Physical and Statistical Models for Steam Generator Clogging Diagnosis

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...

Πλήρης περιγραφή

Λεπτομέρειες βιβλιογραφικής εγγραφής
Κύριος συγγραφέας: Girard, Sylvain (Συγγραφέας)
Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
Γλώσσα:English
Έκδοση: Cham : Springer International Publishing : Imprint: Springer, 2014.
Σειρά:SpringerBriefs in Applied Sciences and Technology,
Θέματα:
Διαθέσιμο Online:Full Text via HEAL-Link
Περιγραφή
Περίληψη: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 postgraduate students working on heat exchanger modeling and computational engineering.
Φυσική περιγραφή:IX, 97 p. 76 illus., 42 illus. in color. online resource.
ISBN:9783319093215
ISSN:2191-530X