Nuclear systems initiative: implementing a managed approach to risk communication
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Microreactors are a subset of advanced nuclear reactors that can be factory fabricated, transportable, and self-regulating. They have the potential to be used in microgrids, rural and remote areas, or emergency response applications, replacing fossil fuel sources like diesel generators and enabling sustainable energy generation. In order to make microreactor operation cost-effective, it is likely that remote communications will be needed to reduce the number of personnel required to be on site. While remote operation of energy generation and other industrial control systems is common in other industries, it is not yet adopted in the nuclear community and has many perceived and actual risks. In this paper, the severity of the risks introduced by remote operations for microreactors are explored. The primary changes in the operations involve the addition of a remote communications network and a certification system for data and controls. These changes lend themselves to considerations of cyber risks, whether unintentional or adversarial, but the assessment considers not just cyber risks introduced, but also how physical and human factors-based risks will impact the remote operations system and change the overall risk profile. This initial assessment indicates that there are standard cyber and mitigation measures that can be put in place so the risk of doing remote operations does not dramatically increase compared to local operations. This evaluation is a critical step in the process of evaluating if remote operations of microreactors is a suitable solution to meet future sustainable grid needs
RAVEN is a generic software framework to perform parametric and probabilistic analysis based on the response of complex system codes. The initial development was aimed to provide dynamic risk analysis capabilities to the Thermo-Hydraulic code RELAP-7, currently under development at the Idaho National Laboratory (INL). Although the initial goal has been fully accomplished, RAVEN is now a multi-purpose probabilistic and uncertainty quantification platform, capable to agnostically communicate with any system code. This agnosticism includes providing Application Programming Interfaces (APIs). These APIs are used to allow RAVEN to interact with any code as long as all the parameters that need to be perturbed are accessible by inputs files or via python interfaces. RAVEN is capable of investigating the system response, and investigating the input space using Monte Carlo, Grid, or Latin Hyper Cube sampling schemes, but its strength is focused to- ward system feature discovery, such as limit surfaces, separating regions of the input space leading to system failure, using dynamic supervised learning techniques. The development of RAVEN has started in 2012, when, within the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program, the need to provide a modern risk evaluation framework became stronger. RAVEN principal assignment is to provide the necessary software and algorithms in order to employ the concept developed by the Risk Informed Safety Margin Characterization (RISMC) program. RISMC is one of the pathways defined within the Light Water Reactor Sustainability (LWRS) program. In the RISMC approach, the goal is not just the individuation of the frequency of an event potentially leading to a system failure, but the closeness (or not) to key safety-related events. Hence, the approach is interested in identifying and increasing the safety margins related to those events. A safety margin is a numerical value quantifying the probability that a safety metric (e.g. for an important process such as peak pressure in a pipe) is exceeded under certain conditions. The initial development of RAVEN has been focused on providing dynamic risk assessment capability to RELAP-7, currently under development at the INL and, likely, future replacement of the RELAP5-3D code. Most the capabilities that have been implemented having RELAP-7 as principal focus are easily deployable for other system codes. For this reason, several side activates are currently ongoing for coupling RAVEN with soft- ware such as RELAP5-3D, etc. The aim of this document is the explanation of the input requirements, focalizing on the input structure.
RAVEN is a software framework able to perform parametric and stochastic analysis based on the response of complex system codes. The initial development was aimed at providing dynamic risk analysis capabilities to the thermohydraulic code RELAP-7, currently under development at Idaho National Laboratory (INL). Although the initial goal has been fully accomplished, RAVEN is now a multi-purpose stochastic and uncertainty quantification platform, capable of communicating with any system code. In fact, the provided Application Programming Interfaces (APIs) allow RAVEN to interact with any code as long as all the parameters that need to be perturbed are accessible by input files or via python interfaces. RAVEN is capable of investigating system response and explore input space using various sampling schemes such as Monte Carlo, grid, or Latin hypercube. However, RAVEN strength lies in its system feature discovery capabilities such as: constructing limit surfaces, separating regions of the input space leading to system failure, and using dynamic supervised learning techniques. The development of RAVEN started in 2012 when, within the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program, the need to provide a modern risk evaluation framework arose. RAVEN’s principal assignment is to provide the necessary software and algorithms in order to employ the concepts developed by the Risk Informed Safety Margin Characterization (RISMC) program. RISMC is one of the pathways defined within the Light Water Reactor Sustainability (LWRS) program. In the RISMC approach, the goal is not just to identify the frequency of an event potentially leading to a system failure, but the proximity (or lack thereof) to key safety-related events. Hence, the approach is interested in identifying and increasing the safety margins related to those events. A safety margin is a numerical value quantifying the probability that a safety metric (e.g. peak pressure in a pipe) is exceeded under certain conditions. Most of the capabilities, implemented having RELAP-7 as a principal focus, are easily deployable to other system codes. For this reason, several side activates have been employed (e.g. RELAP5-3D, any MOOSE-based App, etc.) or are currently ongoing for coupling RAVEN with several different software. The aim of this document is to provide a set of commented examples that can help the user to become familiar with the RAVEN code usage.
