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At least 541 records · Page 30

An Integrated Risk Assessment Process of Safety-Related Digital I&C Systems in Nuclear Power Plants

Upgrading the existing analog instrumentation and control (I&C) systems to state-of-the-art digital I&C (DI&C) systems will greatly benefit existing light water reactors. However, the issue of software common cause failure (CCF) remains an obstacle in terms of qualification for digital technologies. Existing analyses of CCFs in I&C systems mainly focus on hardware failures. With the application and upgrading of new DI&C systems, design flaws could cause software CCFs to become a potential threat to plant safety, considering that most redundancy designs use similar digital platforms or software in their operating and application systems. With complex multilayer redundancy designs to meet the single failure criterion, these I&C safety systems are of particular concern in U.S. Nuclear Regulatory Commission licensing procedures. In Fiscal Year 2019, the Risk-Informed Systems Analysis (RISA) Pathway of the U.S. Department of Energy’s Light Water Reactor Sustainability Program initiated a project to develop a risk assessment strategy for delivering a strong technical basis to support effective, licensable, and secure DI&C technologies for digital upgrades and designs. An integrated risk assessment for the DI&C process was proposed for this strategy to identify potential key digital-induced failures, implement reliability analyses of related digital safety I&C systems, and evaluate the unanalyzed sequences introduced by these failures (particularly software CCFs) at the plant level. Here this paper summarizes these RISA efforts in the risk analysis of safety-related DI&C systems at Idaho National Laboratory.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Design of Timer Circuit for Dynamic Data System

The Branch That I work in is in the Aero Electronic Test Branch, which is part of the Research and Testing Division. The Aero Electronic Test Branch deals with electronic control and instrumentation systems. This branch supports the research and test study of wind tunnels such as the l0x10,9x15, and 8x6. Wind tunnels are used in research to test certain parts of a jet, plane, shuttle or any other flying object in certain test conditions. My assignment is to design a programmable trigger circuit on a 19 standard rack mount that will allow the circuit to latch and hold for a predefined amount of time entered by the user when receiving a signal. It should then re-arm itself within 0.25 seconds after the time is finished. The time should be able to be seen on a display showing the time entered. The time range has to be from 0-600 seconds in 0.01 second increments (600.00). From the information given, counters will be needed to design and build this circuit. A counter, in it s simplest form, is a group of flip flops that can temporarily store bits of information put into the circuit. They can be constructed in many different ways, such as in 4 flip flops (4-bit counter) or 8 flip flops and even higher. Counters are usually cascaded with other counters to reach higher bits, such as 16 or 24 bit counters. The application in which I will use the counters will be to count down from any programmable number that I input either by a keyboard or a thumbwheel. Also, I will use counters that will be used specifically as a frequency divider to divide the pulses that enter the circuit through an input signal from a crystal clock. The pulses will need to be divided so that it will function as a 100Hz clock putting out 100 pulses per second. A switch will be used to load my inputs in and more than likely a button also so that I can stop and hold the count at any point of time. I will use 5 BCD up/down programmable counters, and a certain amount (depending on what kind of "divide by N" counter I use) of frequency dividing counters for the assignment. After the design is carefully made, a task order will be written and then given to the manufacturer to create a rack mount circuit board that will match my specifications given. The applications in which this design will be used for is in the use of the six-component balance signal conditioner for measurement and electronic system control. It can be used as a timer system for the balance signal conditioner in which it does numerous tests for the Wind tunnel research, in which a preset time can be set for how long it performs its tests. Specifically, my design should be applied to the balance signal conditioner used for the 8x6 wind tunnel research. Hopefully this design should aid in more efficient research for the 8x6 wind tunnel.

