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At least 307 records · Page 17

Understanding Risk Tolerance and Building an Effective Safety Culture

Estimates range from 65-90 percent of catastrophic mishaps are due to human error. NASA's human factors-related mishaps causes are estimated at approximately 75 percent. As much as we'd like to error-proof our work environment, even the most automated and complex technical endeavors require human interaction... and are vulnerable to human frailty. Industry and government are focusing not only on human factors integration into hazardous work environments, but also looking for practical approaches to cultivating a strong Safety Culture that diminishes risk. Industry and government organizations have recognized the value of monitoring leading indicators to identify potential risk vulnerabilities. NASA has adapted this approach to assess risk controls associated with hazardous, critical, and complex facilities. NASA's facility risk assessments integrate commercial loss control, OSHA (Occupational Safety and Health Administration) Process Safety, API (American Petroleum Institute) Performance Indicator Standard, and NASA Operational Readiness Inspection concepts to identify risk control vulnerabilities.

Loyd, David↗

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

This report documents the activities performed by Idaho National Laboratory (INL) during Fiscal Year (FY) 2022 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 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. To achieve these technical goals, the 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 on nuclear power plant (NPPs).

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Data requirements for improving the Quantitative Risk Assessment of liquid hydrogen storage systems

Quantitative Risk Assessment (QRA) supports the development of risk-informed safety codes and standards which are employed to enable the safe deployment of hydrogen technologies essential to decarbonize the transportation sector. System reliability data is a necessary input for rigorous QRA. Here, the lack of reliability data for bulk liquid hydrogen (LH 2 ) storage systems located on site at fueling stations limits the use of QRAs. In turn, this hinders the ability to develop the necessary safety codes and standards that enable worldwide deployment of these stations. Through a QRA-based analysis of a LH 2 storage system, this work focuses on identifying relevant scenario and probability data currently available and ascertaining future data collection requirements regarding risks specific to liquid hydrogen releases. The work developed consists of the analysis of a general bulk LH 2 storage system design located at a hydrogen fueling station. Failure Mode and Effect Analysis (FMEA) and traditional QRA modeling tools such as Event Sequence Diagrams (ESD) and Fault Tree Analysis (FTA) are employed to identify, rank, and model risk scenarios related to the release of LH 2 . Based on this analysis, scenario and reliability data needs to add LH 2 -related components to QRA are identified with the purpose of improving the future safety and risk assessment of these systems.

08 HYDROGEN↗

Evolution of NASA’s Nuclear Flight Safety Program to Infuse Risk Leadership and Assurance Framework Concepts

In recent years, the United States (U.S.) Government has issued several new National policies that fundamentally change the approach to nuclear flight safety for aerospace applications, including the complete revision of the Federal policy for handling launch of spacecraft containing space nuclear systems. In response, the National Aeronautics and Space Administration (NASA) is updating its nuclear flight safety program while still maintaining consistency with other Federal policies, international conventions, and NASA’s own policies. To achieve this evolution, NASA is factoring in an objectives-driven and assurance case mindset to develop a risk-informed and performance-based program. NASA and others have successfully applied this mindset in other disciplines and contexts and it is being pursued here via broad cooperation within NASA and with external stakeholders. This paper will briefly describe how the NASA nuclear flight safety program is evolving to meet these changing needs.

Matthew J. Forsbacka↗

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

This report documents activities performed by Idaho National Laboratory (INL) during fiscal year (FY) 2024 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. The goal of the RISA Pathway is to optimize safety margins and minimize uncertainties to achieve economic efficiencies while maintaining high levels of safety. This is accomplished by providing scientific basis to better represent safety margins and factors that contribute to cost and safety, and by developing new technologies that reduce operating costs. The research efforts for FY 2024 encompass methodology refinement and exploration. The efforts include: (1) The implementation of a natural language processing tool to expedite key aspects of the reliability analysis methods developed by INL; (2) advances to support intersystem CCF analysis by providing guidance for and identification of coupling mechanisms that may contribute to CCF; (3) the investigation of how generative artificial intelligence tools can aid in hazard analysis and diversity and defense in depth (i.e., D3) assessments; (4) Industry collaboration, allowing the demonstration of and INL's risk assessment tools to support risk assessment of DI&C systems at early and late stages of development; (4) a roadmap for the development of a software for each of INL's risk assessment tools; (5) The development of a theory and methodology manual for a risk quantification methodology; (6) the development of a reliability analysis for machine learning (ML)-integrated control systems.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Exploring Advanced Computational Tools and Techniques with Artificial Intelligence and Machine Learning in Operating Nuclear Plants

