Assimilation de Données et Mesures Primaires REP

Abstract : A Pressurized Water Reactor (PWR) Reactor Coolant System (RCS) is a highly complex physical process: heterogeneous power, flow and temperature distributions are difficult to be accurately measured, since instrumentations are limited in number, thus leading to the relevant safety and protection margins. EDF R&D is seeking to assess the potential benefits of applying Data Assimilation to a PWR's RCS (Reactor Coolant System) measurements, in order to improve the estimators for parameters of a reactor's operating setpoint, i.e. improving accuracy and reducing uncertainties and biases of measured RCS parameters. In this thesis, we define a 0D semi-empirical model for RCS, satisfying the description level usually chosen by plant operators, and construct a Monte-Carlo Method (inspired from Ensemble Methods) in order to use this model with Data Assimilation tools. We apply this method on simulated data in order to assess the reduction of uncertainties on key parameters: results are beyond expectations, however strong hypotheses are required, implying a careful preprocessing of input data.
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https://pastel.archives-ouvertes.fr/tel-01214018
Contributor : Thibaud Mercier <>
Submitted on : Friday, October 9, 2015 - 3:46:08 PM
Last modification on : Wednesday, March 27, 2019 - 4:08:31 PM
Long-term archiving on : Sunday, January 10, 2016 - 10:30:43 AM

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  • HAL Id : tel-01214018, version 1

Citation

Thibaud Mercier. Assimilation de Données et Mesures Primaires REP. Applications [stat.AP]. Ecole polytechnique X, 2015. Français. ⟨tel-01214018⟩

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