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All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Constellation's best estimate alternate source term methodology overview

Safety analyses for a nuclear power plants need to consider postulated accidents that results in at risk of accidental release of radiation. The regulations require plant specific safety analysis reports to include an evaluation of the requirements of 10CFR50.67. Such a safety analysis report mandates limits such that calculated radiological consequences relative to certain dose locations do not exceed a total effective dose equivalent (TEDE) limits following a postulated release of radioactivity. Calculations are performed to estimate the radiological consequences, in terms of dose, to people and equipment to ensure the estimated doses are within the prescribed limits. Analysis should demonstrate, with reasonable assurance, that these prescribed limits are complied with. Conventional methodologies utilize conservative approaches to address lack of uncertainty quantification in the utilized approaches, methods, and/or inputs. These built-in excess conservatisms often result in compounding effects and hence overly conservative results in the estimated radiological consequences, which leads to inaccurate margin evaluation for operation and accident mitigation. Therefore, evaluating accurate dose consequences is needed for both operational and safety reasons. The research documented in this paper provides an overview of Constellation's Best Estimate Alternate Source Term (BEAST) Methodology. BEAST methodology relies upon the use of realistic yet bounding input distributions for key analysis parameters, which replaces use of conservative deterministic singular inputs that bound overall analysis domain. This approach enables evaluating a more accurate accident analysis response, while enabling a bounding licensing basis envelope via more accurate quantification of uncertainty in the application. Therefore, built-in margin for a given scenario is more accurately evaluated.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Protocol-dependent frictional granular jamming simulations: cyclical, compression, and expansion

Granular matter takes many paths to pack in natural and industrial processes. The path influences the packing microstructure, particularly for frictional grains. We perform discrete element modeling simulations of different paths to construct packings of frictional spheres. Specifically, we explore four stress-controlled protocols implementing packing expansions and compressions in various combinations thereof. We characterize the eventual packed states through their dependence of the packing fraction and coordination number on packing pressure, identifying non-monotonicities with pressure that correlate with the fraction of frictional contacts. These stress-controlled, bulk-like particle simulations access very low-pressure packings, namely, the marginally stable limit, and demonstrate the strong protocol dependence of frictional granular matter.

36 MATERIALS SCIENCE↗
DOE OSTI2023

An Integrated Framework for Risk Assessment of Safety-related Digital Instrumentation and Control Systems in Nuclear Power Plants: Methodology Refinement and Exploration

This report documents activities performed by Idaho National Laboratory (INL) during Fiscal Year (FY) 2023 for the U.S. Department of Energy (DOE) Light Water Reactor Sustainability (LWRS) Program, Risk Informed Systems Analysis (RISA) Pathway, digital instrumentation and control (DI&C) risk assessment project. In FY 2019, the RISA Pathway initiated a project to develop a risk assessment strategy for delivering a technical basis to support effective, and secure DI&C technologies for digital upgrades/designs. A risk assessment-informed framework was proposed for this strategy, which aims to (1) provide a best-estimate, risk informed capability to quantitatively estimate the safety margin obtained from plant modernization, especially for safety-related DI&C systems, (2) support and supplement existing risk informed DI&C design guides by providing quantitative risk information and evidence, (3) offer a capability of design architecture evaluation of various DI&C systems, (4) assure the long-term safety and reliability of safety-related DI&C systems, and (5) reduce uncertainty in costs and support integration of DI&C systems in the plant. To achieve these technical goals, the LWRS-developed framework provides a means to address relevant technical issues by: (1) defining a risk informed analysis process for DI&C upgrade that integrates hazard analysis, reliability analysis, and consequence analysis, (2) applying risk informed tools to address common cause failures (CCFs) and quantify corresponding failure probabilities for DI&C technologies, particularly software CCFs, (3) evaluating the impact of digital failures at the component level, system level, and plant level, and (4) providing insights and suggestions on designs to manage the risks, thus to support the development and deployment of advanced DI&C technologies in nuclear power plants (NPPs). Adding diversity within a system or components is the primary means to eliminate and mitigate CCFs, but diversity also increases system complexity and may not address all sources of systematic failures. Optimization of diversity and redundancy applications for the safety-critical DI&C systems remains a challenge. To deal with the technical issues in addressing potential software CCFs in safety-related DI&C systems of NPPs and supporting relevant design optimization, the proposed framework provides: (a) A best-estimate, risk informed capability to address new technical digital issues quantitatively, focusing on software CCFs in safety-related DI&C systems of NPPs; (b) A common and a modularized platform for DI&C designers, software developers, cybersecurity analysts, and plant engineers to predict and prevent risk in the early design stage of DI&C systems; (c) Technical bases and risk informed insights to assist users address the risk informed alternatives for evaluation of CCFs in safety-related DI&C systems of NPPs; and (d) A risk informed tool that offers a capability of design architecture evaluation of various DI&C systems to support system design decisions in diversity and redundancy applications. The research and development efforts of this project in FY 2023 are focused on refining current methods on software CCF modeling and estimation and exploring additional innovative approaches to risk assessment of DI&C systems to enable a more comprehensive and complete assessment of various safety-related DI&C design architectures. The primary audience of this report are DI&C designers, engineers, and probabilistic risk assessment (PRA) practitioners. This includes stakeholders, such as the nuclear utilities and regulators who consider the deployment and upgrade of DI&C systems, DI&C software developers and reviewers, and cybersecurity specialists. It should be noted that all the analyses are performed for the demonstration of the methodology, not for the evaluation of an actual digital control system. Results are obtained based on limited design information and testing data.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