Young, Nathaniel, III↗

Investigation of the Use of Dynamic Probabilistic Risk Assessment Methodologies for Identifying Digital I&C System Common Cause Failures

Digital Instrumentation and Control (I&C) systems have a key role in nuclear power plants in the upgrade of aging analog systems. Digital systems improve plant safety and reliability through features such as increased hardware reliability and stability and improved failure detection capability. There is no consensus on which of the current probabilistic risk assessment methods are most suitable for use in the reliability analysis of digital I&C systems. While the traditional event-tree/fault-tree (ET/FT) approach is still used for their reliability modeling, there are concerns regarding this approach in properly accounting for dynamic interactions among system components since potentially significant dependencies among failure events may not be identified and/or their likelihood may not be properly quantified. Dynamic methodologies are expected to provide a much more accurate representation of probabilistic evolution of the I&C systems in time due to their capability to more properly account for complex interactions than the static approach. The applicability of dynamic PRA methodologies for digital I&C system is investigated using the criteria presented in the NUREG/CR-6901, and the comparisons made in NUREG/CR-6901 are updated in light of the latest studies. The Dynamic Event Tree (DET) approach has been identified as one of the top dynamic methods when evaluated against the requirements for the reliability modeling of digital I&C systems. The DET method is a strong candidate for integration into existing PRA studies, as it bears many similarities to the traditional ET approach. In this study, the DET approach has been applied to the Plant Protection System of the APR1400 design, and the results are compared to results from its available traditional ET/FT analysis. Possible approaches to evaluate and quantify the effects of common cause failures on system safety using dynamic methods are also examined.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Application of Orthogonal Defect Classification for Software Reliability Analysis

The modernization of existing and new nuclear power plants with digital instrumentation and control systems (DI&C) is a recent and highly trending topic. However, there lacks strong consensus on best-estimate reliability methodologies by both the United States (U.S.) Nuclear Regulatory Commission (NRC) and the industry. This has resulted in hesitation for further modernization projects until a more unified methodology is realized. In this work, we develop an approach called Orthogonal-defect Classification for Assessing Software Reliability (ORCAS) to quantify probabilities of various software failure modes in a DI&C system. The method utilizes accepted industry methodologies for software quality assurance that are also verified by experimental or mathematical formulations. In essence, the approach combines a semantic failure classification model with a reliability growth model to predict (and quantify) the potential failure modes of a DI&C software system. The semantic classification model is used to address the question: How do latent defects in software contribute to different software failure root causes? The use of reliability growth models is then used to address the question: Given the connection between latent defects and software failure root causes, how can we quantify the reliability of the software? A case study was conducted on a representative I&C platform (ChibiOS) running a smart sensor acquisition software developed by Virginia Commonwealth University (VCU). The testing and evidence collection guidance in ORCAS was applied, and defects were uncovered in the software. Qualitative evidence, such as condition coverage, was used to gauge the completeness and trustworthiness of the assessment while quantitative evidence was used to determine the software failure probabilities. The reliability of the software was then estimated and compared to existing operational data of the sensor device. It is demonstrated that by using ORCAS, a semantic reasoning framework can be developed to justify software reliability (or unreliability) while still leveraging the strength of the existing methods.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Application of Orthogonal Defect Classification for Software Reliability Analysis

The modernization of existing and new nuclear power plants with digital instrumentation and control systems (DI&C) is a recent and highly trending topic. However, there lacks strong consensus on best-estimate reliability methodologies by both the United States (U.S.) Nuclear Regulatory Commission (NRC) and the industry. This has resulted in hesitation for further modernization projects until a more unified methodology is realized. In this work, we develop an approach called Orthogonal-defect Classification for Assessing Software Reliability (ORCAS) to quantify probabilities of various software failure modes in a DI&C system. The method utilizes accepted industry methodologies for software quality assurance that are also verified by experimental or mathematical formulations. In essence, the approach combines a semantic failure classification model with a reliability growth model to predict (and quantify) the potential failure modes of a DI&C software system. The semantic classification model is used to address the question: How do latent defects in software contribute to different software failure root causes? The use of reliability growth models is then used to address the question: Given the connection between latent defects and software failure root causes, how can we quantify the reliability of the software? A case study was conducted on a representative I&C platform (ChibiOS) running a smart sensor acquisition software developed by Virginia Commonwealth University (VCU). The testing and evidence collection guidance in ORCAS was applied, and defects were uncovered in the software. Qualitative evidence, such as condition coverage, was used to gauge the completeness and trustworthiness of the assessment while quantitative evidence was used to determine the software failure probabilities. The reliability of the software was then estimated and compared to existing operational data of the sensor device. It is demonstrated that by using ORCAS, a semantic reasoning framework can be developed to justify if the software is reliable (or unreliable) while still leveraging the strength of the existing methods.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Contamination control program results from three years of ground operations on the Extreme Ultraviolet Explorer instruments

