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At least 217 records · Page 12

Design and Analysis of the US ITER Central Solenoid Module Lifting Fixture

The central solenoid (CS) consists of six large high field superconducting magnets (also known as modules) approximately 4 m in diameter and 2 m tall that weigh approximately 120 tonnes each. These large and complex modules create challenges during assembly of the CS that require the development of custom assembly tooling such as the CS lifting fixture. The CS module lifting fixture is designed to lift and stack the six CS modules in the assembly building on the ITER site. Because of its unique design, fabrication, and assembly features, no lifting attachments could be incorporated within or under the CS modules. This limitation motivated the development of a friction-based lift fixture. The design and evaluation of the CS module lifting fixture considered both worker safety and investment protection, and the assessments were performed to international codes and standards. The CS module lifting fixture consists of two principal subassemblies: spider assembly and ring weldment. These subassemblies allow the frictional force to be augmented by the mechanical advantage of shallow-angle wedges. Large radial preloads created by both screw jack assemblies and the weight of a CS module develop frictional forces capable of performing a lift with a safety factor of at least 2. The design effort resulted in the use of low friction linear bearings on angle surfaces to ensure constant pressure, integrated jacks for pretensioning the fixture prior to lifting, and load pin strain gauges for monitoring the normal force. Testing of various materials and surface treatments led to the selection of laminated aluminum and rubber pads as the friction interface on the CS lifting fixture side and a grit-blasted Nitronic 50 stainless steel band on the CS module side. A redundant lifting method using the module slings between the spider and module is also utilized after the initial friction lift. The CS lifting fixture provides a safe and reliable solution for lifting and stacking the CS module during assembly.

Morris, Eric↗

New cyclophilin D inhibitor rescues mitochondrial and cognitive function in Alzheimer’s disease

Abstract Mitochondrial dysfunction is an early pathological feature of Alzheimer disease and plays a crucial role in the development and progression of Alzheimer’s disease. Strategies to rescue mitochondrial function and cognition remain to be explored. Cyclophilin D (CypD), the peptidylprolyl isomerase F (PPIase), is a key component in opening the mitochondrial membrane permeability transition pore, leading to mitochondrial dysfunction and cell death. Blocking membrane permeability transition pore opening by inhibiting CypD activity is a promising therapeutic approach for Alzheimer’s disease. However, there is currently no effective CypD inhibitor for Alzheimer’s disease, with previous candidates demonstrating high toxicity, poor ability to cross the blood–brain barrier, compromised biocompatibility and low selectivity. Here, we report a new class of non-toxic and biocompatible CypD inhibitor, ebselen, using a conventional PPIase assay to screen a library of ∼2000 FDA-approved drugs with crystallographic analysis of the CypD-ebselen crystal structure (PDB code: 8EJX). More importantly, we assessed the effects of genetic and pharmacological blockade of CypD on Alzheimer’s disease mitochondrial and glycolytic bioenergetics in Alzheimer’s disease-derived mitochondrial cybrid cells, an ex vivo human sporadic Alzheimer’s disease mitochondrial model, and on synaptic function, inflammatory response and learning and memory in Alzheimer’s disease mouse models. Inhibition of CypD by ebselen protects against sporadic Alzheimer’s disease- and amyloid-β-induced mitochondrial and glycolytic perturbation, synaptic and cognitive dysfunction, together with suppressing neuroinflammation in the brain of Alzheimer’s disease mouse models, which is linked to CypD-related membrane permeability transition pore formation. Thus, CypD inhibitors have the potential to slow the progression of neurodegenerative diseases, including Alzheimer’s disease, by boosting mitochondrial bioenergetics and improving synaptic and cognitive function.

