IAEA-TECDOC-1889

IAEA-TECDOC-1889

IAEA TECDOC SERIES

Fuel Modelling in Accident Conditions (FUMAC)

IAEA-TECDOC-1889

Fuel Modelling in Accident
Conditions (FUMAC)
Final Report of a Coordinated Research ProjectInternational Atomic Energy Agency
ViennaISBN 978–92–0–163919–6
ISSN 1011–4289@

FUEL MODELLING IN ACCIDENT
CONDITIONS (FUMAC)

The following States are Members of the International Atomic Energy Agency:
AFGHANISTANALBANIA
ALGERIAANGOLA
ANTIGUA AND BARBUDA
ARGENTINA
ARMENIA
AUSTRALIA
AUSTRIAAZERBAIJAN
BAHAMAS
BAHRAINBANGLADESHBARBADOSBELARUSBELGIUM
BELIZEBENIN
BOLIVIA, PLURINATIONAL
STATE OFBOSNIA AND HERZEGOVINABOTSWANABRAZILBRUNEI DARUSSALAM
BULGARIA
BURKINA FASO
BURUNDICAMBODIACAMEROONCANADACENTRAL AFRICAN
REPUBLIC
CHAD
CHILE
CHINA
COLOMBIACONGOCOSTA RICA
CÔTE D’IVOIRECROATIACUBACYPRUSCZECH REPUBLIC
DEMOCRATIC REPUBLIC
OF THE CONGO
DENMARKDJIBOUTIDOMINICADOMINICAN REPUBLICECUADOREGYPTEL SALVADORERITREAESTONIA
ESWATINIETHIOPIAFIJI
FINLANDFRANCEGABONGEORGIAGERMANYGHANA
GREECE
GRENADAGUATEMALAGUYANAHAITI
HOLY SEE
HONDURASHUNGARYICELAND
INDIA
INDONESIA
IRAN, ISLAMIC REPUBLIC OFIRAQIRELANDISRAELITALY
JAMAICAJAPANJORDANKAZAKHSTANKENYAKOREA, REPUBLIC OFKUWAITKYRGYZSTANLAO PEOPLE’S DEMOCRATIC
REPUBLICLATVIALEBANONLESOTHO
LIBERIA
LIBYA
LIECHTENSTEIN
LITHUANIALUXEMBOURG
MADAGASCARMALAWI
MALAYSIAMALI
MALTA
MARSHALL ISLANDS
MAURITANIA
MAURITIUS
MEXICOMONACOMONGOLIAMONTENEGRO
MOROCCOMOZAMBIQUE
MYANMAR
NAMIBIANEPAL
NETHERLANDSNEW ZEALANDNICARAGUANIGERNIGERIANORTH MACEDONIANORWAYOMANPAKISTAN
PALAU
PANAMAPAPUA NEW GUINEAPARAGUAYPERU
PHILIPPINESPOLANDPORTUGALQATARREPUBLIC OF MOLDOVAROMANIARUSSIAN FEDERATIONRWANDASAINT LUCIA
SAINT VINCENT AND
THE GRENADINESSAN MARINOSAUDI ARABIASENEGALSERBIASEYCHELLESSIERRA LEONESINGAPORESLOVAKIASLOVENIA
SOUTH AFRICASPAIN
SRI LANKA
SUDAN
SWEDENSWITZERLANDSYRIAN ARAB REPUBLICTAJIKISTANTHAILANDTOGO
TRINIDAD AND TOBAGOTUNISIA
TURKEYTURKMENISTANUGANDAUKRAINE
UNITED ARAB EMIRATESUNITED KINGDOM OFGREAT BRITAIN ANDNORTHERN IRELAND
UNITED REPUBLICOF TANZANIAUNITED STATES OF AMERICAURUGUAYUZBEKISTANVANUATU
VENEZUELA, BOLIVARIAN
REPUBLIC OFVIET NAMYEMEN
ZAMBIA
ZIMBABWE

The Agency’s Statute was approved on 23 October 1956 by the Conference on the Statute of the
IAEA held at United Nations Headquarters, New York; it entered into force on 29 July 1957.
The Headquarters of the Agency are situated in Vienna. Its principal objective is “to accelerate and enlarge
the contribution of atomic energy to peace, health and prosperity throughout the world’’.

IAEA-TECDOC-1889

FUEL MODELLING IN ACCIDENT
CONDITIONS (FUMAC)
FINAL REPORT OF A COORDINATED RESEARCH PROJECTINTERNATIONAL ATOMIC ENERGY AGENCY
VIENNA, 2019

COPYRIGHT NOTICEAll IAEA scientific and technical publications are protected by the terms of
the Universal Copyright Convention as adopted in 1952 (Berne) and as revisedin 1972 (Paris). The copyright has since been extended by the World Intellectual
Property Organization (Geneva) to include electronic and virtual intellectual
property. Permission to use whole or parts of texts contained in IAEA publicationsin printed or electronic form must be obtained and is usually subject to royalty
agreements. Proposals for non-commercial reproductions and translations arewelcomed and considered on a case-by-case basis. Enquiries should be addressedto the IAEA Publishing Section at:
Marketing and Sales Unit, Publishing Section
International Atomic Energy Agency
Vienna International Centre
PO Box 100
1400 Vienna, Austria
fax: +43 1 26007 22529
tel.: +43 1 2600 22417
email: sales.publications@iaea.org
www.iaea.org/publications

For further information on this publication, please contact:
Nuclear Fuel Cycle and Materials Section
International Atomic Energy Agency
Vienna International Centre
PO Box 100
1400 Vienna, Austria
Email: Official.Mail@iaea.org© IAEA, 2019
Printed by the IAEA in Austria
December 2019

IAEA Library Cataloguing in Publication Data
Names: International Atomic Energy Agency.
Title: Fuel modelling in accident conditions (FUMAC) / International Atomic Energy
Agency.
Description: Vienna : International Atomic Energy Agency, 2019. | Series: IAEA TECDOC
series, ISSN 1011–4289 ; no. 1889 | Includes bibliographical references.
Identifiers: IAEAL 19-01281 | ISBN 978–92–0–163919–6 (paperback : alk. paper) | ISBN
978–92–0–164019–2 (pdf)
Subjects: LCSH: Nuclear fuels. | Computer simulation. | Nuclear reactors — Safety measures.
| Nuclear reactors — Computer programs.

FOREWORD
Improved understanding of fuel performance can lead to a reduction in operating margins,increased flexibility in fuel management and improved operating economics. To better
understand fuel performance, the IAEA has addressed different aspects of fuel behaviourmodelling in a series of coordinated research projects aimed at assessing fuel performancecodes and supporting countries with code development and application needs (FUMEX series);
building a database of well defined experiments suitable for code validation, in association with
the OECD Nuclear Energy Agency (OECD/NEA); transferring a mature fuel modelling code
to developing countries and supporting its adaptation to the requirements of particular reactors;
providing guidance on applying that code to reactor operation and safety assessments; andproviding guidelines for code quality assurance, code licensing and code application to fuellicensing.
The present publication describes the results of the coordinated research project on Fuel
Modelling in Accident Conditions (FUMAC), initiated under the IAEA Action Plan on Nuclear
Safety implemented after the accident at the Fukushima Daiichi nuclear power plant. The
project, which ran from 2014 to 2018, followed previous projects on fuel modelling: D-COM
1982–1984, FUMEX 1993–1996, FUMEX-II 2002–2006 and FUMEX-III 2008–2012.
The project participants used data derived from accident simulation experiments, inparticular data designed to investigate the fuel behaviour during design basis accident anddesign extension conditions, to carry out calculations on selected priority cases identified at thefirst research coordination meeting. These priority cases were designed to support theparticipants’ individual priorities and were chosen as the best available to help determine whichof the many models used in the codes most closely reflect reality. The cases were also used forverification and validation purposes, and for inter-code comparisons.
The IAEA would like to thank all the organizations and individuals who contributed to
the FUMAC project, in particular the Technical Working Group on Fuel Performance andTechnology for suggesting and supporting the project; the OECD/NEA Halden Reactor Project,
the United States Nuclear Regulatory Commission, the Hungarian Academy of Sciences Centre
for Energy Research (MTA EK) and the Karlsruhe Institute of Technology (KIT) for providing
experimental data; the OECD/NEA for supporting the International Fuel Performance
Experiments Database; and the project participants for performing the calculations andsubmitting summaries and meeting contributions. The IAEA would also like to thank all those
who prepared the intermediate working material and the final report. The IAEA officer
responsible for this publication was M. Veshchunov of the Division of Nuclear Fuel Cycle andWaste Technology.

EDITORIAL NOTEThis publication has been prepared from the original material as submitted by the contributors and has not been edited by the editorial
staff of the IAEA. The views expressed remain the responsibility of the contributors and do not necessarily represent the views of the
IAEA or its Member States.
Neither the IAEA nor its Member States assume any responsibility for consequences which may arise from the use of this publication.
This publication does not address questions of responsibility, legal or otherwise, for acts or omissions on the part of any person.
The use of particular designations of countries or territories does not imply any judgement by the publisher, the IAEA, as to the legal
status of such countries or territories, of their authorities and institutions or of the delimitation of their boundaries.
The mention of names of specific companies or products (whether or not indicated as registered) does not imply any intention to
infringe proprietary rights, nor should it be construed as an endorsement or recommendation on the part of the IAEA.
The authors are responsible for having obtained the necessary permission for the IAEA to reproduce, translate or use material fromsources already protected by copyrights.
The IAEA has no responsibility for the persistence or accuracy of URLs for external or third party Internet web sites referred to in thispublication and does not guarantee that any content on such web sites is, or will remain, accurate or appropriate.

CONTENTS
1.

INTRODUCTION ................................................................................................... 1
BACKGROUND ..................................................................................................... 1
OBJECTIVES .......................................................................................................... 1
SCOPE ................................................................................................................... 1
STRUCTURE .......................................................................................................... 22.

DESCRIPTION OF CASES .................................................................................... 5
2.1.
2.2.

2.3.

2.4.
2.5.
3.

DESCRIPTION OF CODES AND MODEL IMPROVEMENTS ........................ 33
3.1.

3.2.
3.3.

4.

SEPARATE EFFECT TESTS (MTA-EK BURST TESTS) ..................... 5
HALDEN LOCA TESTS (IFA-650.2, 9, 10 AND 11) ............................. 6
2.2.1. Test design end execution .............................................................. 6
2.2.2. Data accuracy and data acquisition ................................................ 8
2.2.3. Description of the tests .................................................................. 8
STUDSVIK LOCA TEST (NRC-192) .................................................... 26
2.3.1. Design and operation of the Studsvik LOCA test rig .................. 26
2.3.2. Test rodlet NRC-Studsvik-192 .................................................... 28
2.3.3. Summary of test conditions and test results................................. 29
KIT QUENCH-L1 BUNDLE TEST ....................................................... 30
CORA-15 ................................................................................................. 31

SINGLE FUEL ROD CODES ................................................................ 33
3.1.1. FRAPTRAN................................................................................. 33
3.1.2. TRANSURANUS ........................................................................ 33
3.1.3. ALCYONE .................................................................................. 35
3.1.4. BISON ......................................................................................... 37
3.1.5. DIONISIO .................................................................................... 38
3.1.6. FTPAC and FTPAC - ABAQUS ................................................. 39
3.1.7. RAPTA-5.2 .................................................................................. 40
3.1.8. SFPR ............................................................................................ 41
COUPLED THERMAL HYDRAULIC AND FUEL ROD CODES ...... 41
3.2.1. MARS-KS.................................................................................... 41
3.2.2. GENFLO-FRAPTRAN ............................................................... 43
SEVERE ACCIDENT CODES ............................................................... 43
3.3.1. ATHLET-CD ............................................................................... 43
3.3.2. SOCRAT ...................................................................................... 44

COMPARISON OF SIMULATION RESULTS ................................................... 46
4.1.

4.2.

4.3.

MTA EK BURST TESTS ....................................................................... 46
4.1.1. Results of time to burst failure ..................................................... 46
4.1.2. Results of pressure at burst failure ............................................... 47
4.1.3. Results of maximum hoop strain at burst failure ......................... 47
HALDEN LOCA TESTS (IFA-650.9, 10, 11) ........................................ 49
4.2.1. IFA-650.9 ..................................................................................... 49
4.2.2. IFA-650.10 ................................................................................... 59
4.2.3. IFA-650.11 ................................................................................... 75
STUDSVIK LOCA TEST (NRC-192) .................................................... 85
4.3.1. Results at the end of the base irradiation ..................................... 85

4.4.
4.5.

5.

4.3.2. Results during the LOCA test ...................................................... 88
4.3.3. Results at the end of the LOCA test ............................................ 92
QUENCH-LOCA L1 ............................................................................... 95
4.4.1. Results during the QUENCH-LOCA test .................................... 96
4.4.2. Results after the QUENCH-LOCA test ....................................... 97
CORA-15 ............................................................................................... 103
4.5.1. Cladding burst parameters for the CORA-15 bundle ................ 104
4.5.2. Time dependences and axial dependences of LOCA events forcentral rod 4.4 of the CORA-15 bundle ..................................... 107
4.5.3. Post-test outer oxide layer thickness of the CORA-15 claddings................................................................................................... 108
4.5.4. Post-test blockage of the CORA-15 bundle ............................... 110
4.5.5. Hydrogen release during the CORA-15 test .............................. 110

UNCERTAINTY AND SENSITIVITY ANALYSIS FOR IFA-650.10............. 113
5.1.
5.2.
5.3.

5.4.

5.5.
5.6.
5.7.