A stringent contamination-control plan has been developed for the optical components of the Extreme Ultraviolet Explorer instruments, whose performance in the 80-900 A wavelength range is highly sensitive to particulate and molecular contamination. The contamination-control program has been implemented over the last three years during assembly, test and calibration phases of the instrument. These phases have now been completed and the optics cavities of the instruments have been sealed until deployment in space. Various approaches are discussed which have been used during ground operations to meet optics' contamination goals within the project schedule and budget. The measured optical properties of EUV witness mirrors are also presented which remained with the flight mirrors during ground operations. These were used to track optical degradation due to contamination from the cleanroom and high-vacuum test-chamber environments.

Ray, David C.↗

Sulfur Solutions: Advancing High Voltage and High Energy Lithium Batteries with Organosulfur Electrolytes

Achieving energy densities exceeding 350 Wh kg -1 while operating at elevated voltages (>4.5 V vs Li/Li + ) is attainable through judicious selection of electrochemical pairs at the cathode and anode. However, current state-of-the-art electrolytes exhibit limited stability when exposed to systems operating at or above 4.3 V. This limitation contributes to the degradation of electrode materials and raises critical safety concerns, impeding the commercialization of such systems. Consequently, there has been a notable surge in research efforts aimed at developing innovative electrolyte compositions capable of supporting high-voltage lithium-ion batteries (LIBs). A substantial portion of this research has focused on the family of organosulfur molecules, which possess high oxidative stability. Organosulfur salts also facilitate the formation of dense, ionically conductive solid electrolyte interfaces (SEI) and demonstrate excellent solubility. This article provides a comprehensive overview of the field of organosulfur electrolyte components for their applications in energy storage, encompassing solvents, alternative conducting salts, and additives. It emphasizes the idea that the deliberate design of electrolyte compositions is instrumental in controlling electrode passivation, with organosulfur-based structures historically proving advantageous in every aspect of the electrolyte. Crucially, it should be noted that many of these components are commercially available, holding significant implications for industrial applications.

25 ENERGY STORAGE↗

Cyber Risk Considerations for Nuclear Digital I&C Systems

Many engineers and scientists researching modeling and analysis methods for nuclear energy advancement are focused on proof-of-concept and early-stage development for new reactor designs. Since instrumentation and control (I&C) systems are traditionally developed later in the systems engineering lifecycle, researchers may be unfamiliar with modern digital technology used in these I&C systems. It is even more likely that they are unfamiliar with the cyber risks associated with them. This paper provides a brief overview of nuclear digital I&C systems before examining the importance of cyber risk management at nuclear reactors and the benefits of including Cyber-Informed Engineering throughout the systems engineering lifecycle. The primary goal is for engineers and scientists to develop a mindset that incorporates cybersecurity as another discipline alongside safety when designing and developing new technologies, regardless of technology readiness level.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Characterization of a selective, zero power sensor for distributed sensing of hydrogen in energy applications

