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The Safety Instrumented System (SIS) for Extreme Fast Charging (XFC) Infrastructure (BA-1359) is responsible for gathering data from multiple sources to monitor the safety and security properties (cyber and physical) of multiple XFC. The data is processed and analyzed by software running on the SIS Core and SIS Aggregator systems.
All industrial facilities deal with safety hazards such as equipment failures, chemical and toxic releases, and fires and explosions just to name a few. A disciplined framework for managing the integrity of operating systems and processes that handle hazardous substances by applying good design principles, engineering, and operating practices is called process safety. The goal of such framewoks is to prevent the release of energy or material that could cause harm to people or damage to equipment and/or environment. Process safety covers all aspects of facility operation also including design, maintenance, and human and organizational factors that could possibly have effect on process safety. As it will be seen from the discussion below, process safety is just one of the pieces of the much bigger matter, a safety culture. Many industries have long recognized the importance of safety culture in their day-to-day operation. Although the definition of safety culture can slightly differ from organization to organization, in general, a safety culture is how things are done to demonstrate a commitment to safety by everyone involved. An organization acquires safety culture over time as the product of individual and group values, actions, and behaviors toward overall safety. It is important to note that safety culture should not be viewed as some static state that an organization wants to reach. It is more like a constantly evolving level of “how things are done when nobody is watching.” Safety culture is an inherent characteristic of an organization, it is always present, but the level can range on a continuum from undesirable to desirable or more commonly used, from negative to positive. An example for an undesirable, negative safety culture would be a company in which accidents resulting in harm (physical and/or emotional) of its employees, equipment or surrounding environment and community occur frequently. At the other end of the spectrum would be a company in which such accidents are rare or do not occur at all (desired or positive safety culture). Every company/industry exists somewhere within this spectrum.
The goal of this research is to theorize and quantify the relationships between safety and the financial performance of nuclear power plants (NPPs). The Socio-Technical Risk Analysis (SoTeRiA) theoretical framework, which connects the social aspects (e.g., safety culture) and structural features (e.g., safety practices) of an organization with organizational safety and financial risks, is used to theorize the direct and indirect relationships between safety and the financial performance of NPPs. An Integrated Enterprise Risk Management (I-ERM) methodological framework is developed to operationalize SoTeRiA to quantify NPP safety and financial performance in a unified platform where their underlying physical degradation mechanisms, coupled with maintenance performance (considering human and organizational factors), are explicitly incorporated to depict the interconnections and dependencies between safety and financial performance. In this study, NPP safety refers to both occupational safety and system safety (estimated from Probabilistic Risk Assessment, PRA), and financial performance refers to the monetary values associated with NPP operation and maintenance (O&M) strategies. This report covers a case study demonstrating the feasibility of the I-ERM methodological framework. More detailed development of one of the I-ERM modules, i.e., Probabilistic Physics-of-Failure (PPoF) analysis, and its connection with other I-ERM modules is demonstrated in a second case study. The outcome of this research will help NPP decision-makers create cost-saving maintenance strategies while maintaining safety by providing cost- and risk-informed recommendations regarding maintenance work processes and operational strategies.
The proper use of fall prevention and fall protection controls can reduce the risk of deaths and injuries caused by falls. This course, Fall Protection Introduction (#33462), is designed as an introduction to various types of recognized fall prevention and fall protection systems at Los Alamos National Laboratory (LANL), including guardrail systems, safety net systems, fall restraint systems, and fall arrest systems. Special emphasis is given to the components, inspection, care, and storage of personal fall arrest systems (PFAS). This course also presents controls for falling object hazards and emergency planning considerations for persons who have fallen.