Integrated energy systems (IES) combine, in mutually beneficial ways, power from variable renewable energy sources and nuclear power plants (NPP) to improve economic viability under uncertain market and weather conditions. The open-source Framework for Optimization of Resources and Economics (FORCE) tool suite, developed at Idaho National Laboratory (INL), has enabled comprehensive modeling and simulation of IES. The capabilities within FORCE include grid portfolio optimization through the Holistic Energy Resource Optimization Network (HERON) and the transient process model analysis library HYBRID, among others. Continuous efforts and investments from the IES programs have been made to expand and improve the versatility of the FORCE toolset in fiscal year 2022. Code-coupling and cross-tool communication have been important methods for improving this versatility. This report focuses on an additional workflow in the HERON tool for capacity and dispatch stochastic optimization through integration with the external tool Design Integration and Synthesis Platform to Advance Tightly Coupled Hybrid Energy Systems (DISPATCHES). DISPATCHES was primarily developed by the National Energy Technology Laboratory, in collaboration with other national laboratories, which included INL, universities, and industry partners. It is coupled to a library of algebraic models for specific plant components, and to a framework for stochastic optimization different from that provided in the current Risk Analysis Virtual Environment (RAVEN)-running-RAVEN algorithm in HERON. HERON currently conducts stochastic optimization via an outer-inner loop: it optimizes over variable capacity on the outer loop, and at each step within the capacity parameter space, conducts an inner optimization over scenarios (of market signals, demand, and/or weather patterns) and hourly dispatch throughout a user-specified number of years. On the other hand, DISPATCHES conducts stochastic optimization via an “all-at-once” strategy in which capacity variables are optimized at the same level as dispatch variables, as all scenarios are considered at once. The latter method works especially well for projects of limited size and project length, as the necessary computational power and memory increases with the number of variables and scenarios. The new capability to use the DISPATCHES workflow in HERON enhances standalone simulations by leveraging FORCE tools—namely, the economic metrics from the Tool for Economic Analysis (TEAL) and reduced-order model (ROM) sampling from RAVEN. The initial demonstration of the DISPATCHES workflow simulates an existing nuclear-case flowsheet within the DISPATCHES repository—this models a NPP with a secondary revenue stream for hydrogen production. Electrical output from the plant is converted to hydrogen via a proton-exchange membrane (PEM) electrolyzer, hydrogen tanks are used for storage, and an additional turbine is added for hydrogen combustion. Continued work regarding this FORCE-DISPATCHES integration will include automatic generation of DISPATCHES models from HERON inputs, offering analysts the option of using either the RAVEN-runsRAVEN or DISPATCHES workflow to solve technoeconomic optimization problems.
One nuclear electric propulsion (NEP) reactor systems under consideration is a hydride moderated thermal spectrum reactor fueled by high assay low enriched uranium (HALEU). While such a reactor is expected to yield the lightest HALEU reactor design, its development challenges grow exponentially with increasing mission demands, most notably power output, specific weight of the overall system (which may require operation at temperatures exceeding 1200 K), service lifetime, and human-rated reliability. Two of the greatest cost drivers are full-powered nuclear demonstrations and extensive material development campaigns, so it is important to consider options that can minimize the need for or complexity of such tasks. This paper discusses a structured framework being developed for assessing how NEP design choices, such as materials selection, neutronic features, and heat-removal technologies, can translate into project risk and how project performance goals can be traded with development cost.Reactors operating at high temperatures often require cutting-edge heat transfer technologies and creep-resistant materials. Use of new materials in high temperature reactors brings additional complication beyond those common to any new space materials development campaign. For example, such materials may not possess necessary neutronic cross-sectional or neutronic irradiation data. Similarly, use of new materials may significantly influence core neutronics; in some extreme cases, neutronic reactivity feed-back of certain new materials can vary during their service life as radiation damage impacts the scattering cross-section. In an affordable development approach, high fidelity modeling and simulation tools are used to identify and characterize potential ‘knees-in-the-curves’ in the relationship that exists between the mission characteristics and the project risk. Of particular significance is use of modern uncertainty management and variance reduction methods to perform gap analyses that feed into phenomena identification and ranking tables (PIRT) commonly used to communicate nuclear readiness levels. Model-based measurements techniques are used to design sub-scale experiments as a substitute to minimize orcompletely eliminate the need for nuclear demonstrations.This paper will describe the approach and present preliminary results. It will lay the groundwork for developing a set of metrics that can be broadly characterized as system nuclear readiness levels and advancement degree of difficulty for nuclear systems. Equally importantly, a goal of this paper is to initiate a dialogue among stakeholders on what is the sufficient level of maturity that is required for launching a demonstration unit.
