storage and transportation systems meet the applicable limits set forth in 10 CFR 72 for storage and 10 CFR 71 for transportation is essential for the safe handling of radioactive material. The Used Nuclear Fuel-Storage, Transportation, and Disposal Analysis Resource and Data System (UNF-ST&DARDS) [2] is used to provide realistic estimates of SNF-related safety margins. The UNF-ST&DARDS dose rate analysis approach differs from that used in typical licensing approaches, which use design-basis assemblies with bounding source term characteristics to demonstrate the packaging design complies with the regulations. These bounding licensing approaches can increase the time needed to qualify fuel for loading into dry storage and the time a loaded system must wait prior to transportation. UNF-ST&DARDS dose rate assessments allow quantification of realistic, uncredited safety margins associated with actual fuel loading compared with the regulatory limits. While realistic estimation of the dose field surrounding SNF systems may allow for additional flexibility in operations, it is essential to understand how these predictions compare to measured doses. The U.S. Department of Energy Office of Integrated Waste Management and the Prairie Island Indian Community conducted a transportation dose assessment to estimate the site-specific incident-free radiation doses from shipping SNF by rail from the Prairie Island Nuclear Generating Plant (PINGP) through the Prairie Island Indian Community Reservation and Trust Land [5,6]. For that effort, the dose rates were obtained for 50 TN-40 and TN-40HT systems in storage configurations. This work compares the predicted dose rates from UNF-ST&DARDS as-loaded calculations with dose rates measured from 50 SNF storage systems at PINGP. The remainder of this paper discusses the data obtained for the evaluation, the modeling methods, and the results of the calculations.

spent nuclear fuel (SNF), UNF-ST&DARDS, Validation↗

Status on Development of Graphite Analytical Tool (GAT)

The DOE-ART Graphite R&D program has been generating significant amounts of irradiated and unirradiated graphite data since 2006 when the program was part of the DOE NGNP (Next Generation Nuclear Plant) Project. This data includes critical irradiation creep and irradiated material property changes from the Advanced Graphite Creep (AGR) experiment as well as significant amounts of data on unirradiated material property values on several current nuclear graphite grades (Baseline program). Previously, Idaho National Laboratory has developed an internal analysis tool to assist with analysis of the unirradiated and irradiated data. The Graphite Analytical Tool (GAT) is intended to provide easy access to the graphite data in the form of comparing unirradiated and irradiated material property changes, comparison of material property differences between various nuclear graphite grades, and illustrate trends within the irradiated and unirradiated data generated within the DOE-ART Graphite R&D program. This report summarizes the progress to-date on the development of this analytical tool.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