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All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Summary of Technical Peer Review on the Risk Assessment Framework proposed in Report INL/RPT-22-68656 for Digital Instrumentation and Control Systems

This report summarizes the peer review activities initiated by Idaho National Laboratory (INL) during fiscal year (FY) 2023 for the evaluation and improvement of the methodology developed under 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 framework was proposed for this strategy, which aims to (1) provide a best-estimate, risk-informed capability to quantitatively and accurately estimate the risk impact of plant modernization, considering the introduction of high safety-significant safety-related (HSSSR) 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 HSSSR DI&C systems, and (5) reduce uncertainty in costs and support integration of DI&C systems in the plant. The R&D efforts of this project from FY 2019 through FY 2022 were focused on methodology improvement and demonstration of the proposed framework for the risk assessment and design optimization of safety-critical DI&C systems. Collaborations with the nuclear industry have been initiated to support the reliability and risk assessment of their DI&C systems by using the proposed framework. In FY 2023, the framework has reached to a point for a technical peer review and obtain stakeholder feedback. This peer review activity includes coordination of the reviews performed by a group of industry stakeholders, documentation of the peer review suggestions, providing resolutions and responses to the peer review comments. The objective of this technical peer review is to obtain representative feedback on the proposed framework to improve the technical qualities of its methodology and readiness for deployment to the industry. Feedback may identify potential areas for improvement and further development. The Subject Matter experts were invited to review the latest project report documenting the methodology developed in the project and provide evaluations of the technical qualities of the proposed framework and relevant methods. The reviewed project report is “An Integrated Framework for Risk Assessment of High Safety-significant Safety-related Digital Instrumentation and Control Systems in Nuclear Power Plants: Methodology and Demonstration” INL/RPT-22-68656 (short as “INL/RPT-22-68656” in this report). This peer review report documents the technical questions provided for technical peer review and introduces the technical peer reviewers from the stakeholders including nuclear utilities, regulators, and universities. Comments from technical peer reviewers and the resolutions and responses to these comments are outlined. Insights and lessons learned from the technical peer review are summarized in conclusions and future work. 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.

99 GENERAL AND MISCELLANEOUS↗
NASA NTRS1983

LANDSAT-4 image data quality analysis for energy related applications

No useable LANDSAT 4 TM data were obtained for the Hanford site in the Columbia Plateau region, but TM simulator data for a Virginia Electric Company nuclear power plant was used to test image processing algorithms. Principal component analyses of this data set clearly indicated that thermal plumes in surface waters used for reactor cooling would be discrenible. Image processing and analysis programs were successfully testing using the 7 band Arkansas test scene and preliminary analysis of TM data for the Savanah River Plant shows that current interactive, image enhancement, analysis and integration techniques can be effectively used for LANDSAT 4 data. Thermal band data appear adequate for gross estimates of thermal changes occurring near operating nuclear facilities especially in surface water bodies being used for reactor cooling purposes. Additional image processing software was written and tested which provides for more rapid and effective analysis of the 7 band TM data.

Wukelic, G. E.↗
NASA NTRS2001

Automated Theorem Proving in High-Quality Software Design

The amount and complexity of software developed during the last few years has increased tremendously. In particular, programs are being used more and more in embedded systems (from car-brakes to plant-control). Many of these applications are safety-relevant, i.e. a malfunction of hardware or software can cause severe damage or loss. Tremendous risks are typically present in the area of aviation, (nuclear) power plants or (chemical) plant control. Here, even small problems can lead to thousands of casualties and huge financial losses. Large financial risks also exist when computer systems are used in the area of telecommunication (telephone, electronic commerce) or space exploration. Computer applications in this area are not only subject to safety considerations, but also security issues are important. All these systems must be designed and developed to guarantee high quality with respect to safety and security. Even in an industrial setting which is (or at least should be) aware of the high requirements in Software Engineering, many incidents occur. For example, the Warshaw Airbus crash, was caused by an incomplete requirements specification. Uncontrolled reuse of an Ariane 4 software module was the reason for the Ariane 5 disaster. Some recent incidents in the telecommunication area, like illegal "cloning" of smart-cards of D2GSM handies, or the extraction of (secret) passwords from German T-online users show that also in this area serious flaws can happen. Due to the inherent complexity of computer systems, most authors claim that only a rigorous application of formal methods in all stages of the software life cycle can ensure high quality of the software and lead to real safe and secure systems. In this paper, we will have a look, in how far automated theorem proving can contribute to a more widespread application of formal methods and their tools, and what automated theorem provers (ATPs) must provide in order to be useful.