INTRODUCTION ................................................................................. 113
PARTICIPANTS AND USED CODES ................................................ 113
SPECIFICATIONS ............................................................................... 113
5.3.1. Methodology .............................................................................. 113
5.3.2. Definition of input uncertainty parameters ................................ 114
5.3.3. Modelling assumptions .............................................................. 115
5.3.4. Output parameters ...................................................................... 116
COMPARISON OF UNCERTAINTY ANALYSIS RESULTS .......... 117
5.4.1. Rod internal pressure (RIP) ....................................................... 117
5.4.2. Clad outer surface temperature (TCO) ...................................... 120
5.4.3. Fuel outer surface temperature (TFO) ....................................... 123
5.4.4. Clad elongation (ECT) ............................................................... 126
5.4.5. Clad outside diameter (COD) at burst node............................... 129
COMPARISON OF SENSITIVITY ANALYSIS RESULTS .............. 132
CONCLUSIONS ................................................................................... 136
SUMMARY AND RECOMMENDATIONS ....................................... 137

REFERENCES .............................................................................................................. 139
ANNEX I: ..................................................................................................................... 147
SPECIFICATIONS FOR UNCERTAINTY ANALYSIS ON MODELLING OF THE
HALDEN LOCA TEST IFA-650.10 ................................................................... 147
I–1. INTRODUCTION ............................................................................................... 147
I–2. METHODOLOGY .............................................................................................. 147
I–2.1. Uncertainty analysis: input uncertainty propagation method .... 147
I–2.2. Sensitivity analysis: Global sensitivity analysis method ........... 150
I–2.3. The tool ...................................................................................... 151
I–3. SPECIFICATION OF THE CASE ...................................................................... 152
I–3.1. Test IFA-650.10 ......................................................................... 152
I–3.2. Modelling ................................................................................... 152

I–4. DEFINITION OF INPUT UNCERTAINTIES ................................................... 154
I–4.1. Identification of uncertainty parameters .................................... 154
I–4.2. Uncertainties in fuel rod design/manufacturing data ................. 154
I–4.3. Uncertainties in fuel rod operation and test boundary conditions................................................................................................... 155
I–4.4. Uncertainties in physical properties and key models................. 155
I–4.5. Definition of INPUT uncertain parameters ............................... 156
I–5. OUTPUT SPECIFICATION ............................................................................... 156
I–5.1. Uncertainty analysis output ....................................................... 156
I–5.2. Sensitivity analysis output ......................................................... 156
I–5.3. Proposed Process and Schedule As per agreements .................. 157
REFERENCES TO THE ANNEX I ............................................................................. 159

ANNEX II (CAN BE FOUND IN THE ATTACHED CD)
ACCIDENT CONDITION MODELS IN THE DIONISIO 2.0 CODE ........................... 1
A. Soba, M. Lemes, E. Goldberg, M. Loza, M. Cazado, M.E. Gonzalez, A. Denis

QUALIFICATION OF FRAPCON/ FRAPTRAN CODES FOR LOCA FUELBEHAVIOUR MODELLING AND SAFETY EVALUATION: TRACTEBELCONTRIBUTION TO FUMAC PROJECT (2014-2017) .............................................. 21
J. Zhang, A. Dethioux, T. Drieu, C. Schneidesch

DEVELOPMENT AND APPLICATION OF MODIFIED FUEL PERFORMANCECODE BASED ON STAINLESS STEEL AS CLADDING UNDER STEADY STATE,TRANSIENT AND ACCIDENT CONDITIONS .......................................................... 55
A. Abe, A.T.E. Silva, C. Giovedi, C. Melo, D.S. Gomes, R.R. Muniz

FUEL ROD BEHAVIOUR MODELLING AND SAFETY EVALUATION BY
TRANSURANUS CODE: HALDEN LOCA TESTS IFA-650 .................................. 82
S. Boneva, M. Manolova, N. Mihaylov, Ml. Mitev

DEVELOPMENT OF FTPAC CODE AND APPLICATION ON SAFETYPERFORMANCE RESEARCH UNDER LOCA CONDITION ................................... 95
A. Abe, A.T.E. Silva, C. Giovedi, C. Melo, D.S. Gomes, R.R. Muniz

SIMULATION OF FUEL ROD LOCA BEHAVIOR TESTS IFA-650.9/10/11 WITH
FRAPCON & FRAPTRAN CODE............................................................................... 109
X. Yiran, R. Qisen, C. Mengteng, Z. Yongdong

FUEL BEHAVIOUR UNDER LOCA CONDITIONS ESTIMATED WITH
FRAPTRAN .................................................................................................................. 128
J. Heikinheimo, V. Tulkki, J. Kättö, T. Ikonen, H. Loukusa

FUEL SIMULATION OF LOCA TESTS USING ALCYONE FUEL PERFORMANCECODE ............................................................................................................................ 143
A. Bouloré, C. Struzik

RESULTS OF THE CORA-15 BUNDLE TEST WITH PRESSURIZED RODS ....... 159
J. Stuckert

RESULTS OF THE LOCA REFERENCE BUNDLE TEST QUENCH-L1 WITHZIRCALOY-4 CLADDINGS ....................................................................................... 174
J. Stuckert, M. Große, M. Steinbrück, M. Walter

POST-TEST SIMULATION OF CORA TEST 15 WITH ATHLET-CD .................... 205
H. Austregesilo, Ch. Bals, Th. Hollands

FINAL REPORT FOR THE DEVELOPMENT AND APPLICATION OF THE
TRANSURANUS CODE FOR THE FUMAC PROJECT ........................................ 213
P. Van Uffelen, A. Schubert, J. Van De Laar

MTA EK ACTIVITIES IN THE IAEA FUMAC CRP ................................................ 245
K. Kulacsy

MODELLING OF THE BEHAVIOUR OF INERT GASES IN OXIDE AND MIXEDOXIDE NUCLEAR FUEL UNDER DESIGN BASIS ACCIDENT CONDITIONS .. 259
L. Luzzi, T. Barani, L. Cognini, D. Pizzocri

SIMULATION OF FUEL BEHAVIOR DURING LOCA CONDITION USINGFRAPCON/FRAPTRAN AND THE COUPLED MARS-KS CODE: ......................... 268
H. Kim, C. Shin, Y. Yang, Y. Koo, T. Kim

NUMERICAL ANALISYS OF CORA-15 TEST BY SOCRAT CODE ..................... 282
K.S. Dolganov, A.E. Kiselev, A.E.Tarasov, D.Yu. Tomashchik, T.A. Yudina

SIMULATION OF INITIAL AND BOUNDARY CONDITIONS WITH SOCRATCODE FOR BENCHMARKS BASED ON IFA-650.10 AND IFA-650.11 TESTS.... 296
K.S. Dolganov, A.E. Kiselev, D.Yu. Tomashchik, T.A. Yudina

CALCULATION MODELING OF THERMOMECHANICAL BEHAVIOR OF FUELRODS IN IFA-650.9, IFA-650.10 AND IFA-650.11 EXPERIMENTSUSING RAPTA5.2 CODE ...................................................................................................................... 315
V.I. Kuznetsov, A.V. Kumachev, V.V. Novikov, A.V. Salatov, P.V. Fedotov

ANALYSIS OF FUEL CLAD DOUBLE-SIDE OXIDATION AND SECONDARYHYDRIDING UNDER LOCA CONDITIONS IN IFA-650.2 TEST....................... 339
V.E. Shestak, B.C. Oberländer, M.S. Veshchunov

IMPLEMENTATION OF THE MOLTEN U-ZR-O SLUG (BLOCKAGE)
RELOCATION MODEL INTO THE SFPR CODE .................................................. 349
V.E. Shestak, A.V. Boldyrev, M.S. Veshchunov

FRAPTRAN CAPABILITIES TO MODEL LOCA THERMO-MECHANICS .......... 360
L.E. Herranz, S.B. Peláez

IMPROVING THE FRAPTRAN PROGRAM FOR FUEL ROD LOCA ANALYSESBY NOVEL MODELS AND ASSESSMENT OF RECENT DATA .......................... 381
L.O. Jernkvist, A. Massih

TESTING OF THE TRANSURANUS COMPUTER CODE BY JOINT SOLUTION
OF TEST PROBLEMS WITHIN FUMAC PROJECT ................................................ 452
M. Ieremenko

CONTRIBUTION OF IDAHO NATIONAL LABORATORY TO THE CRP FUMAC............................................................................................................................. 470
G. Pastore, R. Williamson, J. Hales, K. Gamble, R. Gardner, J. Tompkins

1. INTRODUCTIONBACKGROUND
Fuel modelling is a priority within the IAEA sub-programme “Nuclear Power Reactor
Fuel Engineering”. Development and verification of computer codes are possible based on goodexperiments that requires very expensive and carefully executed in-reactor tests and postirradiation studies. That is why international cooperation in this area is highly desirable. IAEA
supports interested Member States in their efforts to enhance the capacities of their computercodes used for predicting fuel behaviour.
Since the 1980’s, a series of four Coordinated Research Projects (CRPs): D-COM (1982–
1984) [1], FUMEX (1993–1996) [2], FUMEX-II (2002–2007) [3] and FUMEX-III (2008–2012) [4], were carried out that targeted nuclear fuel modelling under normal operating
conditions. Those projects were highly appreciated (and valued) by Member States. The
proposed CRP T12028 on Fuel Modelling in Accident Conditions (FUMAC) is to continue theseries with the focus on fuel behaviour under Design Basis Accident (DBA) and Design
Extension Conditions (DEC).
The current CRP on Fuel Modelling in Accident Conditions (FUMAC) was initiatedbecause of the Fukushima accident under the IAEA Action Plan on Nuclear Safety, following
a recommendation from the IAEA Technical Working Group on Fuel Performance andTechnology (TWGFPT, in 2012) to launch a new fuel modelling CRP focusing on accident
conditions. Preliminary ideas were brainstormed during the Technical Meeting on Fuel
Behaviour and Modelling under Severe Transient and Loss of Coolant Accident (LOCA)
conditions that took place in Japan in October 2011, agreed with NEA/OECD in 2012 andfinalized through more detailed discussions during another Technical Meeting on Modelling of
Water-Cooled Fuel Including Design Basis and Severe Accidents, in China in 2013 and finallyat the International QUENCH Workshop in Germany the same year. The CRP FUMAC has
been launched by the IAEA since 2014, with the end-date in 2018.
OBJECTIVES
The objectives of the CRP FUMAC are to:Analyse and better understand fuel behaviour in accident conditions, with a focus on
LOCA (DBA), in line with the early phase of the Fukushima accident (DEC);
Assemble quality results from accident simulation experiments, and disseminate
experience from Member States;
Identify best practices in the application of physical models and computer codes used indifferent Member States for modelling fuel in accident conditions, and enhance thepredictive capacities of these models and codes.
SCOPE
The CRP FUMAC was planned with the well proven organizational approach used in
FUMEX-III [4], which presumed cross-comparisons of computer codes used in different
Member States. Selected simulations from experimental results, provided by the CRP
participants, will be integrated into the International Fuel Performance Experiments (IFPE)
Database (developed in cooperation and coordination between OECD/NEA, IAEA andIFE/OECD/Halden Reactor Project) and used for codes verification. The codes involved ranged
from fuel performance codes (DIONISIO, FRAPTRAN, FTPAC, RAPTA, SFPR,
TRANSURANUS) to system or severe accident codes (ATHLET-CD, MELCOR, SOCRAT)
as well as multi-dimensional fuel performance codes (ALCYONE, BISON).
The fuel behaviour during LOCAs was extensively studied during the last decades.
Recent LOCA tests, performed in Halden, Norway, and Studsvik, Sweden, revived the interest1

in the fuel relocation and dispersion phenomena. Indeed, test results suggest that high burnup
fuel pellets might pulverize into very fine fragments, with a higher potential for axial relocationand subsequent dispersal than observed for low to medium burnup fuel in early tests. This
research area is also being addressed by the Working Group on Fuel Safety (WGFS) of the
Nuclear Energy Agency (NEA), under the Committee on the Safety of Nuclear Installations(CSNI), and is identified as one of key issues in the IAEA coordinated research project
FUMAC.
The preparatory Consultancy Meeting was held in March 2014 in Vienna, the outcomesof the consultancy group along with the survey of potential participants by means of aquestionnaire were presented and discussed to structure and define the scope of the CRP. A
preliminary list of available experiments for the benchmark were proposed for consideration
The first Research Coordination Meeting (RCM) of the CRP was held from November
11–14, 2014 in KIT (Karlsruhe, Germany) in conjunction with the 20th QUENCH Workshop.
27 participants from 21 organizations representing 18 Member States attended the meeting.
The 2nd Research Coordination Meeting took place in Vienna International Centre fromMay 30 to June 3, 2016. 27 participants from 21 organizations represented 18 Member States
attended the Meeting.
The 3rd Research Coordination Meeting took place in Vienna International Centre on 13–
17 November 2017. 24 participants from 22 organizations and 3 observers from 2 organizations
represented 18 Member States attended the Meeting.
The final Consultancy Meeting to Finalize the Final Report of the CRP on Fuel Modellingin Accident Conditions was held on 21–23 February 2018 in Vienna.
STRUCTURE
This publication summarizes the finding and conclusions of the CRP FUMAC within awork plan jointly agreed on by twenty-six organizations from 18 Member States. A list of theparticipating organizations submitted Individual Contributions to this TECDOC (as Annex II) andtheir used codes (presented in more details in Section 3) are given in Table 1.
A list of chief scientific investigators who represented these organizations within the CRP
is given at the end of this report. Well checked experimental datasets from separate-effect tests:
clad ballooning tests (PUZRY from MTA EK); out-of-pile single rod LOCA tests (Studsvik
192, 198); in-reactor LOCA tests with single rods (IFA 650.9–11 from the Halden Project);
KIT out-of-pile bundle LOCA test (QUENCH-L1) and bundle under severe accident test
(CORA 15) were chosen for benchmark exercises, as outlined in Table 2 and presented in moredetails in Section 2.
Discussions related to the thermal hydraulic (T/H) boundary conditions (BC), new test
cases were carried out during the CRP. It was agreed to apply a common BC to IFA650.9, 10
and 11 to be calculated by the integral severe accident code SOCRAT (from IBRAE, RussianFederation). In addition, the IFA-650.2 test with new PIE data on hydrogen uptake was analysedin view of the preparation of new licensing criteria in various Member States.
It has been also proposed that the available severe accident codes would be comparedwith experimental data for CORA 15 test. The IFA-650 cases and the QUENCH-LOCA1 test
were to provide a common basis (the benchmark cases) for the different types of codes involvedin the CRP.

2

TABLE 1. PARTICIPANTS OF THE CRP FUMAC
Individual
Contribution

Country

Organization

Argentina
BelgiumBrazilBulgaria
China
China
Germany

CNEA
Tractebel
IPEN-CNEN
INRNE
CIAE
CNPRI
JRC

Germany

KIT

FinlandFranceVTT
CEA

Hungary

MTA EK

Data provided(Section 2.1)
Annex II

Italy
Japan
Republic of
Korea

POLIMI
NSR

Annex II–

KAERI

Annex II

NorwayIFE

Data provided(Section 2.2)–

RussianFederation

BochvarInstitute

Annex IIRAPTA-5.2

RussianFederation

Annex II
Annex II
Annex II
Annex II
Annex II
Annex II
Annex II
Data provided(Sections 2.4,2.5) Annex II
Annex II
Annex II

Code

Experiment

DIONISIO-2.0
FRAPTRAN-TE-1.5
FRAPTRAN
TRANSURANUS
FTPAC
FRAPTRAN-1.5
TRANSURANUS

FRAPTRAN-1.5, 2.0
ALCYONE-1D

–
–
–
–
–
–
–
QUENCHLOCA1,
CORA-15––

FRAPTRAN-2.0

PUZRY

Modelling–
FRAPTRAN-1.5/
S-FRAPTRAN

–
–
–

–

IBRAE

Annex IISOCRAT, SFPR

Annex IIFRAPTRAN-1.5

Annex IIFRAPTRAN-QT-1.5

UkraineUkraineUSA
USA

CIEMAT
SwedishRadiation
SafetyAuthority (SSA)
Energorisk
SSTC NRS
Battelle INL
Westinghouse

MELCOR
TRANSURANUS
BISON-2D
MAAP

USA

US NRC–
Annex II
Annex II
Annex II
Data provided(Section 2.3)

Spain

SwedenGermany
International

GRS(Activeobserver)OECD/NEA

Annex II–

IFA650.9/10/11
and 650.2
Boundary
conditions
for IFA650.9/10/11
–
–

–
–
–
–
Studsvik
192, 198–

ATHLET-CD
Observer–3

TABLE 2. TEST MATRIX FOR BENCHMARK EXERCISES
IFA650.9

IFA650.10

IFA650.11

Studsvik
192, 198

MTA-EKQUENCH
LOCA1

CORA
15

Uncertainty
analysisWith UO2
dispersal

PWR

VVER

Out-ofFuel rod
pile single
segments
fuel rod

Out-of-pilebundleOut-ofpile
bundleDAKOTA,URANIE,
etc.

