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Statistical Large-Break LOCA analysis for PWRs with combined ECC injection

  • G.-J. Seeberger , E.-M. Pauli , R. Trewin und L.-P. Zeisler
Veröffentlicht/Copyright: 15. April 2014
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Abstract

A statistical analysis methodology based on the code scaling, applicability and uncertainty (CSAU) evaluation approach for predicting the safety margin in case of a postulated large-break loss-of-coolant accident (LBLOCA) in a pressurized-water reactor (PWR) was developed by AREVA. All expected LBLOCA phenomena are listed in the Phenomena Identification and Ranking Table (PIRT) and are prioritized according to their importance on the figure of merit, here the fuel rod peak cladding temperature (PCT). For the high-ranked phenomena parameters are identified, which allow a quantification of the analysis uncertainty. AREVA has updated the PIRT to the state of the art and extended it to the application to pressurized-water reactors with combined emergency core cooling injection of German-type PWRs. This paper describes how the uncertainty distributions, required for a statistical analysis, have been derived and presents the result of an exemplary statistical analysis for a German-type 4-loop plant compared to that of a conservative deterministic analysis.

Kurzfassung

Von AREVA wurde eine statistische Analysemethode auf Basis der Code Scaling, Applicability and Uncertainty (CSAU) Methode zur Bewertung der Auswirkungen eines postulierten großen Lecks im Primärsystem eines Druckwasserreaktors auf die Anlagensicherheit entwickelt. Alle im Störfall erwarteten Phänomene werden in einer Phenomena Identification and Ranking Table (PIRT) aufgeführt und entsprechend ihres Einflusses auf das Nachweisziel (maximale Brennstabhüllrohrtemperatur) eingestuft. Den wichtigen Phänomenen werden Parameter zugeordnet, die es erlauben, die Analyseunsicherheit zu quantifizieren. Die PIRT wurde von AREVA an den Stand von Wissenschaft und Technik angepasst und auf Anlagen mit kombinierter Notkühleinspeisung erweitert. Dieses Papier erläutert die Ermittlung der für die statistische Analyse benötigten Verteilungsfunktionen und zeigt das Ergebnis einer beispielhaften Analyse für eine deutsche 4-loop-Anlage im Vergleich mit dem Ergebnis einer konservativen deterministischen Analyse.

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Received: 2013-08-01
Published Online: 2014-04-15
Published in Print: 2014-04-28

© 2014, Carl Hanser Verlag, München

Heruntergeladen am 26.10.2025 von https://www.degruyterbrill.com/document/doi/10.3139/124.110393/html?lang=de
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