Neurosciences & Neurology↗

Regulatory networks underlying mycorrhizal development delineated by genome-wide expression profiling and functional analysis of the transcription factor repertoire of the plant symbiotic fungus Laccaria bicolor

Background: Ectomycorrhizal (ECM) fungi develop a mutualistic symbiotic interaction with the roots of their host plants. During this process, they undergo a series of developmental transitions from the running hyphae in the rhizosphere to the coenocytic hyphae forming finger-like structures within the root apoplastic space. These transitions, which involve profound, symbiosis-associated metabolic changes, also entail a substantial transcriptome reprogramming with coordinated waves of differentially expressed genes. To date, little is known about the key transcriptional regulators driving these changes, and the aim of the present study was to delineate and functionally characterize the transcription factor (TF) repertoire of the model ECM fungus Laccaria bicolor. Results: We curated the L. bicolor gene models coding for transcription factors and assessed their expression and regulation in Poplar and Douglas fir ectomycorrhizae. We identified 285 TFs, 191 of which share a significant similarity with known transcriptional regulators. Expression profiling of the corresponding transcripts identified TF-encoding fungal genes differentially expressed in the ECM root tips of both host plants. The L. bicolor core set of differentially expressed TFs consists of 12 and 22 genes that are, respectively, upregulated and downregulated in symbiotic tissues. These TFs resemble known fungal regulators involved in the control of fungal invasive growth, fungal cell wall integrity, carbon and nitrogen metabolism, invasive stress response and fruiting-body development. However, this core set of mycorrhiza-regulated TFs seems to be characteristic of L. bicolor and our data suggest that each mycorrhizal fungus has evolved its own set of ECM development regulators. A subset of the above TFs was functionally validated with the use of a heterologous, transcription activation assay in yeast, which also allowed the identification of previously unknown, transcriptionally active yet secreted polypeptides designated as Secreted Transcriptional Activator Proteins (STAPs). Conclusions: Transcriptional regulators required for ECM symbiosis development in L. bicolor have been uncovered and classified through genome-wide analysis. This study also identifies the STAPs as a new class of potential ECM effectors, highly expressed in mycorrhizae, which may be involved in the control of the symbiotic root transcriptome.

59 BASIC BIOLOGICAL SCIENCES↗

Fulcrum House – Towards a Sustainable Composite Architecture

In the last decades, the accessibility to digital fabrication technologies positioned composites as an affordable, structurally efficient and low-maintenance alternative to traditional mineral-based and high-energy materials. Of special interest are carbon nanotubes (CNT) and carbon foam (CFoam) from methane and coal pyrolysis respectively, as an environmentally friendly substitute to glass and carbon fiber. This paper presents the design of a principled single-family house, as a first case study to identify the constraints of such a material system, including technology gap, techno-economic and life cycle assessment, as well as building code requirements. In turn, the investigation proposes a suitable design-to-fabrication workflow, which potentially could bring CNT and CFoam materials to the construction of buildings.

01 COAL, LIGNITE, AND PEAT↗

Verification and Validation of Open-Source Computational Fluid Dynamics Capabilities in MOOSE

The Multiphysics Object Oriented Simulation Environment (MOOSE) advances predictive modeling in nuclear research by simplifying the application design process and making modeling more efficient and accessible to researchers and the broader community. Because of MOOSE’s critical role in the scientific computation field, verification and validation are important to evaluate the reliability and credibility of MOOSE’s code, simulations, and models. To assess MOOSE’s Navier Stokes module and turbulence models, the following verification and validation University of Manchester ERCOFTAC cases were simulated in MOOSE, and the results were compared: Case 032 Turbulent Flow in a 2D Channel Case 079 Natural Convection in an Enclosed Cavity

46 - INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AN↗

SimLBR: Learning to Detect Fake Images by Learning to Detect Real Images

The rapid advancement of generative models has made the detection of AI-generated images a critical challenge for both research and society. Recent works have shown that most state-of-the-art fake image detection methods overfit to their training data and catastrophically fail when evaluated on curated hard test sets with strong distribution shifts. In this work, we argue that it is more principled to learn a tight decision boundary around the real image distribution and treat the fake category as a sink class. To this end, we propose SimLBR, a simple and efficient framework for fake image detection with Latent Blending Regularization (LBR). Our method significantly improves cross-generator generalization, achieving up to +24.85% accuracy and +69.62% recall on the challenging Chameleon benchmark. SimLBR is also highly efficient, training orders of magnitude faster than existing approaches. Furthermore, we emphasize the need for reliability-oriented evaluation in fake image detection, introducing risk-adjusted metrics and worst-case estimates to better assess model robustness. All the code and models are availabe at: https://github.com/mvrl/SimLBR