Many of the participants used the CRP to develop and provide (or extend) a validation
database for their codes. Some were using commercial codes and used the CRP to help develop
an understanding of their codes and to train young professionals. The wide range of participants
and their needs contributed to valuable informative discussions and widespread cooperation
between the participants. Comparison of simulation results were carried within the CRP, aspresented in Section 4.
Finally, the participants also agreed to extend the analysis by means of an uncertainty andsensitivity analysis, as presented in Section 5 for IFA-650.10 test. Uncertainty analysis and its
detailed specification prepared by Tractebel is summarized in Annex I. Final reports submitted
by the participants are compiled as Annex II.

4

2.

DESCRIPTION OF CASES

2.1. SEPARATE EFFECT TESTS (MTA-EK BURST TESTS)
The separate effect ballooning and burst tests provided to FUMAC were performed at thepredecessor of MTA EK (KFKI AEKI).
The experiments proposed for benchmarking were ballooning and burst tests using
unirradiated, unoxidized Zircaloy-4 tubing. The tubing was 50 mm long with inner/outer
diameters of 9.3/10.75 mm. The specimens were heated in an induction furnace and held atconstant temperature while the inner pressure was increased at a constant rate until burst
occurred.
A detailed description of these tests and the test apparatus could be found in Refs [5, 6].
Six cases were selected as closest to real large-break LOCA scenarios:
PUZRY-26 (700 °C, 0.119 bar/s);
PUZRY-30 (800 °C, 0.263 bar/s);
PUZRY-18 (900 °C, 0.115 bar/s);
PUZRY-8 (1000 °C, 0.076 bar/s);
PUZRY-10 (1100 °C, 0.071 bar/s);
PUZRY-12 (1200 °C, 0.072 bar/s).
The results of these tests are illustrated in Figs 1 and 2.

FIG. 1. Time of burst vs. temperature for the 6 PUZRY tests.

5

FIG. 2. Burst pressure vs. temperature for the 6 PUZRY tests.
2.2. HALDEN LOCA TESTS (IFA-650.2, 9, 10 AND 11)
The Halden Reactor test series IFA-650 was part of the joint international programme of
the Halden Reactor Project. These tests addressed the LOCA performance of high burnup fuelirradiated in commercial nuclear power plants. The three experiments selected for FUMAC
were:
IFA-650.9 (PWR fuel): considerable ballooning, fuel fragmentation and relocation, whensubjected to LOCA were indicated;
IFA-650.10 (PWR fuel): moderate ballooning, fuel fragmentation and dispersal wereindicated;
IFA-650.11 (VVER fuel): little ballooning and fuel fragmentation were indicated.
IFA-650.2, a commissioning test with fresh fuel, was also evaluated by some participants
and discussed during the research coordination meetings. Considering the complexity of IFA650.9 (very high burnup, complicated T/H conditions, an axial relocation model is also
required), participants agreed to use IFA-650.10 as the case for the uncertainty and sensitivity
analysis (UASA), see Annex I.
Results obtained from various codes, as reported from participants, were in generalhaving the same trends for both the IFA-650.10 and 11 tests.
2.2.1. Test design end execution
A schematic drawing of the test rig with its instrumentation is shown in Fig. 3. Most of
the energy to drive the LOCA heat-up came from a low level of fission power in the fuel rod.
An electrical heater surrounding the rod, served as a flow path divider, was installed to simulate
some of the energies coming from neighbouring rods.
The instrumentation consisted of three cladding surface thermocouples (TCC), a cladding
extensometer (EC), a fuel pressure sensor (PF), three vanadium neutron flux detectors, twoheater surface thermocouples (TCH) and thermocouples at the inlet (TI) and outlet (TO) of therig. The temperature of the heater was measured by two embedded thermocouples. The axial
power distribution was determined with three self-powered vanadium neutron detectors(SPND).
6

A schematic sketch of the loop for the LOCA experiments in the Halden reactor is shownin Fig. 4. Initially, forced circulation was maintained through the in-core part (pressure flask,
designated ‘IFA-650’ in Fig. 4) and the entire loop indicated by the flow path was marked asblue. Prior to blow-down, the pressure flask was isolated from the rest of the loop wherecirculation was maintained and marked as red, while the fuel rod was cooled by natural
circulation in the pressure flask. To start the LOCA, valves in the green line to the blow-downtank were opened.
The blow-down tank had a volume of 100 L and initially contained 15–20 L of water. The
water was cooled, and the steam from the in-core flask was condensed. At the end of blowdown, the pressure in the system was typically 2–3 bar due to non-condensable gases.
The LOCA test was performed at a rod power of 10–30 W/cm depending on target peakclad temperature. After a few minutes at maximum temperature, the experiment was terminatedby switching off the electrical heating and scramming the reactor which caused the fission heatgeneration in the fuel rod to cease. The test rods were cooled down relatively slowly with thereactor to avoid disturbances, e.g. vibrations, which might possibly cause an unintentional fuelrelocation.

FIG. 3. Test rig used in IFA-650 tests (left) and a schematic cross section of the rig (right).

7

FIG. 4. Simplified drawing of the loop used for the IFA-650 experiments.
2.2.2. Data accuracy and data acquisition
Before test execution, the reactor was operated for 7–8 hours at about 15 MW toaccumulate fresh fission products for the gamma scanning after unloading. The power wascalibrated during this period. The calibration was to establish the relation between average
neutron detector signal and total power.
The neutron detectors were, outside the pressure flask, in the moderator and would not beaffected by temperature change during a transient. The relation between neutron flux and power
found during calibration was therefore also valid for the transient. The power uncertainty wasapproximately ±5 % for the total power or the average linear heat rating. The uncertainty of thelocal power, which was derived from the neutron flux distribution, was slightly higher. There
were additional uncertainties coming from the axial flux distribution that was based on:
measurements at three points, the nature of the SPNDs that measured the average flux over a
10 cm length of their emitters, and the assumption that the fissile content was constant over thelength of the test rod. The thermocouples for measuring the cladding surface temperature werestandard industry type K-type thermocouple (Nickel-Chromium / Nickel-Alumel). The
accuracy was ±2.2°C or ±0.75 %, whichever was greater. The thermocouple diameter at the tip
was 0.5 mm. It was attached in contact with the cladding. The measured temperature waspractically the same as the cladding surface temperature according to Quickfield temperature
calculations.
Data logging and permanent storage were done with a frequency of two measurements
per second.
2.2.3. Description of the tests
IFA-650.2 (fresh fuel)The LOCA loop system was checked out with two trial runs using fresh fuel. The
measurements from these runs could be used to calibrate codes to the geometry and dynamics
of the Halden LOCA system before analyzing the outcome of tests with pre-irradiated fuels.
The main rod data of trial run IFA-650.2, which was used by some participants, aresummarized in Table 3.

8

TABLE 3. MAIN DESIGN DATA OF IFA-650.2
Item
Active length (mm)Burnup, (MWd/kgU)

650.2

Enrichment (%)

2

Pellet Diameter (mm)8.29

Diam. Clearance (mm)0.070

Pellet length (mm)Dishing (both ends) (mm)8Land width (mm)1.15

Cladding material

500
0 (fresh)0.20
Zry-4 low tin

Cladding outer diam., (mm)9.50

Cladding thickness (mm)0.57Fill gas/ rt pressure (bar)Helium / 40

3

Plenum volume (cm )15

The rod power was set to 23 W/cm and kept constant during the test. When the target
peak cladding temperature of 1100°C was reached, the rod ballooned and failed as expected.
The main measurements are shown in Figs 5 and 6.

FIG. 5. Temperature in cladding (TCC1-4) and heater (TCH1,2).
The test run showed that the target temperature, which mainly depended on the rod power,
could be achieved with a sufficient accuracy. The volume change due to ballooning was clearlyreflected in the rod pressure data. It also manifested itself in the cladding elongation data (seeFig. 6).

9

FIG. 6. Rod pressure and cladding elongation response to transient.
The test rod was equipped with three cladding thermocouples (TCC 2, 3, 4) attached
10 cm below the upper end of the fuel stack, 120 degrees apart from each other, to check thecircumferential temperature distribution. Fig. 7 shows the respective temperature deviations
from their average. The deviations were approximately ±3 K until the point of ballooning andrupture was reached at about 800°C. A uniform circumferential temperature distribution was
intended in the Halden reactor LOCA tests to maximize ballooning.
In other tests selected for FUMAC, only two thermocouples were attached at the same
axial elevation. A similarly uniform circumferential temperature distribution was observed.

FIG. 7. Circumferential variation of cladding temperature at upper end.
Post-test examinations, IFA-650.2
The gamma scan (the left part of Fig. 8) indicated a ballooning and some fuel protruding
into the opening. The scanning resolution was 5 mm vertically and 1 mm horizontally.
Visual inspection (the right part of Fig. 8) revealed a similar appearance. The opening
was about 35 mm long and 20 mm wide. The pellets, which did not exceed 10 kW/m during
their short irradiation, appeared to be broken into two equal pieces.
The rod developed a bow of about 7 mm, bending in the direction of the burst opening.
Fig. 9 shows the cladding diameter measured at three orientations. The expansion increased
gradually from both ends towards the burst region. The effects of secondary hydriding andoxide thickness, around the burst areas, are indicated in Fig. 10.

10FIG. 8. Gamma scan and visual appearance, IFA-650.2

FIG. 9. Diameter measured at 0, 45 and 135 degrees orientation, IFA-650.2.

11

FIG. 10.

Oxygen and hydrogen distribution after LOCA, IFA-650.2.

IFA-650.9 (PWR)
The fuel was provided by Framatome ANP and had been irradiated in the Swiss NPP
Gösgen to 89.9 MWd/kgU. The rod power was set to 25 kW/m to achieve a target peak cladding
temperature of 1100°C. Due to fuel relocation, the temperature measured with the lower
cladding thermocouple approached 1200°C, and the test was terminated to avoid even higher
temperatures. Cladding failure occurred at about 800°C, which was 130 s after the start of blowdown.
A special feature of this experiment is the strong fuel fragmentation, relocation anddispersal.
Rod characteristics and pre-test irradiation data
TABLE 4. ROD CHARACTERISTICS FOR IFA-650.9
Items

Fuel - as fabricated andirradiatedCladding - as fabricated andirradiatedFree volume - as fabricated12

Properties
Initial enrichment (wt%U235)
UO2 density (g/cm3)
Pellet diameter (mm)Dishing volume (total of bothsides) (mm3)
Burnup (MWd/kgU)
Type
Outer diameter (mm)Thickness (mm)Outer liner (mm)Oxide thickness, irradiated,mean (µm)
Hydrogen content, irradiated,ppm
Fill gas / pressure (bar)Free volume (cm3)

Value
3.5
10.43
9.131

16
89.9
DX Zr2.5Nb (duplex)
10.75
0.725
0.100

7
30
95% Ar + 5% He / 40
19

The pre-test irradiation history for the tested fuel rod in the PWR unit is shown in Fig. 11.

FIG. 11.

Pre-irradiation history for the IFA-650.9 test fuel rod.

In-core measurements
The transient was executed according to the general procedure described in Section 2.2.1
and terminated by a reactor scram and gradual cool-down without reflood. Rod burst occurred
130 s after the start of blow-down.
The principal measurements, i.e., cladding and heater temperatures, rod pressure andcladding elongation, are shown in Figs 12 and 13, respectively. Cladding thermocouples wereattached 100 mm above the lower end (TCC1) and 80 mm below the upper end (TCC2, TCC3).

FIG. 12.

Cladding and heater temperatures, IFA-650.9.

13

FIG. 13.

Rod pressure and cladding elongation, IFA-650.9.

The temperatures at the upper end, as measured by TCC3 (similar to TTC2), started toincrease at about the same time and changed with the same rate as measured by TCC1 at thelower end. At the time of ballooning and burst, the temperature difference between the lower
and upper end was about 35C. However, when burst occurred, the cladding temperatures at
the two ends started to take completely different courses which was attributed to fuel relocation.
Cladding elongation (EC2) and rod pressure (PF1) showed a strong response to the rod
burst about 130 s after the start of blow-down, see Fig. 13. The rod pressure did not drop
instantaneously, but required about 200 s to reach equilibrium with the loop pressure.
The gamma monitor (MON40) on the blow-down line registered the failure as shown in
Fig. 13. The maximum activity of about 120 mSv/h was reached when the experiment was
terminated with a reactor scram.
Post-irradiation examination results
The gamma scan taken after the LOCA test (Fig. 14) showed that the rod wasconsiderably ballooned at the lower end. A ‘hot spot’ at half height is associated with asecondary ballooning.
At the upper end, a plug of two pellets remained while 12.5 cm below contained no fuel.
The balloon, which expanded to the heater limit, was filled with relocated fuel. Fuel had beenejected and was found at the bottom of the pressure flask and in the blow-down line.

14

FIG. 14.

Gamma scan IFA-650.9.

Figure 15 shows the profile of the rod diameter determined by visual inspection. The
expansion of the cladding increased gradually until reached about half-height where asecondary ballooning (no failure) could be seen. Ballooning was indicated continuously to theheater wall of the lower half.
20

D iameter (mm)

18
16
14
12
10
8
0

100

200

300

400

500

600

Length (mm)FIG. 15.

Diameter profile of IFA-650.9.

The neutron radiography picture is shown in Fig. 16. The rod was broken into two pieces
at the location of the primary balloon. Due to transportation and handling after gamma scanning,fuel fragments moved back to what was used to be the upper part where gamma scanningshowed a gap in the fuel stack. Where the fuel stayed in place, the dishing had disappeared
except for a few pellets at the upper and lower ends. In general, the fuel appeared to be
extremely fragmented and could easily be relocated.

15

FIG. 16.

Neutron radiography, IFA-650.9.

The burst opening (see Fig. 17) was about 40 mm long and 7 mm wide (maximum). Two
fuel ceramography pictures are shown in Fig. 18; fine and often oblong fragments have formed.

FIG. 17.

FIG. 18.

Burst opening, IFA-650.9.

Ceramography showing fuel fragmentation, IFA-650.9.

IFA-650.10 (PWR)
The fuel was supplied by EDF/FRAMATOME and had been irradiated in the French
Graveline 5 PWR to 61 MWd/kgU. The target peak cladding temperature (PCT) was 850°C.