This report presents the project Idaho National Laboratory conducted for Nuclear Regulatory Commission to explore the advanced computational tools and techniques, such as artificial intelligence (AI) and machine learning (ML), for operating nuclear plants. The report reviews the nuclear data sources, with the focus on the operating experience data, that could be applied by advanced computational tools and techniques. Plant-specific and generic (national and international) data from different sources are described. The report describes the relationships between statistics and AI/ML and then introduces the most widely used AI/ML algorithms in both supervised and unsupervised learning. The report reviews the recent applications of advanced computational tools and techniques in various fields of nuclear industry, such as reactor system design and analysis, plant operation and maintenance, and nuclear safety and risk analysis. Finally, the report presents the insights from the project on the potential applicability of AI/ML techniques in improving advanced computational capabilities, how the advanced tools and techniques could contribute to the understanding of safety and risk, and what information would be needed to provide meaningful insights to decision makers. The report also documents an NRC survey on the current state of commercial nuclear power operations relative to the use of AI and ML tools as well as the role of AI/ML tools in nuclear power operations was published by the NRC as in FRN NRC-2021-0048 in April 2021. A summary of the survey including the survey questions, survey participants, survey responses, and the conclusions and insights derived from the survey is provided in the report. Finally, the report investigates potential applications of using AI/ML in operating NPPs and advanced reactors (both advanced LWRs and advanced NLWRs) to improve nuclear plant safety and efficiency. Three main application fields are defined and discussed: (1) plant safety and security assessments; (2) plant degradation modeling, fault and accident diagnosis and prognosis; and (3) plant operation and maintenance efficiency improvement.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

The Future of Safety Management

As the pace of aviation evolution accelerates, our approach to safety and risk management needs to evolve to cover expanded current day operations as well as participants not traditionally included in the airspace. To assure safety of an increasingly complex aviation system it is essential to leverage new processes and techniques that can more quickly identify and respond to emerging risks. The concept of an In-Time Aviation Safety Management System (IASMS) presents an advanced SMS framework designed to enable integrated safety management and assurance. To assure safety of future aviation operations and technologies, advanced SMS concepts must be designed such that they can evolve to keep pace as aviation continues to change and as new safety and risk management tools and techniques emerge.

safety↗

REFSafE: A RAG-Enabled Framework for Predictive Risk Analysis and Automated Safety Report Generation in Mission-Critical Environments

Operational safety in mission-critical environments requires AI systems that are accurate, interpretable, and resistant to hallucination. We present an agentic Retrieval-Augmented Generation (RAG) framework, REFSafe, for grounded hazard analysis and automated safety report generation. The system integrates Large Language Models (LLMs) with structured operational data, historical incident repositories, policy documents, and external authoritative sources. Through iterative agentic reasoning, the framework retrieves, verifies, and synthesizes evidence prior to generation, enforcing citation-backed outputs with explicit source attribution (documents, links, and prior events) to ensure traceability and trust. To mitigate hallucinations and unsupported claims, all risk assessments and forecasts are constrained to retrieved evidence, with confidence signals derived from retrieval relevance and source consistency. A transparent pipeline enables subject matter experts (SMEs) to validate predictions, and provide structured feedback, forming a continuous performance calibration loop. Preliminary deployment demonstrates improved reliability in hazard detection and safety/vulnerability report generation. This work advances trustworthy, evidence-grounded AI for predictive safety intelligence in mission-critical operations.

Das, Sanjay [ORNL] (ORCID:0009000542591915)↗

Integrating Cybersecurity Risk Assessment with Process Safety in Chemical Process Industries

This dissertation bridges the gap between industrial cybersecurity and traditional process safety by introducing an integrated Cyber-LOPA framework that combines the Purdue Enterprise Reference Architecture, Cyber Kill Chain, and CVSS v4.0 metrics. Demonstrated on a High-Density Polyethylene slurry process, the work illustrates how cyber threats targeting automation systems can bypass physical protection layers, proving the necessity of unified risk assessments to prevent cyber-induced physical incidents in chemical manufacturing plants.

Cyber-LOPA (CLOPA)↗

Another Approach to Enhance Airline Safety: Using Management Safety Tools

The ultimate goal of conducting an accident investigation is to prevent similar accidents from happening again and to make operations safer system-wide. Based on the findings extracted from the investigation, the "lesson learned" becomes a genuine part of the safety database making risk management available to safety analysts. The airline industry is no exception. In the US, the FAA has advocated the usage of the System Safety concept in enhancing safety since 2000. Yet, in today s usage of System Safety, the airline industry mainly focuses on risk management, which is a reactive process of the System Safety discipline. In order to extend the merit of System Safety and to prevent accidents beforehand, a specific System Safety tool needs to be applied; so a model of hazard prediction can be formed. To do so, the authors initiated this study by reviewing 189 final accident reports from the National Transportation Safety Board (NTSB) covering FAR Part 121 scheduled operations. The discovered accident causes (direct hazards) were categorized into 10 groups Flight Operations, Ground Crew, Turbulence, Maintenance, Foreign Object Damage (FOD), Flight Attendant, Air Traffic Control, Manufacturer, Passenger, and Federal Aviation Administration. These direct hazards were associated with 36 root factors prepared for an error-elimination model using Fault Tree Analysis (FTA), a leading tool for System Safety experts. An FTA block-diagram model was created, followed by a probability simulation of accidents. Five case studies and reports were provided in order to fully demonstrate the usefulness of System Safety tools in promoting airline safety.

