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Structural Health Monitoring Solutions for Power Plants

Abstract : Structural health monitoring solutions gain in importance not only as part of the ageing management of nuclear power plant components but also in the context of conventional power plants and renewables such as wind power plants. Consequently, lots of operators have to deal with demanding security requirements to ensure the safe operation of power plants and to cope with plant lifetime extension (PLEX) related issues. AREVA disposes of a long tradition in the development of structural health monitoring (SHM) solutions. Nuclear and conventional power plant applications require the qualified assessment of measured thermo-mechanical loads. The methodology is transferable to mechanical loading conditions such as those of wind energy plants. The core challenge is the identification and qualified processing of realistic load-time histories. In terms of the nuclear industry, the ageing management of power plant components is nowadays a main issue for all actors: states, regulatory agencies, operators, designers or suppliants. As regards fatigue assessment of nuclear components stringent safety standards imply the consideration of new parameters in the framework of the fatigue analysis process: new design fatigue curves, consideration of environmental fatigue (EAF) parameters and stratification effects. In this general context AREVA developed the integral approach AREVA Fatigue Concept (AFC) with new tools and methods in order to live up to operators expectations: Simplified Fatigue Estimation (SFE), Fast Fatigue Evaluation (FFE) and Detailed Fatigue Check (DFC). Based on real measured thermal loads and superposed mechanical loads the Fast Fatigue Evaluation (FFE) process allows a highly automated and reliable data processing.
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Submitted on : Tuesday, July 8, 2014 - 10:08:52 AM
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  • HAL Id : hal-01020407, version 1



Benoît Jouan, Jürgen Rudolph, Steffen Bergholz. Structural Health Monitoring Solutions for Power Plants. EWSHM - 7th European Workshop on Structural Health Monitoring, IFFSTTAR, Inria, Université de Nantes, Jul 2014, Nantes, France. ⟨hal-01020407⟩



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