ARDP Natrium Neutronic Methodology: Argonne Neutronic Assessment of ABR-1000

The Natrium Sodium-cooled Fast Reactor (SFR) concept developed by TerraPower, LLC was selected as one of the advanced reactor designs for demonstration under the Advanced Reactor Demonstration Program Natrium Demo project. In collaboration with TerraPower, the Argonne National Laboratory (ANL) team provide independent reviews of the neutronic methodology being used for the Natrium design. As part of this activity, both the TerraPower and ANL teams agreed to perform independent neutronics analyses of the ABR-1000 reactor problem as a demonstration on the usage of the neutronics methodologies. Comparison of the results from TerraPower and ANL would expose any methodological differences in the modeling approaches. This report describes and presents the Argonne analysis work on the ABR-1000, and will be provided to TerraPower, along with data files, to complete the comparison study. The comparison will cover the methodology to evaluate the reactivity coefficients for a safety analysis, the shutdown margin, and the reconstructed pin power distribution. The methods and models used to calculate the kinetic parameters and the reactivity coefficients (density, Doppler, axial/radial expansion, etc.) are described in detail with recommendations of specific method options and modelling techniques. The control system reactivity worth and the excess reactivity due to temperature defect are calculated for the shutdown margin analysis. The method to evaluate the excess reactivity is discussed in detail. The pin power reconstruction methodology used in SE2ANL, SE2RCT, and DASSH are discussed in this report. The pin power distribution evaluated by different methods are compared and discussed in the report.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Credible Criticality Safety Margin in the 30B Package with LEU+ UF 6 and Hypothetical Water Ingress