Schumann, Johann↗
DOE OSTI2022

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↗
DOE OSTI2022

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↗
DOE OSTI2023

Advanced Reactor Cyber Analysis and Development Environment (ARCADE) for System-Level Design Analysis

Cybersecurity is a persistent concern to the safety and security of Nuclear Power Plants (NPPs), but has lacked data-driven, evidence-based research. Rigorous cybersecurity analysis is critical for the licensing of advanced reactors using a performance-based approach. One tool that enables cybersecurity analysis is modeling and simulation. The nuclear industry makes extensive use of modeling and simulation throughout the decision process but lacks a method to incorporate cybersecurity analysis with existing models. To meet this need, the Advanced Reactor Cyber Analysis and Development Environment (ARCADE) was developed. ARCADE is a suite of publicly available tools that can be used to develop emulations of industrial control system devices and networks and integrate those emulations with physics simulators. This integration of cyber emulations and physics models enables rigorous cyber-physical analysis of cyber-attacks on NPP systems. This report provides an overview of key considerations for using ARCADE with existing physics models and demonstrates ARCADE’s capabilities for cybersecurity analysis. Using a model of the Small Modular Advanced High Temperature Reactor (SmAHTR), ARCADE was able to determine the sensitivity of the primary heat exchangers (PHX) to coordinated cyber-attacks. The analysis determined that while the PHX’s failures cause disruption to the reactor, they did not cause any safety limits to be exceeded because of the plant design, including passive safety features. Further development of ARCADE will enable rigorous, repeatable, and automated cyber-physical analysis of advanced reactor control systems. These efforts will also help reduce regulatory uncertainty by presenting similar types of cybersecurity analyses in a common format, driving standard approaches and reporting.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

OVERVIEW OF PARTICLE DEPOSITION MODELS FOR SPENT NUCLEAR FUEL STORAGE SYSTEMS

Deposition models were built to evaluate contaminant deposition on spent nuclear fuel (SNF) canisters. The primary contaminant of concern is chloride, which is dispersed in the atmosphere and then deposits onto the canisters. During dry storage, the primary degradation process is likely to be Chloride Induced Stress Corrosion Cracking (CISCC) at the heat-affected zones of the canister welds. It is known that stainless steel canisters are susceptible to CISCC; however, the rate of chloride deposition onto the canisters is poorly known, based on sparse field data from a small number of sites. The models presented in this study could be useful for determining the rate of deposition on the canisters and the likelihood of CISCC to help with SNF canister ageing management. The deposition models were developed with the commercial computational fluid dynamics (CFD) code STAR-CCM+. Various deposition mechanisms were considered and incorporated into the models, and a sensitivity study was conducted to determine the most important mechanisms for deposition within a SNF storage system. The models included both a vertical and horizontal configuration storage system: NAC International’s Modular, Advanced Generation, Nuclear All-purpose STORage System (MAGNASTOR®) and a NUHOMS® horizontal storage module respectively. The resulting canister deposition on the horizontal canister is visually compared with inspection data taken onsite at the Calvert Cliffs Nuclear Power Plant. These models are preliminary, and development of the models will continue. Future validation exercises are currently being planned, including the Canister Deposition Field Demonstration (CDFD) effort funded by U.S. Department of Energy office of Nuclear Energy office of Spent Fuel Waste Science and Technology. The goal of the modeling presented is to demonstrate a potential modeling technique that could be used to plan and inform SNF canister ageing management programs with predictive models for the timing and occurrence of canister CISCC.