16

Rod burst was detected 249 s after the start of blow-down. Minor fuel relocation was
confirmed by gamma scanning and PIE.
Rod characteristics and pre-test irradiation data
TABLE 5. ROD CHARACTERISTICS FOR IFA-650.10
Items

Fuel - as fabricated andirradiatedCladding - as fabricated andirradiatedFree volume - as fabricatedProperties
Initial enrichment (wt%U235)
UO2 density (g/cm3)
Pellet diameter (mm)Dishing volume (total of bothsides) (mm3)
Burnup (MWd/kgU)
Type
Outer diameter (mm)Thickness (mm)Oxide thickness, irradiated,mean (µm)
Hydrogen content, irradiated,ppm
Fill gas / pressure (bar)Free volume (cm3)

Value
4.49
95.32
8.21
n/a (dished)
61
Zry-4
9.50
0.57
20–30

150–220
95% Ar + 5% He / 40
17

The pre-test irradiation history for the tested fuel rod in the PWR unit is shown in Fig.
19.

FIG. 19.

Pre-irradiation history for the IFA-650.10 test fuel rod.

17In-core measurements
The transient was executed according to the general procedure described in Section 2.2.1
and terminated by a reactor scram and gradual cool-down without reflood.
The principal measurements, i.e., cladding and heater temperatures, rod pressure andcladding elongation, are shown in Figs 20 and 21, respectively.
After the burst, the cladding and heater temperatures continued to increase at similar rates.
Extensive fuel relocation was not observed from this experiment. PIE revealed that theballooning and the burst opening were moderate.
Burst was detected 249 s after the start of blow-down. The rod pressure dropped
instantaneously.

FIG. 20.

FIG. 21.

Cladding and heater temperatures, IFA-650.10.

Rod pressure and cladding elongation, IFA-650.10.

The gamma monitor (MON 40) installed on the blow-down line registered the failure asshown in Fig. 21. The maximum equivalent dose rate of 22 mSv/h was reached shortly after the
burst and decayed rapidly.

18

Post irradiation examination
The gamma scan taken after the LOCA test is shown in Fig. 22. The rod was slightly
bowed, with ballooning and a burst opening indicated at an elevation of 200. There was no
indication of fuel relocation in the fuel stack itself, but some fuel had fallen to the bottom of thepressure flask (at elevation 500). The faint gamma signal at elevation 525 and below (thehorizontal lines) stemmed from fuel in the blow-down line.
The neutron radiography picture is shown in Fig. 23. The burst location was covered bysome materials. The dishing and pellet-pellet interfaces were preserved and not smeared out as
in IFA-650.9. Fuel cracks were visible, but not strongly correlated with the burst location.
Fig. 24 indicated the diameter profile determined from visual inspection and neutron
radiography. The cladding expansion increased from the both ends towards the ballooning
location.

FIG. 22.

Gamma scan IFA-650.10.

19

FIG. 23. Neutron radiography, IFA-650.10.

FIG. 24. Diameter profile of IFA-650.10.
The burst opening (Fig. 25) had an axial length of about 15 mm and a maximum width ofabout 5 mm. Fuel fragments were visible through the opening.

FIG. 25. Burst opening, IFA-650.10.
Some cross-section ceramography pictures are presented in Fig. 26. The elevations as
indicated were corresponded to the scale displayed in Fig. 24. Ceramography revealed pellet
fragmentation where the larger fragments seemed to have separated mainly along cracks
stemming from the base irradiation. Fine fragments seemed to be originated from the highburnup structure from the pellet periphery (micrometre size pores within the fragments wereindicated in the bottom left of Fig. 26).

20

FIG. 26.

Ceramography showing fuel fragmentation, IFA-650.10.

IFA-650.11 (VVER)
The fuel, manufactured by JSC TVEL, was supplied by Fortum Nuclear Services Ltd(Finland). The VVER-440 fuel segment had been irradiated in the Finnish Loviisa NPP to aburnup of 56.0 MWd/kgU. The LOCA test was performed at a rod heat rating of 24 W/cm fora target peak cladding temperature (PCT) of 1273 K. The rod failed in 207 s after the start ofblow-down.
Tested fuel rod characteristics are shown in Table 6. The pre-test irradiation history forthe tested fuel rod in the VVER unit is shown in Fig. 27.
Analysis of the IFA-650.9–11 tests by an integral code SOCRAT/V3 (presented in Annex
II) that was nominated to provide T/H boundary conditions for fuel performance codes (seeSection 4.2) has revealed quite a good agreement between the measured and calculated data for
IFA-650.9 and 650.10 tests, However, the cladding and heater temperatures in the IFA-650.11
test were apparently overestimated. Basing on additional parametric calculations to understandthe possible reasons of observed differences in the IFA-650.11 test (see Annex II), a reductionof the rod power to 71% was substantiated and agreed with the CRP participants from Halden
Project.

21

TABLE 6. ROD CHARACTERISTICS FOR IFA-650.11
Items

Properties

Value
235

Initial enrichment (wt%U
Fuel - asfabricated andirradiatedCladding - asfabricated andirradiatedFree volume - asfabricated)

3.6

UO2 density (g/cm3)

10.64

Pellet diameter (mm)7.55

Pellet centre hole (mm)1.484Dishing volume (total of both sides) (mm3)

No dishing

Burnup (MWd/kgU)

56.0

Type

E110

Outer diameter (mm)9.13

Thickness (mm)0.679

Oxide thickness, irradiated mean (µm)

5Hydrogen content, irradiated, ppm

100

Fill gas / pressure (bar)

95% Ar + 5% He / 30

Free volume (cm3)16

FIG. 27.

Pre-irradiation history for the IFA-650.11 test fuel rod.

In-core measurements
The transient was executed according to the general procedure described in Section 2.2.1
and terminated by a reactor scram and gradual cool-down without reflood.
The heater power was increased from 16 to 20 W/cm after the burst to obtain the desired
peak clad temperature.
The principal measurements, i.e., cladding and heater temperatures, and rod pressure areshown in Figs 28 and 29, respectively. The heater had only two TCs, one at the bottom and one

22

in the middle. The third TC was mounted on the outside surface at the axial mid-plane of theplenum.

FIG. 28.

FIG. 29.

Cladding and heater temperatures, IFA-650.11.

Rod pressure and cladding elongation, IFA-650.11.

Burst was detected at about 207 s after the start of the blow-down. The rod pressure
dropped instantaneously after the burst. The gamma monitor installed on the blow-down line
responded to the failure as shown in Fig. 29. The activity peaked at ~30 mSv/h at about 20 safter the burst and decayed rapidly thereafter.
Post irradiation examination
The gamma scan taken after the LOCA test is shown in Fig. 30. The rod was bent. There
were signs of ballooning in the lower half. This ballooning region was filled with fuel, but there23was no sign of fuel on the bottom of the flask. The axial gap at position 90 might have beencaused by fuel relocation.

FIG. 30.

Gamma scan IFA-650.11.

The diameter measurement results are shown in Fig. 31. The cladding expansion was
more pronounced in the lower half and gradually decreased towards the upper end. The axial
shape reflected the temperature distribution along the element where higher temperatures were
measured at the bottom half. The maximum uniform diameter increase was about 20 %.
Neutron radiography, Fig. 32, revealed fuel broken into coarse pieces. The cracking wascorrelated with the radial expansion.
Ceramography revealed the fuel pellet fragmentation, Fig. 33. The pellets were broken
into several large pieces. It could be assumed that the fragments were formed during the baseirradiation in the Loviisa VVER. The fragmentation pattern together with a small burst opening(of about 3 mm long and max. 1 mm wide, Fig. 34) supported the fact that no fuel was detected
at the bottom of the pressure flask.

24

FIG. 31. Diameter profile of IFA-650.11 after the test.

FIG. 32. Neutron radiography, IFA-650.11.

25

FIG. 33. Fuel fragmentation, IFA-650.11.

FIG. 34. Burst opening, IFA-650.11.
2.3. STUDSVIK LOCA TEST (NRC-192)
A series of six out-of-reactor LOCA simulation tests were performed from 2011 to 2012
by Studsvik Nuclear AB, Sweden, under contract with the U.S. Nuclear Regulatory
Commission (U.S. NRC). The tests were done on fuel pellets that had been sampled from fulllength elements with average burnups ranging from 55 to 72 MWd/kgU. All the fuel elements
were of Westinghouse PWR design, with UO2 fuel pellets and first generation ZIRLO (Zr1.03Nb-0.98Sn by wt%) cladding. The tests were designed to assess the mechanicalperformance of ballooned and ruptured high burnup fuel rods under typical LWR LOCA
conditions; useful information on fuel fragmentation, axial relocation and dispersal wereachieved from these tests [7, 8].
2.3.1. Design and operation of the Studsvik LOCA test rig
The design of the Studsvik LOCA test rig is shown in Fig. 35. A single test element withan active length of about 0.30 m was centred inside a quartz tube and externally heated byinfrared radiation from a clamshell furnace. There was no nuclear heating in the tests, and the
rig was placed in a hot cell. The rodlet was heated with steam at atmospheric pressure, and thetest could be terminated by quenching the rodlet with room temperature water.

26

FIG. 35. Design of the Studsvik LOCA test rig [8] .
A typical test started at a temperature of 573 K, the rodlet was heated with a nearly
constant heating rate of 5 Ks-1. The cladding temperature was monitored by a single
thermocouple, attached by a metal clamp and, located at about 50 mm above the axial midplaneof the element. The peak cladding temperature ranged from about 1220 to 1430 K for the six
tests, and the rodlets were held at the peak temperature for 0, 5, 25 or 85 s to achieve various
degrees of oxidation. Following the high temperature hold, two of the tests (189 and 196) were
terminated by switching off the furnace and letting the rodlets cool slowly. In the other four
tests, the rodlets were first cooled with an average rate of 3 Ks-1 to 1073 K, after which they
were quenched rapidly by filling the quartz tube with room temperature water [7, 8].
The test elements were initially filled with helium to pressures between 8.2 and 11.0 MPa
at 573 K. These pressures corresponded to the of internal pressures in PWR fuel rods at the endof-life and were chosen to induce cladding ballooning and rupture with hoop rupture strains in
the range of 30–50%. Rupture typically occurred at cladding temperatures around 950–1000 K,
i.e. significantly below the peak cladding temperatures targeted in these tests.
During the tests, the rod internal pressure was monitored by pressure transducers
connected to the top and bottom ends of the element; see Fig. 35. The internal free volume ofthe pressure lines to the transducers was large: about 7.3 cm3 in the upper end and 3.1 cm3 inthe lower end of the test element. Most of this gas volume remained near room temperatureduring the tests.
After each LOCA simulation test, the element was subjected to a four-point bend test atroom temperature to measure the residual mechanical strength and ductility at the ballooned
and ruptured regions. The two broken halves of the element were then inverted and gently
shaken to dislodge loose fuel pellet fragments. Mass measurements were made before and after

27

the LOCA simulation test, after the bend test and after the shake test to determine the fuelrelease at each stage. After the final stage, the size distribution of the dislodged fuel fragments
was measured for five of those six elements [7–9].
2.3.2. Test rodlet NRC-Studsvik-192
The element used in the NRC-Studsvik LOCA Test # 192 was sampled from the middle
section of a full-length Westinghouse 17×17 PWR UO2 fuel rod with the first generation ZIRLO
cladding, which had been operated to a rod average discharge burnup of 68.2 MWd/kgU during
four reactor cycles at a twin-unit plant in the USA. The first three cycles took place in the firstunit from 1987 to 1994 with a two-year interruption between the first and second cycle. Afterthe first cycle, the fuel rod was removed from the discharged fuel assembly and re-inserted into
a new assembly, which was operated for an additional reactor cycle in the second unit of theplant from 1999 to 2001. This procedure was applied for a total of ten elements in the original
fuel assembly. Some of the other high burnup elements (from the same assembly) wererefabricated into elements and used for other tests by Studsvik Nuclear [10, 11]. The design andpre-test material conditions for Test# 192 are summarized in Table 7.
The pre-irradiation history for the re-fabricated short length elements tested in the two
PWR units is shown in Fig. 36.
TABLE 7. DESIGN DATA AND PRE-TEST CONDITIONS [7], [10]–[12](for the NRC-Studsvik-192 Test rodlet)
Parameter

Value

Rodlet active length (mm)300

Cold free volume (cm3)10.4

Fill gas pressure at 573 K (MPa)235

As fabricated enrichment of U

8.2
(wt%)

3.99

As fabricated fuel pellet density (kgm-3)

10440

As-fabricated fuel pellet diameter (mm)8.192

As-fabricated fuel pellet height (mm)9.830

As-fabricated dish volume per pellet (mm3)4.2Pre-test average fuel burnup (MWd/kgU)

78

Cladding tube design

Monotube

Cladding tube material

ZIRLO

Heat Treatment

SRA

As-fabricated cladding outer diameter (mm)9.500

As-fabricated cladding wall thickness (mm)0.571Pre-test oxide thickness (mean) (µm)

27Pre-test oxide thickness (max) (µm)

30Pre-test hydrogen concentration (wppm)

235

Pre-test fast neutron fluence (> 1 MeV) (m-2)

1.31×1026

Note: The data for the rod design are taken from open literature reports on sibling fuel rodsthat have been used in earlier tests by Studsvik Nuclear AB.

28

FIG. 36.

Pre-irradiation history for the NRC-Studsvik-192 LOCA test rodlet [12].

2.3.3. Summary of test conditions and test results
The important test parameters for the NRC-Studsvik LOCA Test # 192 are summarizedin Table 8. Further details on the test and the results of PIE were given in reference [13].
Temperature, pressure and diametral expansion are indicated in Figs 37 and 38.
TABLE 8. SUMMARY OF TEST PARAMETERS FOR THE [7] [12](for the NRC-Studsvik LOCA Test 192)

Parameter

Value

Initial temperature (K)Initial rod pressure (at 574 K) (MPa)

574
8.21

Cladding temperature at failure (K)981

Peak cladding temperature (PCT) (K)
Hold time at PCT (s)1446
5Steam mass flow (kgs-1)

1.8×10-4

Timing of events (after start of heating):
Cladding tube failure (s)81Hold at PCT (s)173–178

Quenching (s)

297

29

FIG. 37.

Experimental data during test (pressure/temperature) for Studsvik Test # 192.

FIG. 38.

Profilometry after test (Studsvik Test # 192).