The commercial nuclear industry is pursuing advancements in fuel and reactor design that increase the uranium enrichment above 5 wt. % 235 U. These advancements will necessitate the ability to transport bulk quantities of UF 6 at increased enrichments. Currently, the 30B cylinder is the primary container used by the industry for UF 6 storage and transportation and has a long history of successful shipments. This container can support up to 2,277 kg of UF 6 at a maximum enrichment of 5 wt. % 235 U. Previous evaluations have assessed the potential impact of criticality safety for 30B transport at higher enrichments but assumed moderator intrusion would not require evaluation. Although current regulations allow for the exception of moderator intrusion for UF 6 packages through the design and quality control of the package content, this exception is limited to enrichments up to 5 wt. % 235 U. Thus, an investigation of moderator intrusion into a 30B cylinder should be performed. Moderator intrusion into a 30B cylinder is a unique condition for criticality safety evaluation in transportation because of the violent chemical reactions that occur between UF 6 and H 2 O. The resulting intrusion is strongly dependent on the breach size, breach location, breach interface solid/ullage of the UF 6 content, the UF 6 distribution (which is temperature dependent), and temperature/pressure conditions which are dynamic in accident conditions. Additionally, the complexity of the HF-UO 2 F 2 -H 2 O interface that occurs during the event can influence the potential solubility of uranium in the system, as well as influence the amount of UF 6 reaction with H 2 O. With the operating experience from Orano Federal Services LLC, the UF 6 chemical expertise from Oak Ridge National Laboratory (ORNL), and the criticality safety expertise from ORNL, this paper evaluates the neutronic conditions (i.e., k eff ) that apply the understood chemistry and experimental conditions that occur during moderator intrusion of a breached 30B cylinder under postulated accidents. This report examines the historical evaluations of UF 6 transport and expands these evaluations for the enrichments expected for nuclear industry advancement. These simulations primarily feature a homogeneous mixture of UF 6 and H 2 O as an infinite media system and as a sphere with water reflection given an impurity limit of 0.5 wt. % UF 6 . This report demonstrates that this H/U limit is valid up to 8 wt. % enrichment for both H 2 O and HF as the moderating mixture. The water-reflected homogeneous mixed spheres evaluated demonstrate the amount of safety margin applied by restricting the 30B cylinder impurity limit to 0.5 wt. %. Additionally, this report evaluates moderator ingress scenarios of a 30B cylinder. The 30B cylinder simulations vary the cylinder orientation, the mass of UF 6 in the system, the mass of H 2 O in the system, and how much H 2 O has reacted with UF 6 . The moderator ingress of a 30B cylinder was evaluated for the water-reflected homogeneous mixed spheres to demonstrate the amount of safety margin applied by restricting the 30B cylinder impurity limit to 0.5 wt. %. These simulations are standard practice and are independent of the UF 6 -H 2 O reaction. This work also explored more complex simulations that layer the H 2 O over the UF 6 , which incorporates the amount of reacted UF 6 as a separate layer and considers solubility limits of UO 2 F 2 in H 2 O as it is produced. This approach is intended to simulate the postulated event of a large hairline crack occurring on a submerged cylinder. Finally, this work considers the potential of H 2 O mixing into the UF 6 solid heterogeneously using a sponge-like model. The water ingress into the UF 6 is treated as random size spheres, and the reaction products form into a layer over the spheres.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

The Sensitivity of PBX 9502 to Drilling Operations

Polymer-bonded explosive (PBX) 9502 (95% TATB, 5% Kel-F 800 by weight) is dry-drilled on a CNC milling machine and its thermomechanical response to varying feed rates, drilling speeds, and peck depths with 4 mm and 5 mm diameter drill bits is investigated. The tested samples are affixed to a force sensor that enables recording temporally resolved cutting forces and torques, and a drill-embedded thermocouple yields local temperature data. From the data, an empirical relationship between temperature changes and feed per revolution is developed, which reveals reduced temperatures in higher feed per revolution regimes for PBX 9502. The observed relationship allows extrapolating to temperatures for other hole diameters, indicating increased temperature for smaller diameter drilling across the board. Additional testing was performed with PBX 9501 (95% HMX, 2.5% Estane®, 2.5% BDNPA/BDNPF by weight), albeit over a reduced parameter space, which revealed the opposite behavior for the feed per revolution temperature dependence. It is concluded that both PBX 9502 and PBX 9501 can be dry-drilled efficiently beyond the limits of presently applicable US-DOE standards, where cutting interface temperatures remain far below material critical temperatures. Finally, data reveals that coolant usage in the drilling process for these materials provides a wide safety margin.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

High-yield implosion modeling using the Frustraum: Assessing and controlling the formation of polar jets and enhancing implosion performance with applied magnetization