Suffield, Sarah R.↗
DOE OSTI2023

Protecting People and Planet

To produce energy, civilian nuclear power plants require fuel. The majority of existing plants rely on solid ceramic fuels that contain concentrations of about 3 to 5% of the element uranium-235. This specific isotope is well suited to sustaining the type of chain reaction required for a nuclear reactor to harness the heat produced by nuclear fission. Title I of the United States Atomic Energy Act of 1954 defines “special nuclear material” as plutonium, uranium-233, or uranium enriched in the isotopes uranium-233 or uranium-235. This label identifies materials that at high concentrations can be used to produce nuclear weapons. The United States and broader international community are fully committed to ensuring the peaceful use of nuclear energy by committing to practices known as safeguards.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2022

Evaluation of Mechanistic and Empirical Models against Existing FFRD and LOCA Experimental Databases

The desire of the nuclear industry to improve the economics of existing nuclear power plants has necessitated research into the potential of a phenomenon known as fuel fragmentation, relocation, and dispersal (FFRD). This phenomenon is possible during a loss-of-coolant accident (LOCA) at relatively high burnup. The Nuclear Energy Advanced Modeling and Simulation program has been developing simulation capabilities for FFRD and LOCA in the BISON fuel performance code for multiple years. This year, the effort has been focused on evaluating new lower length scale informed pulverization thresholds as well as updating and adding new empirical models for various phenomena. Models added or updated this year include a preliminary transient fission gas release model, new high-temperature Zircaloy creep models, a Zircaloy rupture opening area model, and a temperature-dependent emissivity during radiation from the fuel rod to the surrounding atmosphere. The models are verified through implementation tests to demonstrate code correctness after addition to BISON. The models are then assessed against a subset of the existing BISON validation suite for LOCA and FFRD cases. Two new cases, Studsvik Rods 192 and 193, have been added. The results indicate that the inclusion of a bubble pressure evolution model in the bubbles in the high-burnup structure has the largest impact compared to the 3D fracture criterion on reducing the calculated amount of pulverized fuel.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

Probabilistic Risk Assessment Research Needs and Activities

Probabilistic risk assessments (PRAs) have benefitted the safe operation of the U.S. reactor fleet over many decades. Risk insights from these PRAs have provided information from many different perspectives, from what is most important to maintain at a facility to a better understanding of how to address new information regarding safety issues. The methods and tools that have supported the creation and enhancement of PRA models were established through multiple decades of research, from the 1970s starting with the WASH-1400 Reactor Safety Study through comprehensive plant-specific models in use today. Because PRA models are being used to support such a diverse array of plant decisions, they are now being applied to analyze an increasing number and diverse set of aspects of the plant, which are well beyond the initial efforts envisioned in the 1970s. These demands on PRA methods and tools have led to challenges in terms of further expansion of the use of PRA and raised the potential for future research into how to address these challenges to ensure continued nuclear safety. In addition to the PRA needs, the domain of computer science has led to advances in computational approaches that may serve to help nuclear power plant PRA applications. These newer technologies have great potential to improve the effectiveness and economics of PRA and are being considered for exploration of potential benefits to the PRA and nuclear-power communities.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