2.4. KIT QUENCH-L1 BUNDLE TEST
Test QUENCH-LOCA-1 (QUENCH-L1) with electrically heated bundle (tantalum (Ta)heaters inside each 21 rods) was performed in accordance with a temperature/time-scenario thatwas typical for a LBLOCA in a German PWR with maximal heat-up rate of 7 K/s during atransient. During the transient, a gas mixture of steam (at 2 g/s) and argon (at 6 g/s) was injectedfrom the bundle bottom. The cooling stage was performed in steam (20 g/s) and argon (6 g/s)
during the lasted 120 s and terminated by flooding with 3.3 g/s of water per fuel element. The
maximal temperature of 1373 K was reached at the end of the heat-up phase at an elevation of30

850 mm. The details of the QUENCH facility and the test procedure could be found from theparticipant final report (see Annex II).
The test results were as follows: The decreased yield strength and increased ductility of
the heated claddings with increasing temperature resulted in a progressive ballooning andconsequent burst of all elements during the transient. Due to prototypical internal heating andenhanced heat transfer at the contact between pellet and cladding, the non-uniform heating had
caused thinning on one-side of the cladding during ballooning. In accordance with the ultrasound results, the cladding wall thickness was varied from 725 to 350 µm at about 50 mm below
and above the burst opening.
The cladding burst occurred at temperatures between 801 and 896 °C, with an averagevalue of 853 ± 30 °C. The inner rod pressure was relieved in less than 40 s. The average linear
burst opening dimensions were 4.2 ± 2.6 mm in width and 15 ± 6 mm in length. These opening
sizes were quite small for the release of pellet fragments.
Element bending of up to 23 mm was observed for several rods (as the axial expansion
was restricted by the heaters). The average cladding strain at the burst opening location was
about 30 ± 6% including the opening width (or about 20 ± 5% only for cladding perimeter
without opening). At a cladding location of about 15 mm above and below the opening, thecladding diameter was minimal and the difference between maximal and minimal cladding
diameters was up to 0.5 mm.
The maximum blockage of ~24% was observed for cooling channels at an elevation of
950 mm. If hypothetically all breaks were to locate at the same level, the blockage would be
46%. The 46% was still enough to maintain bundle coolability. According to the REBEKA tests[14], a flow blockage of up to 90% was still acceptable.
After the burst, the steam penetrated the gap (between cladding and pellet) and oxidized
the inner surface of the cladding. The hydrogen diffused partially into the cladding (secondary
hydriding) and built asymmetrical bands above and below the burst opening. Like thecommissioning test QUENCH-L0 [15], the oxide layer thickness on the inner cladding surface
was measured up to 25 µm at burst elevations and less than 2 µm at hydrogenated bands.
No hydrogen bands around the burst openings were observed by means of neutron
radiography for outer elements. The maximum hydrogen content in cladding, with a crosssection area of about 25  25 µm2, inside the hydrogen bands of inner elements varied between
700 and 1800 ppm. It is comparable with values predicted by the SVECHA/QUENCH
mechanistic code [16]. Concentration of hydrogen dissolved in metallic matrix was estimatedas < 300 ppm.
During quenching, following the high-temperature phase, no fragmentation of claddings
was observed. This implies residual strengths or ductility was sufficient.
During tensile tests at room temperature, all thirteen tested claddings were fractured due
to stress concentration at the burst position. This observation was similar to elements of the
QUENCH-L0 bundle with maximum hydrogen concentrations of < 1500 ppm. For the central
element (#1) with a maximum hydrogen concentrations of > 1500 ppm, the element was brittle
at the hydrogen bands and was damaged when pulling it out of its heater.
2.5. CORA-15
The CORA-15 bundle test was performed under transient conditions typical for many
CORA-PWR tests with bundle containing two Ag-In-Cd neutron absorber rods. Unlike other
CORA bundles, all heated and unheated fuel rod simulators (16 + 7 correspondingly) werefilled with helium and pressurized to 6.0 MPa before transient. During the transient, all rods
underwent ballooning and burst. Ballooning progressed for about 100 s. Bursts occurred within
150 s (between 3500 and 3650 s) in the temperature bandwidth between about 700 and 800 °C.

31

The mostly probable burst elevation for the bundle was at 750 mm (which was the hottest
elevation during the burst period).
During further heat-ups, temperature escalation due to the zirconium-steam reaction starts
at elevations of 550 to 950 mm at temperature of about 1100 °C. In presence of PWR absorberrods, the sequence of failure starts with the release, relocation and re-solidification of the (Ag,In, Cd) melt. The melt release occurred between 1290 and 1350 °C at elevations between 750
and 800 mm. Most of the melt reacted with the cladding and guide tube by liquefying thezirconium components, forming a metallic melt of the type (Ag, In, Zr). This melt was capableof dissolving Zircaloy as low as 1250 °C, i.e. clearly below the melting point of Zircaloy(1760 °C).
During the temperature escalation above 1800 °C, Zr melt formed in the gap between
ZrO2 and UO2 was relocated partially inside the gap to lower bundle elevations and partiallypenetrated through the failed ZrO2 layer into the space between its neighbouring elements. The
resulting melt of the fuel rod interaction, containing mainly U, Zr and O relocated downwards
as a slug and solidified between 400 and 550 mm according to its solidus temperature as a large
lump of porous structure. The maximum bundle blockage (almost 100%) was observed at the
top of the Inconel grid spacer (at about 500 mm). The (Ag, In, Cd) absorber melt with the much
lower solidus temperature solidified down at the lower elevation of about 150 mm.
Post-test investigations showed negligible oxidized cladding up to elevation of about
350 mm. The claddings were completely oxidized between elevations 480 and 1000 mm. The
maximum hydrogen release rate of 210 mg/s was measured on the end of the transient (4800 s).
The total hydrogen release was 145 ± 15 g.
Based on the CORA-15 experimental data, computer codes ATHLET-CD and SOCRAT
were used for a benchmarking exercise. Corresponding descriptions of code applications arepresented in Sections 3.3.1 and 3.3.3; the comparison of simulation results is given in
Section 4.5.
In the framework of the FUMAC project, the implementation of a slug
relocation/oxidation model in the single-rod SFPR code (IBRAE) demonstrated the possibilityof extending the fuel performance codes to severe accidents (see Annex II).

32

3. DESCRIPTION OF CODES AND MODEL IMPROVEMENTS
3.1. SINGLE FUEL ROD CODES
3.1.1. FRAPTRANFRAPTRAN code is a fuel rod transient analysis code, designed to calculate the thermal
and mechanical behaviour of a LWR single fuel rod during hypothetical accident and operationtransients such as reactivity insertion accidents (RIA) or loss-of-coolant accidents (LOCA), andpower oscillations without scram.
The latest version FRAPTRAN-1.5 was released in May 2014. The code was describedin [17] and an integral assessment was performed in [18]. This standard version has been usedby several participants. Several improvements have been made to FRAPTRAN code during the
FUMAC project.
SSM/QT-version of the fuel rod analysis program FRAPTRAN-QT-1.5
In a recent project funded by the Swedish Radiation Safety Authority (SSM), Quantum
Technologies AB developed a computational model for axial fuel relocation under LOCA [19].
The relocation model has been fully integrated with an in-house SSM/QT-version of the fuelrod analysis program FRAPTRAN 1.5. In contrast to earlier relocation models for fuel rod
analysis programs (such as the one developed by SCK•CEN [20]), the model consideredthermal feedback effects from the fuel relocation. It also uses sub-models to estimate thepacking fraction and effective thermal conductivity of particle beds formed by crumbled fuelin ballooned regions of the fuel rod, based on the estimated state of fragmentation andpulverization of the fuel pellets. Models in the SSM/QT-version of FRAPTRAN 1.5, including
the fuel relocation model, were validated against recent LOCA tests in Halden and Studsvik[20].
Tractebel-version of the fuel rod analysis program FRAPTRAN-TE-1.5
Tractebel requested the SSM/ Quantum Technologies to implement their model in theTractebel version of FRAPTRAN-1.5 [22–24] and to perform further model validation andimprovements. The extensions and adaptations in the FRAPTRAN-TE-1.5 code were
documented in the SSM/ Quantum Technologies report [25].
The correctness of the code changes had been verified by comparing calculated resultswith simple analytical solutions. In addition, FRAPTRAN-TE-1.5 had also been validated
against three LOCA simulation experiments in the Halden IFA-650 test series. The results ofthese tests are summarized, and recommendations for further testing and for using different
modelling options in FRAPTRAN-TE-1.5 program are given in Ref. [25].
3.1.2. TRANSURANUS
TRANSURANUS is a computer programme written in FORTRAN95 for the thermal andmechanical analysis of fuel rods in nuclear reactors that is owned by the Joint Research Centreof the European Commission. TRANSURANUS has been used by research centres, nuclear
safety authorities, universities and industrial partners, (see Refs [26–38]).
International benchmark exercises are of high importance for developing simulation
systems of various nuclear reactor components. One of the main benefits of this CRP is thepossibility for cross-comparison and complementary validation of many codes involved.
Several exercises were organized during the last 3 decades: D-COM in the mid 80's, FUMEXI from 1992 to 1996, FUMEX-II from 2002 to 2006 and FUMEX-III from 2008 to 2012.
TRANSURANUS is generally referred to as a fuel performance code meaning that it
solves the equations for the radial heat transfer, the radial displacement along with the stress
distribution in both the fuel and its surrounding cladding, and the release of fission product and33

its behaviour as a function of time. The equations, in general for fuel performance prediction,
embody the following phenomena:
Thermal performance: heat conduction, radiation and convection;
Mechanical performance: creeps (radiation and high temperature), densification, thermal
expansion, pellet cracking and relocation, solid and gaseous swelling;
Actinide behaviour: depletion and build-up of main Th, U, Np, Pu, Am and Cm nuclides,
impact on the radial power profile;
Fuel restructuring: Pu and Am redistribution, grain growth (normal and columnar),central void formation;
Fission product behaviour: creation in the fuel matrix, diffusion to grain boundaries,
release to free rod volume after saturation of grain boundaries, athermal release, recoil,formation of High Burnup Structure (HBS, which is depleted and contain porosity).
The heat transfer in the fuel-to-cladding gap is simulated by means of a combinationof heat conduction, radiation and convection (URGAP model [39]). Main assumptions andequations for mechanical performance are provided in Ref. [27].
Main assumptions and equations for actinide concentrations could be found in Refs
[37, 38].
In the TUBRNP model the calculation of the radial power profiles is split into (a) the
approximation of the neutron flux through thermal diffusion theory, and (b) the computation of
the local concentrations of the relevant actinide isotopes with simplified depletion equations.
The most recent extension covers the nuclides 232Th, 233-236,238U, 237Np, 238–242Pu, 241Am, 243Am,
242–245
Cm. More details are given in Ref. [40].
The TRANSURANUS code consists of a well defined mechanical and mathematicalframework, which additional physical models can easily be incorporated. The code has acomprehensive material data files for oxide, mixed oxide, carbide and nitride fuel types,
Zircaloy and steel claddings and several different coolants (water, sodium, potassium, lead,bismuth). TRANSURANUS can be used as a single code system for simulating both long-term
irradiations under normal operating conditions as well as transient tests. The 'restart' mode
allows simulating re-fabricated (recycled) fuel rods, where the fill gas has been completelychanged as an example.
The code can be employed in two different approaches: as a deterministic or a statisticalcode. Restart may be used to perform a statistical analysis employing the Monte Carlotechnique. This option may be helpful for the analysis of a long base irradiation then followed
by a transient. Fig. 39 gives an overview of these possibilities.
Besides its flexibility for fuel rod design, the TRANSURANUS code can deal with a wide
range of different situations, as demonstrated in experiments, under normal, off-normal andaccident conditions, although some models specific for RIA (e.g. plenum temperature) are still
under development. Furthermore, the code is being used for BWRs, PWRs and VVERs. The
time scale of the problems to be treated may range from milliseconds to years. Hence complex
irradiation experiments can be simulated including re-fabricated instrumented fuel rods andchanging operating conditions.

34a) deterministic analysis; multiple restarts
2

2

INTRUP = 1

restartrestart22

restartrestartTimeb) Monte Carlo statistics

Timec) Combination of restart and Monte Carlo statistics
INTRUP = 1

2

restartTime

FIG. 39.

An illustration of deterministic and probabilistic approaches with restarts.

3.1.3. ALCYONE
ALCYONE [41] is a multi-dimensional fuel performance code co-developed in the
PLEIADES [42]platform by the CEA, EDF and AREVA. It is dedicated to the modelling of thein-reactor behaviour of PWR fuel rods during normal (the base irradiation) and off-normal (withpower ramp and transient) operating conditions. ALCYONE has incorporated three calculation
schemes. A one-dimensional reference scheme, based on a symmetric description of the fuelelement with a discrete axial composition of the fuel rod in a stack (i.e. slumping), is used to
study the behaviour of the complete fuel rod [43]. A two-dimensional scheme, which describes
Pellet-Cladding Interaction (PCI), to assess stress concentration in the cladding near a pellet
crack tip [44]. A three-dimensional model with a complete pellet fragment for a detail analysisof PCI at the pellet-cladding interfaces [45]. These schemes use the Finite Element (FE) code
(Cast3M) to solve the thermo-mechanical problem and share the same physical material models
at each node or integration points of the FE mesh. Fig. 40 presents the flows chart of ALCYONE
1D. This Fig. identifies difference convergence loops in blue, the thermal-physical models inbeige and the other models are in green if they are calculated before the thermal physical loop
or in grey pink if after.
ALCYONE has been extensively validated for PWR rods (UO2 and MOX fuel up to 80
GWd/tM with Zry-4 or M5 cladding) under base-loaded irradiation during the French survey
program. Power ramp tests performed in MTR are used to validate the behaviour of the fuel rod
in case of power transients. Fuel temperature calculations are validated specifically by a MTR
experiment, which has a representative thermocouple located at the fuel center [43].

35

FIG. 40.

ALCYONE flow chart.

The coupling of ALCYONE [46] with the system code CATHARE will be available soon.
For LOCA analysis, the evaluation of the rod internal pressure is crucial. The evaluation of thequantity of fuel which could be fractured during the accident phase (i.e. at least the fuel zone
which are restructured) is also important. These calculations are performed by two fission gas
models CARACAS [47] or MARGARET [48].
The EDGAR model [41] describes the viscoplastic behaviour of a zirconium alloy tube
under a pressure (an imposed loading) and at a high temperature (more than 950 K). This model
also gives the phase fractions evolution (alpha, beta and a transition phase are considered).
The EDGAR model is established as a point model in a Finite Element 3D calculation
tool. The mechanical analysis and definition of the mechanical constitutive equations are
discussed in detail in Ref. [42].
The mechanical behaviour is expressed in the logarithmic strain framework proposed byMiehe et al [45]. The EDGAR experiments are being simulated using ALCYONE to validate
this implementation.
The 1D code generally considers that for a solid pellet, the radial displacement of thecentral point is not permitted. In case of LOCA, the thermal gradient is significantly lower, thegap is considered as open. One may consider that the central point of the pellet is able to move
radially.
Figure 41 presents stress distribution in the pellet when the gap is open under cold
conditions at the end of a base irradiation. During a LOCA, stresses distribution is likely to bein the same shape, as the thermal gradient remains low in the fuel pellet. Nevertheless, the actual
value of the stress level depends on the fission gas swelling contribution and the irradiation
power history.

36

FIG. 41.

Hydrostatic stresses distribution in the pellet at room temperature.

