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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 793 records · Page 44
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

In Situ High-Pressure Synthesis of New Outstanding Light-Element Materials under Industrial P-T Range

High-pressure synthesis (which refers to pressure synthesis in the range of 1 to several GPa) adds a promising additional dimension for exploration of compounds that are inaccessible to traditional chemical methods and can lead to new industrially outstanding materials. It is nowadays a vast exciting field of industrial and academic research opening up new frontiers. In this context, an emerging and important methodology for the rapid exploration of composition-pressure-temperature-time space is the in situ method by synchrotron X-ray diffraction. This review introduces the latest advances of high-pressure devices that are adapted to X-ray diffraction in synchrotrons. It focuses particularly on the “large volume” presses (able to compress the volume above several mm3 to pressure higher than several GPa) designed for in situ exploration and that are suitable for discovering and scaling the stable or metastable compounds under “traditional” industrial pressure range (3–8 GPa). We illustrated the power of such methodology by (i) two classical examples of “reference” superhard high-pressure materials, diamond and cubic boron nitride c-BN; and (ii) recent successful in situ high-pressure syntheses of light-element compounds that allowed expanding the domain of possible application high-pressure materials toward solar optoelectronic and infra-red photonics. Finally, in the last section, we summarize some perspectives regarding the current challenges and future directions in which the field of in situ high-pressure synthesis in industrial pressure scale may have great breakthroughs in the next years.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Coherent Acoustic Interferometry during the Photodriven Oxygen Evolution Reaction Associates Strain Fields with the Reactive Oxygen Intermediate (Ti–OH*)

The oxygen evolution reaction (OER) from water requires the formation of metastable, reactive oxygen intermediates to enable oxygen–oxygen bond formation. Conversely, such reactive intermediates could also structurally modify the catalyst. Here, a descriptor for the overall catalytic activity, the first electron and proton transfer OER intermediate from water, (M–OH*), has been associated with significant distortions of the metal–oxygen bonds upon charge-trapping. Time-resolved spectroscopy of in situ, photodriven OER on transition metal oxide surfaces has characterized M–OH* for the charge trapping and the symmetry of the lattice distortions by optical and vibrational transitions, respectively, but had yet to detect an interfacial strain field arising from a surface coverage M–OH*. Here, we utilize picosecond, coherent acoustic interferometry to detect the uniaxial strain normal to the SrTiO 3 /aqueous interface directly caused by Ti–OH*. The spectral analysis applies a fairly general methodology for detecting a combination of the spatial extent, magnitude, and generation time of the interfacial strain through the coherent oscillations’ phase. For lightly n-doped SrTiO 3 , we identify the strain generation time (1.31 ps), which occurs simultaneously with Ti–OH* formation, and a tensile strain of 0.06% (upper limit 0.6%). In addition to fully characterizing this intermediate across visible, mid-infrared, and now GHz-THz probes on SrTiO 3 , we show that strain fields occur with the creation of some M–OH*, which modifies design strategies for tuning catalytic activity and provides insight into photo-induced degradation so prevalent for OER. To that end, the work put forth here provides a unique methodology to characterize intermediate-induced interfacial strain across OER catalysts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Designing Monte Carlo Simulation and an Optimal Machine Learning to Optimize and Model Space Missions

This paper investigates applying artificial intelligence (AI) algorithms to attitude control system of satellites to optimally tune the controller using high performance computing. This methodology is applied to the Virtual Telescope for X-ray Observation mission, which is a precise formation of two separate spacecraft observing multiple objects in the space in the X-ray domain. The mission is divided into phases based on the instrumentation and the mission goal. To reach an stable precise formation robust to stochastic slew and slew rate (i.e., Euler angles and angular velocities) in a minimal constrained time T , consumed energy of the attitude control system, denoted as E, and root-mean-square state error of attitude control system, denoted as e, are minimized. Monte-Carlo simulation is used for the sensitivity analysis of optimization and designing a controller. Deep neural networks (DNN), Gaussian processes (GP), and support vector regression (SVR) learn this optimization as a surrogate model, while their hyperparameters are optimized in a novel approach. THETA supercomputer at Argonne Leadership Computing Facility (ALCF) is used for optimizing the hyperparameters of DNN. The surrogate model meets the requirements of the mission, and it shows a better performance over the optimization and Monte-Carlo. The optimal DNN can satisfy the mission requirements e and T while reducing E for 90% compared to the other given methods.