Counterfeit refrigerants pose significant challenges to safety, system reliability, and operational effectiveness due to their harmful contaminants or incompatible chemical compositions. Utilizing these noncompliant products can lead to reduced efficiency, equipment failures, and expensive repairs. Additionally, heightened demand for alternative refrigerants during the industry's transition has created supply gaps, enabling counterfeit products to proliferate. Accurate detection and analysis tools are therefore essential to verify refrigerant authenticity and ensure system integrity in diverse applications. This paper presents the development of a portable device designed for reliable identification and detailed analysis of refrigerant composition. By integrating precision gas sampling, controlled pressure regulation, and automated sensor technology, the device not only detects deviations from standard refrigerant properties but also provides a comprehensive composition breakdown. Pre-calibrated sensors measure the refrigerant gas to identify specific concentrations and contaminants, with an intuitive LED-based indicator system ensuring quick interpretation of results. The user-friendly interface enables operators to select refrigerant types for targeted testing, further enhancing accuracy and usability for field technicians. Comprehensive testing was conducted on mildly flammable A2L refrigerants, showcasing the device’s robustness and adaptability in analyzing composition and detecting discrepancies. The device demonstrated consistent accuracy across a range of refrigerant samples, affirming its reliability in diverse operational environments. Its design minimizes contamination risks during sampling and provides detailed composition results within 90 seconds, ensuring efficient and precise analysis. With a projected price point under $150, the proposed solution delivers affordability alongside its lightweight portability and straightforward operation. Unlike complex and costly alternatives, such as gas chromatography systems, this device provides an accessible option for technicians, customs personnel, and industry operators in need of quick and effective refrigerant verification. Compatible with both current formulations and emerging refrigerant technologies, the device addresses critical counterfeit detection needs across a range of applications. By delivering accurate composition analysis and counterfeit identification, this innovation enhances system performance, safety, and operational reliability in crucial industries.
A train safety system comprises a cable connected to at least two conducting contacts, an electrical load between said two conducting magnetic contacts, and a DC track circuit associated with railroad tracks wherein the at least two conducting plates can be connected to each of the railroad rails in order to shunt the DC track circuit and alert oncoming trains of fouling of the tracks or crossing ahead.
Probability of loss of assured safety (PLOAS) is modeled for weak link (WL)/strong link (SL) systems in which one or more WLs or SLs could potentially degrade into a precursor condition to link failure that will be followed by an actual link failure after some amount of elapsed time. The descriptor loss of assured safety (LOAS) is used because failure of the WL system places the entire system in an inoperable configuration while failure of the SL system before failure of the WL system, although undesirable, does not necessarily result in an unintended operation of the entire system. Thus, safety is “assured” by failure of the WL system before failure of the SL system. Here, the following topics are considered: (i) Definition of precursor occurrence time cumulative distribution functions (CDFs) for individual WLs and SLs, (ii) Formal representation, approximation and illustration of PLOAS with (a) constant delay times, (b) aleatory uncertainty in delay times, and (c) delay times defined by functions of link properties at occurrence times for link failure precursors, and (iii) Procedures for the verification of PLOAS calculations for the three indicated definitions of delayed link failure.
Replacing the existing aging analog instrumentation and control (I&C) systems with modern safety control and protection digital technology offers one of the foremost means of performance improvements and cost reductions for the existing nuclear power plants (NPPs). However, the qualification of digital I&C systems remains a challenge, especially considering the issue of software common-cause failures (CCFs), which are difficult to address. With the application and upgrades of advanced digital I&C systems, software CCFs have become a potential threat to plant safety because most redundant designs use similar digital platforms or software in the operating and application systems. With complex designs of multilayer redundancy to meet the single-failure criterion, digital I&C safety systems (e.g., engineered safety-features actuation system [ESFAS]) are of a particular concern in the U.S. Nuclear Regulatory Commission (NRC) licensing procedures. This paper applies a modularized approach to conduct redundancy-guided systems-theoretic hazard analysis for an advanced digital ESFAS with multilevel redundancy designs. Systematic methods and risk-informed tools are incorporated to address both hardware and software CCFs, which provide guidance to eliminate the triggers of potential single points of failure in the design of digital safety systems in advanced plant designs.
This presentation will be presented at FY 2020 SDRD Annual (Webex) Meeting scheduled for September 23–24, 2020. Evaluating Use of the NASA Nowcastof Atmospheric Ionizing Radiation for Aviation Safety (NAIRAS) System for Verifying/Validating AMS Cosmic Background Radiation Measurements, RSLA-006-20, Year 1
One of the lessons learned from the Fukushima Daiichi nuclear power plant (NPP) accident is strengthening the station blackout (SBO) mitigation capabilities by enhancing defense in depth for all existing and new NPPs. One of the possible remedies is diverse and flexible coping strategies (FLEX). The objective of this study is to address the benefits of FLEX in various accident scenarios in terms of both risk and cost. FLEX was originally devised against SBO accidents. In this research, we investigate the fundamental plant responses against accidents considering two fundamentally different cases: accidents that lead to high pressure on the primary side and accidents that lead to low pressure on the primary side. Several uncertainties are associated with the characteristics of the FLEX portable equipment. Specifically, the time for FLEX deployment may depend on several factors such as type of accident, point of injection, availability of safety systems, battery backup timings, and human actions. This study utilizes a dynamic risk assessment framework to analyze accident scenarios and suggests a novel importance measure, which is a cumulative distribution function– based importance metric that characterizes the influence of input distribution on complete output distribution. The importance of the existing and newly developed FLEX strategy based on risk significance is illustrated with examples. The suggested measure provides clear insight into how FLEX affects risk of the whole system and additional risk margins thanks to new safety systems.