Dhakal, Aayush [Washington University, St. Louis]↗

Choosing the Best Modeling Platform for Radiological Risk Assessment Models - 20468

Radiological risk assessments, in the form of performance or safety assessments, are often required under regulations or guidance for remediation of contaminated land, decommissioning of contaminated buildings or structures, and radioactive waste disposal. These risk assessments are usually supported by fate and transport models that address decay and ingrowth of radionuclides, as well as their movement through engineered systems and the natural environment. These models are often projected thousands, or more, years into the future, largely because the radioactive species change through decay and ingrowth, and hence the magnitude of the radioactive effect changes with time. There are many computer codes that are available to address this type of modeling. They range from addressing specific pathways or processes such as infiltration of water, groundwater, surface water, air, biota, diffusion and advection of water and gases, to those that try to couple all processes together to evaluate the impact of fate and transport through the entire system to places in space and time to which access is assumed. These different types of codes are sometimes separated with the monikers process-level and systems-level codes, although it is often not clear that this separation does justice to the capabilities of the many codes that are available to evaluate fate and transport of radionuclides. The focus of this paper is the latter group of modeling codes. Several systems level modeling codes exist and are used. There are differences between these codes in terms of utility, flexibility, complexity and cost. The purpose of this paper is to compare a few of these codes in the context of work currently being performed by the International Atomic Energy Agency (IAEA) Modeling and Data for Radiological Impact Assessments (MODARIA) II Working Group 1 (WG1). The MODARIA II WG1's main focus is how stakeholder engaged decision analysis can, or should, be applied to radiological contamination problems so that better, longstanding, sustainable, solutions are reached. However, the WG1 also recognizes the potential impact of the modeling tools that are chosen to address radiological risk, which is often a primary objective of decision making for radiological problems. Other objectives might also be important, such as constraining costs, obtaining financing, minimizing impact on ecosystems, saving cultural resources, saving jobs, farmland, environmental justice, etc., in a full decision analysis for a given radiological contamination problem, but none of these other objectives have the same types of complex modeling needs as minimize radiological dose. Consequently, a further focus of WG1 is to evaluate the potential impacts on decision making of the choice of fate and transport, and risk assessment, modeling codes that are used to support decision making. The WG1 will produce a report at the end of 2020 that will focus on an approach to effective decision making and stakeholder engagement. The report will also consider the role that performance assessment modeling should play in the decision-making process, including the impact of the choice of modeling tools or computer codes on risk-informed decision making. Several sites around the World have been made available by Member States for these model comparisons, and several modeling tools have been considered. However, the focus of this paper is on two of the sites, one in Belgium and one in Ukraine, and on three of the tools: NORMALYSA (NORM And Legacy Site Assessment); GoldSim{sup C}, and AMBER{sup C}. The final report from this working group will also cover other modeling tools, including RESRAD, and PC-Cream{sup R}. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Impacts of Model Building Energy Codes – Interim Update

The U.S. Department of Energy (DOE) Building Energy Codes Program (BECP) periodically evaluates state and national impacts associated with energy codes in residential and commercial buildings. Pacific Northwest National Laboratory (PNNL), funded by DOE, assessed the prospective impacts of national model building energy codes from 2010 through 2040. The model codes of interest in this report are the International Energy Conservation Code (IECC) for residential buildings and ASHRAE Standard 90.1 for commercial buildings. This report describes the methodology used for the assessment and presents the impacts in terms of energy savings, consumer cost savings, and reduced CO 2 emissions at the state and national levels.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Impacts of Model Building Energy Codes

The Department of Energy (DOE) Building Energy Codes Program (BECP) periodically evaluates state and national impacts associated with energy codes in residential and commercial buildings. Pacific Northwest National Laboratory (PNNL), funded by DOE, assessed the prospective impacts of national model building energy codes from 2010 through 2040. The model codes of interest in this report are the International Energy Conservation Code (IECC) for residential buildings and ASHRAE Standard 90.1 for commercial buildings. This report describes the methodology used for the assessment and presents the impacts in terms of energy savings, consumer cost savings, and reduced CO 2 emissions at the state and national levels.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

