Uncertainty Modelling, Data Assimilation and Decision Support for Management of Off-Site Nuclear Emergencies

French, Simon

doi:10.1093/oxfordjournals.rpd.a032110

Cited by 7 publications

(4 citation statements)

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“…Data from NPPs can be categorized into two types: static and dynamic. Within the emergency decision support system of an NPP, the following data require monitoring, as highlighted by French et al [145]: (a) plant status data, which encompasses the readings from various sensors within the facility, such as temperature, pressure, humidity, and radiation monitoring; (b) current and predicted meteorological information; (c) on-site stack and periphery monitoring data, which include off-site fixed and mobile data; (d) hydrological data, which pertain to flow rates, depths, and contamination levels; (e) population data, detailing the demographics of those potentially exposed to risks, such as villages, towns, and cities around the site [146]; (f) agricultural, economic, and land use data; and (g) data concerning the adherence to and effectiveness of implemented countermeasures. It is worth noting that meteorological data used in simulations usually come from two sources, the European Centre for Medium-Range Weather Forecasts (ECMWF) and the National Centers for Environmental Prediction (NCEP).…”

Section: Monitoring and Detectionmentioning

confidence: 99%

Emergency Decision Support Techniques for Nuclear Power Plants: Current State, Challenges, and Future Trends

Xiao,

Liang,

Tong

et al. 2024

Energies

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Emergency decision support techniques play an important role in complex and safety-critical systems such as nuclear power plants (NPPs). Emergency decision-making is not a single method but a framework comprising a combination of various technologies. This paper presents a review of various methods for emergency decision support systems in NPPs. We first discuss the theoretical foundations of nuclear power plant emergency decision support technologies. Based on this exposition, the key technologies of emergency decision support systems in NPPs are presented, including training operators in emergency management, risk assessment, fault detection and diagnosis, multi-criteria decision support, and accident consequence assessment. The principles, application, and comparative analysis of these methods are systematically described. Additionally, we present an overview of emergency decision support systems in NPPs across different countries and feature profiles of prominent systems like the Real-Time Online Decision Support System for Nuclear Emergencies (RODOS), the Accident Reporting and Guiding Operational System (ARGOS), and the Decision Support Tool for Severe Accidents (Severa). Then, the existing challenges and issues in this field are summarized, including the need for better integration of risk assessment, methods to enhance education and training, the acceleration of simulation calculations, the application of large language models, and international cooperation. Finally, we propose a new decision support system that integrates Level 1, 2, and 3 probabilistic safety assessment for emergency management in NPPs.

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Section: Monitoring and Detectionmentioning

confidence: 99%

Emergency Decision Support Techniques for Nuclear Power Plants: Current State, Challenges, and Future Trends

Xiao,

Liang,

Tong

et al. 2024

Energies

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“…The range of uncertainties that need be considered has been in focus for decades (French, 1997), but until recently in developing tools and procedures for nuclear emergencies, they have not been addressed in a comprehensive sense. Indeed, current decision procedures tend to ignore uncertainties and focus on an expected or reasonable worst case (French et al, 2016).…”

Section: Uncertainties In Nuclear Emergency Managementmentioning

confidence: 99%

“…In short, many uncertainties need to be addressed in the decision making. This paper builds on existing literature on uncertainty types (French, 1997;Snowden, 2002;Walker et al, 2003), and discusses various forms of uncertainty, how they arise and how we might analyse them in the context of emergency management. Examples from CONFIDENCE work are included as to contextualise the challenges and possible approaches to addressing different uncertainty types.…”

Section: Introductionmentioning

confidence: 99%

Different types of uncertainty in nuclear emergency management

et al. 2020

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The objective of the CONFIDENCE project has been to identify, assess and communicate the uncertainties that arise in managing and recovering from a nuclear accident. To do that, it is important to be clear on what uncertainty means, how it arises and how we might analyse it. In fact, there are many forms of uncertainty, some of which we can assess with current tools, but some of which are more nebulous and difficult to deal with. Nonetheless, all need to be communicated to the emergency managers. Starting with a review of different categories of uncertainties, and using examples from the CONFIDENCE project, this paper discusses how the various uncertainties are manifested in nuclear emergency management. It concludes with a simple framework for categorising and analysing them. The overall intention is that such a framework could contribute to a broader discussion on identifying and handling uncertainties with nuclear emergency management actors

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“…All have at their heart complicated quantitative consequence models: for examples of such models, see (Chan et al, 1998). Such models are too detailed, confusing requisite modelling for prediction and decision support with more comprehensive modelling needed for explanatory and confirmatory science (French, 1997;French and Rios Insua, 2000;Phillips, 1982). Moreover, the inherent uncertainty inherent in such models is often grossly underestimated and poorly represented (Goossens and Kelly, 2000).…”

Section: Models Conflict and Uncertaintymentioning

confidence: 99%

Believe in the Model: Mishandle the Emergency

French¹,

Niculae²

2005

Journal of Homeland Security and Emergency Management

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You can hardly tell where the computer models finish and the dinosaurs begin." Laura Dern, on the film Jurassic Park During the past quarter century there have been many developments in scientific models and computer codes to help predict the ongoing consequences in the aftermath of many types of emergency: e.g. storms and flooding, chemical and nuclear accident, epidemics such as SARS and terrorist attack. Some of these models relate to the immediate events and can help in managing the emergency; others predict longer term impacts and thus can help shape the strategy for the return to normality. But there are many pitfalls in the way of using these models effectively. Firstly, nonscientists and, sadly, many scientists believe in the models' predictions too much. The inherent uncertainties in the models are underestimated; sometimes almost unacknowledged. This means that initial strategies may later need to be revised in ways that unsettle the public, losing their trust in the emergency management process. Secondly, the output from these models form an extremely valuable input to the decision making process; but only one such input. There is a need to draw on much tacit knowledge which by definition cannot reside in a decision support system. Most emergencies are events that have huge social and economic impacts alongside the health and environmental consequences. While we can model the latter passably well, we are not so good at modelling economic impacts and very poor at modelling social impacts. Our knowledge of them is tacit and they lie in the complex space of Snowden's Cynefin categorisation of decision contexts. Thus we draw upon recent thinking in both decision support and knowledge management systems to suggest that we need a more socio-technical approach to developing crisis response system; and, in particular, we explore how model predictions should be drawn into emergency management processes in more balanced ways than often has occurred in the past.

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Uncertainty Modelling, Data Assimilation and Decision Support for Management of Off-Site Nuclear Emergencies

Cited by 7 publications

References 0 publications

Emergency Decision Support Techniques for Nuclear Power Plants: Current State, Challenges, and Future Trends

Emergency Decision Support Techniques for Nuclear Power Plants: Current State, Challenges, and Future Trends

Different types of uncertainty in nuclear emergency management

Believe in the Model: Mishandle the Emergency

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