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Preliminary Risk assessment of ex-vessle debris bed coolability for a Nordic BWR
KTH, School of Engineering Sciences (SCI), Physics, Nuclear Power Safety.ORCID iD: 0000-0002-9123-2944
KTH, School of Engineering Sciences (SCI), Physics, Nuclear Power Safety.ORCID iD: 0000-0002-2725-0558
KTH, School of Engineering Sciences (SCI), Physics, Nuclear Power Safety.ORCID iD: 0000-0002-0683-9136
(English)In: Nuclear Engineering and Design, ISSN 0029-5493, E-ISSN 1872-759XArticle in journal (Refereed) Submitted
Abstract [en]

In Nordic design of boiling water reactors (BWRs) a deep water pool under the reactor vessel is employed as a severe accident management strategy for the core melt fragmentation and the long term cooling of corium debris. The height and shape of the debris bed are among the most important factors that determine if decay heat can be removed from the porous debris bed by natural circulation of water. The debris bed geometry is formed as a result of melt release, fragmentation, sedimentation and settlement on the containment basemat. After settlement, the shape can change with time due to movement of particles promoted by the coolant flow (debris bed self-leveling process). Both aleatory (accident scenario, stochastic) and epistemic (modeling, lack of knowledge) uncertainties are important for assessing the risks.

 

The present work describes a preliminary risk analysis of debris bed coolability for Nordic BWRs under severe accident conditions. It was assumed that once debris remelting starts containment failure becomes imminent. Such assumption allows to estimate the containment failure probability by calculating the probability that the time necessary for the spreading debris bed to achieve a coolable configuration will be shorter than the onset time of debris bed re-melting. An artificial neural network was employed as a surrogate model (SM) for the mechanistic full model (FM) of the debris spreading in order to achieve computationally efficient propagation of uncertainties. The effect of uncertainty in the ranges and probability density functions (PDFs) of the input parameters was addressed. Parameters defining shapes of the PDFs were varied for three different distribution families (beta, truncated normal and triangular). The results of the risk analysis were reported as complementary cumulative distribution functions (CCDFs) of the conditional containment failure probability (CCFP). It is demonstrated that CCFP can vary in wide ranges depending on the randomly selected combinations of the PDFs of the input parameters. Given the selected ranges of the input parameters, sensitivity analyses identified: the effective particle diameter and the debris bed porosity as the largest contributors to the CCFP uncertainty. It was shown that the self-leveling phenomenon reduces sensitivity of debris coolability to the initial shape of the bed. However, the initial shape remains an important uncertainty factor for the most likely values of the particle size and porosity. Importance of the initial shape increases when the effectiveness of the self-leveling is small (e.g. in case of high initial temperature or heat up rate of the debris). Findings of this work in combination with consideration of the necessary efforts can be used for prioritization of the future research on obtaining new information on the uncertain parameters.

National Category
Energy Engineering
Identifiers
URN: urn:nbn:se:kth:diva-203134OAI: oai:DiVA.org:kth-203134DiVA: diva2:1081193
Note

QC 20170315

Available from: 2017-03-13 Created: 2017-03-13 Last updated: 2017-03-15Bibliographically approved
In thesis
1. Particulate Debris Spreading and Coolability
Open this publication in new window or tab >>Particulate Debris Spreading and Coolability
2017 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

In Nordic design of boiling water reactors, a deep water pool under the reactor vessel is employed for the core melt fragmentation and the long term cooling of decay heated corium debris in case of a severe accident. To assess the effectiveness of such accident management strategy the Risk-Oriented Accident Analysis Methodology has been proposed. The present work contributes to the further development of the methodology and is focused on the issue of ex-vessel debris coolability.

The height and shape of the porous debris bed are among the most important factors that determine if the debris can be cooled by natural circulation of water. The bed geometry is formed in the process of melt release, fragmentation, sedimentation and packing of the debris in the pool. Bed shape is affected by the coolant flow that induces movement of particles in the pool and after settling on top of the bed. The later one is called debris bed self-leveling phenomenon.

In this study, the self-leveling was investigated experimentally and analytically. Experiments were carried out in order to collect data necessary for the development of a numerical model with an empirical closure. The self-leveling model was coupled to a model for prediction of the debris bed dryout. Such coupled code allows to calculate the time necessary to have a coolable configuration of the bed. The influence of input parameters was assessed through sensitivity analysis in order to screen out the less influential parameters.