42 ENGINEERING↗
DOE OSTI2025

Building Performance Standards and Energy Code Alignment - Technical Brief

Building energy codes focus on building design, construction and renovation and have significantly increased building efficiency since the first national energy code was published in 1975. Most jurisdictions have energy codes based on ANSI/ASHRAE/IES Standard 90.1 (hereto referred to as Standard 90.1) and the International Energy Conservation Code (IECC). Compliance options available in these model energy codes include a prescriptive path, whole building performance paths – including IECC Total Building Performance (TBP), Standard 90.1 Energy Cost Budget (ECB) method and Performance Rating Method (PRM) – and system performance paths for envelope and heating, ventilation, and air-conditioning systems. Building performance standard (BPS) policies are an emerging policy tool used by jurisdictions to reduce the operational energy use or greenhouse gas (GHG) emissions of the existing commercial building stock. BPS policies vary widely between jurisdictions and are tailored to each location’s climate and energy goals. Intuitively, projects that met a recent edition of the energy code should comply with the BPS targets. However, some new buildings may struggle with meeting the BPS for the following reasons: 1. Energy codes focus on the design of the building and its projected ability to perform efficiently, while BPS compliance is dependent on the actual ongoing performance of the building, considering variables like occupancy, operation, and maintenance. 2. There are significant differences in the methodologies used to determine BPS compliance versus code compliance, including how each handles compliance metrics, handling of building amenities, and renewable energy generation. 3. The prescriptive compliance path in the energy code is based on performance of individual building components, as opposed to the performance compliance path which accounts for holistic building design strategies and interdependent building systems. This can result in a significant variability in post-occupancy performance for buildings built using the prescriptive path. Designs on the lower end of the permitted efficiency range may struggle with meeting the BPS.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Strangely attractive: Collaboration and feedback in the field of molecular magnetism

The fluid synergy between experimentalists and theoreticians has, for decades, led to a deeper understanding of the processes that govern single-molecule magnets. This approach has allowed for the establishment of proven design criteria for the control of magnetic properties through molecular architecture and the development of new magnetic measurement techniques and innovative computational methodologies. Here, we give an account of the experimental and theoretical joint endeavor carried out as part of the synthesis group led by David Mills and the computational/theoretical team led by Nicholas Chilton, together with colleagues in synthetic f-element chemistry and magnetism at the University of Manchester. In addition, we provide a personal perspective on collaborative work in molecular magnetism and how such collaborations are essential for advancing the field further.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Hybrid power plants: An effective way of decreasing loss-of-load expectation

Diversifying variable renewable resources by combining wind, solar photovoltaic, and battery assets in a hybrid power plant can increase renewable energy usage efficiency and improve system flexibility, particularly in distributed energy systems. However, the resilience impact of these systems, particularly outage mitigation, can be difficult to quantify due to uncertainty in resource, energy demand, and outage occurrence. Here, this study outlines a framework to quantify the incremental benefit of hybrid power plant assets for reducing loss-of-load expectation during random outage events. Hybrid power plant performance during outages (considering varying duration and severity) is simulated using a Monte Carlo methodology to reflect uncertainty associated with renewable resource, load demand, and outage timing. Results demonstrate the additional incremental value from increasingly hybrid designs, in which relative capacities of wind, solar photovoltaic, and storage assets contribute to lower loss-of-load expectation than the constituent technologies would alone. The value of added wind or solar capacity increases as the plant composition approaches an equal split. The value of added battery capacity depends on the outage duration and severity, but the first 50 MWh of added storage capacity is the most valuable for reducing the loss-of-load expectation for all plant designs.

14 SOLAR ENERGY↗
DOE OSTI2021

Damage detection through Förster Resonance Energy Transfer in mechanoresponsive polymer nanocomposites

