Lesson learned from the SARNET wall condensation benchmarks.
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| Title: | Lesson learned from the SARNET wall condensation benchmarks. |
|---|---|
| Authors: | Ambrosini, W.1 walter.ambrosini@ing.unipi.it, Forgione, N.1, Merli, F.1, Oriolo, F.1, Paci, S.1, Kljenak, I.2, Kostka, P.3, Vyskocil, L.4, Travis, J.R.5, Lehmkuhl, J.6, Kelm, S.6, Chin, Y.-S.7, Bucci, M.8 |
| Source: | Annals of Nuclear Energy. Dec2014, Vol. 74, p153-164. 12p. |
| Subjects: | Condensation, Nuclear reactor accidents, European Commission, Computational fluid dynamics, Nuclear reactor containment, Reactor experimental facilities |
| Abstract: | The prediction of condensation in the presence of noncondensable gases has received continuing attention in the frame of the Severe Accident Research Network of Excellence, both in the first (2004–2008) and in the second (2009–2013) EC integrated projects. Among the different reasons for considering so relevant this basic phenomenon, coped with by classical treatments dated in the first decades of the last century, there is the interest for developing updated CFD models for reactor containment analysis, requiring validating at a different level the available modelling techniques. In the frame of SARNET, benchmarking activities were undertaken taking advantage of the work performed at different institutions in setting up and developing models for steam condensation in conditions of interest for nuclear reactor containment. Four steps were performed in the activity, involving: (1) an idealized problem freely inspired at the actual conditions occurring in an experimental facility, CONAN, installed at the University of Pisa; (2) a first comparison with experimental data purposely collected by the CONAN facility; (3) a second comparison with data available from experimental campaigns performed in the same apparatus before the inclusion of the activities in SARNET; (4) a third exercise involving data obtained at lower mixture velocity than in previous campaigns, aimed at providing conditions closer to those addressed in reactor containment analyses. The last step of the benchmarking activity required to change the configuration of the experimental apparatus to achieve the lower flow rates involved in the new test specifications. The four benchmarking steps received the interest of a number of participants (more or less in the order of ten in each phase), who applied their models to the proposed blind exercises, receiving by the University of Pisa, as the hosting organization, comparisons with the reference data. Since the same geometry and relatively similar conditions were addressed in the four steps, though considering different operating conditions, a gradual improvement of the quality of results was observed with respect to the first applications. The activity revealed to be fruitful in providing the needed awareness about the capabilities of condensation models, at least in the simple configuration involved by the benchmark exercises. [ABSTRACT FROM AUTHOR] |
| Copyright of Annals of Nuclear Energy is the property of Pergamon Press - An Imprint of Elsevier Science and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
| FullText | Text: Availability: 0 |
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| Header | DbId: egs DbLabel: Engineering Source An: 98554353 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Lesson learned from the SARNET wall condensation benchmarks. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Ambrosini%2C+W%2E%22">Ambrosini, W.</searchLink><relatesTo>1</relatesTo><i> walter.ambrosini@ing.unipi.it</i><br /><searchLink fieldCode="AR" term="%22Forgione%2C+N%2E%22">Forgione, N.</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Merli%2C+F%2E%22">Merli, F.</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Oriolo%2C+F%2E%22">Oriolo, F.</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Paci%2C+S%2E%22">Paci, S.</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Kljenak%2C+I%2E%22">Kljenak, I.</searchLink><relatesTo>2</relatesTo><br /><searchLink fieldCode="AR" term="%22Kostka%2C+P%2E%22">Kostka, P.</searchLink><relatesTo>3</relatesTo><br /><searchLink fieldCode="AR" term="%22Vyskocil%2C+L%2E%22">Vyskocil, L.</searchLink><relatesTo>4</relatesTo><br /><searchLink fieldCode="AR" term="%22Travis%2C+J%2ER%2E%22">Travis, J.R.</searchLink><relatesTo>5</relatesTo><br /><searchLink fieldCode="AR" term="%22Lehmkuhl%2C+J%2E%22">Lehmkuhl, J.</searchLink><relatesTo>6</relatesTo><br /><searchLink fieldCode="AR" term="%22Kelm%2C+S%2E%22">Kelm, S.</searchLink><relatesTo>6</relatesTo><br /><searchLink fieldCode="AR" term="%22Chin%2C+Y%2E-S%2E%22">Chin, Y.-S.</searchLink><relatesTo>7</relatesTo><br /><searchLink fieldCode="AR" term="%22Bucci%2C+M%2E%22">Bucci, M.