Frustraums have a higher laser-to-capsule x-ray radiation coupling efficiency and can accommodate a large capsule, thus potentially generating a higher yield with less laser energy than cylindrical Hohlraums for a given Hohlraum volume [Amendt et al., Phys. Plasmas 26, 082707 (2019]. Frustraums are expected to have less m = 4 azimuthal asymmetries arising from the intrinsic inner-laser-beam geometry on the National Ignition Facility. An experimental campaign at Lawrence Livermore National Laboratory to demonstrate the high-coupling efficiency and radiation symmetry tuning of the Frustraum has been under way since 2021. Simulations benchmarked against experimental data show that implosions using Frustraums can achieve more yield with higher ignition margins than cylindrical Hohlraums using the same laser energy. Hydrodynamic jets in capsules along the Hohlraum axis, driven by radiation-flux asymmetries in a Hohlraum with a gold liner on a depleted uranium (DU) wall, are present around stagnation, and these “polar” jets can cause severe yield degradation. The early-time Legendre mode P4<0 radiation-flux asymmetry is a leading cause of these jets, which can be reduced by using an unlined DU Hohlraum because the shape of the shell is predicted to be more prolate. Magnetization can increase the implosion robustness and reduce the required hotspot ρR for ignition; therefore, magnetizing the Frustraum can maintain the same yield while reducing the required laser energy or increase the yield using the same laser energy—all under the constraint that the ignition margin is preserved. Reducing polar jets is particularly important for magnetized implosions because of the intrinsic toroidal hotspot ion temperature topology.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Enhanced LWR High Burnup Transient Simulation Capabilities to Support AOO Margin Identification

As part of ongoing efforts to support the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program’s development of a fuel fragmentation, relocation, and dispersal (FFRD) screening methodology, a number of improvements are required for the NEAMS core simulation capabilities, namely the Virtual Environment for Reactor Applications (VERA). Three areas of improvement were identified in VERA which are important for continued development and application of the FFRD screening methodology. First, the FFRD screening methodology will soon be extended to boiling water reactors (BWRs), requiring development and validation of the VERA BWR capabilities. Second, the screening methodology occasionally requires that VERA be used to simulate a transient in addition to nominal operations. Thus, improvements to both accuracy and performance of the VERA transient capabilities are necessary. Third, the VERAOneWay component of VERA is used to develop BISON fuel performance inputs using the rod-by-rod histories calculated by VERA. Prior use of VERAOneWay exposed significant accuracy, robustness, and performance issues with VERAOneWay; these must be addressed for it to be an effective tool in the NEAMS FFRD methodology. This report documents the efforts in FY23 in each of these three areas to enable successful use of VERA and VERAOneWay for FFRD calculations in FY24 and following years.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

On the use of neural networks for energy reconstruction in high-granularity calorimeters

We contrasted the performance of deep neural networks — Convolutional Neural Network (CNN) and Graph Neural Network (GNN) — to current state of the art energy regression methods in a finely 3D-segmented calorimeter simulated by GEANT4. This comparative benchmark gives us some insight to assess the particular latent signals neural network methods exploit to achieve superior resolution. A CNN trained solely on a pure sample of pions achieved substantial improvement in the energy resolution for both single pions and jets over the conventional approaches. It maintained good performance for electron and photon reconstruction. We also used the Graph Neural Network (GNN) with edge convolution to assess the importance of timing information in the shower development for improved energy reconstruction. We implement a simple simulation based correction to the energy sum derived from the fraction of energy deposited in the electromagnetic shower component. This serves as an approximate dual-readout analogue for our benchmark comparison. Although this study does not include the simulation of detector effects, such as electronic noise, the margin of improvement seems robust enough to suggest these benefits will endure in real-world application. We also find reason to infer that the CNN/GNN methods leverage latent features that concur with our current understanding of the physics of calorimeter measurement.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

Intermediate-Term Thermal Aging Effect Evaluation for Grade 92 and 316L at The LWR Relevant Temperature