The fission gas model used in the ALCYONE calculations is CARACAS [47], which
considers the following fission gas populations: nanometric intragranular bubbles, precipitatedintragranular bubbles, intergranular bubbles, rim structure formation and rim bubbles evolution.
This model is validated for base irradiation and power ramp conditions for UO2 up to 70
GWd/tM.
During the first part of the LOCA transient, fuel temperature remains low enough to affectonly the intergranular gas diffusion. A specific criterion for the initiation of intergranularfracture has been developed. It is based on the evaluation of stress applied to grain boundary
resulting from macroscopic hydrostatic stress and from stress induced by over-pressurizedintergranular bubbles (tensile stress). If the tensile stress on the grain boundary induced byintergranular bubbles is higher than the grain boundary yield stress, partial or total fracture of
the grain boundaries is possible. This allows a connected path for fission gas release. One has
also assumed that grain boundary yield stress is reduced by irradiation (fission gas atoms
dissolved on the grain boundary).
3.1.4. BISONThe US Department of Energy (DOE) has been developing capabilities to simulate
nuclear fuel behaviour within the Nuclear Energy Advanced Modelling and Simulation(NEAMS) and Consortium for Advanced Simulation of Light Water Reactors (CASL)
programs. The result is the BISON code [49], a multidimensional, finite-element based fuelperformance code developed at Idaho National Laboratory (INL).
BISON is built using the INL Multiphysics Object-Oriented Simulation Environment, or
MOOSE [50]. MOOSE is a massively parallel, finite element-based framework to solve
systems of coupled non-linear partial differential equations using the Jacobian-Free Newton
Krylov (JFNK) method. BISON can use 1D, 2D or 3D geometric representation to analyze theglobal fuel element behaviour including local multidimensional effects. BISON’s ability to use
massively parallel computing allows for analyzing integral fuel rods in 2D for a detailed
irradiation history as well as for large 3D problems. BISON has been applied to a variety offuel types including LWR fuel rods, TRISO particle fuel, fast reactor oxide fuel, and metallic
fuel in both rod and plate geometries. The code is applicable to both steady-state and transientconditions and is used for the analysis of fuel behaviour during both operational and designbasis accident conditions.
Most recent applications of BISON include 3D analysis of BWR fuel with missing pellet
surface (MPS, as manufacturing defects), analysis of accident tolerant fuel (ATF concepts, suchas FeCrAl cladding and U3Si2 fuel), and design calculations for a new Halden experiment (IFA800) that investigates MPS effects. Details are given in separate publications.

37

The BISON governing equations consist of fully-coupled partial differential equations forenergy, species, and momentum conservation. Nonlinear kinematics in BISON follows theapproach described in [51].
Material models are included in BISON for UO2 fuel to describe temperature and burnup
dependent thermal properties, solid and gaseous fission product swelling, densification,
cracking, pellet-fragment relocation, thermal and irradiation creep [50, 52]. Fission gas swelling
and release are calculated using the model described in Reference [53]. For Zircaloy cladding,models are available for thermal physical properties, instantaneous plasticity, thermal andirradiation creep, irradiation growth, oxidation, as well as cladding phase transition, ballooning
and burst failure during LOCAs. Gap heat transfer is modelled in the traditional manner withthe total conductance across the gap computed as a sum of the gas conductance, the increased
conductance due to solid-solid contact, and the conductance due to radiant heat transfer.
Mechanical contact between materials is implemented using node/face constraints [49, 52].
A variety of other material models are available in BISON. These include fuel models for
MOX, U3Si2, U-Pu-Zr and U-10Mo, and cladding models for HT9, 316 and FeCrAl claddings.
The BISON models are described in more detail in Ref. [52].
For BISON an extensive set of code verification problems exists, from fundamental finite
element solid mechanics and heat transfer tests, to problems specific to nuclear fuel models. In
addition to code verification, the numerical accuracy of the solution is performed. For thispurpose, simulations with representative validation-problem features were spatially andtemporally resolved and the results compared.
Validation work for BISON has focused initially on LWR fuel during normal operating
conditions and power ramps [54,55]. In recent years, significant work has also been performedon the analysis of design-basis accident scenarios (DBAs), including both LOCA [56, 57] andRIA [58, 59]. For TRISO particle fuel, several benchmark cases have been considered which
compare BISON results to those from other fuel performance codes [55] [60].
BISON has incorporated a large-strain mechanics formulation, essential to correctly
analyze cladding ballooning during LOCAs. In addition, specific material models for the hightemperature, transient phenomena involved in fuel rod behaviour during LOCAs.
Specifically, models are implemented in BISON for high temperature cladding oxidation,
Zircaloy solid-solid phase transformation, Zircaloy high temperature creep, and cladding burst
failure [56, 57]. In addition, BISON’s model of fission gas swelling and release in UO2 wasextended to include a specific treatment of the burst release effect during transients [61, 62].
This capability can potentially be adapted and applied to the simulation of LOCA transients.
Also, models for cladding oxidation energy deposition and axial fuel relocation have recently
been implemented and will be applied in future LOCA simulations with BISON.
The extended BISON code has been applied to simulations of LOCA experiments,
including many separate effects tests from the PUZRY, REBEKA and Hardy experiments aswell as integral fuel rod experiments including QUENCH L1 rods 4 and 7, NRU-MT4 and
MT6A tests, and Halden IFA-650.2 and IFA-650.10 tests. Details and simulation results can befound in [55].
BISON models for LOCA analysis and results for the simulations of the FUMAC cases
are presented in detail in the final report on INL’s contribution to FUMAC (see Annex II).
3.1.5. DIONISIODIONISIO 2.0 is a code able to simulate a fuel rod in extended burnup conditions.
Particularly, in the high burnup range, when the inventory of the more relevant isotopes and themicrostructure at the pellet periphery are described.
The code results have been compared with 34 experiments published in the IFPE database, covering more than 380 fuel rods irradiated up to average burnup levels of 40-60

38MWd/kgU. The results of these comparisons are satisfactory and reveal the good quality of thesimulations. They were performed within the frame of the IAEA Research Project FUMEX III.
The diverse models have been explained in detail in several papers [63–67].
In the framework of the Research Project FUMAC, the application range of the code isexpanded to conditions typical for LOCA. To this end, a new module able to reproduce thethermal-hydraulic conditions in the coolant has been developed. This module is intended toaccount for numerous parameters that govern the heat exchange between the fuel rod and thecoolant in accident situations, thus providing the boundary conditions necessary to simulate thefuel rod behaviour during a fast excursion.
3.1.6. FTPAC and FTPAC - ABAQUSFTPAC consists of models calculating the behaviour of LWR fuel rods under transientconditions, which simulates the following processes [68]:Heat conduction from fuel pellet to coolant through gas gap-cladding and claddingcoolant;
Fuel pellet cladding deformation;
Fuel rod gas pressure history;
and cladding oxidation evolution.
The fuel pellet deformation model is used to calculate the fuel stack length change andfuel radial displacement. If the fuel pellet and cladding is in contact, there will be pelletcladding mechanical interaction (PCMI). The fuel deformation model will apply a driving force
to the cladding deformation model. A slip coefficient is calculated to decide the extent of
cladding elongation transmitted by axial expansion of fuel pellet stack. The larger the contactpressure is, the bigger the slip coefficient is. The slip coefficient is associated with friction
factor and interface area between fuel pellet and cladding.
If the cladding effective plastic strain is greater than the cladding instability strain, theballooning model is used to calculate the localized large deformation of cladding. Large
deformation model calculates the extent and shape of the cladding ballooning node. Anotherballooning model is added to FTPAC code recently by coupling ABAQUS [69]. The coupledcode calculation framework is illustrated in Fig. 42.
Deformation and stresses under large deformation condition in the cladding are calculatedusing an ABAQUS model which considers the cladding to be a thick cylindrical shell loadedwith specified internal and external pressures and a prescribed uniform temperature [70]. The
deformation result from the ballooning model is fed back to the main program FTPAC used for
subsequent calculation.
The cladding-steam reaction is modelled by means of kinetic correlations for both theoxygen mass gain and the ZrO2 layer thickness growth. A few experiments were selected todemonstrate the specific models in FTPAC are working correctly. The selected tests were the
IFA-432, FA-513, IFA-507, NSRR and CABRI experiments [71]. The experimental data weresuccessfully used to compare against the FTPAC prediction as a function of time.

39

Start

Thermal-mechanical calculation

Ballooning？

Yes
D, T,P, t

No
Gas Pressure
calculation

ABAQUSσ,εABAQUS ballooning model

Yes

Next Step
No
End

FTPAC

FIG. 42.

The calculation framework of FTPAC coupled ABAQUS.

3.1.7. RAPTA-5.2
Organization-developer of the code RAPTA-5.2 is A.A. Bochvar High-Technology
Research Institute of Inorganic Materials (JSC "VNIINM"). RAPTA-5.2 is a licensing code for
VVER fuel rods used by JSC "VNIINM" to model fuel rods behaviour in design basis accidents.
The code determines the fuel rod characteristics and verifies the fuel safety criteria such as:
maximum fuel temperature, peak fuel enthalpy, peak cladding temperature, number of failed
rods, cladding oxidation and hydrogen production.
The RAPTA-5.2 code was approved, and licensed by the Federal Environmental,
Industrial and Nuclear Supervision Service of Russia, to extend its applicability up to a burnup
of 75 MWd/kgU [72].
The RAPTA-5.2 code solves the thermal-mechanical deformation of LWR fuel rods
during fast transients such as LOCA and RIA accidents. The following physical phenomena aremodelled:a) Heat transfer in fuel rod by considering:Transient power generation in the fuel volume (input data) accounting for the radial power
distribution at various burnups;
Surface thermal effect due to zirconium oxidation in steam;Transient boundary conditions (time stepping) on the cladding surface (input data);
Changes in the geometric cross-sectional area of the fuel rod;Material properties at high temperatures and burnups considering the radial power
distribution;
Change in the fission gases content, release and pressure in the fuel rods during a transient.
b) Geometry in fuel rod by considering:40

Boundary conditions before the initiation of an accident with accumulated burnup (inputdata);
Thermomechanical deformations of fuel and cladding, considering fuel-cladding
interaction, during steady and transient states;
Fuel swelling and FGR during steady and transient states;
Cladding rupture as the result of excessive strains;
Zirconium oxide thickness on the cladding outer and inner (after rupture) surfaces.
c) Cladding oxidation under non-isothermal conditions, with feedback from heat releaseand hydrogen generation.
Temperature and irradiation will affect the material properties during normal operation
prior to the initiation of an accident. For calculating the cladding deformation kinetics under
non-steady state conditions, such as temperature and non-linear contact, the flow stress andstrain of E110 alloy also considered is the effect of annealing on radiation damages [73–75].
To analyze the cladding depressurization under internal overpressure, the deformation criterion
is used [4].
The steam-zirconium reaction is calculated using weight gain. Conservative and realistic
dependencies derived for electrolytic and sponge based E110 alloy could be used. CathcartPawel or Baker-Just correlations are considered as optional. The ECR and integral weight gainof oxygen are determined taking into the consideration cladding deformation. In case of
cladding rupture, the oxidation of the cladding inner surface is also considered for determining
the total amount of hydrogen gas being generated. The thermal effect due to the steamzirconium exothermic reaction is also included when solving the heat transfer problem.
3.1.8. SFPRThe SFPR code [76] for mechanistic modelling of single fuel rod behaviour under various
regimes of LWR reactor operation (normal and off-normal, including severe accidents) is underdevelopment at IBRAE (Moscow). The code is designed by coupling of the two stand-alone
mechanistic codes MFPR (for mesoscale modelling of irradiated UO2 fuel behaviour and fission
products release, in collaboration with IRSN, Cadarache) [77, 78] and SVECHA/QUENCH, or
S/Q (for modelling of fuel rod thermo-mechanical and physico-chemical behaviour, incollaboration with KIT (former FZK, Karlsruhe) experimentalists [79, 80], intensively
developed during the last two decades. Coupling of the two codes allows mechanistic modellingof LWR fuel element behaviour in steady, transient and abnormal conditions.
The main physical models of the two codes were adapted and used in the Russian bestestimate integral code SOCRAT (see Section 3.3.2) designed for analysis of DBA and DEC at
Nuclear Power Plants. For this reason, SOCRAT was used in FUMAC benchmark exercises on
simulation of the reactor tests IFA-650.9–11 and integral bundle test CORA-15, whereas SFPR
was applied to analysis of cladding oxidation and secondary hydriding measured in IFA-650.2
test (see Annex II). Besides, SFPR was further developed for description of corium melt
relocation and oxidation during core degradation observed in CORA tests by implementationin the code of the molten corium slug relocation/oxidation model [81], demonstrating
possibility of a fuel performance code extension to severe accident conditions (one of the goalsof the FUMAC Project), as presented also in Annex II.
3.2. COUPLED THERMAL HYDRAULIC AND FUEL ROD CODES
3.2.1. MARS-KS
The MARS-KS (Multi-dimensional Analysis of Reactor Safety) code has been developedby KAERI for a multi-dimensional and multi-purpose realistic thermal-hydraulic system
41

analysis of light water reactor transients. The backbone of the code has been built by unifying
and restructuring the RELAP5/MOD3 and COBRA-TF1 codes. The MARS-KS code has thecapability of analyzing a one-dimensional and three-dimensional thermal-hydraulic system aswell as the fuel responses of light water reactor transients. Many improved models andcapabilities were added to the code, and the latest version of the series is the MARS-KS 1.4.
Notable upgrades include 3-dimensional simulation capabilities incorporated into the latest
version with a turbulent mixing model and a conduction model. MARS-KS has been mainly
used for regulatory activities by Korea Institute of Nuclear Safety (KINS) [82–84].
To develop the MARS-KS/FRAPTRAN code system, the coupling methodology should
be developed, because each code system has already been used and validated with their own
methodology (see details in Annex II). FRAPTRAN2.0 code was modified as S-fraptran
module for implementation into MARS-KS. To couple the variables of two codes, a newmodule (MARSLINK) was created in S-FRAPTRAN.
As shown in Fig. 43, a coupling methodology for steady state and transient analyses bymaintaining each calculation flow and I/O (Input/Output) system is developed.

FIG. 43.

Methodology of fully coupled MARS-KS/FRAPTRAN.

Coupling variables between MARS-KS and FRAPTRAN are shown in Table 9. For thecurrent time step, MARS-KS calculates the time increment, LHGR, coolant pressure, heattransfer coefficient, and coolant temperature. All variables are stored for S-FRAPTRAN
calculation. Subsequently, S-FRAPTRAN calculates the deformed cladding diameter, heat flux,and cladding surface temperature. Those variables are also stored for MARS-KS calculation for
the next time step.
The fuel module requires power and thermal hydraulic boundary conditions at the surfaceof the outer cladding to calculate the thermo-mechanical behaviour of fuel during a LOCA. In
addition, the coolant pressure affects the cladding deformation. The system code requires theouter diameter of the cladding and heat flux considering the radial burnup distribution, gap
conductance, and metal water reaction energy. All variables are stored in the module andupdated at each time step.