sCO 2 Brayton Energy Conversion Customer Discovery

All energy production systems need efficient energy conversion systems. Current Rankine cycles use water to generate steam at temperatures where efficiency is limited to around 40%. As existing fossil and nuclear power plants are decommissioned due to end of effective life and/or societies’ desire for cleaner generation options, more efficient energy conversion is needed to keep up with increasing electricity demands. Modern energy generation technologies, such as advanced nuclear reactors and concentrated solar, coupled to high efficiency sCO 2 conversion systems provide a solution to efficient, clean energy systems. Leading R&D communities worldwide agree that the successful development of sCO 2 Brayton power cycle technology will eventually bring about large-scale changes to existing multi-billion-dollar global markets and enable power applications not currently possible or economically justifiable. However, all new technologies face challenges in the path to commercialization and the electricity sector is distinctively risk averse. The Sandia sCO 2 Brayton team needs to better understand what the electricity sector needs in terms of new technology risk mitigation, generation efficiency, reliability improvements above current technology, and cost requirements which would make new technology adoption worthwhile. Relying on the R&D community consensus that a sCO 2 power cycle will increase the revenue of the electrical industry, without addressing the electrical industry’s concerns, significantly decreases the potential for adoption at commercial scale. With a clear understanding of the market perspectives on technology adoption, including military, private sector, and utilities customers, the Sandia Brayton Team can resolve industry concerns for smoother development and faster transition to commercialization. An extensive customer discovery process, similar to that executed through the NSF’s I-Corp program, is necessary in order to understand the pain points of the market and articulate the value proposition of Brayton systems in terms that engage decision makers and facilitate commercialization of the technology.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2025

Technical Assessment of the Application of Digital Twin and Prognostic Tools for Condition Monitoring

This report was prepared for the U.S. Nuclear Regulatory Commission (NRC) to present use cases of the application of advanced technologies toward meeting the current and future regulatory requirements for maintenance and condition monitoring of structures, systems, and components (SSCs). The advanced technologies considered in this work, collectively referred to as digital twin (DT) technologies, are advanced sensors and instrumentation, data analytics, machine learning and artificial intelligence (ML/AI), and physics-based models. The report presents two use cases of reactor coolant pumps (RCPs) and heat pipes in nuclear power plants (NPPs) with technical and regulatory considerations and opportunities in using advanced technologies for conditional monitoring. Key findings from the exploration of these considerations are as follows: - Uncertainties in sensor data and model predictions must be rigorously addressed through validation and verification processes - Regulatory compliance is paramount, necessitating data driven models to be developed in line with existing codes and standards, as well as considering potential future guidelines for advanced reactors - Explainability and transparency in ML/AI models are essential for developing operator trust and regulatory review, including methods that enhance the interpretability of complex data-driven predictions - Condition monitoring programs must be evaluated for their effectiveness in reducing maintenance-preventable function failures (MPFF) and aligning with plant performance criteria - The deployment of advanced technologies for condition monitoring could lead to a transition from periodic to continuous monitoring, thereby optimizing maintenance schedules - Collaborative efforts between industry stakeholders, regulatory bodies, and technology developers are crucial for the successful adoption of advanced technologies for condition monitoring systems in nuclear facilities In summary, the introduction of advanced technologies into condition monitoring programs represents a significant leap forward in the domain of NPP maintenance. By harnessing the capabilities of advanced sensors, data analytics, and ML/AI, NPP operators can transition from a time-based to a condition-based maintenance approach. This shift can potentially enhance the reliability and safety of critical plant components while optimizing maintenance efforts and minimizing unnecessary outages. The NRC is continuing to explore the regulatory aspects of advanced technologies as part of inservice inspection and inservice testing (ISI and IST) programs by pursuing additional research in this technical area.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2021

Update on the Simulation of Commercial Drying of Spent Nuclear Fuel

The purpose of this report is to document improvements in the simulation of commercial vacuum drying procedures at the Nuclear Energy Work Complex at Sandia National Laboratories. Validation of the extent of water removal in a dry spent nuclear fuel storage system based on drying procedures used at nuclear power plants is needed to close existing technical gaps. Operational conditions leading to incomplete drying may have potential impacts on the fuel, cladding, and other components in the system. A general lack of data suitable for model validation of commercial nuclear canister drying processes necessitates additional, well-designed investigations of drying process efficacy and water retention. Scaled tests that incorporate relevant physics and well-controlled boundary conditions are essential to provide insight and guidance to the simulation of prototypic systems undergoing drying processes.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