A Comparison of Select USDOE and USEPA Risk and Dose Assessment Tools Utilized at Two FUSRAP Projects - 17388

The US Army Corps of Engineers (USACE) utilizes several computer programs and models to conduct risk and dose assessments at Formerly Utilized Sites Remedial Action Program (FUSRAP) projects. In the past, the USACE has primarily relied on the US Department of Energy (USDOE)'s Argonne National Lab (ANL) RESidual Radioactivity (RESRAD) computer code for performing dose and risk assessments involving radiological contamination in onsite soils and the US Environmental Protection Agency (USEPA) Preliminary Remediation Goal (PRG) and Dose Compliance Calculator (DCC) for radiological contamination in ground water. Recent USEPA guidance requires use of USEPA calculators for all media at National Priority List sites, which includes some FUSRAP sites. The USACE recently utilized both RESRAD and the USEPA PRG and DCC calculators in assessments at two FUSRAP projects for all media in order to evaluate differences in the models and determine adjustments to potentially resolve differences. The two projects involve soil and groundwater assessments and address typical FUSRAP contaminants such as uranium, radium, thorium and their progeny. This paper discusses differences between the models, lessons learned, and methods used to address stakeholder and other concerns regarding these assessments. The paper's discussions are useful for anyone performing risk or dose assessments for radiological contamination and especially those using RESRAD and the PRG and DCC calculators. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Differentiable Multiphysics Codes: A Breakthrough Technology for Simulation and Computing

This document summarizes the findings of a strategic planning exercise commissioned by the Weapons Simulation and Computing, Computational Physics (WSC/CP) program at the Lawrence Livermore National Laboratory (LLNL) in FY24. During the year, the committee met with multiple stakeholder communities to gather input, opinions, suggestions and concerns which have been incorporated throughout this document. The key findings from this exercise are summarized: • The development of multiphysics modelling and simulation (mod/sim) codes and software technologies, their deployment on exascale compute platforms, and their broad adoption across the NNSA is a major success of the Advanced Simulation and Computing (ASC) program and the Exascale Computing Project (ECP). Sustained investment in these core technologies is essential. • Today’s state of the art involves running ensembles of O(100K) simulations to perform uncertainty quantification (UQ) and design studies using multiple statistical methods such as Bayesian optimization to understand sensitivities of our models and explore parameterized design spaces. Even with exascale computing, we are practically limited to O(10) parameters in these studies since the number of simulations required to sample the space scales exponentially with the number of design parameters. • The data from these simulation ensembles is increasingly being used to train machine learned (ML) surrogates (or reduced order models, ROMs) which can then be used for optimization or real time design exploration. However, the trained surrogates are still limited in the number of parameters they can represent due to the sampling limitations previously noted. • Augmenting our suite of integrated multiphysics simulation codes, both current and emerging, with the ability to compute gradients (solution derivatives) of arbitrary simulation outputs with respect to (some or all) simulation inputs would be a breakthrough technology, opening the door to a new era of efficient and automated inverse design based on verified and validated mod/sim capabilities. • This capability, which we refer to as differentiable multiphysics codes (DMCs), would revolutionize both UQ and optimization studies by breaking the curse of dimensionality that presently limits our “gradient-free” ensemble based computing approach. A similar breakthrough occurred in the AI/ML community once the ability to compute gradients of arbitrary loss functions using back-propagation became commonplace. Gradient information from the multiphysics codes can also be used to dramatically improve the efficiency and scale of training of ML/ROM surrogates for rapid assessments. • Achieving this in our suite of codes will be a grand challenge, similar to the amount of effort that was required to transition from CPU to GPU computing. It will require buy-in from the entire WSC/CP program and beyond, including all integrated codes, physics and engineering models, third-party library dependencies and performance portability abstractions. It will also require investment in research and development of numerical methods for computing adjoints of coupled physics across multiple adaptively refined moving meshes and of stochastic (Monte Carlo) and mesh free (SPH) methods. • New software and numerical techniques, largely pioneered by the AI/ML community, make this feasible. Chief among these is automatic differentiation (AD), the ability to employ AD at point-wise locations in a physics calculation (instead of traditional black-box approaches) and the ability to perform “back-propagation in time” (or reverse mode AD) for non-linear partial differential equations (PDEs). Fundamentally, the conclusion of this strategic planning exercise is that the time is right to undertake a large scale effort in WSC, centered on the existing integrated codes, to continue the natural evolution of mod/sim in the age of AI/ML. Instead of attempting to replace mod/sim with purely data driven AI/ML models, we believe the key to success is to integrate AI/ML by building on top of the decades of hard-won knowledge and the verified/validated multiphysics modelling capability that is the hallmark of the ASC program.