42

TABLE 9. COUPLED VARIABLES OF MARS-KS/FRAPTRAN CODE SYSTEM
Calling module

S-fraptran

MARS-KS

Variable nameContent

Timeincrement
Power
CoolPress
Htc
Tbulk
OutdiaHeatflux
Tsurf

Size of Time step
Linear Heat Generation Rate (LHGR)
Coolant pressure
Heat transfer coefficient of cladding surface
Coolant T
Cladding outer diameter (incl. oxide thickness)
Cladding heat flux
Cladding surface T

3.2.2. GENFLO-FRAPTRAN
The single-rod transient fuel performance code FRAPTRAN developed by PNNL for
U.S.NRC [85], has been coupled with the thermal hydraulics code GENFLO, developed at VTT[86, 87].
GENFLO is a fast running program due to its non-iterative solution model of the thermal
hydraulics equations. The coupled code has been verified against the experimental results fromthe Halden project IFA-650 LOCA tests [88]. The principles and models used during the LOCA
are based on the SMABRE code developed at VTT [89]. The coupled code, FRAPTRANGENFLO, has been previously applied in [90, 91].
3.3. SEVERE ACCIDENT CODES
3.3.1. ATHLET-CD
The system code ATHLET-CD (Analysis of THermal-hydraulics of LEaks andTransients with Core Degradation) [92] describes the reactor coolant system thermal-hydraulicresponse during severe accidents, including core damage progression as well as fission productand aerosol behaviour, to calculate the source term for containment analyses and to evaluate
accident management measures. It is developed by GRS in cooperation with IKE, Universityof Stuttgart. ATHLET-CD includes also the aerosol and fission product transport code
SOPHAEROS, developed by IRSN, and is coupled with the GRS code COCOSYS formodelling thermal-hydraulics and iodine behaviour in the containment.
The code structure is highly modular to include a manifold spectrum of models and tooffer an optimum basis for further development (see Fig. 44). The ATHLET code comprises athermo-fluid-dynamic module, a heat transfer and heat conduction module, a neutron kinetics
module, a general control simulation module, and a general-purpose solver of differential
equation systems called FEBE. The thermo-fluid-dynamic module is based on a six-equation
model, with fully separated balance equations for liquid and vapor, complemented by massconservation equations for up to 5 different non-condensable gases and by a boron tracking
model. Specific models for pumps, valves, separators, mixture level tracking, critical flow etc.
are also included in ATHLET.
The rod module ECORE consists of models for fuel rods, absorber rods (AgInCd andB4C) and for the fuel assemblies including BWR canisters and absorbers. It describes
mechanical rod behaviour (ballooning), Zr-alloy and B4C oxidation (Arrhenius-type rateequations), Zr-UO2 dissolution and melting of metallic and ceramic components. Melt
relocation (candling) is simulated by rivulets with constant velocity and cross-section, startingfrom the node of a rod failure. The models allow oxidation, freezing, re-melting, re-freezing
and melt accumulation due to blockage formation. Feedback to the thermal-hydraulics

43considers steam starvation and blockage formation. Besides convective heat transfer, energy
can be exchanged by radiation amongst fuel rods and to surrounding core structures.
The release of fission products is modelled by rate equations or by a diffusion model
within the module FIPREM. The transport and retention of fission products and aerosols in thereactor coolant system are simulated by the module SOPHAEROS. For the simulation of debris
bed, a specific model MEWA can be applied, with its own thermal-hydraulic equation system,
coupled to the ATHLET fluid-dynamics on the outer boundaries of the debris bed. The
transition of the simulation of the core zones from ECORE to MEWA depends on the degreeof degradation in the zone. Finally, the code also comprises late phase models for coreslumping, melt pool behaviour in the lower plenum and vessel failure within the module AIDA.
The code validation is based on integral- and separate-effect tests, as proposed by the
CSNI validation matrices, and covers thermal hydraulics, bundle degradation as well as releaseand transport of fission products and aerosols. They include out-of-pile bundle experiments
performed in the CORA and in the QUENCH facility as well as in-pile experiments performedin the PHÉBUS or in the LOFT facility. The TMI-2 accident is used to assess the code forreactor applications.

FIG. 44.

Modular structure of the system code ATHLET-CD.

3.3.2. SOCRAT
Code SOCRAT is designed for safety assessment of NPP with LWR under severe
accident conditions [93]. At in-vessel stage of severe accidents, the following general processes
are considered (Fig. 45): core uncover and heat up; radiative and convective heat transfer inside
the core and between the core and surrounding the in-vessel structures; deformation and burst(collapse) of fuel rod claddings; release of fission products from solid fuel into reactor coolant
system (RCS); coagulation, transport and deposition/resuspension of fission products in RCS;
oxidation of fuel rod claddings, absorbers and steel structures in steam or air; fuel degradation(dissolution of UO2 and ZrO2 by solid and molten Zr, failure of ZrO2 protective layer; meltingof oxides); fission product release from molten fuel; material relocation (formation of eutectics
U-Zr-O, SS-Zr, SS-B4C; candling down of liquid masses; collapse of fuel rods with formationof debris bed; formation and spreading of molten pools; relocation of corium to lower plenum);
melt oxidation, especially containing liquid Zr; account for failure of RCS boundaries (hot leg
nozzles, surge-line of pressurizer, SG tubes); fuel-coolant interaction in lower plenum;44

behaviour of molten corium inside RPV (convection; crust formation, stratification into
metallic and oxide layers); degradation of lower head by molten corium impact; release ofmolten materials into containment after to RPV breach.
At ex-vessel stage, the following processes are focused in models: hydrogen and steamair mixture distribution in multicompartment containment by coupling with lumped parametercontainment codes KUPOL-M or ANGAR; molten corium – concrete interaction (or retention
in core catcher, for example in new designs of VVER); FP behaviour in containment (transport,
deposition and resuspension, iodine chemistry, sump chemistry); FP leakage into environment
following containment non-tightness; FP release into environment due to containment failure
or bypass.

FIG. 45. Phenomena modelled in SOCRAT (reprinted from Ref. [93] with permission from
Elsevier).
In the framework of FUMAC Project, the goal of the application of the SOCRAT code
was twofold. The first one was to verify the code capability to model balloning and burst ofirradiated claddings against the Halden IFA-650 tests as well as pressurised fuel bundle
degradation in the high temperature CORA-15 test. The second goal was to provide the Project
participants with common thermal hydraulic boundary conditions for the fuel performancecodes in the benchmark exerсise based on Halden IFA-650.9, 10 and 11 tests .

45

4. COMPARISON OF SIMULATION RESULTS
4.1. MTA EK BURST TESTSFive organizations provided results for the MTA EK isothermal ballooning cases
described in Section 2.1:
MTA EK (Hungary), FRAPTRAN 2.0 code;
JRC (European Commission), TRANSURANUS v1m2j17 code;
INL (USA), BISON 1.4 code;
CIEMAT (Spain), FRAPTRAN 1.5 code;
SSTC (Ukraine), TRANSURANUS v1m1j11 code.
Participants were asked to provide results in terms of: 1) time to cladding burst failure, 2)
cladding inner pressure at burst and 3) maximum cladding outer hoop strain at burst.
4.1.1. Results of time to burst failure
Result from participants in terms of time to burst for the six MTA EK cases are reported
in histogram form in Fig. 46. Experimental data are also included. Test temperature is being
arranged in the order of decreasing.
There was a general tendency of the codes to underpredict the time to burst. The
TRANSURANUS code (both JRC and SSTC), however, compared very well to theexperimental data. The BISON code also compared well, although it was moderately
underpredicted the data. The FRAPTRAN code underpredicted the time to cladding burst more
pronouncedly than other codes, as indicated from results obtained from both MTA EK and
CIEMAT. CIEMAT conducted a parametric exercise to explore the sensitivity of the results tothe internal thermal state of the tube. This sensitivity analysis was performed because the gas
in the tube might not have reached a thermal equilibrium with the furnace in the FRAPTRAN
heat transfer calculation. The study was limited to tests PUZRY-12 and 26 as the time to failure
was sensitive to temperature, even doubles in one case (Test # 12), when considering atemperature of 60–80 K lower than the furnace temperature.
JRC commented that the accuracy of the TRANSURANUS predictions of time to burst
was in line with previous simulations of similar ballooning tests [94]. Also, JRC tested two
different criteria for rod failure (i.e., limiting hoops stress and limiting hoop strain) and notedthat the cladding failure criterion had only a small influence on predicting the time to burst,
because ballooning occurred very rapidly at its late stage.
Both JRC and INL analyzed the burst time results obtained with TRANSURANUIS andBISON, respectively, as a function of the test temperature. Both institutions noted that the
reduction of the burst time as a function of the temperature was reproduced. Deviations ofpredictions from the experimental data appeared to increase at low temperatures. The lattercircumstance was also confirmed by MTA EK in terms of their calculations with FRAPTRAN.
Higher discrepancies between calculations and experiments at lower temperatures indicatedthat deviations might be partly due to a lack of properly modelling of anisotropic creep
behaviour, which characterized the alpha-Zr [95].

46FIG. 46. Time to burst for the MTA-EK ballooning tests. Code-to-code comparisons andexperimental data are illustrated.
The high-temperature creep correlations in the codes were generally based on theexperimental work of Erbacher et al. [95]. Differences might exist in the chemical composition
between the Zr-4 alloy used in the PUZRY experiment and those used in Ref. [95].
Consequently, the observed difference in creep behaviour.
Users effects observed for results obtained from TRANSURANUS and FRAPTRAN
might be due to differences in the code versions, as well as a different selection of the modelling
options available (such as the burst failure criterion).
4.1.2. Results of pressure at burst failure
Results from participants in terms of cladding inner pressure at the time of burst failure
are reported in Fig. 47. Experimental data are also included.
Underpredicting the experimental values for the burst pressure was generally observed.
The pressure increase rate was an experimental parameter and an input for the code calculations.
An underprediction of the pressure reached at burst time corresponds to an underprediction of
the burst time itself.
The calculations from both TRANSURANUS users appeared to be in good agreementwith the data. Predictions with the BISON code were also reasonable. A significant
underprediction was associated with the FRAPTRAN calculations.
4.1.3. Results of maximum hoop strain at burst failure
Results from participants in terms of hoop strain at the axial peak position (burst location)on the cladding outer surface, at the time of burst failure, are reported in Fig. 48. Experimental
data are also included.
Large differences were observed between predictions from different codes and, in manycases, predictions were deviated markedly from the experimental data.

47

FIG. 47. Cladding inner pressure at burst for the MTA-EK ballooning tests. Code-to-code
comparisons and experimental data are illustrated.

FIG. 48. Maximum cladding outer hoop strain at burst time for the MTA-EK ballooning tests.
Code-to-code comparisons and experimental data are illustrated.
Prediction of cladding maximum strain was a difficult task for fuel performance codes,
which relates to the number, complexity and mutual dependence of the involved phenomena.
Uncertainties in cladding burst strain calculations could be large for LOCA analysis, as very
high strain rates were reached when cladding burst was approached. This implied that the
maximum strain was very sensitive to the specific criterion adopted to determine the time-offailure, since a small difference in the failure time could correspond to a large difference in the
maximum strain. This was demonstrated by JRC-Karlsruhe when different failure criteria were
tested in cladding ballooning and burst simulations with the TRANSURANUS code [94].
48

INL, JRC and CIEMAT noted that the uncertainty in burst strain predictions was related
to the burst criterion. The burst strain results obtained from TRANSURANUS should beconsidered carefully, since those values exceed the range of acceptability of the models. JRC
further commented that the strains obtained from bundle tests (e.g. QUENCH) were typicallysmaller than those observed in single rod tests, which could be attributed in part due to theazimuthal temperature gradient along the cladding, as indicated by the available experimental
evidence [96]. Taking this aspect into calculations would require a full 3D modelling1, while
calculations within FUMAC were performed using either 1.5D or 2D-rz geometricalrepresentations.
Besides modelling uncertainties, measurement and instrument uncertainties could also be
added to the expected discrepancies between calculations and experimental data. Theinterpretation of the burst opening (cladding flaps that protrude outwards following burst) mightalso introduce a bias in the measured strain relative to the strain due to ballooning only. Thiswas evident in the post-test cladding diameter profile measured for the Halden IFA-650.10
experiment2 [97]. Code predictions referred to the strain in the cladding just before burst, i.e.,the maximum ballooning strain. For the MTA EK tests, the nature of the measurements could
not be clarified.
4.2. HALDEN LOCA TESTS (IFA-650.9, 10, 11)
It was agreed at the 2nd Research Coordination Meeting to use common thermal hydraulic(T/H) boundary conditions (BCs) for all fuel performance codes in the benchmark exerсise
based on Halden IFA-650.9, 10 and 11 tests, which were provided by the integral code
SOCRAT.
The developed Halden IFA-650 geometrical model of the test rig in SOCRAT allowed
simulating the main phases of the test scenarios – natural circulation, blowdown, heat-up andspray operation, and cool-down phases. It comprised the test flask, blowdown system, and somepart of high-pressure heavy water loop connected to the flask (both hot and cold legs). The
nodalization of the test flask was furher completed for each test in order to account for somespecific details of the test section (for example, fuel rod geometry).
The delivered information for the code benchmarking was: evolution of the cladding andcoolant temperatures, heat transfer rates by convection and radiation (for the derivation of theheat transfer coefficient) in 26 nodes, coolant inlet/outlet pressure, temperatures of both phases,
void fraction, and flowrates of the fluid and the gas mixture components (steam, hydrogen,argon and helium) at the time span from the end of phase 1 (forced circulation) to the end of
the tests. Total rod and heater power evolutions were provided for information to obtain moreconsistent results. More details on the development of the T/H boundary conditions can befound in Annex II (paper entitled “Simulation of initial and boundary conditions with SOCRAT
code for benchmarks based on IFA-650.10 AND IFA-650.11 tests”).
4.2.1. IFA-650.9
Results from code prediction for these Halden LOCA Tests (IFA-650.9, 10, 11), from theparticipants were similar, in terms of comparison with the experimental data. Ten organizations
from different countries provided results for the IFA-650.9 test:

1

Strictly speaking, azimuthal variations can be also captured with 2D-rz representations. However, 3D
is needed to include also axial variations.
2
During the FUMAC RCM 3, it was clarified that the peak observed in the measured cladding diameter
profile for IFA-650.10 [97] is an effect of the burst opening and should not be considered whencomparing to calculations.
49CIAE (China), FTPAC 1.0;
CIEMAT (Spain), FRAPCON 3.5 and FRAPTRAN 1.5;
CNPRI (China), FRAPCON 3.4 and FRAPTRAN 1.5;
CNEA (Argentina), DIONISIO 2.0;
KAERI (Republic of Korea), FRAPCON 3.4 and FRAPTRAN 2.0;
IBRAE (Russia), SOCRAT/V3;
IPEN (Brazil), FRAPCON 3.4 and FRAPTRAN 1.5;
SSM/ Quantum Technologies AB (Sweden), FRAPCON 3.5 and FRAPTRAN-QT-1.5b;
Tractebel (Belgium), FRAPCON 4.0 and FRAPTRAN-TE-1.5 (with axial fuel relocation
and FEA models);
VNIINM, Bochvar Institute (Russia), RAPTA 5.2.
4.2.1.1. Results at the end of the base irradiation
For all participants, the calculated burnup was close to the average measured discharge
burnup for the fuel rod (Fig. 49). The predicted pellet to cladding gap at the end of the irradiation
was more scattered (Fig. 50), with gap closure predicted by one participant. As a general trend,
low values of residual gap were expected at this burnup, but no experimental data was available.
The diametral clad strain was also scattered among various calculations (Fig. 51). On the other
hand, a reasonable agreement was achieved for the clad elongation (Fig. 52). The calculated
corrosion layer (Fig. 53) was in good agreement with the experimental data (7 µm) for most of
the participants.
Only two participants provided results for the radial distribution of fission gas inventory
before the transient (Fig. 54). A significant discrepancy between the calculated and measured
values was evident.
Calculated data after the pre-test irradiation, presented in Figs 49–54, were used by someparticipants as the initial conditions for the IFA-650.9 transient calculations. For some codessuch as SOCRAT, RAPTA 5.2 and FTPAC 1.0 that were used by IBRAE, Bochvar Instituteand CIAE respectively, experimental data were used as the initial conditions for the benchmark
exercise, for example a burnup of 89.9 MWd/kgU and a corrosion layer of 7 μm were used for
IFA-650.9. Similar approaches were applied for the other IFA-650 transient simulations.

