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DOE OSTI2025

Risk-informed Graded Approach for Reliability and Performance Assessment of Machine Learning and Artificial Intelligence for Advanced Condition Monitoring Techniques

With the shift away from time-based maintenance and toward condition-based maintenance, and to reduce overall maintenance costs, there has been an upsurge in the usage and development of advanced condition monitoring (ACM) techniques for real-time monitoring of nuclear power plant (NPP) components. ACM is particularly useful in the development of digital twins, which are designed to predict the failure or degradation of plant components. Successful implementation of ACM requires an assessment to inform the development of a risk-informed approach to evaluate the use of ACM to meet Nuclear Regulatory Committee (NRC) regulations for in-service testing (IST) programs. This includes the monitoring and diagnostics of reactor components and systems in current, new, and advanced reactors. A key component in ACM is the usage of machine learning (ML) and artificial intelligence (AI) algorithms that can employ real-time data from instrumentation and sensors to detect and predict reactor component degradations. Such predictive capabilities enable early detection of component degradation so as to help plant personnel plan and execute necessary maintenance. For successful implementation of ML/AI in ACM such that regulatory requirements are met, a risk-informed graded approach is needed to assess the reliability and performance of ML/AI for ACM. The American Society for Mechanical Engineers (ASME) developed their Operations and Maintenance (O&M) Code to provide guidance on safe, reliable O&M of NPPs. The IST section of the O&M Code specifically establishes requirements for IST and examination to gauge operational readiness of components in water-cooled NPPs. This paper presents a state-of-the-art review of how reliability and risk assessment can be integrated with ACM to assess component performance by non-nuclear industries. This is followed by different methodologies and approaches for conducting performance and reliability assessments so as to meet IST requirements for NPP components.

97 - MATHEMATICS AND COMPUTING↗

DOE OSTI2025

Risk-informed Graded Approach for Reliability and Performance Assessment for Advanced Condition Monitoring Techniques

99 - GENERAL AND MISCELLANEOUS↗

DOE OSTI2019

Quantitative Performance Assessment of Proxy Apps and Parents (Report for ECP Proxy App Project Milestone AD-CD-PA-504-5)

Proxy applications are small, simplified codes that allow application developers to share important features of large applications without forcing collaborators to assimilate large and complex code bases. Proxies can also be though of as models for larger codes. Because proxies omit features and capabilities of their parent applications (otherwise they wouldn’t be small), the question naturally arises whether any given proxy is actually a faithful model for its parent application for some particular modeling purpose. This report sets out to answer that question for some of the proxies in the ECP proxy app collection, with particular attention to performance. It also completes the AD-CD-PA-504 Milestone: "We will assess the fidelity of 8 proxy applications with respect to their respective parent applications using the methodology previously developed."

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2019

Implementation of a Risk-Informed Monitoring Program for the Saltstone Disposal Facility - 19374

Section 3116(b) of the Ronald W. Reagan National Defense Authorization Act for Fiscal Year 2005 (NDAA) requires the US NRC, in coordination with the appropriate State agency, to monitor certain disposal actions of the US DOE to assess compliance with the performance objectives in Subpart C of Part 61 of Title 10 of the Code of Federal Regulations (CFR). Under Section 3116(b), the US NRC monitors the US DOE disposal of salt waste at the Saltstone Disposal Facility (SDF) at the Savannah River Site (SRS) in South Carolina. Since the first US NRC monitoring plan for the SDF was issued in 2007, the US NRC staff has made the risk-significant areas of interest more specific. Following the US DOE issuance of the 2009 performance assessment for the SDF and the US NRC review of that document, the US NRC issued its second monitoring plan for the SDF in 2013. The 2013 US NRC monitoring plan included 11 monitoring areas, which were broken down into 40 specific monitoring factors. The US NRC prioritized those monitoring factors (i.e., low, medium, high) based on the sensitivity of model results to the assumptions or processes covered by the monitoring factor and the uncertainty in those assumptions or processes. Those monitoring factors can be opened, closed, revised, and re-prioritized based on new information or changes in the US DOE activities and plans. For example, the list of US NRC high-priority monitoring factors has changed in response to changing information. The flexibility of this approach allows the US NRC to remain focused on risk-significant areas of interest. The US NRC staff has made changes to the NDAA monitoring program at the SDF since the issuance of the 2007 monitoring plan. First, the development of more specific monitoring factors and the prioritization of those monitoring factors has been successful in focusing the US NRC and the US DOE resources on risk-significant issues and providing transparency to stakeholders. Second, the US NRC reviews have become more focused on addressing specific monitoring factors, which has made the process for updating the monitoring plan more transparent. Finally, periodic management meetings and monthly telephone calls maintain open communications between the US NRC, US DOE, South Carolina Department of Health and Environmental Control (SCDHEC), and US EPA. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2026