Hot cells are used to safely shield workers from high radiation environments while allowing a process to take place within the cell's shielded enclosure, often with the assistance of remote manipulators. The interior of a cell may not be accessible by personnel for years at a time, either due to the lingering radiation environment or due to the constant use of these specialized pieces of equipment. High radiation levels are known to cause undesirable effects and changes to different materials in varying degrees. Selecting equipment for a radiation environment requires an evaluation of materials used (preferably completed assembles), to ensure all interactions of materials are known and ensure that the equipment will have a high degree of reliability and functionality over the intended life of the facility. Hot cells contain systems to support the primary purpose of the enclosure. Fire detection is one such support system. Safety of hot cell operations often establish limits on the amounts of combustibles with the cells, but the presence of some combustible materials is unavoidable. Fire detection is provided to quickly detect a fire and summon manual intervention before damage is too great. Detection may also be used to initiate fire suppression systems. As a safety system, fire detection needs to remain functional to protect the facility throughout the facility's life. Equally important is that the false alarms from the fire detection are minimized to retain confidence in the alarm system and avoid unnecessary interruptions in the hot cell operations. There are many types of fire detection available with various pros and cons. Not all types of fire detection are suited for hot cell application.
The Oak Ridge National Laboratory (ORNL) is implementing a major upgrade to the Spallation Neutron Source (SNS) facility, encompassing the addition of the Second Target Station (STS). Preliminary design reviews have been conducted on several STS Personnel Protection Systems (PPS). The reviews focused primarily on the integration with the existing SNS PPS, the new proton transport tunnel, and the target areas. Development of the PPS is ongoing, to ensure a coherent safety system with the mission of protecting users and workers from prompt radiation hazards while providing high beam availability to operations. The STS PPS element in the Integrated Control System (ICS) is a facility-wide system composed of multiple safety subsystems, including the Ring to Second Target (RTST) beam transport tunnel, Target, Bunker and Instruments. Personnel working in all these geographic areas are protected by modular reliable PPS solutions. The safety system enforces access controls, radiation monitoring, beam destination control, and application of critical device inhibit upon detection of abnormal condition. It uses well-documented processes, Common Industrial Protocol (CIP) safety, pulsed test, and redundancy to achieve the desired Safety Integrity Level (SIL). This paper gives an architectural overview of the STS PPS and a detailed safety plan for the SNS facility, addressing safety solutions and human factors.
Nearly all large commercial buildings have heating, ventilation and air conditioning (HVAC) systems, lighting systems, safety and other systems controlled by a computer—a dedicated server with a building energy management system (BMS). However, these BMSs are proprietary with each building’s assets (that is, fans, valves, pumps, and their setpoints) named and coded uniquely by the BMS vendor or engineer; building analytics and control algorithms are written specific to the assets and the building. Thus, any control updates or analytics to improve building performance—especially critical to reduce greenhouse emissions or improve load flexibility—are labor intensive and costly. The Brick schema was developed so the same analysis or control algorithms can work on a variety of buildings if each is digitally represented in a Brick data model. The goal of this project was to further the development of Brick to extend it beyond an academic project with demonstrated success in a small field study, to a practical choice for industrial and commercial stakeholders seeking to realize value from building data. To do this, we executed four objectives: (1) expand the Brick schema including its modeling capabilities and vocabulary, (2) develop tools for integrating Brick with existing digital technologies and representations in buildings, (3) develop an open-source analytics platform to facilitate use of Brick in delivering data value, and (4) demonstrate Brick-driven analytics and controls in real settings.
The AP1000 power plant has implemented multiple layers of passive safety systems to enhance reactor safety and ensure system integrity during postulated scenarios, such as loss of coolant accident (LOCA) and main steam line break (MSLB). Among these, the passive containment cooling system (PCCS) is a safety-related system designed to prevent the containment from exceeding the design limits of both pressure and temperature following a postulated design basis accident, by transferring heat from the steel containment vessel to the atmosphere. During LOCA, natural air convection plays a vital role in removing heat from the steel containment vessel to the atmosphere. This is integrated with the condensate film from the Passive Containment Cooling Water Storage Tank (PCCWST). Air natural convection is also the only heat removal mechanism after the dry-out of the PCCWST and during the loss of shutdown decay heat removal (LOSDHR) event. Therefore, it is essential to investigate the thermal hydraulics behavior of the containment under transient conditions to ensure its safety and integrity. This paper presents a simplified CFD/ANSYS FLUENT model developed to analyze the impact of different parameters, such as air relative humidity, air temperature, and steel containment temperature, on the natural convection capability to remove the decay heat following LOCA. The model aims to examine the thermal behavior of the containment and provides a comprehensive understanding of the system's natural convection capability during postulated accidents. The results obtained from the model can be used to improve the safety and integrity of the containment system and provide valuable insights for future research in the field.
