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Particulate Debris Spreading and Coolability
KTH, School of Engineering Sciences (SCI), Physics, Nuclear Power Safety.ORCID iD: 0000-0002-9123-2944
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. , p. 78
Series
TRITA-FYS, ISSN 0280-316X ; 2017:15
Keywords [en]
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: urn:nbn:se:kth:diva-203136ISBN: 978-91-7729-309-5 (print)OAI: oai:DiVA.org:kth-203136DiVA, id: diva2:1081210
Public defence
2017-04-18, FA31, Roslagstullsbacken 21, Stockholm, 14:00 (English)
Opponent
Supervisors
Projects
APRI
Note

QC 20170315

Available from: 2017-03-15 Created: 2017-03-13 Last updated: 2017-03-15Bibliographically approved
List of papers
1. Empirical closures for particulate debris bed spreading induced by gas-liquid flow
Open this publication in new window or tab >>Empirical closures for particulate debris bed spreading induced by gas-liquid flow
2016 (English)In: Nuclear Engineering and Design, ISSN 0029-5493, E-ISSN 1872-759X, Vol. 297, p. 19-25Article in journal (Refereed) Published
Abstract [en]

Efficient removal of decay heat from the nuclear reactor core debris is paramount for termination of severe accident progression. One of the strategies is based on melt fragmentation, quenching and cooling in a deep pool of water under the reactor vessel. Geometrical configuration of the debris bed is among the important factors which determine possibility of removing the decay heat from the debris bed by natural circulation of the coolant. For instance, a tall mound-shape debris bed can be non-coolable, while the same debris can be coolable if spread uniformly. Decay heat generates a significant amount of thermal energy which goes to production of steam inside the debris bed. Two-phase flow escaping through the top layer of the bed becomes a source of mechanical energy which can move the particulate debris along the slope of the bed. The motion of the debris will lead to flattening of the bed. Such process is often called "self-leveling" phenomenon. Spreading of the debris bed by the self-leveling process can take significant time, depending on the initial debris bed configuration and other parameters. There is a competition between the time scales for reaching (i) a coolable configuration of the bed, and (ii) onset of dryout and re-melting of the debris. In the previous work we have demonstrated that the rate of particulate debris spreading is determined by local gas velocity and local slope angle of the bed. In this work we develop a scaling approach and a closure for prediction of debris spreading rate based on generalization of available experimental data. We demonstrate that introduced scaling criteria are universal for particles of different shapes and size distributions.

Place, publisher, year, edition, pages
Elsevier, 2016
National Category
Energy Engineering
Identifiers
urn:nbn:se:kth:diva-180926 (URN)10.1016/j.nucengdes.2015.10.016 (DOI)000369167700003 ()2-s2.0-84950119479 (Scopus ID)
Funder
Swedish Radiation Safety Authority
Note

QC 20160126. QC 20160304

Available from: 2016-01-26 Created: 2016-01-25 Last updated: 2017-11-30Bibliographically approved
2. The effect of self-leveling on debris bed coolability under severe accident conditions
Open this publication in new window or tab >>The effect of self-leveling on debris bed coolability under severe accident conditions
2016 (English)In: Nuclear Engineering and Design, ISSN 0029-5493, E-ISSN 1872-759X, Vol. 305, p. 246-259Article in journal (Refereed) Published
Abstract [en]

Nordic-type boiling water reactors employ melt fragmentation, quenching, and long term cooling of the debris bed in a deep pool of water under the reactor vessel as a severe accident (SA) mitigation strategy. The height and shape of the 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 depends on its formation process (melt release, fragmentation, sedimentation and settlement on the containment basemat), but it also changes with time afterwards, due to particle redistribution promoted by coolant flow (self-leveling). The ultimate goal of this work is to develop an approach to the assessment of the probability that debris in such a variable-shape bed can reach re-melting (which means failure of SA mitigation strategy), i.e. the time necessary for the slumping debris bed to reach a coolable configuration is larger than the time necessary for the debris to reach the re-melting temperature. For this purpose, previously developed models for particulate debris spreading by self-leveling and debris bed dryout are combined to assess the time necessary to reach a coolable state and evaluate its uncertainty. Sensitivity analysis was performed to screen out less important input parameters, after which Monte Carlo simulation was carried out in order to collect statistical characteristics of the coolability time. The obtained results suggest that, given the parameters ranges typical of Nordic BWR5, only a small fraction of debris beds configurations exhibits the occurrence of dryout. Of the initially non-coolable configurations, a significant portion becomes coolable due to debris bed self-leveling.

Place, publisher, year, edition, pages
Elsevier, 2016
National Category
Physical Sciences
Identifiers
urn:nbn:se:kth:diva-193436 (URN)10.1016/j.nucengdes.2016.05.020 (DOI)000383003400024 ()2-s2.0-84973925908 (Scopus ID)
Funder
Swedish Radiation Safety Authority
Note

QC 20161012

Available from: 2016-10-12 Created: 2016-10-03 Last updated: 2017-11-29Bibliographically approved
3. Effectiveness of the debris bed self-leveling under severe accident conditions
Open this publication in new window or tab >>Effectiveness of the debris bed self-leveling under severe accident conditions
2016 (English)In: Annals of Nuclear Energy, ISSN 0306-4549, E-ISSN 1873-2100, Vol. 95, p. 75-85Article in journal (Refereed) Published
Abstract [en]

Melt fragmentation, quenching and long term coolability in a deep pool of water under the reactor vessel are employed as a severe accident mitigation strategy in several designs of light water reactors. The success of such strategy is contingent upon the natural circulation effectiveness in removing the decay heat generated in the porous debris bed. The maximum height of the bed is one of the important factors which affect the debris coolability. The two-phase flow within the bed generates mechanical energy which can change the geometry of the debris bed by the "self-leveling" phenomenon. In this work.we developed an approach to modeling of the self-leveling phenomenon. Sensitivity analysis was carried out to rank the importance of the model uncertainties and uncertain input parameters i.e. the conditions of the accident scenario and the debris bed properties. The results provided some useful insights for further improvement of the model and reduction of the output uncertainties through separate-effect experimental studies. Finally, we assessed the self-leveling effectiveness, quantified its uncertainties in prototypic severe accident conditions and demonstrated that the effect of self-leveling phenomenon is robust with respect to the considered input uncertainties.

Keywords
Severe accident, Debris bed, Self-leveling, Spreading, Sensitivity analysis, Granular flow
National Category
Atom and Molecular Physics and Optics
Identifiers
urn:nbn:se:kth:diva-190636 (URN)10.1016/j.anucene.2016.04.048 (DOI)000379369100009 ()2-s2.0-84969567863 (Scopus ID)
Note

QC 20160818

Available from: 2016-08-18 Created: 2016-08-12 Last updated: 2017-11-28Bibliographically approved
4. Preliminary Risk assessment of ex-vessle debris bed coolability for a Nordic BWR
Open this publication in new window or tab >>Preliminary Risk assessment of ex-vessle debris bed coolability for a Nordic BWR
(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:nbn:se:kth:diva-203134 (URN)
Note

QC 20170315

Available from: 2017-03-13 Created: 2017-03-13 Last updated: 2017-11-29Bibliographically approved

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