Life extension of the existing nuclear reactors imposes accumulated damages, such as higher fluences and longer period of corrosion, to structural materials, which would result in significant challenges to the traditional reactor materials such as type 304 and 316 stainless steels. Advanced alloys with superior radiation resistance will increase safety margins, design flexibility, and economics for not only the life extension of the existing fleet but also new builds with advanced reactor designs. The Electric Power Research Institute (EPRI) teamed up with Department of Energy (DOE) on the Advanced Radiation Resistant Materials (ARRM) program, aiming to develop and test degradation resistant alloys from current commercial alloy specifications by 2021 to a new advanced alloy with superior degradation resistance in light water reactor (LWR)-relevant environments by 2024. Based on a comprehensive microstructure and property screening performed in Phase-1 of the ARRM program, a total of five alloys, together with 316L and X-750 as references, were down-selected for Phase-2 neutron irradiation studies. Because thermal aging could exert a synergistic effect on neutron irradiation due to the low neutron damage rate on the order of 10 –7 displacements per atom per second (dpa/s), Grade 92 (one of the five down-selected alloys) and two heats of 316L were selected in this task to study the effect of aging at 350°C for 12.5–12.7 kh on microstructure and mechanical properties. The aging time is approximately corresponding to 5 dpa neutron irradiation, which can be served as a reference for the 5-dpa-irradiated samples of the alloys to help understand the independent neutron damage influence on microstructure and mechanical properties. Optical microscopy and scanning electron microscopy were used for microstructural characterization. Hardness, tensile, Charpy impact toughness, and fracture toughness in the ductile regime of the aged samples were examined. The aging of Grade 92 led to the formation of many Laves phase in sizes of ~100–200 nm and resulted in some reduction in hardness and yield/ultimate tensile strength with some increases in uniform and total plastic elongations, which may have helped the enhancement of Charpy impact toughness, e.g., ~4 J increase in upper-shelf energy and 20.5°C reduction in ductile-brittle transition temperature compared with the unaged condition. The fracture toughness of the aged Grade 92 showed decent toughness of ~303 MPa√m (K Jq ) with ~87 tearing modulus at 22°C, which reduced to ~241 MPa√m (~20% reduction) with ~75 tearing modulus at 300°C. The two heats of 316L are differentiated by their amounts of δ-ferrite, i.e., ~1 vol% in heat T1103 and ~4 vol% in heat N5B8. The two heats of 316L were subjected to 15% cold work (CW) as this condition is often used in nuclear reactors to help trapping radiation-induced defects and thus postpone the steady state swelling stage. The aging did not result in any noticeable microstructure changes, except for possible segregations at grain boundaries that need to be further investigated. The aging resulted in slight reduction in hardness of 316L-T1103 and slight increase in hardness of 316L-N5B8, which is consistent with their tensile testing results. The 15%CW might have introduced some inhomogeneity, resulting in large standard deviations in hardness, which were reduced after the aging. The aged 316L followed the same trend as the unaged condition for the strength and elongation results from the tensile testing. Minimum elongations appeared within ~300–600°C, above which the elongations seem to increase. Unlike the negligible or minor changes in microstructure, hardness and tensile results of the two heats of 316L, their fracture toughness showed noticeable difference. The aged 316L-T1103 showed good toughness of ~350 MPa√m with ~80 tearing modulus at 22°C, which reduced to ~271 MPa√m (~23% reduction) with ~83 tearing modulus at 300°C. In contrast, the aged 316L-N5B8 showed lower toughness of ~244 MPa√m with ~53 tearing modulus at 22°C, which reduced to ~180 MPa√m (~26% reduction) with ~31 tearing modulus at 300°C. The preliminary results indicate that the presence of high volume of δ-ferrite would noticeable impair fracture toughness although it may not influence hardness and tensile properties.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

Evaluating GHG Mitigation Potential from ESPC Projects [Slides]