There are clear advantages of development of a Nuclear Thermal Rocket (NTR) for a crewed mission to Mars. NTR for in-space propulsion enables more ambitious space missions by providing high thrust at high specific impulse (approximately 900 sec) that is 2 times the best theoretical performance possible for chemical rockets. Missions can be optimized for maximum payload capability to take more payload with reduced total mass to orbit; saving cost on reduction of the number of launch vehicles needed. Or missions can be optimized to minimize trip time significantly to reduce the deep space radiation exposure to the crew. NTR propulsion technology is a game changer for space exploration. However, "NUCLEAR" is a word that is feared and vilified by some groups and the hostility towards development of any nuclear systems can meet great opposition by the public as well as from national leaders and people in authority. Communication of nuclear safety will be critical to the success of the development of the NTR. Why is there a fear of nuclear? A bomb that can level a city is a scary weapon. The first and only times the Nuclear Bomb was used in a war was on Hiroshima and Nagasaki during World War 2. The "Little Boy" atomic bomb was dropped on Hiroshima on August 6, 1945 and the "Fat Man" on Nagasaki 3 days later on August 9th. Within the first 4 months of bombings, 90- 166 thousand people died in Hiroshima and 60-80 thousand died in Nagasaki. It is important to note for comparison that over 500 thousand people died and 5 million made homeless due to strategic bombing (approximately 150 thousand tons) of Japanese cities and war assets with conventional non-nuclear weapons between 1942- 1945. A major bombing campaign of "firebombing" of Tokyo called "Operation Meetinghouse" on March 9 and 10 consisting of 334 B-29's dropped approximately1,700 tons of bombs around 16 square mile area and over 100 thousand people have been estimated to have died. The declaration of death is very clear for conventional weapons and then the declaration of death due to radiation becomes vague and unclear. This may have been due to people mis-understanding the dangers and effects of radiation when assessing the damage and harm to people initially, but it is also become insidious when expressing opposition to nuclear energy. A nuclear radiation accident can be scary due to the power involved and the fear of radiation release. The International Atomic Energy Agency defines a nuclear and radiation accident a "an event that has led to significant consequences to people, the environment or the facility." There have been 3 commercial nuclear reactor accidents (Chernobyl, Three Mile Island, and Fukushima) that stand out to the public and much of the information about the result and impact to workers, environment, and public can be misleading. Often information is presented without clear correlation with radiation and other pertinent information is left out presenting a very scary situation to affect the emotions of the reader. A very boring but "critically acclaimed" movie was made in 1979 called "The China Syndrome" starring Jane Fonda and Jack Lemmon. The film was released on March 16, 1979, 12 days before the 3-Mile Island nuclear accident in Pennsylvania. The basis from the movie was from a few nuclear plant incidents and in particular, the Brown's Ferry Alabama Power Plant fire. In one scene from the movie, a physicist Dr. Elliott Lowell played by Donald Hotton states that a China Syndrome event would make "an area the size of Pennsylvania" permanently uninhabitable. Real serious nuclear incidents like Chernobyl and Fukushima are often sited to make people fear the consequences of using nuclear power. However, the consequences are at best poorly communicated and at worst fictitiously inflated to instigate social unrest against nuclear power. There is an article being circulated on Facebook with a title "28 Signs that the (US) West Coast is being absolutely fried with nuclear radiation from Fukushima" which focus on mis-information and fear mongering. Nuclear power and NTR are powerful resources that can open many doors for future prosperity and capability. With great power comes great responsibility. Radiation and its effects need to be better understood, quantified, and communicated. A human mission to mars has its own risks of deep space radiation and is considered a considerable risk at 400 milli-Sieverts per year in deep space and 245 milli-Sieverts per year on the surface of Mars as measured by the Mars Curiosity mission. Although these quantities of ionizing radiation are within the astronaut career limit, it exceeds the yearly average amounts of ionizing radiation. Astronaut crews have experienced these levels of radiation before, but for durations shorter than a year, and a mission to Mars could possibly be 3 years in length. There is also evidence that people can comfortably handle higher levels of ionizing radiation where the radiation occurs naturally like Ramsar, Iran when people can experience 270 milli-Sieverts per year. A risk posture that the development, test, and flight of an NTR will meet opposition from groups who oppose nuclear energy must be likely and the impact can be sever to the effort. Active risk mitigation must be taken for an NTR full-scale development project. The NTR design must take into account safety for transport and off nominal conditions. Nuclear fuel element must consider containment of fission products and Low Enriched Uranium (LEU) that may meet less opposition should be considered for safety and security reasons. Even though testing was conducted on Rover/NERVA safely and successfully in the 60's with exhaust sent heavenward in to open air, modern testing of NTR must consider full containment and no release of ionizing radiation to the public and must meet the current requirement of no more than 0.1 milli-Sieverts per year to the public. 