Response of a Pressurized Water Reactor Dashpot Region to Commercial Drying Cycles

The purpose of this report is to document updates to the simulation of commercial vacuum drying procedures at the Nuclear Energy Work Complex at Sandia National Laboratories. Validation of the extent of water removal in a dry spent nuclear fuel storage system based on drying procedures used at nuclear power plants is needed to close existing technical gaps. Operational conditions leading to incomplete drying may have potential impacts on the fuel, cladding, and other components in the system. A general lack of data suitable for model validation of commercial nuclear canister drying processes necessitates additional, well-designed investigations of drying process efficacy and water retention. Scaled tests that incorporate relevant physics and well-controlled boundary conditions are essential to provide insight and guidance to the simulation of prototypic systems undergoing drying processes. This report documents testing updates for the Dashpot Drying Apparatus (DDA), an apparatus constructed at a reduced scale with multiple Pressurized Water Reactor (PWR) fuel rod surrogates and a single guide tube dashpot. This apparatus is fashioned from a truncated 5×5 section of a prototypic 17×17 PWR fuel skeleton and includes the lowest segment of a single guide tube, often referred to as the dashpot region. The guide tube in this assembly is open and allows for insertion of a poison rod (neutron absorber) surrogate.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

METHODOLOGY AND APPLICATION OF PHYSICAL SECURITY EFFECTIVENESS BASED ON DYNAMIC FORCE-ON-FORCE MODELING

This paper describes ongoing work within the Light Water Reactor Sustainability (LWRS) Program at Idaho National Laboratory (INL) to optimize security and cost of nuclear power plants (NPPs). It reviews the conservatisms in conventional physical security posture and regulations. It introduces the dynamic risk assessment tool developed at INL, Event Modeling Risk Assessment using Linked Diagrams (EMRALD). The dynamic assessment methodology leverages EMRALD to process results of force-on-force (FOF) simulations and crediting safety mitigation actions from probabilistic risk assessment (PRA) models as well as diverse and flexible coping strategies (FLEX) mitigation strategies. Timing information from these simulations are compared against the available time to perform mitigations obtained from Reactor Excursion and Leak Analysis Program (RELAP5) simulations. To illustrate the methodology, a station blackout (SBO) attack scenario was modeled in commercially available FOF simulation tools. The simulation results provide valuable insights into possible attack outcomes and as the probabilistic risk of a core damage event given these outcomes. Safety mitigation procedures were modeled in EMRALD, and were dependent on the attack outcomes by considering human operator uncertainties. RELAP5 simulations incorporating human and hardware uncertainties were performed to estimate the distribution of time-to-core damage. The results demonstrate that, even in the extreme case of a successful adversarial attack, plant mitigation strategies provide significantly high-likelihood of preventing radiological release. The proposed modeling and simulation framework of integrating FLEX equipment with FOF models enables the NPPs to credit FLEX portable equipment in the plant security posture, resulting in an efficient and optimized physical security.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2020

MASTODON: An Open-Source Software for Seismic Analysis and Risk Assessment of Critical Infrastructure

Seismic analysis and risk assessment of safety-critical infrastructure like hospitals, nuclear power plants, dams, and facilities handling radioactive materials involve computationally intensive numerical models and coupled multiphysics scenarios. They are also performed in a strict regulatory environment that requires high software quality assurance standards, and in the case of safety-related nuclear facilities, a conformance to the American Society of Mechanical Engineers Nuclear Quality Assurance (NQA-1) standard. This paper introduces the open-source finite-element software, MASTODON (Multi-hazard Analysis of Stochastic Time-Domain Phenomena), which implements state-of-the-art seismic analysis and risk assessment tools in a quality-controlled environment. MASTODON is built on MOOSE (Multi-physics Object-Oriented Simulation Environment), which is a highly parallelizable, NQA-1 conforming, coupled multiphysics, finite-element framework developed at Idaho National Laboratory. MASTODON is capable of fault rupture and source-to-site wave propagation using the domain reduction method, nonlinear site response, and soil-structure interaction analysis, implicit and explicit time integration, automated stochastic simulations, and seismic probabilistic risk assessment. When coupled with other MOOSE applications, MASTODON can also solve strongly and weakly coupled multiphysics problems. This paper presents a summary of the capabilities of MASTODON and some demonstrative examples.