This report explores the impact of implemented ESPC projects on the projected greenhouse gas (GHG) emissions reductions in the U.S. buildings sector, and the associated projected annual cost savings and marginal abatement costs. It is important to investigate the role that energy retrofits can play in achieving GHG emission reduction targets given the use of ESPC by public agencies to reduce emissions from energy use in addition to the historical use of ESPC to to achieve cost/energy savings and ancillary benefits (e.g., addressing deferred maintenance, aging infrastructure, etc.). The analysis draws from LBNL’s eProject Builder (ePB) database, which contains approximately 3,000 energy retrofit projects implemented by energy service companies (ESCOs), mostly energy savings performance contract (ESPC) projects. This is the first report to model GHG emission reductions from ongoing ESPC projects in the U.S public sector based on ePB project data. It is intended for policymakers, federal, state and local government officials and other potential ESPC customers, the ESCO industry, researchers, and other energy policy professionals.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2020

Thermal Model Heat Rate Predictions of the AGR-5/6/7 Experiment

Several fuel and material irradiation experiments have been planned for the U.S. Department of Energy Advanced Gas Reactor Fuel Development and Qualification Program, which supports the development and qualification of tristructural isotropic (TRISO) coated particle fuel for use in high-temperature gas-cooled reactors. The goals of these experiments are to provide irradiation performance data to support fuel process development, qualify fuel for normal operating conditions, support development of fuel performance models and codes, and provide irradiated fuel and materials for post-irradiation examination and safety testing. Originally planned and named as separate fuel experiments, but subsequently combined into a single test train. AGR-5/6/7 will test low-enriched uranium oxycarbide (UCO – a heterogeneous mixture of uranium oxide and uranium carbide) TRISO fuel. The AGR-5/6 portion of the experiment will provide data to support qualification of the selected reference fuel design, while the AGR-7 portion will serve as a margin test, irradiating the fuel beyond normal operating conditions. During irradiation, the temperature in each capsule is controlled by varying the helium / neon gas mixture flowing through the capsule until the desired thermocouple temperature is reached. Further adjustments can be made by changing the lobe power and the neutron filter. Three neutron filters are available to use as the experiment burns up the fissionable fuel. A thermal finite element model has been created for the five capsules comprising the AGR-5/6/7 experiment. Heat rates from a physics analysis are imported into the model along with fast neutron fluence. Graphite shrinkage due to the fast neutron fluence is incorporated into the model. Gas gaps change as a function of fast neutron fluence. Radiation heat transfer is a major contributor in this model. This is a large model with more than 1 million finite element brick elements. More than 150 different parts are modeled in the finite element model and communicate with each other from a heat transfer sense. More than 50 thermocouples are used in the experiment and are compared to actual measurements. The experiment is composed of five separate stainless steel capsules all welded together. This paper presents a method used to predict the gas mixture in the event that all of the thermocouples fail in a particular capsule. Curve fitting of heat rates from previous cycles and projecting them into the future is the basis of the method.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Key Nuclear Data Impacting Reactivity in Advanced Reactors

Advanced reactor concepts currently being developed throughout the industry are significantly different from light water reactor (LWR) designs with respect to geometry, materials, and operating conditions, and consequently, with respect to their reactor physics behavior. Given the limited operating experience with non-LWRs, the accurate simulation of reactor physics and the quantification of associated uncertainties are critical for ensuring that advanced reactor concepts operate within the appropriate safety margins. Nuclear data are a major source of input uncertainties in reactor physics analysis. As part of an ongoing project at Oak Ridge National Laboratory (ORNL), the effects of nuclear data uncertainties on key figures of merit associated with advanced reactor safety are being assessed for selected advanced reactor technologies. Key nuclear data relevant for reactor safety analysis for each selected advanced reactor technology were identified, and their impact on important key figures of merit was assessed. Available advanced reactor specifications were reviewed, results from studies performed at ORNL and other research institutions were consulted, and available evaluated nuclear data libraries were analyzed. This report summarizes the key nuclear data for nuclides in the fuel, as well as other significant data, including scattering and neutron capture in various materials for the moderator, coolant, and structure of the considered advanced reactors. For the considered advanced reactors that use low-enriched uranium (LEU) fuel, results from LWR studies provided insight into relevant nuclear data given the lack of available studies specifically addressing these new systems. The major nominal missing data that were identified consist of thermal scattering data and 135m Xe cross section data for molten salt reactor (MSR) analysis. The identified major gaps with respect to nuclear data uncertainties are missing uncertainties of thermal scattering data for high temperature gas-cooled reactors and moderated MSR systems, and incomplete uncertainties on angular distributions in particular for fast spectrum systems, such as sodiumcooled fast reactors, fast molten salt reactors, and heat pipe reactors. Furthermore, it was found that special attention should be paid to cross section and uncertainty differences between different evaluated nuclear data library releases, because significant differences in nuclear data that can lead to major differences in reactivity calculations were found, even for well-known nuclides.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2024