97 MATHEMATICS AND COMPUTING↗

Hydrogen Quantitative Risk Assessment (Annual Progress Report)

DOE has identified consistent safety, codes, and standards as a critical need for the deployment of hydrogen technologies, with key barriers related to the availability and implementation of technical information in the development of regulations, codes, and standards. Advances in codes and standards have been enabled by risk-informed approaches to create and implement revisions to codes, such as National Fire Protection Association (NFPA) 2, NFPA 55, and International Organization for Standardization (ISO) Technical Specification (TS)-19880-1. This project provides the technical basis for these revisions, enabling the assessment of the safety of hydrogen fuel cell systems and infrastructure using QRA and physics-based models of hydrogen behavior. The risk and behavior tools that are developed in this project are motivated by, shared directly with, and used by the committees revising relevant codes and standards, thus forming the scientific basis to ensure that code requirements are consistent, logical, and defensible.

08 HYDROGEN↗

Assessment of the strength of kinetic effects of parallel electron transport in the SOL and divertor of JET high radiative H-mode plasmas using EDGE2D-EIRENE and KIPP codes

The kinetic code for plasma periphery (KIPP) was used here to assess the importance of the kinetic effects of parallel electron transport in the scrape-off layer (SOL) and divertor of JET high radiative H-mode inter-ELM plasma conditions with the ITER-like wall and strong nitrogen (N 2 ) injection. Plasma parameter profiles along a magnetic field from one of the EDGE2D-EIRENE simulation cases were used as an input for KIPP runs. Profiles were maintained by particle and power sources. KIPP generated electron distribution functions, f e , parallel power fluxes, electron–ion thermoforces, Debye sheath potential drops and electron sheath transmission factors at divertor targets. For heat fluxes in the main SOL, KIPP results showed deviations from classical (e.g. Braginskii) fluxes by factors typically of ~1.5, sometimes up to 2, with the flux limiting for more upstream positions and flux enhancement near entrances to the divertor. In the divertor, at the same time, for radial positions closer to the separatrix, very large heat flux enhancement factors of up to ten or even higher, indicative of a strong nonlocal heat transport, were found at the outer target, with heat power flux density exhibiting bump-on-tail features at high energies. Under such extreme conditions, however, contributions of conductive power fluxes to total power fluxes were strongly reduced, with convective power fluxes becoming comparable, or sometimes exceeding, conductive power fluxes. Electron–ion thermoforce, on the other hand, which is known to be determined mostly by thermal and subthermal electrons, was found to be in good agreement with Braginskii formulas, including the Z eff dependence. Overall, KIPP results indicate, at least for the plasma conditions used in this modelling, a sizable, but not dominant, effect of kinetics on parallel electron transport.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

ADETS User Manual

ADETS (Automated DEpletion Transport System) calculates coupled neutronic/isotopic results for nuclear systems and produces a large number of criticality and burnup results based on various material feed/removal specifications, power(s), and time intervals. ADETS is a fully automated tool that links the LANL MCNP Monte Carlo transport code with the SCALE system, specifically ORIGEN-ARP (radioactive decay and burnup code). Additionally, ADETS can compute the dose at various distances of the reactor using a point gamma source, whose characteristics are computed by ORIGEN-ARP. In addition, ADETS is fully coupled with the Uncertanty Quantification, Probabilistic Risk Assessment, Parameter Optimization and Data Analysis code RAVEN (developed at the Idaho National Laboratory as well). RAVEN is released with ADETS but MCNP and SCALE (ORIGEN-ARP) are not included.

