Physical and Statistical Models for Steam Generator Clogging Diagnosis (SpringerBriefs in Applied Sciences and Technology) - Softcover

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Dr. Sylvain Girard current research interests are uncertainty analysis and dimension reduction applied to models of complex industrial and environmental systems. Since 2013, he has been working on the characterisation of uncertainties of radionuclides atmospheric dispersion models for the Institut de radioprotection et de sûreté nucléaire (IRSN).

Dr. Girard investigated nuclear steam generators clogging during his PhD at Électricité de France (EDF, the french electricity company and a leader in nuclear engineering worldwide) under the direction of Pr. Hans Wackernagel at École des Mines Paris Tech. He elaborated a new methodology for clogging diagnosis coupling physical and statistical modelling.

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Clogging of steam generators in nuclear power plants is a highly sensitive issue in terms of performance and safety, and this book proposes a completely novel methodology for diagnosing this phenomenon. It demonstrates real-life industrial applications of this approach to French steam generators, and applies the approach to operational data gathered from French nuclear power plants. The book presents a detailed review of in situ diagnosis techniques, and assesses existing methodologies for clogging diagnosis, whilst examining their limitations. It also addresses numerical modelling of the dynamic behaviour of steam generators and provides a thorough analysis of statistical methods for sensitivity analysis and dimension reduction. Steam generators are heat exchangers found in nuclear power plants, and over time they become increasingly clogged by iron oxides. This clogging then hampers the flow inside steam generators and compromises their mechanical integrity, which hinders performance and safety. This book is intended for nuclear safety specialists, nuclear performance engineers, and researchers and postgraduates students working on heat exchanger modeling and computational engineering.