Transport from electron-scale turbulence in toroidal magnetic confinement devices

Plasma transport driven by turbulence ultimately determines the energy confinement performance of controlled fusion devices regardless of their confinement schemes and configurations. A large variety of plasma instabilities have been proposed for driving turbulence responsible for anomalous plasma transport beyond classical/neoclassical transport due to collisions. Although ion-scale turbulence usually dominates due to its large eddy size and saturation level, electron-scale turbulence has been recognized to be important in regions where ion-scale turbulence is suppressed (e.g., in internal transport barrier and in spherical tokamak H-mode plasmas) or is close to marginality. Electron-scale turbulence has been shown to nonlinearly interact with ion-scale turbulence, which modifies the dynamics of both and affects the resulting plasma transport, particularly when ion-scale instability is weakly driven. In this review paper, we focus on electron-scale turbulence that is believed to operate in magnetically confinement fusion devices and aim to provide a review of theoretical, numerical, and experimental developments in understanding electron-scale turbulence and its role in driving anomalous plasma turbulence. In particular, we focus on the electrostatic electron temperature gradient (ETG) mode which is the most widely recognized plasma instability underlying electron-scale turbulence observed in magnetically confined plasmas. Finally, we note that there are other less studied instabilities that might be responsible for observed electron-scale turbulence, most notably ubiquitous mode, and short-wavelength ion temperature gradient (SWITG) mode, which will be briefly touched on in this review.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

Correlating and Simulating Socio-Demographically Driven Residential End-Use Activity Schedules

Incorporating socio-demographic and behavioral considerations into decision-support tools is crucial for identifying gaps and addressing consumer needs to ensure reliable and affordable energy solutions. In energy simulation models, the correlation between socio-demographics and time-use behavior is not well-captured. Thus, we developed a large-scale simulation workflow to generate schedules for 10 residential activities across 24 population segments defined by age, income, and employment status. Using pre-pandemic 2015-2019 American Time Use Survey (ATUS) data, we used ANOVA to confirm the correlation between demographic factors and time use. We explored three k-modes clustering methods-backward, forward, and a new hybrid approach-to delineate the occupancy patterns based on demographics. Using the probability of cluster membership for each population segment and a time inhomogeneous Markov chain to generate activity transition probabilities for each cluster, we simulated 50,000 schedules per segment and validated them against the ATUS data. The hybrid method produced the most socio-demographically differentiated clusters while demonstrating comparable performance to other approaches, with an overall root mean square error of 0.12 for both weekday and weekend schedules. Thus, the hybrid method, where each cluster is dominated by certain demographic segments and occupancy patterns, offers more modeling versatility in terms of scenario analysis. The new workflow improves the socio demographic differentiation of energy consumption by considering differences in time use. This approach enables future research on demographically segmented time of use (TOU) energy consumption, including impacts of TOU utility bills and rate analysis, long-run marginal emissions, and energy retrofits.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2026

Self-driving thin film laboratory: autonomous epitaxial atomic-layer synthesis via real-time computer vision analysis of electron diffraction