The incorporation of remote operations into reactor operations is a topic of high interest among advanced and small modular reactor (A/SMR) vendors, with some considering it essential to the success of their business models. However, remote operations are a concept novel to the nuclear industry. While various technical aspects of remote operations have been explored, a significant gap remains in understanding the security implications of integrating remote operations into reactor designs, particularly concerning the security requirements for remote-operations facilities and infrastructure. This report aims to address this gap by first defining classes of remote operation based on the extent of remote access to reactor control systems and grounded in the existing regulatory framework with compatible terminology. Secondly, the report outlines the physical and cybersecurity requirements applicable to remote-operations facilities and infrastructure at each defined class. These requirements are based on existing licensing frameworks provided by 10 Code of Federal Regulations (CFR) Part 50 and 10 CFR Part 52, as well as the upcoming A/SMR licensing framework in the proposed Part 53. The assessment focuses specifically on security regulations, such as 10 CFR Part 73, which includes provisions for both cybersecurity (§ 73.54) and physical security (§ 73.55). This report proposes five classes of remote reactor operations. Class 1 involves remote monitoring only, with no control over reactor systems. Class 2 allows for the remote issuance of allowlisted commands to the reactor facility. Class 3 extends control to non-safety-significant, non-safety-related, or not important to safety systems and equipment. Class 4 permits remote control of safety-significant systems. Finally, Class 5 allows remote control of safety-related systems. It is important to note that these classes were defined purely with functionality in mind, without considering the practicality or feasibility of implementation for each class under current or upcoming regulatory guidance. The intention behind this approach is to enable an assessment of which security requirements apply to each class, allowing readers to evaluate the implementation possibilities for their specific use cases. Following the definition of remote-operation classes, the report assesses the specific physical and cybersecurity requirements applicable to the remote-operations facility and infrastructure within each defined class. This includes defining the types and locations of operators that are possible at each class of operation and, based on operator type and location, as well as functionality within each class, outlining the physical and cybersecurity requirements. By detailing the security requirements by class, the report provides readers with the information needed to determine the type of security program they may need to implement for their desired concept of operation. The next contribution of this report was to assess the practicality of implementing each proposed class of remote operations based upon the security requirement assessment. In short, three of the five proposed remote-operation classes were found to possibly have a practical path forward to implementation under the U.S. regulatory framework. Class 1 remote operations are currently in use in the U.S. while Class 2 and 3 remote operations may be logistically possible to implement under the U.S. regulatory framework. The final two Classes, 4 and 5, would likely be logistically difficult, if not infeasible to implement within the current U.S. physical- and cybersecurity regulatory framework. Given the results of the feasibility assessment, an example architecture is proposed for both Class 2, remote allowlisted commands, and Class 3, remote control of non-safety systems as well as security implication assessments of each architecture. These example implementations are not meant to be prescriptive in terms of how Class 2 or Class 3 remote operations should be deployed; instead, they are intended to be informative to stakeholders on how Class 2 or Class 3 could potentially be applied in order to inform their system design. An example architecture for Class 1 remote monitoring was not provided as Class 1 in already in use in U.S. nuclear operations. Example architectures for Class 4 and Class 5 were not provided due to their assessment of being likely infeasible to implement. The final contribution is an assessment of the physical- and cybersecurity implications of introducing autonomous operations into an A/SMR. What was found was that the security implications can be separated into two cases. Autonomous operations supported by SSCs located only at the reactor site, and autonomous operations supported by SSCs outside of the reactor site. For the first case, the introduction of autonomous systems will likely not change the facility’s requirement to comply with existing cyber and physical security regulation
In the last decade, 97% of the worldwide commercial nuclear reactors connected to the grid were Light Water Reactors (LWRs). LWRs are expected to stay the dominant type of nuclear reactors for the next few decades. Reliable and redundant safety systems are required in nuclear reactors to ensure safe operation and shutdown in abnormal conditions. These safety systems are actuated by the signals obtained from several sensors and instrumentation in and out of the reactor core. Research and Development (R&D) in advanced sensors and instrumentation has gained extra attention, particularly following the accident at the Three Mile Island Unit-2 (TMI-2). In LWRs, these sensors and instrumentation have shown a high level of maturity with long operating experience. Ensuring the compatibility of these sensors and instrumentation with advanced nuclear reactors (Generation IV) is necessary, particularly with the expected expansion of the nuclear industry in the next few decades. Nuclear Sensor and instrumentation technologies used in the current generation of LWRs were investigated. The compatibility of these technologies with advanced reactors was assessed by comparing the advanced reactors' environments with those of the currently operating reactors. In addition to that, the needed R&D for such technologies was highlighted. In comparison with the LWRs environment, it was shown that advanced reactor environments are expected to experience elevated temperatures, a fast neutron spectrum, and a harsh corrosion environment. It was demonstrated that R&D is required mainly for fixed in-core nuclear sensors and instrumentation, while it is not a priority for ex-core nuclear sensors and instrumentation.