FAST-1.2.2: Integral Assessment

This integral assessment quantifies the predictive capabilities of Fuel Analysis under Steady-state and Transients (FAST), a thermal-mechanical nuclear fuel performance code designed to analyze fuel behavior from beginning of life to burnup levels allowed by the U.S. Nuclear Regulatory Commission. FAST code calculations are shown to compare satisfactorily to a pre-selected set of experimental data with both steady-state and anticipated operating occurrence conditions and design basis accident transient operating conditions. This document describes the assessment of FAST-1.2.2, the latest version of FAST, released April 2026.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

NASA NTRS2012

Development of Benchmark Examples for Quasi-Static Delamination Propagation and Fatigue Growth Predictions

The development of benchmark examples for quasi-static delamination propagation and cyclic delamination onset and growth prediction is presented and demonstrated for Abaqus/Standard. The example is based on a finite element model of a Double-Cantilever Beam specimen. The example is independent of the analysis software used and allows the assessment of the automated delamination propagation, onset and growth prediction capabilities in commercial finite element codes based on the virtual crack closure technique (VCCT). First, a quasi-static benchmark example was created for the specimen. Second, based on the static results, benchmark examples for cyclic delamination growth were created. Third, the load-displacement relationship from a propagation analysis and the benchmark results were compared, and good agreement could be achieved by selecting the appropriate input parameters. Fourth, starting from an initially straight front, the delamination was allowed to grow under cyclic loading. The number of cycles to delamination onset and the number of cycles during delamination growth for each growth increment were obtained from the automated analysis and compared to the benchmark examples. Again, good agreement between the results obtained from the growth analysis and the benchmark results could be achieved by selecting the appropriate input parameters. The benchmarking procedure proved valuable by highlighting the issues associated with choosing the input parameters of the particular implementation. Selecting the appropriate input parameters, however, was not straightforward and often required an iterative procedure. Overall the results are encouraging, but further assessment for mixed-mode delamination is required.

Krueger, Ronald↗

DOE OSTI2016

Flame ignition in the counterflow configuration: Reassessing the experimental assumptions

The counterflow configuration is widely used to study experimentally premixed and non-premixed flame ignition, with the advantage being that the data can be modeled using quasi one-dimensional codes. In this study, experiments and direct numerical simulations were carried out in order to assess the validity of the assumptions of the one-dimensional formulation. Experimentally, particle image velocimetry, shadowgraph, and a high-speed camera were employed to characterize the flow field before ignition, and to capture the ignition position and further evolution of the flame. The modeling involved axisymmetric numerical simulations using detailed molecular transport and chemical kinetic models. We report both experiments and simulations revealed that if solid surfaces are present in the vicinity of the jets exit, the flow separates generating recirculation zones that are unstable and result in the bifurcation of the flow field. As a result, for a given set of boundary conditions at the burners’ exits, there exists two possible stable states of the flow field which have different velocity and scalars distribution, and the fuel concentration at which ignition occurs was determined to differ for these two states. A novel approach is proposed to correct for the unavoidable radial non-uniformity of the temperature profile at the exit of the heated jet and the conditions that do not result in bifurcation are outlined, so that the results from one-dimensional codes can be compared to the data with confidence.