</searchLink><relatesTo>8</relatesTo> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Annals+of+Nuclear+Energy%22">Annals of Nuclear Energy</searchLink>. Dec2014, Vol. 74, p153-164. 12p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Condensation%22">Condensation</searchLink><br /><searchLink fieldCode="DE" term="%22Nuclear+reactor+accidents%22">Nuclear reactor accidents</searchLink><br /><searchLink fieldCode="DE" term="%22European+Commission%22">European Commission</searchLink><br /><searchLink fieldCode="DE" term="%22Computational+fluid+dynamics%22">Computational fluid dynamics</searchLink><br /><searchLink fieldCode="DE" term="%22Nuclear+reactor+containment%22">Nuclear reactor containment</searchLink><br /><searchLink fieldCode="DE" term="%22Reactor+experimental+facilities%22">Reactor experimental facilities</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: The prediction of condensation in the presence of noncondensable gases has received continuing attention in the frame of the Severe Accident Research Network of Excellence, both in the first (2004–2008) and in the second (2009–2013) EC integrated projects. Among the different reasons for considering so relevant this basic phenomenon, coped with by classical treatments dated in the first decades of the last century, there is the interest for developing updated CFD models for reactor containment analysis, requiring validating at a different level the available modelling techniques. In the frame of SARNET, benchmarking activities were undertaken taking advantage of the work performed at different institutions in setting up and developing models for steam condensation in conditions of interest for nuclear reactor containment. Four steps were performed in the activity, involving: (1) an idealized problem freely inspired at the actual conditions occurring in an experimental facility, CONAN, installed at the University of Pisa; (2) a first comparison with experimental data purposely collected by the CONAN facility; (3) a second comparison with data available from experimental campaigns performed in the same apparatus before the inclusion of the activities in SARNET; (4) a third exercise involving data obtained at lower mixture velocity than in previous campaigns, aimed at providing conditions closer to those addressed in reactor containment analyses. The last step of the benchmarking activity required to change the configuration of the experimental apparatus to achieve the lower flow rates involved in the new test specifications. The four benchmarking steps received the interest of a number of participants (more or less in the order of ten in each phase), who applied their models to the proposed blind exercises, receiving by the University of Pisa, as the hosting organization, comparisons with the reference data. Since the same geometry and relatively similar conditions were addressed in the four steps, though considering different operating conditions, a gradual improvement of the quality of results was observed with respect to the first applications. The activity revealed to be fruitful in providing the needed awareness about the capabilities of condensation models, at least in the simple configuration involved by the benchmark exercises. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Annals of Nuclear Energy is the property of Pergamon Press - An Imprint of Elsevier Science and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1016/j.anucene.2014.07.014 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 12 StartPage: 153 Subjects: – SubjectFull: Condensation Type: general – SubjectFull: Nuclear reactor accidents Type: general – SubjectFull: European Commission Type: general – SubjectFull: Computational fluid dynamics Type: general – SubjectFull: Nuclear reactor containment Type: general – SubjectFull: Reactor experimental facilities Type: general Titles: – TitleFull: Lesson learned from the SARNET wall condensation benchmarks. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Ambrosini, W. – PersonEntity: Name: NameFull: Forgione, N. – PersonEntity: Name: NameFull: Merli, F. – PersonEntity: Name: NameFull: Oriolo, F. – PersonEntity: Name: NameFull: Paci, S. – PersonEntity: Name: NameFull: Kljenak, I. – PersonEntity: Name: NameFull: Kostka, P. – PersonEntity: Name: NameFull: Vyskocil, L. – PersonEntity: Name: NameFull: Travis, J.R. – PersonEntity: Name: NameFull: Lehmkuhl, J. – PersonEntity: Name: NameFull: Kelm, S. – PersonEntity: Name: NameFull: Chin, Y.-S. – PersonEntity: Name: NameFull: Bucci, M. IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 12 Text: Dec2014 Type: published Y: 2014 Identifiers: – Type: issn-print Value: 03064549 Numbering: – Type: volume Value: 74 Titles: – TitleFull: Annals of Nuclear Energy Type: main |
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