Emerging materials science platforms with the ability to make autonomous decisions on the fly are fundamentally changing the outlook and protocols for materials optimization and discovery. Because AI-driven self-navigating schemes can effectively reduce the total number of iterations needed to arrive at the "answer" (i.e. the best stochiometric composition for a desired physical property, optimum materials processing parameters, etc.) by significant margins, they have the potential to revolutionize materials and chemical manufacturing processes at large in research laboratory settings as well as in industrial plants. Here, we demonstrate a successful implementation of real-time closed-loop autonomous navigation of a multi-dimensional materials synthesis parameter space for fabricating phase-pure epitaxial films of a metastable phase of a functional oxide in a combinatorial pulsed laser deposition chamber. Sequential epitaxial growth iterations in search of the optimized recipe to stabilize the desired crystal phase were performed using frame-by-frame quantitative computer vision analysis of reflection high-energy electron diffraction (RHEED) images of the unit-cell level film being deposited. The autonomous scheme regularly resulted in > 30-fold reduction in the number of required experiments compared to a comprehensive mapping of the parameter space. The real-time workflow developed here can be readily extended to a variety of thin film synthesis platforms opening the door for self-driving atomic-level materials design as well as autonomous optimization of semiconductor manufacturing.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Artificial intelligence-empowered cellular morphometric risk score improves prognostic stratification of cutaneous squamous cell carcinoma

Abstract Background Risk stratification of cutaneous squamous cell carcinoma (cSCC) is essential for managing patients. Objectives To determine if artificial intelligence and machine learning might help to stratify patients with cSCC by risk using more than solely clinical and histopathological factors. Methods We retrieved a retrospective cohort of 104 patients whose cSCCs had been excised with clear margins. Clinical and histopathological risk factors were evaluated. Haematoxylin and eosin-stained slides were scanned and analysed by an algorithm based on the stacked predictive sparse decomposition technique. Cellular morphometric biomarkers (CMBs) were identified via machine learning and used to derive a cellular morphometric risk score (CMRS) that classified cSCCs into clusters of differential prognoses. Concordance analysis, sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV) and accuracy were calculated and compared with results obtained with the Brigham and Women’s Hospital (BWH) staging system. The performance of the combination of the BWH staging system and the CMBs was also analysed. Results There were no differences among the CMRS groups in terms of clinical and histopathological risk factors and T-stage assignment, but there were significant differences in prognosis. Combining the CMRS with BWH staging systems increased distinctiveness and improved prognostic performance. C-indices were 0.91 local recurrence and 0.91 for nodal metastasis when combining the two approaches. The NPV was 94.41% and 96.00%, the PPV was 36.36% and 41.67%, and accuracy reached 86.75% and 89.16%, respectively, with the combined approach. Conclusions CMRS is helpful for cSCC risk stratification beyond classic clinical and histopathological risk features. Combining the information from the CMRS and the BWH staging system offers outstanding prognostic performance for patients with high-risk cSCC.

Pérez-Baena, Manuel J.↗
DOE OSTI2022

Bridging Equipment Reliability Data and Robust Decisions in a Plant Operation Context

In order to reduce operation and maintenance (O&M) costs, nuclear power plants (NPPs) are moving from corrective and periodic maintenance to predictive maintenance strategies. Such transition requires changes on the data that needs to be retrieved and on the type of decision processes to be employed. Advanced monitoring and data analysis technologies are essential to support predictive strategies. They can in fact provide precise information about health of a component, track its degradation trends, and provide information of its expected failure time. With such information, maintenance operations for a component can be performed right before its expected failure time. This dynamic context of O&M operations requires new methods to analyze data, propagate component health information from the component to the system level, and optimize plant resources. In this respect, the risk informed asset management (RIAM) project has been tasked to develop and test this new class of methods into a risk analytics toolset. This toolset consists of data analytics tools coupled with reliability methods designed to manage plant assets and performances in a predictive maintenance context. This report shows the latest improvements on such development and the initial testing of our methods on the three main research areas that the RIAM project is focusing on. These areas are the following: equipment reliability data analytics, system reliability modeling, and plant resources optimization methods. We show how the methods developed in these areas can support predictive maintenance strategies by: 1) analyzing equipment reliability data (either in numeric and textual form), 2) assessing component and system health through an innovative margin-based reliability approach, and 3) identifying the most critical components and set optimal maintenance schedule based on plant economic and operational constraints.

97 MATHEMATICS AND COMPUTING↗