Polymer nanocomposites offer design solutions to control and tune optical, conductive, topological, and thermomechanical properties of advanced and multifunctional materials. Because of their ubiquitous nature, methodologies to diagnose failure or structural changes in the nanocomposites are of significant interest. Herein, we report a nanocomposite system loaded with quantum dots and coumarin-modified carbon nanotubes that transduce mechanical force into fluorescence at a strain, for the first time, as low as 7.5%. Our comprehensive studies detail the optical, morphological, and thermomechanical properties of these nanocomposites to establish the fundamental reason behind the activation of fluorescence. Here our results indicate that bare carbon nanotubes can irreversibly quench the fluorescence from quantum dots and that the coumarin-modified carbon nanotubes mitigate the quenching through Förster Resonance Energy Transfer. Next, the application of force to the sample changes the quantum dot-carbon nanotube spacing as well as the carbon nanotube morphology to activate fluorescence in the nanocomposite. Overall, this force activation of fluorescence can serve as a general strategy for the development of a new class of mechano-responsive nanocomposites that impart polymeric materials with desirable functionalities including damage sensing and mechanical strength.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Free electron lasers driven by plasma accelerators: status and near-term prospects

Owing to their ultra-high accelerating gradients, combined with injection inside micrometer-scale accelerating wakefield buckets, plasma-based accelerators hold great potential to drive a new generation of free-electron lasers (FELs). Indeed, the first demonstration of plasma-driven FEL gain was reported recently, representing a major milestone for the field. Several groups around the world are pursuing these novel light sources, with methodology varying in the use of wakefield driver (laser-driven or beam-driven), plasma structure, phase-space manipulation, beamline design, and undulator technology, among others. This paper presents our best attempt to provide a comprehensive overview of the global community efforts towards plasma-based FEL research and development.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

QUBIC II: Spectral polarimetry with bolometric interferometry

Bolometric interferometry is a novel technique that has the ability to perform spectral imaging. A bolometric interferometer observes the sky in a wide frequency band and can reconstruct sky maps in several sub-bands within the physical band in post-processing of the data. This provides a powerful spectral method to discriminate between the cosmic microwave background (CMB) and astrophysical foregrounds. In this paper, the methodology is illustrated with examples based on the Q & U Bolometric Interferometer for Cosmology (QUBIC) which is a ground-based instrument designed to measure the B-mode polarization of the sky at millimeter wavelengths. We consider the specific cases of point source reconstruction and Galactic dust mapping and we characterize the point spread function as a function of frequency. We study the noise properties of spectral imaging, especially the correlations between sub-bands, using end-to-end simulations together with a fast noise simulator. Finally, we conclude showing that spectral imaging performance are nearly optimal up to five sub-bands in the case of QUBIC.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

A Cast of Thousands: How the IDEAS Productivity Project Has Advanced Software Productivity and Sustainability

Computational and data-enabled science and engineering are revolutionizing advances throughout science and society, at all scales of computing. For example, teams in the U.S. Department of Energy’s Exascale Computing Project have been tackling new frontiers in modeling, simulation, and analysis by exploiting unprecedented exascale computing capabilities—building an advanced software ecosystem that supports next-generation applications and addresses disruptive changes in computer architectures. However, concerns are growing about the productivity of the developers of scientific software. Members of the Interoperable Design of Extreme-scale Application Software project serve as catalysts to address these challenges through fostering software communities, incubating and curating methodologies and resources, and disseminating knowledge to advance developer productivity and software sustainability. This article discusses how these synergistic activities are advancing scientific discovery—mitigating technical risks by building a firmer foundation for reproducible, sustainable science at all scales of computing, from laptops to clusters to exascale and beyond.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Revealing conductivity of p-type delta layer systems for novel computing applications

This project uses a quantum simulation technique to reveal the true conducting properties of novel atomic precision advanced manufacturing materials. With Moore's law approaching the limit of scaling for the CMOS technology, it is crucial to provide the best computing power and resources to National Security missions. Atomic precision advanced manufacturing-based computing systems can become the key to the design, use, and security of modern weapon systems, critical infrastructure, and communications. We will utilize the state-of-the-art computational methodology to create a predictive simulator for p-type atomic precision advanced manufacturing systems, which may also find applications in counterfeit detection and anti-tamper.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Comparison Between Pin-by-Pin Subchannel and System Level Thermal Hydraulic Results for High Burnup Loss-of-Coolant Applications

