I have read that there is a common approach to start developing a Risk Management Plan in nuclear plant projects, which is a Probabilistic Risk Assessment (PRA). Investigating, I found that a PRA identifies and evaluates what experts think are the most important risks. Sophisticated methods as Markov Chains and Bayesians Inferences are useful to make a precise probabilistic analysis. This quantitative analysis is founded on a good identification stage. What if the experts identify a poor percentage of risk sources?. What have we learned about risk identification at 9/11?. We make a good manage of known risks but sometimes a poor manage of unknown risks.
I have heard that nuclear power plant design strategy for preventing accidents and mitigating their potential effects is "defense in depth". It means that if something fails, there is a back-up system to limit the harm done, if this back-up system also fail, there is another back-up system for it, and so on. It's what we are seeing in the Fukushima Dai-ichi power plant. We haven’t seen a full meltdown yet, but we have known about the discharge of over 10,000 metric tons of low-level radioactive water into the ocean, what in risk management is called a secondary risk.
I don’t want to be a strong critic of efforts that are beyond my capabilities. I hope this could end well for that people. Probably, nobody can do more than Tokyo Electric Power Co (Tepco) in current circumstances. But what we can do is to learn. Even more important than a good quantitative analysis in a PRA is the Risks Identification Stage. We are using experience and imagination to face this problem. I propose to create models, algebras and discover what is not obvious. Computer science could help us to explore possibilities with inference engines or can help us in solving big equations. We don’t have better tools to deal with what we don’t know. Using experiences is not a solution when we are working with so many new technologies and new possibilities.