42 ENGINEERING↗

DOE OSTI2017

xLPR Post-Processing Documentation

The outputs available in the xLPR Version 2.0 code can be analyzed using statistical techniques that have been developed to compare sampling scheme selection, identify inputs for importance sampling, and assess result convergence and uncertainty. These techniques were developed and piloted for both the xLPR Scenario Analysis (SA) Report and the xLPR Sensitivity Analysis Template. This document provides a walk-through of the post-processing R code that was used to generate the results and figures presented in these documents. This page intentionally left blank.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2017

Automating cell detection and classification in human brain fluorescent microscopy images using dictionary learning and sparse coding

Background Immunofluorescence (IF) plays a major role in quantifying protein expression in situ and understanding cell function. It is widely applied in assessing disease mechanisms and in drug discovery research. Automation of IF analysis can transform studies using experimental cell models. However, IF analysis of postmortem human tissue relies mostly on manual interaction, often subjected to low-throughput and prone to error, leading to low inter and intra-observer reproducibility. Human postmortem brain samples challenges neuroscientists because of the high level of autofluorescence caused by accumulation of lipofuscin pigment during aging, hindering systematic analyses. We propose a method for automating cell counting and classification in IF microscopy of human postmortem brains. Our algorithm speeds up the quantification task while improving reproducibility. New method Dictionary learning and sparse coding allow for constructing improved cell representations using IF images. These models are input for detection and segmentation methods. Classification occurs by means of color distances between cells and a learned set. Results Our method successfully detected and classified cells in 49 human brain images. We evaluated our results regarding true positive, false positive, false negative, precision, recall, false positive rate and F1 score metrics. We also measured user-experience and time saved compared to manual countings. Comparison with existing methods We compared our results to four open-access IF-based cell-counting tools available in the literature. Lastly, our method showed improved accuracy for all data samples. Conclusion The proposed method satisfactorily detects and classifies cells from human postmortem brain IF images, with potential to be generalized for applications in other counting tasks.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2016

Radiative rates for E1, E2, M1, and M2 transitions in F-like ions with 37 ≤ Z ≤ 53

Calculations of energy levels, radiative rates and lifetimes are reported for 17 F-like ions with 37≤Z≤53. For brevity, results are only presented among the lowest 113 levels of the 2s{sup 2}2p{sup 5}, 2s2p{sup 6}, 2s{sup 2}2p{sup 4}3ℓ, 2s2p{sup 5}3ℓ, and 2p{sup 6}3ℓ configurations, although the calculations have been performed for up to 501 levels in each ion. The general-purpose relativistic atomic structure package (grasp) has been adopted for the calculations, and radiative rates (along with oscillator strengths and line strengths) are listed for all E1, E2, M1, and M2 transitions of the ions. Comparisons are made with earlier available experimental and theoretical energies, although these are limited to only a few levels for most ions. Therefore for additional accuracy assessments, particularly for energy levels, analogous calculations have been performed with the Flexible Atomic Code (fac), for up to 72 259 levels. Limited previous results are available for radiative rates for comparison purposes, and no large discrepancy is observed for any transition and/or ion.

74 ATOMIC AND MOLECULAR PHYSICS↗

DOE OSTI2016

Radiative rates for E1, E2, M1, and M2 transitions in S-like to F-like tungsten ions (W LIX to W LXVI)

Calculations of energy levels, radiative rates and lifetimes are reported for eight ions of tungsten, i.e. S-like (W LIX) to F-like (W LXVI). A large number of levels have been considered for each ion and extensive configuration interaction has been included among a range of configurations. For the calculations, the general-purpose relativistic atomic structure package (grasp) has been adopted, and radiative rates (as well as oscillator strengths and line strengths) are listed for all E1, E2, M1, and M2 transitions of the ions. Comparisons have been made with earlier available experimental and theoretical energies, although these are limited to only a few levels for most ions. Therefore for additional accuracy assessments, particularly for energy levels, analogous calculations have been performed with the flexible atomic code (fac).

