Exploring risk analysis using quantum algorithms

par Ahmed Zaiou

Projet de thèse en Doctorat informatique

Sous la direction de Basarab Matei.

Thèses en préparation à Paris 13 , dans le cadre de École doctorale Galilée (Villetaneuse, Seine-Saint-Denis) depuis le 28-01-2020 .


  • Résumé

    The march 11 Fukushima accident revealed to the nuclear safety community and particularly to Probabilistic Safety Assessment practitioners a number of new challenges and issues that have to be considered to ensure/enhance safety of nuclear power plants regarding events that may seem extremely rare and others that we have to imagine and expect. The different deterministic and probabilistic approaches commonly and widely adopted have to be revisited to comply with the reality of our world, its spectacular accidents, the learned lessons from Fukushima catastrophe, and more generally with the Great Acceleration 1 and its numerous consequences. Safety assessment of nuclear power plants is a problem with many complexity issues due to many aspects (nature of the systems at hand with their technical and socio-organizational dimensions, complexity of the models underlying the different representations of the system and its dynamics, cultural change and digital revolution2 . . . ). It is time to consider our tools and the way we are framing conceptually and cognitively probabilistic safety assessment problems. This has a huge impact on the way we are solving them .It is pointed out a number of lessons from the Robinson event (March 28, 2010). Some of these issues is related to the way Reality happens in detail ! Many limitations are related to the safety mesures and the quantitative aspect (the P in PRA) that makes PRA a number-driven discipline. This is mainly due to the common confusion between a bet and an exposure (a bet is a binary outcome, an exposure has more nuanced results and depends on full distribution) . Therefore, we have to answer or at least to set the following questions: • Do our models represent the reality of our systems and their life in a changing environment (cultural, human, climate, . . . )? • Could we comply with these complexity questions and lead to appropriate models that may serve for decision processes in operational times and ...


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