Results of the risk analysis are reported as complementary cumulative distribution functions of the conditional containment failure probability (CCFP).

Sensitivity analyses identified: effective particle diameter and debris bed porosity as the parameters that provide the largest contribution to the CCFP uncertainty. It is found that the effect of the initial maximum height of the bed on the CCFP is reduced by the self-leveling.

Abstract [sv]

Kokvattenreaktorer av nordisk typ har en djup vattenbassäng under reaktorkärlet som kan utnyttjas för att kyla härdsmältan och de fragmenterade härdresterna vid ett svårt reaktorhaveri. För att bedöma effektiviteten av en sådan haverihantering har man föreslagit användande av en riskorienterad metodik för haverianalysen (ROAAM, från engelska ”Risk-Oriented Accident Analysis Methodology”). Föreliggande projekt fokuserar på kylbarhet hos härdresterna utanför reaktortanken och bidrar till den pågående vidareutvecklingen av ROAAM till ROAAM+.

Höjden på och formen för den porösa ansamlingen av härdrester (här också kallad partikelbädd) är bland de viktigaste faktorerna som avgör om resteffekten kan kylas bort med hjälp av naturlig cirkulation av vattnet i bassängen. Ansamlingens geometriska form skapas under hela processen från utsläpp av  härdsmältan via fragmentering och sedimentering i bassängens botten. Formen kan sedan förändras med tiden genom att partiklar rör sig och omfördelas i kylflödet. Detta fenomen kallas en självnivellerande process.

I detta arbete studeras denna självnivellerande process experimentellt och analytiskt. Experimenten utfördes i en särskild experimentuppställning utformad för att att samla in data och parametrar som behövs för att simulera fenomenet och utveckla en beräkningsmodell som sluts empiriskt. Denna modell kopplades sedan till en modell för beräkning av dryout i partikelbädden. Genom denna koppling av de två beräkningsprogrammen är det är möjligt att beräkna tiden för partikelbädden att nå en kylbar konfiguration. Inverkan av variationer i modellens indata studeras med hjälp av känslighetsanalys. Härigenom identifierades de minst inflytelserika parametrarna såsom effektiv drifttid, partikeldensitet, experimentell ovisshet i de empiriska samband som används för att sluta modellen, samt omlokaliseringstid efter det att reaktorn snabbstoppats (SCRAM).  Dessa parametrar avfördes sedan från den fortsatta känslighetsanalysen.

Ett artificiellt neuralt nätverk tränades för att användas i stället för den kopplade koden och möjliggöra den beräkningseffektivitet som krävs för att studera hur osäkerheter i indata förs vidare i riskanalysen. Resultaten är presenterade i form av komplementära, kumulativa fördelningsfunktioner för den betingade sannolikheten för brott på reaktorinneslutningen (CCFP, från engelska ”conditional containment failure probability”).

Det visas att CCFP kan variera inom ett brett område beroende på de valda kombinationerna av frekvensfunktioner för ingångsparametrarna. Resultaten visar att effektiv partikeldiameter och hög porositet är de två parametrar som ger de största bidragen till osäkerheten i CCFP.

Vi har också funnit att fenomenet självnivellering har en gynnsam inverkan på CCFP och leder till lägre utsläppsrisk.

Det vore värdefullt att förfina de modeller som beskriver bildandet av den initiala partikelbädden. Detta är särskilt viktigt i de scenarier där det finns kort tid för självnivellering innan partikelbädden börjar smälta igen, dvs när man har relativt hög initial temperatur i partikelbädden och/eller hög specifik värmeeffekt.

Place, publisher, year, edition, pages
Stockholm: KTH Royal Institute of Technology, 2017. 78 p.
Series
TRITA-FYS, ISSN 0280-316X ; 2017:15
Keyword
Self-leveling, debris bed, spreading, coolability, severe accident, probabilistic framework, Monte Carlo, uncertainty, sensitivity
National Category
Other Engineering and Technologies not elsewhere specified
Research subject
Physics
Identifiers
urn:nbn:se:kth:diva-203136 (URN)978-91-7729-309-5 (ISBN)
Public defence
2017-04-18, FA31, Roslagstullsbacken 21, Stockholm, 14:00 (English)
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Note

QC 20170315

Available from: 2017-03-15 Created: 2017-03-13 Last updated: 2017-03-15Bibliographically approved

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