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2022

Machine Learning in Infectious Disease for Risk Factor Identification and Hypothesis Generation: Proof of Concept Using Invasive Candidiasis

Machine learning (ML) models can handle large data sets without assuming underlying relationships and can be useful for evaluating disease characteristics, yet they are more commonly used for predicting individual disease risk than for identifying factors at the population level. We offer a proof of concept applying random forest (RF) algorithms to Candida-positive hospital encounters in an electronic health record database of patients in the United States. Candida-positive encounters were extracted from the Cerner HealthFacts database; invasive infections were laboratory-positive sterile site Candida infections. Features included demographics, admission source, care setting, physician specialty, diagnostic and procedure codes, and medications received before the first positive Candida culture. We used RF to assess risk factors for 3 outcomes: any invasive candidiasis (IC) vs non-IC, within-species IC vs non-IC (eg, invasive C. glabrata vs noninvasive C. glabrata), and between-species IC (eg, invasive C. glabrata vs all other IC). Fourteen of 169 (8%) variables were consistently identified as important features in the ML models. When evaluating within-species IC, for example, invasive C. glabrata vs non-invasive C. glabrata, we identified known features like central venous catheters, intensive care unit stay, and gastrointestinal operations. In contrast, important variables for invasive C. glabrata vs all other IC included renal disease and medications like diabetes therapeutics, cholesterol medications, and antiarrhythmics. Known and novel risk factors for IC were identified using ML, demonstrating the hypothesis-generating utility of this approach for infectious disease conditions about which less is known, specifically at the species level or for rarer diseases.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

Engineered Option Treatment of Remediated Nitrate Salts: Surrogate Batch-Blending Testing

This report provides results from batch-blending test work for remediated nitrate salt (RNS) treatment. Batch blending was identified as a preferred option for blending RNS and unremediated nitrate salt (UNS) material with zeolite to effectively safe the salt/Swheat material identified as ignitable (U.S. Environmental Protection Agency code D001). Blending with zeolite was the preferred remediation option identified in the Options Assessment Report and was originally proposed as the best option for remediation by Clark and Funk in their report, Chemical Reactivity and Recommended Remediation Strategy for Los Alamos Remediated Nitrate Salt (RNS) Wastes, and also found to be a preferred option in the Engineering Options Assessment Report: Nitrate Salt Waste Stream Processing. This test work evaluated equipment and recipe alternatives to achieve effective blending of surrogate waste with zeolite.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2017

MPAS-Ocean NESAP Status Report

NESAP performance improvements on MPAS-Ocean have resulted in a 5% to 7% speed-up on each of the examined systems including Cori-KNL, Cori-Haswell, and Edison. These tests were configured to emulate a production workload by using 128 nodes and a high-resolution ocean domain. Overall, the gap between standard and many-core architecture performance has been narrowed, but Cori-KNL remains considerably under-performing relative to Edison. NESAP code alterations affected 600 lines of code, and most of these improvements will benefit other MPAS codes (sea ice, land ice) that are also components within ACME. Modifications are fully tested within MPAS. Testing in ACME across many platforms is underway, and must be completed before the code is merged. In addition, a ten-year production ACME global simulation was conducted on Cori-KNL in late 2016 with the pre-NESAP code in order to test readiness and configurations for scientific studies. Next steps include assessing performance across a range of nodes, threads per node, and ocean resolutions on Cori-KNL.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

Preliminary Study on TRISO Fuel Cross Section Generation

Cross section self-shielding methodologies for TRISO fuel were assessed to provide accurate multigroup cross sections for a high-fidelity reactor physics code so that the code is able to accurately model and simulate advanced reactors with TRISO fuel. Initially, the two existing methodologies (the SCALE method and the Sanchez-Pomraning method) were studied and implemented to MC2-3 for detailed performance tests. Additionally, a new spatial self-shielding method, named the iterative local spatial self-shielding (ILSS) method, for particulate fuels was developed based on the disadvantage factor and implemented to MC2-3 as well. The new method approximately accounts for the effect of randomly distributed particles on the particle shadowing effect using a homogenized compact region surrounding a particle of interest at the center. The self-shielded cross sections of the particle at the center are determined iteratively since the cross sections of the homogenized compact region are calculated using them. For the energy range above 100 keV where the fuel-to-moderator ratio is more important than the random distribution of particles, a single particle unit-cell model is used by preserving the average amount of moderator per fuel particle in the system. The three self-shielding methods implemented in MC2-3 were tested using numerical benchmark problems made based on fuel compact problems of a prismatic-type very high temperature reactor. Test results indicated that the ILSS method produced slightly better results than the SCALE and Sanchez-Pomraning methods, compared to the Serpent-2 Monte Carlo results obtained with 25 independent random particle configurations. The SCALE and Sanchez-Pomraning methods tend to underestimate the heterogeneity effect by 150 and 100 pcm, respectively, while the new ILSS method overestimates the heterogeneity effect by 70 pcm. In future, the new self-shielding method will be extended to perform pebble calculations and compare results with those from the SCALE and Sanchez-Pomraning methods. Furthermore, the new method will be optimized for practical applications to on-the-fly resonance treatment for lattice or whole-core calculations for advanced reactors.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2019