The use of hydrogen as a clean and renewable energy source is increasing rapidly for both vehicle and stationary applications. There are safety concerns for the locations in which hydrogen is made, used, and transported (i.e., pipelines and tanker trucks). Sensors are needed to comply with safety regulations and to enable a smooth and safe rollout of hydrogen as an alternative energy. However, hydrogen sensors do not yet exist that have the combined features of small size and low power for easy deployment coupled with high-volume manufacturability and low cost. This is necessary to accommodate the emerging fixed and mobile markets while retaining critical metrological metrics, including measurement range, detection limits, selectivity, fast response, stability, and long lifetime. An amperometric gas sensor for hydrogen (AGS) has been developed using an innovative manufacturing method. The sensor was designed using scalable fabrication strategies based on “Printed Electronics” (PE) methodology which are compatible with large-scale production. Prototype sensors were batch fabricated with multiple individual elements on a substrate compatible in size with a standard 8-inch wafer to enable high-volume, low-cost manufacturing, thereby leveraging PE and semiconductor fabrication infrastructure. This novel AGS was instrumented with control circuitry and evaluated for hydrogen detection in the range of 0–5000 ppmv H2 in air. Specific performance evaluations included assessment of the sensor measurement range, repeatability, and selectivity.

08 HYDROGEN↗

Survey of Cyber Risk Analysis Techniques for Use in the Nuclear Industry

Using traditional probabilistic risk analysis methods for severe accident safety risk management on non-digital systems, structures, and components at nuclear power plants is well-established. In contrast, cyber risk analysis of digital assets is still an immature field with unproven techniques due, in part, to the continuously changing threat environment and the challenge of digital assets failing in unexpected ways. As the nuclear fleet continues to adopt digital instrumentation and control systems, it is increasingly important to have effective and efficient cyber risk analysis techniques to support risk management decisions, such as risk elimination by system redesign or risk mitigation by implementation of prioritized security controls. To understand the state of the art in cyber risk analysis for future research, we surveyed 36 publications across ten application domains. We describe our survey methodology and rate each technique based upon scope, adoptability, and repeatability. In this work, we examine the unique constraints of the nuclear industry and outline the strengths and weaknesses of using the cyber risk analysis techniques in the industry, highlighting gaps with current techniques. We also discuss challenges and potential research directions for advancing the science for both existing and new advanced reactors.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Barriers to adopting artificial intelligence and machine learning technologies in nuclear power

Artificial intelligence and machine learning (AI/ML) technologies offer unique opportunities to transform nuclear plant operations and power generation. Benefits will be felt not only within existing analog and digital instrumentation and control, but also within work processes, the integration of people with technology and most importantly, the business case. The application of this new technology can help simplify complex problems and produce more effective decision-making, making nuclear power safer, more efficient, and more economically viable in the current energy market. Nonetheless, there are potential barriers to its adoption that must be overcome. The purpose of this paper is to categorize, review, and discuss barriers to AI/ML adoption within the nuclear power industry, with a focus on existing commercial reactors. Unique considerations for advanced reactors are also offered. Here we provide a comprehensive overview of the historical, technical, and business barriers that the industry faces, as well as stakeholder readiness, and end-user acceptance. We underscore the importance of user experience and offer potential solutions in overcoming each barrier. These include provisions for easier plant data access, a friendly regulatory environment, and investment in user trust and explainable AI.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Advancing conventional High-Resolution Electron Microscopy

Due to the exceptional performance of most modern commercial transmission electron microscopes, the achievement of phase-contrast imaging resolution in the sub-2Å range is today a routine exercise, provided the samples are compliant. Nonetheless, there remains room for improvement, and the purpose of this manuscript is to highlight procedures that might be employed by the practicing microscopist for advancing conventional high resolution electron microscopy.

440800* -- Miscellaneous Instrumentation-- (1990-)↗

Online Biogenic Carbon Analysis Enables Refineries to Reduce Carbon Footprint during Coprocessing Biomass- and Petroleum-Derived Liquids

To mitigate green-house gas (GHG) emissions, governments around the world are enacting legislation to reduce carbon intensity in transportation fuels. Coprocessing biomass and petroleum-derived liquids in existing refineries is a near-term, cost-effective approach for introducing renewable carbon in fuels and enabling refineries to meet regulatory mandates. However, coprocessing biomass-derived liquids in refineries results in variable degrees of biogenic carbon incorporation, necessitating accurate quantification to verify compliance with mandates. Existing refinery control and instrumentation systems lack the means to measure renewable carbon accurately, reliably, and quickly. Furthermore, accurate measurement of biogenic carbon is key to ensuring refineries meet regulatory mandates. In this Perspective, we present existing methods for measuring biogenic carbon, point out their challenges, and discuss the need for new online analytical capabilities to measure biogenic carbon in fuel intermediates.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Progress in Fast Modular Reactor Conceptual Design

