The three major accidents seen by our industry – Fukushima in 2011, Chernobyl in 1986, and Three Mile Island in 1979 – are, as we are all aware, extremely important sources of lessons learned. These lessons have not only included how to improve on safety design and risk assessment, but also enhanced the defence in depth concept, all the way to enhanced emergency preparedness and response (EP&R) protocols.
The IAEA safety standards clearly point out the importance of being able to classify emergencies and define intervention levels based on observed conditions, but does this mean that all safety assessments performed prior to an incident need to go out the window during the event, or can we still make use of their information? In other words, how much of the vast amounts of information produced by safety assessments made in the “normal situation” can be put to efficient use in EP&R and how much will be thrown away, e.g. due to organizational or regulatory requirements or simply lack of time and resources in an accident situation?
Both the Fukushima and Three Mile Island accidents act as reminders that vital information needed to implement emergency protocols isn’t always available in time to take preventative action in the midst of an event. In practice, this may come down to unforeseen events or sudden situational changes as well as to inaccuracies within a site’s initial safety assessment, under ‘normal’ working conditions. As the investigation report into the Three Mile Island incident highlighted, inadequate communication systems, coupled with data being delayed as a result of misconceptions pertaining to the site characteristics, deprived management teams of critical information which, ultimately, shaped the response to the incident.
At Fukushima, parts of the emergency response plan relied on making dose projections with a system that was unavailable due to the AC power loss. When such details are made apparent, the ability to process any available information and make a risk-informed call becomes an altogether different challenge.
Some 10 years ago, our nuclear safety & licensing team was tasked with the question of how to efficiently use the Probabilistic Risk Assessments (PRAs), also known as Probabilistic Safety Assessments (PSAs) to create a tool for source term estimation to be used during the early stages of a nuclear accident, when information can be expected to be both scarce and contradictory – a tool with low requirements on hardware to increase robustness during potentially challenging conditions.
The concept of PRAs have been increasingly and successfully implemented within the global nuclear sector since the 1970s, resulting in complex level 1 & 2 PSA models and documentation being developed for several plants, to complement the traditionally deterministic design basis. The importance of this development can be illustrated in many ways. For example, a lack of realistic estimates of frequencies of crucial events might have been one of the roots to the Fukushima accident, where assessments questioning the tsunami design basis existed long before the earthquake of 2011. These assessments did also lead to some countermeasures being implemented before the event, however these obviously did not go far enough. We can, in hindsight, take this as encouragement of a view that the safety assessments contain useful information and that we might be able to use it, should we need it.
Inspired by various research projects, we found that Bayesian Belief Networks (BBN), which are applied for decision-support in a variety of fields, may offer a means of bridging the gap between day-to-day safety assessment and emergency response. Causal relationships between factors and outcomes are already explored within the nuclear power industry, however the BBNs provide something that standard assessments of facilities typically disregard – live observations.
Furthermore, all EP&R protocols also need to take in various factors unique to a particular site, such as design specifics and the local population, so no two emergency response plans are ever the same, which requires any commercial decision-support tool to be flexible.
Our efforts led to the development of the RASTEP (Rapid Source Term Prediction) methodology, aiming to create this flexibility, at the same time being able to take already compiled information, in the form of probabilistic data and deterministic source term analyses, from the level 1 and 2 PRA and supplement it with real-time information on observed plant conditions, thereby also following along the lines of the IAEA standards.
While RASTEP has been designed to support decision-making during hopefully infrequent events, we believe that the principles of using BBNs in this way can be translated into other uses and industries, affording emergency teams or decision-makers additional insight, time and resources to make the most appropriate call for their system, with the information currently at their disposal. Information derived from a BBN may, at the very least, provide another level of robust protection against information deficiencies, protection which could be vital in scenarios where seconds matter.
The release of hazardous material from a nuclear emergency also has the potential to cross international borders. Using the RASTEP method with generic plant data to gain an early idea of the effect of different scenarios might actually be sufficiently robust to give local and national authorities the necessary insight to implement relevant protective actions, even if some of the details are unknown, or yet to be realised. Especially in countries without or with small scale nuclear power programs, the use of such tools may be fruitful.
The sharing of information regarding a nuclear incident should ideally be as instant and give the clearest picture as possible. Again, taking the Fukushima accident as example, emergency response outside of Japan, e.g. to protect own citizens abroad, showed large differences between countries, and sharing of information was limited, possibly held back by the extreme uncertainties of the situation and lack of insight in typical safety assessment results.
Finally, it is worth stressing that when available statistics and research is examined, nuclear is already a safe source of energy. Its track record of only three major incidents in 60 years is testament to the robust systems and legislation which exists throughout the sector, backed by continuous learning and improvement. With the increased focus on fossil-free energy, this is indeed not a time to relax, but rather to strengthen our designs and methods further, at the same time making full use the vast bodies of safety assessment information that have already been accumulated. We hope that our method of building such information into a BBN model for EP&R applications can serve as an interesting and inspiring example here.
The success of nuclear in mitigation of climate change and air pollution, as well as its potential to contribute to society in other sectors (hydrogen, heating, propulsion, production of medical isotopes) will be very much a question of performance and safety, both of existing and new plants. Time will tell just how far we can get here and we have both the responsibility and possibility to use the huge amounts of information already at our disposal to increase our chances here.
Vysus Group’s whitepaper, ‘Aiding decision making for accidents at nuclear power plants and wider markets’ is available for download at www.vysusgroup.com/whitepapers/the-rastep-methodology-aiding-decision-making-for-accidents-at-nuclear-power-plants-and-wider-markets.