42 ENGINEERING↗
DOE OSTI2025

Identification of Important Phenomena for Light Water Reactors During Heat Transport System Failure Events in Integrated Energy Systems

This work adapts historical literature and existing phenomena identification and ranking tables (PIRT) to be applicable to a novel nuclear power plant (NPP) and chemical or thermal process integrated energy system (IES), particularly focusing on the process heat and heat transport system failure events that are not a concern during normal NPP operation but become vital when an IES is considered. Nuclear energy has been suggested to go beyond base-load applications and be used for hydrogen co-generation systems, amongst other IESs. Prior to the implementation of nuclear IESs, sufficient analysis must be performed on accident events to ensure public safety. The events considered were deemed important because of their potential to damage systems, structures, and components (SSCs). Process thermal events of concern include loss of heat load and temperature transient events. Loss of heat load events were characterized as having high importance and being well understood. Temperature transient events may be further categorized by the cyclic loading and harmonics phenomena. Cyclic loading issues were classified as medium to high importance with knowledge gaps existing regarding fatigue and low power operation, while harmonics phenomena were classified as low importance and are well understood. Heat transport system failure events of concern include intermediate and process heat exchanger failures, mass addition to reactor coolant, ingress of material from thermal manifold/energy storage, and loss of intermediate fluid. Furthermore, these events tended to be of high or medium importance, with some knowledge gaps needing to be filled for individual reactor systems due to unique designs.

Integrated Energy System (IES)↗
DOE OSTI2020

Status Update on the High Precision Isotopic Measurements on High Burnup LWR Fuel in 2020

The US Department of Energy (DOE) Office of Nuclear Energy (NE) is currently investigating the feasibility of directly disposing dual-purpose (storage and transportation) canisters (DPCs) in a spent nuclear fuel (SNF) repository. Criticality during the repository performance period (10,000 years or more) is one of the major concerns related to direct disposal of DPCs, specifically as the system undergoes degradation in the repository environment and timeframe. Oak Ridge National Laboratory (ORNL) is developing an as-loaded criticality analysis methodology using full (actinides + fission products) burnup credit that exploits the inherent criticality margin associated with actual canister-specific loading configuration. Burnup credit criticality analysis requires validation of the depletion/decay codes used to generate the burned isotopic inventory of an assembly by comparing the code-predicted inventory with experimentally determined isotopic data. Currently, isotopic measurement data for boiling water reactors (BWR) SNF are limited, and additional measurements will be highly beneficial for BWR burnup credit analysis, which is essential to demonstrate disposability of BWR DPCs. Moreover, new pressurized water reactor (PWR) samples of isotopic measurements will expand the PWR sample population and consequently will greatly improve sample statistics. In turn, this will reduce uncertainty in the computational determination of the isotopic composition of commercial SNF and eliminate additional penalties currently used for lack of data. As part of the isotopic analysis task, eight diverse, high burnup (HBU) samples from several PWR rods are being dissolved and isotopically analyzed to provide high-quality measurement data for PWR SNF to reducing the uncertainties associated with PWR isotopic depletion validation. The isotopics of interest focus on nuclides important to burnup credit, shielding, and decay heat in PWR SNF. Additionally, eight high burnup BWR fuel samples from the Limerick nuclear power plant have been identified for measurement to support reducing uncertainties associated with BWR isotopic depletion validation.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