The Fast Modular Reactor (FMR) is a 100-MW(thermal) gas-cooled fast reactor being developed by General Atomics Electromagnetic System with the goal of developing a FMR for flexible and dispatchable power to the U.S. electricity market in the mid-2030s. The conceptual design aims to develop and verify simplified design features. These include an inert helium gas coolant, pellet-loaded fuel rods, installations with air cooling as ultimate heat sink, and small and passive heat removal systems. The goal is to ensure the development of a safe, maintainable, cost-effective, and distributed nuclear energy-generating station. The baseline technologies selected to achieve this goal are a helium coolant that is an inert gas with no chemical reaction with structural components, not activated, single phase, enabling high-temperature operation and a high thermal efficiency Brayton cycle; conventional uranium dioxide (UO 2 ) fuel, which is the most widely used and well-known fuel material, capable of high burnup (100 MWd/kg) and a long fuel life; and silicon carbide composite (SiGA®) cladding and internal structures that are chemically inert in the helium environment, exceptionally radiation tolerant, and being derisked by accident tolerant fuel technology development. Further, the reactor was specifically designed with passive safety features, including high-temperature in-core materials and a reactor vessel cooling system consisting of cooling panels of naturally circulating water. The passive safety of the core was confirmed for the depressurized loss-of–forced cooling accident, which showed the peak cladding temperature at ~1600°C during the transient, which is below the current design limit of 1800°C. The conceptual design of the FMR has been conducted for the reactor system, vessel system, generator and turbomachine, instrumentation and control, residual heat removal system, plant service system, and containment, as well as pre-application licensing documents.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Opportunities, Challenges, and Research Needs for Remote Microreactor Operations

As the nuclear industry develops new advanced reactor technologies, many companies are embracing this advancement by pursuing the development of microreactors. The term microreactor generally refers to a nuclear reactor with an operating power of 20 MW(thermal) or less. The power range of microreactors makes them appealing for many use cases, such as powering remote communities, mining sites, and military bases. Most of the microreactor designs being pursued are expected to incorporate remote facility operations into the final product. However, no framework has yet been developed to determine what remote operations systems require for reliable, resilient, and secure operation of a microreactor. Here, this work identifies the research needs for challenges that are unique to remote operations and monitoring for microreactors, specifically regarding instrumentation and control, communication methods, regulatory requirements, and operational policies. The types of commands and sensor measurements that must be transmitted between the facilities, as well as methods for verifying the trustworthiness of these signals, are assessed. This work evaluates the security, reliability, and performance requirements that must be met when considering the selection of communication hardware and protocols for use in remote operations. Also, an assessment was performed to study how remote operations fit within current regulatory requirements and what may need to be updated in regulatory policy to allow for remote operation. Finally, the operational contingencies unique to remote operations that must be in place for responses to abnormal events are identified. This paper identifies the challenges and research opportunities within the areas of importance for the design of remote operation systems.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Evaluating Methods of Software Bill of Materials Generation to Enhance Nuclear Power Plant Cybersecurity

Instrumentation and control (I&C) systems in nuclear power plants (NPPs) are potential targets of cyberattacks and can prove deleterious for the safety of the NPPs. A Software Bill of Materials (SBOM) provides a detailed list of the various components and their dependencies in software, which helps in vulnerability and risk assessment for cyber hygiene and situational awareness. For an NPP, the process of generating an accurate SBOM report can be complex due to the legacy systems and firmware binaries involved. While most current SBOM tools are focused more on modern internet technology software, this research provides insights and guidelines for an NPP to generate an accurate and efficient SBOM. Here, the paper proposes a new methodology to help NPPs categorize software and use appropriate tools to generate SBOMs for their digital I&C systems.