0.1 milli-Sieverts is equivalent to eating one banana or a 20 hour plane flight. Good communication with the public and regulatory agencies will be essential to show that all effort is applied toward protection to the public and astronauts. The inspiring endeavor to put humans on Mars to study the planet, search for life, and learn more about this Solar System will be full of risks but it will be worth it. NTR will be worth the development effort if it allows humans to explore our Solar System.
This report is an update to a prior report that describes progress and findings for a program of research supporting the design and optimization of information automation systems for nuclear power plants. Much of the domestic nuclear fleet is currently focused on modernizing technologies and processes, including transitioning toward digitalization in the control room and throughout the plant, along with a greater interest in the use of automation, artificial intelligence, robotics, and other emerging technologies. While there are significant opportunities to apply these technologies toward greater plant safety, efficiency, and overall cost-effectiveness, optimizing their design and avoiding potential safety and performance risks depends on ensuring that human performance-related organizational and technical design issues are identified and addressed early in the design process. This report describes modeling tools and techniques, based on sociotechnical systems theory, to support these design goals and their application in the current research effort. The report is primarily intended for senior nuclear energy stakeholders, including regulators, corporate management, and senior plant management. We have developed and employed a method to design an optimized information automation ecosystem (IAE) based on the systems-theoretic constructs underlying sociotechnical systems theory in general and the Systems-Theoretic Accident Modeling and Processes (STAMP) approach in particular. We argue that an IAE can be modeled as an interactive information control system whose behavior can be understood in terms of dynamic control, feedback, and communication relationships amongst the system’s technical and organizational components. We have employed two STAMP-based tools in this effort. The first is Causal Analysis based on STAMP (CAST), an accident and incident analysis technique that was used to examine a performance- and safety-related incident at an industry partner’s plant involving the unintentional activation of an emergency diesel generator. This analysis provided insight into the behavior of the plant’s current information control structure within the context of a specific, significant event. The second tool is Systems Theoretic Process Analysis (STPA) which is a proactive risk analysis tool used to examine existing and potential, planned sociotechnical systems. STPA was used to identify risk factors in the current design of a generic nuclear power plant (NPP) preventive maintenance system. Our analyses focused on identifying near-term system improvements and longer-term design requirements for an optimized IAE system. CAST analysis findings indicate an important underlying contributor to the incident under investigation, and a significant risk to information automation system performance, was perceived time and schedule pressure, which exposed weaknesses in interdepartmental coordination between and within responsible plant organizations and challenged the resilience of established plant processes, until a human caused the eventual event. These findings are discussed in terms of their risk to overall system performance and their implications for information automation system resilience and brittleness. STPA findings exposed several areas of concern in the design of current preventive maintenance systems. We also present two preliminary information automation models. The proactive issue resolution (PIR) model is a test case of an information automation concept with significant near-term potential for application and subsequent reduction in significant plant events. The IAE model is a more general representation of a broader, plantwide information automation system and represents an end-state vision for our work. From our results, we have generated an initial set of preliminary system-level requirements and safety constraints for these models. We have also focused on early development of easy to learn, easy to use “transportable” tools for sociotechnical systems analysis. We intend these to be used by NPP personnel as a means of gaining reliable and relatively quick insight into (1) sociotechnical systems factors impacting incidents and accidents, (2) potential sociotechnical risk factors in existing or planned system designs, and (3) potential weaknesses in a system’s safety and/or information control structure. We conclude the report with a set of summary recommendations, a discussion of planned and potential follow-on research and development, and a draft list of system-level requirements and safety constraints for optimized information automation systems.