42 ENGINEERING↗

Multiview Incomplete Knowledge Graph Integration with application to cross-institutional EHR data harmonization

Objective: The growing availability of electronic health records (EHR) data opens opportunities for integrative analysis of multi-institutional EHR to produce generalizable knowledge. A key barrier to such integrative analyses is the lack of semantic interoperability across different institutions due to coding differences. We propose a Multiview Incomplete Knowledge Graph Integration (MIKGI) algorithm to integrate information from multiple sources with partially overlapping EHR concept codes to enable translations between healthcare systems. Methods: The MIKGI algorithm combines knowledge graph information from (i) embeddings trained from the co-occurrence patterns of medical codes within each EHR system and (ii) semantic embeddings of the textual strings of all medical codes obtained from the Self-Aligning Pretrained BERT (SAPBERT) algorithm. Due to the heterogeneity in the coding across healthcare systems, each EHR source provides partial coverage of the available codes. MIKGI synthesizes the incomplete knowledge graphs derived from these multi-source embeddings by minimizing a spherical loss function that combines the pairwise directional similarities of embeddings computed from all available sources. MIKGI outputs harmonized semantic embedding vectors for all EHR codes, which improves the quality of the embeddings and enables direct assessment of both similarity and relatedness between any pair of codes from multiple healthcare systems. Results: With EHR co-occurrence data from Veteran Affairs (VA) healthcare and Mass General Brigham (MGB), MIKGI algorithm produces high quality embeddings for a variety of downstream tasks including detecting known similar or related entity pairs and mapping VA local codes to the relevant EHR codes used at MGB. Based on the cosine similarity of the MIKGI trained embeddings, the AUC was 0.918 for detecting similar entity pairs and 0.809 for detecting related pairs. For cross-institutional medical code mapping, the top 1 and top 5 accuracy were 91.0% and 97.5% when mapping medication codes at VA to RxNorm medication codes at MGB; 59.1% and 75.8% when mapping VA local laboratory codes to LOINC hierarchy. When trained with 500 labels, the lab code mapping attained top 1 and 5 accuracy at 77.7% and 87.9%. MIKGI also attained best performance in selecting VA local lab codes for desired laboratory tests and COVID-19 related features for COVID EHR studies. Compared to existing methods, MIKGI attained the most robust performance with accuracy the highest or near the highest across all tasks. Conclusions: The proposed MIKGI algorithm can effectively integrate incomplete summary data from biomedical text and EHR data to generate harmonized embeddings for EHR codes for knowledge graph modeling and cross-institutional translation of EHR codes.