A Comprehensive Radiological Characterization of the ACRR Facility

Radiation Protection (628) in conjunction with Nuclear Facility Operations (1381) completed a comprehensive radiological conditions characterization of the ACRR facility between August 2015 and January 2017 to better understand the radiological environment in and around the ACRR High-Bay. The overall goals of the characterization, as identified by 1381 and 628, were to determine potential dose to workers during routine reactor operations, areas of potential elevated dose in and around the ACRR High-Bay, the relationship between reactor power and dose during steady-state operations, and the dose per pulse for pulsed operations. To accomplish this, eight configurations were identified of interest for characterization based on increased dose potential for which field surveys were completed to include assessment of the neutron spectra for each, determination of neutron dose conversion factors (Neutron Codes) based on defined neutron spectra, mapped dose surveys for each configuration, as well as determination of the relationship between dose and reactor power level during steady-state reactor operations. Steady-state survey data was also used to calculate dose per pulse approximations during pulsed reactor operations.

61 RADIATION PROTECTION AND DOSIMETRY↗

DOE OSTI2022

Introduction to an MCGIDI Mini-App and Performance Comparisons with XSBench

In high-performance Monte Carlo (MC) radiation transport codes, cross section lookups often account for the majority of computational expens. In response to this observation, a number of nuclear data mini-apps have been developed to profile and optimize the lookup process. A review of these mini-apps can be found in Ref. In contrast to a fully fledged MC code, nuclear data mini-apps do not feature particle tracking; instead, the cross section lookup process is considered in isolation, a simplification that allows for easier implementation and evaluation of various lookup schemes and techniques. GIDI+, as described on its public repository1, is ...a collection of C++ libraries for accessing evaluated and processed nuclear data stored in the Generalized Nuclear Database Structure (GNDS). In addition to reading GNDS files, GIDI+ has functions to sum and collapse multi-group data as needed by deterministic transport codes, and to sample GNDS data as needed by Monte Carlo transport codes. Certain modes of Mercury, a LLNL-developed MC radiation transport code, utilize GIDI+ for cross section lookups. Specifically, Mercury uses the MCGIDI library contained within GIDI+ to perform lookups on GPUs. A mini-app exercising MCGIDI’s cross section lookup capabilities would prove useful for optimization, which in turn could improve the performance of client codes such as Mercury. Such a mini-app could also be used to assess the performance of MCGIDI compared to other nuclear data mini-apps. In this document, we introduce a nuclear data mini-app built with the MCGIDI library. The MCGIDI mini-app (MCGIDI-MA) was developed to closely resemble the methodology present in XSBench, a nuclear data mini-app developed at Argonne National Laboratory. The remainder of this section provides an overview on XSBench. Section 2 describes MCGIDI-MA and its usage. Section 3 contains performance results of MCGIDI-MA on LLNL’s Lassen and Quartz compute platforms, as well as comparisons to XSBench performance where appropriate. In Section 4, we present a summary of our findings.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2025

Probabilistic Seismic Hazard Analysis for Iraq Based on the Updated Earthquake Catalog (1900-2021) and Ground Motion Characteristics

Onur et al. (2017) compiled the first comprehensive earthquake catalog for Iraq, covering 1900 to 2009 within 26°–40°N latitude and 36°–51°E longitude. This catalog was utilized in a probabilistic seismic hazard assessment (PSHA) by Abdulnaby et al. (2020) to aid in updating Iraq’s building code seismic provisions. Recently, we have updated the earthquake catalog for Iraq by adding earthquakes recorded from 2010 to 2021 and directly calculating moment magnitude (Mw) for about 2,800 earthquakes using the coda envelope methodology and waveform data from the Mesopotamian Seismological Network (MPSN) in Iraq.

58 GEOSCIENCES↗