Lu, Chien-tsug↗

Increasing Reliability and Safety of Hydrogen Components - Reliability Data Collection

Come learn about the new Hydrogen Component Reliability Database (HyCReD) and participate in discussions on hydrogen component reliability data collection, collaboration, and analysis. Funded by the U.S. Department of Energy's Office of Energy Efficiency and Renewable Energy under the Hydrogen and Fuel Cell Technologies Office, HyCReD is a collaborative project between the National Renewable Energy Laboratory, the University of Maryland, and hydrogen stakeholders to improve safety reliability for hydrogen facilities by integrating risk reduction methodologies and component reliability data taxonomies that support hydrogen infrastructure failure rate analysis.

component↗

Hydrogen Component Reliability Database (HyCReD)

The Hydrogen Component Reliability Database (HyCReD) is a collaborative project between the National Renewable Energy Laboratory, the University of Maryland, and hydrogen stakeholders to improve safety reliability for hydrogen facilities by integrating risk reduction methodologies and component reliability data taxonomies that support hydrogen infrastructure failure rate analysis.

availability↗

Safety issues of defective lithium-ion batteries: identification and risk evaluation

Lithium-ion batteries inevitably suffer minor damage or defects caused by external mechanical abusive loading, e.g. , penetration, deformation, and scratch without triggering a hard/major short circuit. The replacement of cells becomes a dilemma if the safety risk of the defective batteries remains unknown. Herein, by introducing a representative defect form, i.e. , screw indentation, we demonstrate the safety characteristics of defective batteries. We prove that defective batteries have a significantly increased thermal risk and deteriorated mechanical integrity, but can go undetected due to prompt voltage recovery and insignificant local temperature increase. We discover that the voltage curve within the first few cycles contains sufficient information to identify defective batteries from otherwise good ones and propose methodologies to monitor the cells. Capacity loss and current leakage are two characteristics that can be estimated using the voltage curve. According to the defect size and position, the capacity loss could be 1 to 10 2 mA h and the leakage current could be 5–50 mA. Results remove the barriers for defective battery safety risk evaluation, enabling identification, monitoring, and early warning of minor damaged batteries.

25 ENERGY STORAGE↗

Common Approach to Molten Salt Reactor Safety Evaluation [Slides]

The presentation describes the necessary elements of developing a common approach to molten salt reactor (MSR) safety adequacy evaluation. Developing a common approach to establishing adequate safety for MSRs could substantially decrease the developer risks. However, safety adequacy is intimately associated with reactor licensing which is an element with national sovereignty. No reactor class has a common, portable international license. The advantageous performance characteristics of MSRs can be leveraged to decrease the cost and time necessary to develop reasonable confidence of adequate safety. Adequate safety can be demonstrated though either accident prevention or mitigation. MSR have characteristics that may make accident mitigation a preferable safety adequacy evaluation approach. Adequate quality as well as a thorough understanding of accident progression validated through separate and integral effects testing remains central to any safety adequacy demonstration method.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Application of Risk Assessment Tools in the Continuous Risk Management (CRM) Process

Marshall Space Flight Center (MSFC) of the National Aeronautics and Space Administration (NASA) is currently implementing the Continuous Risk Management (CRM) Program developed by the Carnegie Mellon University and recommended by NASA as the Risk Management (RM) implementation approach. The four most frequently used risk assessment tools in the center are: (a) Failure Modes and Effects Analysis (FMEA), Hazard Analysis (HA), Fault Tree Analysis (FTA), and Probabilistic Risk Analysis (PRA). There are some guidelines for selecting the type of risk assessment tools during the project formulation phase of a project, but there is not enough guidance as to how to apply these tools in the Continuous Risk Management process (CRM). But the ways the safety and risk assessment tools are used make a significant difference in the effectiveness in the risk management function. Decisions regarding, what events are to be included in the analysis, to what level of details should the analysis be continued, make significant difference in the effectiveness of risk management program. Tools of risk analysis also depends on the phase of a project e.g. at the initial phase of a project, when not much data are available on hardware, standard FMEA cannot be applied; instead a functional FMEA may be appropriate. This study attempted to provide some directives to alleviate the difficulty in applying FTA, PRA, and FMEA in the CRM process. Hazard Analysis was not included in the scope of the study due to the short duration of the summer research project.

Paul S. Ray↗