Zhou, Doudou↗

SCALE 6.2 Lattice Physics Performance Assessment

The US Nuclear Regulatory Commission relies on the lattice physics analysis capabilities of the SCALE code system to perform confirmatory licensing analyses. Either SCALE lattice physics code—TRITON/NEWT or Polaris—can be used to generate cross section data used by the PARCS nodal core simulator for full-core neutronics calculations. This report presents an assessment of the accuracy of SCALE lattice physics codes for preparation of lattice physics data that are used to support simulator codes such as the NRC’s PARCS, for UO 2 -mixed oxide (MOX)/Zr fueled light water reactor (LWR) analyses. Due to the nature of lattice physics calculations, critical reactor experiment benchmarks cannot be modeled in explicit detail in a lattice physics code. However, this limitation does not mean that these measurement data are not usable for lattice physics studies. Therefore, either geometry approximations or axial buckling must be implemented to determine the critical water height. These modeling limitations have led to development of a three-phase assessment strategy. In the first phase, selected critical experiment benchmarks are modeled using the SCALE 3D continuous-energy (CE) Monte Carlo (MC) code KENO, which is the most rigorous neutron transport method available in SCALE, with no approximations in the spatial, angle, or energy treatments. Biases and statistical uncertainties in quantities of interest such as k eff and pin power distributions are determined by comparing CE KENO results to experimental data. This first phase in the accuracy assessment is to demonstrate and establish the use of CE KENO as a reference solution for the second phase. In the second phase, 14 numerical test suites are used to compare SCALE lattice physics calculations with CE KENO as a reference solution. In the third phase, SCALE lattice physics depletion calculations are performed, and the spent fuel isotopic results are compared with available radiochemical assay measurements. Isotopic measurement comparisons provide quantitative assessment of isotopic density distribution predictions with the depletion models in SCALE lattice physics codes. This report documents results for all test suites. The assessment was performed using standard production techniques unless otherwise noted. Both TRITON/NEWT and Polaris exhibited acceptable accuracy for most test cases. For the few test cases in which acceptable accuracy criteria were not met, further code and data development are planned. The computer codes used in this assessment are as follows: SCALE 6.2 rev19189 (pre-release of 6.2.1) was used for CE KENO, TRITON/NEWT and Polaris (PWR only) calculations; SCALE 6.2.2 was used for Polaris calculations to address several updates in support of support boiling water reactor (BWR) lattice geometries. For this work, there is no difference between SCALE 6.2.1 and SCALE 6.2.2 beyond the inclusion of the Polaris BWR analysis capability; The ENDF/B-VII.1 continuous energy and 252 group libraries deployed in SCALE 6.2 were generated with AMPX 6.2 that is distributed with SCALE.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Graphite Degradation Modeling and Analysis

A graphite component in a nuclear reactor core is subjected to variety of stresses and can experience degradation during normal and off-normal operation. Understanding how a graphite component will behave in service is essential to ensuring core structural stability and safe reactor operation. This report summarizes a graphite modeling tool currently under development at Idaho National Laboratory. The model incorporates several of the anticipated stresses during service and includes the effects of oxidation and irradiation prior to turnaround. This tool is intended to be used to help assess the design of graphite components by utilizing design code rules found in Section III, Division 5 of the American Society of Mechanical Engineering Boiler and Pressure Vessel Code. Specifically, the tool uses the methodologies found within the Full and Simplified assessments from Article HHA-3000 to verify that a graphite component has an acceptably low probability of failure.

36 MATERIALS SCIENCE↗

Assessment of CTF for Steady-state and Transient Post-CHF Conditions in Support of Time-at-Temperature Modeling Applications

The US nuclear industry is exploring options to improve operational economics and uprate the current fleet of light-water reactors by investigating transitioning to cladding performance–based safety criteria as opposed to the current limit, which requires complete avoidance of critical heat flux (CHF)/dryout. Past experience has shown that not all events leading to a dryout are severe enough to cause fuel performance degradation. Allowing temporary dryout of the fuel—that is, using a time-at-temperature (TaT) strategy—could allow for economic improvements via large power uprates and enhanced operational flexibility for current plants without compromising fuel integrity. To support this effort, the US Department of Energy is executing a comprehensive program that includes generating cladding material data under TaT conditions, developing new mechanistic models, and demonstrating modeling and simulation capabilities for transients of interest. This paper presents work performed to assess the CTF thermal-hydraulics subchannel code. CTF is a package used in the VERA core simulator, which will ultimately be used for TaT analysis. CTF will provide the thermal-hydraulic boundary conditions that will be needed for fuel performance analysis in the BISON code. Quantifying both the accuracy and uncertainty of post-CHF models will therefore be necessary. This paper outlines the strategy for the assessment of TaT and presents the results of using the steady-state and transient dryout experiments of the Boiling Fine-mesh Bundle Tests for CTF validation. The results show that the current model tends to overpredict steady-state critical power. This behavior translates to the transient tests, in which CTF is unable to capture transient dryout behavior. Some discussion of sensitivity analysis work being performed is provided to indicate which models must be further analyzed to properly model transient dryout and its uncertainty.

Salko Jr, Robert [ORNL] (ORCID:0000000253566679)↗