Next-generation advanced reactors (ARs) incorporate enhanced safety systems, have smaller source terms, and feature compact modular designs, which should lessen their collective risk profiles. However, to fully evaluate risk, security needs to be a part of the equation. Without taking security into consideration, safety systems and components in the new ARs may be vulnerable to sabotage. These base attributes, coupled with enhanced security features specific to AR design through sound engineering and security-by-design (SeBD), should provide developers and operators with lower inherent security risk profiles. Building security early into the AR design may remove or passively secure potential critical targets from an adversary’s reach , thereby increasing overall safety and security. An integrated approach and diverse design team that includes engineering, operations, and security experts are fundamental to building security into the design without sacrificing fundamental operational efficiencies and principles. The objective of this project was to evaluate the security and safety interfaces for five classes of reactors, identify potential security vulnerabilities of structures, systems, and components (SSC), and underscore the need to consider security alongside safety in the design o f these concepts. The five reactor classes evaluated in this project and presented in this report are molten-salt reactors (MSR), high temperature gas reactors (HTGR), sodium-fast reactors (SFR), advanced light-water reactors (ALWR), and microreactors. These designs were selected because they reflect the concepts that are closest to market deployment and have received significant resource investments from the public and private sector. This project assesses the inherent security risks posed by common classes of ARs, provides a methodology and framework to assess security along with safety, and offers an analysis of potential mitigation strategies that could be incorporated. For each AR technology, the SSCs that relate to radionuclide source safety functions are discussed to understand the SSC contribution to safety and relative importance in the protective strategy for the design. The assumptions that went into evaluating each reactor concept originated from generic publicly available nonproprietary information and should not directly be used to qualify an absolute risk profile nor to rank specific AR designs. Instead, the purpose of the analysis is to understand and compare the generic inherent security risks of different AR technologies.
This code is designed to predict and analyze the decay heat generated in molten salt reactors (MSRs) using a hybrid approach that combines machine learning and segmented polynomial fitting. The accurate prediction of decay heat is essential for reactor safety and the optimization of spent fuel storage. The code operates through several key components: 1) Data Architecture: It incorporates a modular data architecture that handles various MSR-specific operational parameters such as power density, humidity content, and air ingress. These parameters are sampled using Sobol sequences to ensure comprehensive coverage of operational uncertainties. 2) Machine Learning Framework: The code employs a diverse set of machine learning models, including polynomial regression, decision trees, random forests, gradient boosting, support vector regression, k-nearest neighbors, multi-layer perceptrons, and symbolic regression. These models are trained to predict decay heat over a wide temporal range, from immediate shutdown up to 10,000 years. 3) Region-Optimized Training: The temporal domain is divided into multiple regions, each modeled separately to capture distinct decay heat characteristics across different time scales. This approach significantly improves the accuracy and interpretability of predictions. 4) Segmented Polynomial Interpretation (SPI): The SPI method translates machine learning predictions into piecewise polynomial equations. These equations are physically interpretable and can be directly integrated into existing engineering workflows and safety analyses. 5) Front-End Interfaces: The code includes both a Jupyter notebook interface for research development and a Streamlit web application for operational deployment. These interfaces allow users to interactively explore decay heat predictions, adjust operational parameters, and visualize results in real-time. 6) Applications: The framework supports various applications, including safety system validation and spent fuel container optimization. It enables real-time evaluation of worst-case decay heat scenarios, informing the design of passive safety systems and optimizing container designs for long-term storage. Overall, this code provides a robust, accurate, and user-friendly tool for predicting decay heat in MSRs, enhancing reactor safety, and optimizing spent fuel management.