SBOM↗

Optimization of foreground moment deprojection for semi-blind CMB polarization reconstruction

Abstract Upcoming Cosmic Microwave Background (CMB) experiments, aimed at measuring primordial CMB polarization B-modes, require exquisite control of instrumental systematics and Galactic foreground contamination. Blind minimum-variance techniques, like the Needlet Internal Linear Combination (NILC), have proven effective in reconstructing the CMB polarization signal and mitigating foregrounds and systematics across diverse sky models without suffering from foreground mismodelling errors. Still, residual foreground contamination from NILC may bias the recovered CMB polarization at large angular scales when confronted with the most complex foreground scenarios.By adding constraints to NILC to deproject statistical moments of the Galactic emission, the Constrained Moment ILC (cMILC) method has been demonstrated to further enhance foreground subtraction, albeit with an associated increase in overall noise variance. Faced with this trade-off between foreground bias reduction and overall variance minimization, there is still no recipe on which moments to deproject and which are better suited for blind variance minimization. To address this, we introduce the optimized cMILC (ocMILC) pipeline, which performs full automated optimization of the required number and set of foreground moments to deproject, pivot parameter values, and deprojection coefficients across the sky and angular scales, depending on the actual sky complexity, available frequency coverage, and experiment sensitivity. The optimal number of moments for deprojection, before paying significant noise penalty, is determined through a data diagnosis inspired by the Generalized NILC (GNILC) method.Validated on B-mode simulations of thePICOspace mission concept with four challenging foreground models, ocMILC exhibits lower Galactic foreground contamination compared to NILC and cMILC at all angular scales, with limited noise penalty. This multi-layer optimization enables the ocMILC pipeline to achieve unbiased posteriors of the tensor-to-scalar ratio, regardless of foreground complexity.

Astronomy & Astrophysics↗

Requirements on the gain calibration for LiteBIRD polarisation data with blind component separation

The detection of primordial B modes of the cosmic microwave background (CMB) could provide information about the early stages of the Universe's evolution. The faintness of this signal requires exquisite calibration accuracy and control of instrumental systematic effects which otherwise could bias the measurements. In this work, we study the impact of an imperfect relative polarisation gain calibration on the recovered value of the tensor-to-scalar ratio r for the LiteBIRD experiment, through the application of the blind Needlet Internal Linear Combination (NILC) foreground-cleaning method. We derive requirements on the relative calibration accuracy of the overall polarisation gain (Δg ν ) for each LiteBIRD frequency channel. Our results show that minimum variance techniques, as NILC, are less sensitive to systematic gain calibration uncertainties compared to a parametric approach, if the latter is not equipped with a proper modelling of these instrumental effects. In this study, the most stringent requirements are found in the channels where the CMB signal is relatively brighter, with the tightest constraints at 166 GHz (Δg ν ≈ 0.16%). This differs from the outcome of an analogous analysis performed with a parametric method, where the tightest requirements are obtained for the foreground-dominated channels. Gain calibration uncertainties, corresponding to the derived requirements, are then simultaneously propagated into all frequency channels. By doing so, we find that the overall impact on estimated r is lower than the total gain systematic budget for LiteBIRD approximately by a factor 5, due to the correlations of the impacts of gain calibration uncertainties in different frequency channels. In order to decouple the systematic effect from the specific choice of the model, we derive the requirements assuming constant spectral parameters for the foreground emission. To assess the robustness of the obtained results against more realistic scenarios, we repeat the analysis assuming sky models of intermediate and high complexity. In these further cases, we adopt an optimised NILC pipeline, called the Multi-Clustering NILC (MC-NILC). We find that the impact of gain calibration uncertainties on r is lower than the LiteBIRD gain systematics budget for the intermediate-complexity sky model. For the high-complexity case, instead, it would be necessary to tighten the requirements by a factor 1.8.

79 ASTRONOMY AND ASTROPHYSICS↗