This milestone report summarizes recent work to investigate higher fidelity modeling and simulation practices for large-break loss-of-coolant accident (LBLOCA) analysis in high-burnup pressurized water reactor (PWR) cores. Because of current industry interest in extending fuel cycle lengths ranging from 18 to 24-months, the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program has been investigating the susceptibility of high-burnup core designs to fuel fragmentation, release, and dispersal (FFRD) during accident conditions such as LBLOCA. This work has prioritized developing and demonstrating a methodology for calculating core-wide susceptibility to FFRD and addressing uncertainties identified in the analysis and the US Nuclear Regulatory Commission (NRC) Research Information Letter on FFRD. Part of this investigation seeks to quantify differences between system-level thermal hydraulic behavior and higher fidelity subchannel modeling methods to identify potential safety concerns or opportunities to minimize FFRD susceptibility. To this end, the NEAMS subchannel code, CTF, is being used, along with the NRC system analysis code TRACE, for analysis of LBLOCA in a core containing high-burnup fuel. This project includes two thrusts: (1) improving on the existing TRACE model for a 4-loop PWR for LBLOCA so that the model is higher fidelity and consistent with current USNRC best practices, and (2) using CTF to perform pin-resolved modeling of the core region of the reflood phase of a LBLOCA in a high-burnup PWR.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Multi-Fidelity Scheme for Accelerating 4D Finite Element Analysis for Mircoreactors

Next-generation microreactors are currently being designed to be operated terrestrial and extraterrestrial for remote surface power production. These systems will provide an alternative source of carbon-free energy that is versatile and can be utilized for various applications. These applications of microreactors have prompted the usage of high-fidelity unstructured finite element (FE) based approaches to provide time-dependent solutions for multiple physics fields. Computing these high-fidelity (4-D) solutions for multiple design iterations, physics fields, and transient events requires an immense computational cost. These high-fidelity solutions are computational expensive and the cost can be reduced through the implementation of less accurate low-fidelity solutions. Unlike the current fleet of commercial nuclear reactors, these next-gen systems present challenges due to the material and physical limitations required. Due to these constraints, the brute force technique of parameterizing important system characteristics determines whether a design meets the project objective. A system such as a nuclear reactor could have thousands of design parameters that affect system performance. In order to analyze the entire parameter space of such a complex system would require millions of CPU hours and countless design iterations. This costly approach is not practical due to regulatory and budget limitations. In this proposal, an approach that utilizes hybrid high-fidelity and low-fidelity FE models to reduce the computational cost of evaluating these applications in 4-D will be presented. The accuracy of the high-fidelity model and the computational efficiency of the low-fidelity model are taken advantage of to produce a solution that closely resembles the full order high-fidelity solution. By utilizing an unconverged coarse FE mesh, operation limits such as temperature, structural loading, etc., can be evaluated in an accelerated fashion and then can be spatially interpolated onto a finer mesh. The resulting error arising from the coarse mesh can be mitigated with a discrepancy function that actively quantifies and corrects the error in the coarse solution. This discrepancy function can be periodically updated with high-fidelity calculations across the temporal domain thus requiring less iterations on the fine mesh. As a result, the computational cost can be reduced for the evaluation and design iteration of microreactors. The proposal for this research contains three sections: Section 2 provides a literature review, Section 3 outlines the methodology for the proposed multi-fidelity scheme, and Section 4 displays preliminary results of the proposed research.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

MultiPEM Toolbox: User Manual [Rev. 2]

This document explains use of the Multi-Phenomenology Explosion Monitoring (Multi PEM) Toolbox, a collection of R scripts for estimating the unknown device parameters of a new event with uncertainty quantification. The methodology and application used for illustration in this user manual are fully documented in a Los Alamos National Laboratory technical report hereafter designated “WPA” for reference. Additional details on the application are found in a recent journal article. Two assessment types are available: rapid and complete. Rapid assessments are conducted in two stages, as described in Section 2. In the first stage, calibration data are used to estimate forward and error model parameters (WPA, §5.1) and (if relevant) errors-in-variables yield values for calibration sources (WPA, §3, Equation (3)). In the second stage, new event data are used to estimate the unknown new event device parameters (WPA, §5.2) with uncertainty quantification. Two options for treating the inferred first stage parameters in second stage Bayesian analysis are available: fixing them at their maximum likelihood estimate (default), or multiple imputation. Multiple imputation involves utilizing several posterior samples (imputations) of the first stage parameters as fixed values in the second stage posterior sampling of the new event device parameters. Second stage sampling is conducted across imputations in parallel to improve computational efficiency. This method produces improved uncertainty quantification of the new event device parameters compared with the default treatment of the first stage parameters, at the expense of additional computation. Complete assessments are conducted in a single stage, as described in Section 3. Calibration and (if relevant) new event data are used simultaneously to estimate all forward model, error model, and (if relevant) new event device parameters with uncertainty quantification on the latter. As the name suggests, rapid assessments generally run substantially faster than complete assessments (even with multiple imputation), because the results of first stage analysis can be stored and incorporated into estimating a relatively low-dimensional space of new event device parameters whenever relevant new event data becomes available. On the other hand, complete assessments must be run on the full set of model and device parameters with calibration and new event data every time the latter becomes available.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Solenoidal Fields from Permanent Magnets for a Polarized Electron Preinjector

This technical note describes the design of a compact focusing solenoid constructed from permanent bar magnets, intended for the low-energy section of a spin-polarized electron injector. Typically, quadrupole triplets provide appropriate focusing for the low-energy spin rotator section; however, their large footprint precludes the insertion of sufficient beam diagnostics. The primary motivation of this study is to provide beam focusing while preserving the vertical spin orientation of the electron beam. We propose a solenoidal field composed of multiple permanent magnets arranged to naturally yield a zero longitudinal magnetic field integral ($\int B_zdz = 0$). This design serves as a compact, passive, and non-coupling alternative to traditional quadrupole triplets. We present the magnet arrangement, field calculation methodology, spin tracking simulations using space charge codes, and calculations demonstrating that the required field strength is achievable.

43 PARTICLE ACCELERATORS↗
DOE OSTI2026

Automated and Accelerated Continuum Model Development for Electrochemical Systems (Abbreviated Report)

Despite the availability of computational resources and advancements in numerical computing capabilities, the multiscale models core to understanding, predicting the behaviors of, and designing energy and environmental systems involving porous media are still 1.) developed through by-hand derivations and 2.) limited by many methodological assumptions employed during model derivation. As a result, the advancement of effective media models for engineering DOE mission-critical systems (e.g., batteries, flow batteries, electrolyzers, geothermal systems, subsurface chemical storage systems, etc.) is slow (i.e., it takes years for models to traverse from stages of “development” to “practical utilization”), hindering our ability to effectively optimize such systems and stay at the cutting-edge of the energy frontier. In this work, we aimed to address these limitations by 1.) automating and accelerating multiscale model derivation via symbolic computing and 2.) develop a novel multiscale modeling methodology for flow and transport through porous media that avoids the typical assumptions hindering previous models. As a result of our efforts, we 1.) developed a hybrid symbolic-numeric code called Fouriera for fully-automating the implementation of multiphysical and phase-field models via the Fourier spectral method for materials science research, and 2.) advanced a multiscale modeling methodology called The Method of Finite Averages that rigorously predicts the behaviors of flow and transport through heterogeneous porous media under the influence of non-local effects and strong advection. Ultimately, these deliverables provide strong foundations from which further efforts can advance multiscale modeling tools and capabilities that do not intrinsically rely on 1.) the speed and mathematical capabilities of humans, nor 2.) the methodological assumptions limiting current models.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Microbe to Microbiome: A Paradigm Shift in the Application of Microorganisms for Sustainable Agriculture

Light, water and healthy soil are three essential natural resources required for agricultural productivity. Industrialization of agriculture has resulted in intensification of cropping practices using enormous amounts of chemical pesticides and fertilizers that damage these natural resources. Therefore, there is a need to embrace agriculture practices that do not depend on greater use of fertilizers and water to meet the growing demand of global food requirements. Plants and soil harbor millions of microorganisms, which collectively form a microbial community known as the microbiome. An effective microbiome can offer benefits to its host, including plant growth promotion, nutrient use efficiency, and control of pests and phytopathogens. Therefore, there is an immediate need to bring functional potential of plant-associated microbiome and its innovation into crop production. In addition to that, new scientific methodologies that can track the nutrient flux through the plant, its resident microbiome and surrounding soil, will offer new opportunities for the design of more efficient microbial consortia design. It is now increasingly acknowledged that the diversity of a microbial inoculum is as important as its plant growth promoting ability. Not surprisingly, outcomes from such plant and soil microbiome studies have resulted in a paradigm shift away from single, specific soil microbes to a more holistic microbiome approach for enhancing crop productivity and the restoration of soil health. Herein, we have reviewed this paradigm shift and discussed various aspects of benign microbiome-based approaches for sustainable agriculture.

59 BASIC BIOLOGICAL SCIENCES↗
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↗