FIG. 49.

50

Comparison of the rod segment average burnup for the IFA-650.9 test.

FIG. 50. Comparison of the diametral gap at the mid pellet region for the IFA-650.9 test.

FIG. 51.

Comparison of the average diametral clad strain for the IFA-650.9 test.

51

FIG. 52.

FIG. 53.

52

Comparison of clad elongation for the IFA-650.9 test.

Comparison of the average corrosion layer thickness for the IFA-650.9 test.

FIG. 54.

Comparison of gas retention for the IFA-650.9 test.

4.2.1.2. Results during the LOCA transient
For this section, time reference was set at the beginning of the transient. Figure 55
indicated a comparison of the calculated plenum temperature. A clustering in two group of
results was emerged. The difference was probably caused by the modelling assumptions
selected by the participants for the calculation of the plenum temperature. The clustering did
not depend on the code used for the simulation.
A comparison of the calculated total fission gas release is indicated in Fig. 56. The
scattering of results among various participants was significant, as the kinetic evolution of thefission gas release along the transient was deviated significantly. The number of participants
able to calculate this quantity was limited. This observation indicated the importance of further
model development for the prediction of fission gas behaviour during the transients.
A comparison of the calculated internal pressure is indicated in Fig. 57. Instead of theballooning phase (pressure decreased before burst), several participants predicted an increasein the pressure prior to the burst. As described by CIEMAT, a specific algorithm was used by
FRAPTRAN to evaluate the inner pressure in the plenum. The qualitative agreement among
the participants was reasonable.
A comparison of the cladding outer temperature (at the position of the burst) is indicatedin Fig. 58. All results were reasonably close to each other, with a similar time evolution. These
trends depended on the boundary conditions adopted by the participants.
A comparison of the cladding elongation is indicated in Fig. 59. The scattering of results
among various participants was significant. This could be ascribed to the difference in material
properties of the cladding used in different codes, since the thermal boundary conditions are
similar among the partners.
A comparison of the cladding radial displacement (at the position of the burst) is indicatedin Fig. 60. Similar observations and comments as for the elongation (in Fig. 59) could be made.

53

FIG. 55. Comparison of the plenum temperature during the LOCA transient of the IFA-650.9
test.

FIG. 56. Comparison of the integral fission gas release during the LOCA transient of the IFA650.9 test.

54

FIG. 57. Comparison of the internal pressure during the LOCA transient of the IFA-650.9 test.

FIG. 58. Comparison of the clad outer temperature at burst position during the LOCA transientof the IFA-650.9 test.

55

FIG. 59. Comparison of the clad axial elongation during the LOCA transient of the IFA-650.9
test.

FIG. 60. Comparison of the clad radial displacement at burst position during the LOCA
transient of the IFA-650.9 test.
4.2.1.3. Results at the end of the LOCA transient
The scattering in the predicted failure times among the different participant wassignificant (see Fig. 61).
The axial profile of the cladding diameter (and in general indicating the location of the
burst) and the diametral gap are shown in Figs 62 and 65, respectively. The scattering of the56

calculated deformation was related to the burst criteria used in various codes. The experimental
data (i.e. the maximum strain or stress criteria) were quite scattered that led to different results.
The cladding oxide thickness calculated by the participants was also scattered (Fig. 63),
despite the cladding temperature used as an input for the code was similar for all participants.
The same level of scattering was observed for the equivalent cladding reacted (Fig. 64).
Potentially, different oxidation models were existed for different participants.
Some participants provided an assessment of fuel fragmentation volume fraction along
the rod segment, as indicated in Fig. 66. A reasonable agreement was obtained considering thenovelty of the models involved.

FIG. 61. Comparison of the time of failure of the IFA-650.9 test.

FIG. 62. Comparison of the cladding outer diameter after the IFA-650.9 test.

57

FIG. 63. Comparison of the cladding oxide thickness after the IFA-650.9 test.

FIG. 64. Comparison of the equivalent cladding reacted after the IFA-650.9 test.

58

FIG. 65. Comparison of the diametral gap after the IFA-650.9 test.

FIG. 66. Comparison of the fuel fragmentation volume after the IFA-650.9 test.
4.2.2. IFA-650.10
Sixteen organizations from different countries provided results for the IFA-650.10 test:— CNPRI (China), FRAPCON 3.4 and FRAPTRAN 1.5;
— INRNE (Bulgaria), TRANSURANUS v1m1j17;— CEA (France), ALCYONE v1.4;— CIEMAT (Spain), FRAPCON 3.5 and FRAPTRAN 1.5;
— CNEA (Argentina), DIONISIO 2.0;
— IBRAE (Russia), SOCRAT/V3;
59

— JRC-Karlsruhe (European Union), TRANSURANUS;— KAERI (Republic of Korea), FRAPCON 3.4 and FRAPTRAN 2.0;
— CIAE (China), FTPAC 1.0;
— IPEN (Brazil), FRAPCON 3.4 and FRAPTRAN 1.5;
— SSM/ Quantum Technologies AB (Sweden), FRAPCON 3.5 and FRAPTRAN-QT-1.5b;— INL (United States), BISON 1.4;
— SSTC NRS (Ukraine), TRANSURANUS v1m1j17;— Tractebel (Belgium), FRAPCON 4.0 and FRAPTRAN-TE-1.5 (with axial fuel relocation
and FEA models);— VTT (Finland), FRAPCON 4.0 and FRAPTRAN 2.;0
— VNIINM, Bochvar Institute (Russia), RAPTA 5.2.
4.2.2.1. Results at the end of the base irradiation
For all participants, the calculated burnup was quite close to the average measured
discharge burnup of the fuel rod (Fig. 67). The residual pellet to cladding gap was scattered(Fig. 68). As a general trend, a low value of residual gap was expected at this burnup, but noexperimental data was available for comparison. The diametral strain was rather scatteredamong different calculations (Fig. 69). On the other hand, a reasonable agreement was achieved
for the clad elongation (Fig. 70). The corrosion layer calculated (Fig. 71) was in good agreementwith the experimental data (of 25 µm) for most cases.
Some participants provided results for the distribution of the fission gas inventory before
the transient (Fig. 72). However, a significant discrepancy was evident.
For SOCRAT calculation by IBRAE, the experimental data for a burnup of 61 MWd/kgU
and a corrosion layer of 30 μm were used as the initial states for the benchmark exercise.

FIG. 67. Comparison of the rod segment average burnup for the base irradiation of the IFA650.10 test.

60

FIG. 68. Comparison of the diametral gap at the mid pellet at the end of the base irradiation of
the IFA-650.10 test.

FIG. 69. Comparison of the axial average diametral clad strain at the end of the baseirradiation of the IFA-650.10 test.

61

FIG. 70. Comparison of the clad elongation at the end of the base irradiation of the IFA-650.10
test.

FIG. 71. Comparison of the axial average corrosion layer thickness at the end of the baseirradiation of the IFA-650.10 test.

62

FIG. 72. Comparison of fission gas inventory at the end of base irradiation for the IFA-650.10
test. (S) stands for simulated boundary conditions, while (M) stands for measured boundary
conditions.
4.2.2.2. Results during the LOCA transient
For the following Figs, time reference is set at the beginning of the transient. Results are
similar to those obtained for the IFA-650.9 test.
A comparison of the calculated plenum temperature is indicated in Fig. 73. A clusteringof two group of results was evident. The difference was probably caused by the modelling
options selected by the participants for the calculation of the plenum temperature (the clustering
did not depend on the code used for the simulation).
A comparison of the calculated total fission gas release is indicated in Fig. 74. The
scattering among the predicted values was significant. The differences in the kinetic evolutionof the fission gas release along the transient were also significant. The number of participantsthat could calculate this affect was limited. These observations suggested the importance offurther model development for the prediction of fission gas release during a LOCA transient.
A comparison of the calculated internal pressure is indicated in Fig. 75. Instead of theballooning phase (pressure decrease before burst), several participants predicted an increase in
the pressure prior to the burst. As described by CIEMAT, a specific algorithm was used by
FRAPTRAN to evaluate the inner pressure in the plenum. The qualitative agreement among
the participants was reasonable.
A comparison of the cladding outer temperature (at the position of the burst) is indicatedin Fig. 76. Results were reasonably close to each other, with a similar time evolution. The
predicted cladding temperature would depend on the boundary conditions adopted by theparticipants.
A comparison of the cladding elongation is indicated in Fig. 77. The scattering of results
among different participants was significant. This could be ascribed to the difference in material
properties of the cladding used in different codes, since the thermal boundary conditions are
similar among the partners.
A comparison of the cladding radial displacement (at the position of the burst) is indicatedin Fig. 78. Similar explanations as those for the elongation could be made.

63

FIG. 73. Comparison of the plenum temperature during the LOCA transient of the IFA-650.10
test. (S) stands for simulated boundary conditions, while (M) stands for measured boundary
conditions.

64

FIG. 74. Comparison of the total fission gas release during the LOCA transient of the IFA650.10 test. (S) stands for simulated boundary conditions, while (M) stands for measured
boundary conditions.

65

FIG. 75. Comparison of the internal pressure during the LOCA transient of the IFA-650.10 test.
(S) stands for simulated boundary conditions, while (M) stands for measured boundary
conditions.

66

FIG. 76. Comparison of the clad outer temperature at burst position during the LOCA transientof the IFA-650.10 test. (S) stands for simulated boundary conditions, while (M) stands formeasured boundary conditions.

67

FIG. 77. Comparison of the clad axial elongation during the LOCA transient of the IFA-650.10
test. (S) stands for simulated boundary conditions, while (M) stands for measured boundary
conditions.

68

FIG. 78. Comparison of the clad radial displacement at burst position during the LOCA
transient of the IFA-650.10 test. (S) stands for simulated boundary conditions, while (M) stands
for measured boundary conditions.
4.2.2.3. Results at the end of the LOCA transient
The scatter in the predicted failure times among the different participant was significant(see Fig. 79). Results are similar to those obtained from the IFA-650.9 test.
The axial profile of the cladding diameter (and in general indicating the position of the
burst) and the diametral gap are shown in Figs 80 and 83, respectively. The scattering of thecalculated deformation was related to the burst criteria used in various codes. The experimental
data (i.e. the maximum strain and stress criteria) were quite scattered that led different results.
The cladding oxide thickness calculated by the participants was also scattered (Fig. 81),
despite the cladding temperature used as an input for the code was similar for all participants.
The same level of scattering was observed for the equivalent cladding reacted (Fig. 82).
Potentially different oxidation models were existed for different participants.
69

One participant provided an assessment of fuel fragmentation volume fraction along therod segment (Fig. 84). The result was in good qualitative agreement with that of the IFA-650.9
test.

FIG. 79. Comparison of the time of failure of the IFA-650.10 test. (S) stands for simulated
boundary conditions, while (M) stands for measured boundary conditions.

70

FIG. 80. Comparison of the cladding outer diameter after the IFA-650.10 test. (S) stands for
simulated boundary conditions, while (M) stands for measured boundary conditions.

71

FIG. 81. Comparison of the cladding oxide thickness after the IFA-650.10 test. (S) stands for
simulated boundary conditions, while (M) stands for measured boundary conditions.

72

FIG. 82. Comparison of the equivalent cladding reacted after the IFA-650.10 test. (S) stands
for simulated boundary conditions, while (M) stands for measured boundary conditions.

73

FIG. 83. Comparison of the diametral gap after the IFA-650.10 test. (S) stands for simulated
boundary conditions, while (M) stands for measured boundary conditions.

74

FIG. 84. Comparison of the fuel fragmentation volume after the IFA-650.10 test. (S) stands for
simulated boundary conditions, while (M) stands for measured boundary conditions.
4.2.3. IFA-650.11
Nine organizations from different countries provided results for the IFA-650.11 test:
CNPRI (China), FRAPCON 3.4 and FRAPTRAN 1.5;
INRNE (Bulgaria), TRANSURANUS v1m1j17;
CNEA (Argentina), DIONISIO 2.0;
IBRAE (Russia), SOCRAT/V3;
JRC-Karlsruhe (European Union), TRANSURANUS ;IPEN (Brazil), FRAPCON 3.4 and FRAPTRAN 1.5;
SSTC NRS (Ukraine), TRANSURANUS v1m1j17;
VTT (Finland), FRAPCON 4.0 and FRAPTRAN 2.0;
VNIINM, Bochvar Institute (Russia), RAPTA 5.2.
4.2.3.1.Results at the end of the base irradiation
For all participants, the calculated burnup was close to the average measured discharge
burnup of the fuel rod (Fig. 85). The predicted pellet to cladding gap at the end of the irradiation
was more scattered (Fig. 86). As a general trend, low values of residual gap were expected at
this burnup, but no experimental data was available. The diametral clad strain was scatteredamong various calculations (Fig. 87). On the other hand, a reasonable agreement was achieved
for the clad elongation (Fig. 88). The calculated corrosion layer (Fig. 89) was in good agreementwith the experimental data (of 5 µm) for most of the participants.
Some participants provided results for the radial distribution of fission gas inventory
before the transient (Fig. 90). A significant discrepancy between the calculated and measured
values was evident.

75

FIG. 85. Comparison of the rod segment average burnup for the base irradiation of the IFA650.11 test.

FIG. 86. Comparison of the diametral gap at the mid pellet at the end of the base irradiation of
the IFA-650.11 test.

76

FIG. 87. Comparison of the axial average diametral clad strain at the end of the baseirradiation of the IFA-650.11 test.

FIG. 88. Comparison of the clad elongation at the end of the base irradiation of the IFA-650.11
test.

77

FIG. 89. Comparison of the axial average corrosion layer thickness at the end of the baseirradiation of the IFA-650.11 test.

FIG. 90. Comparison of gas retention at the end of the base irradiation for the IFA-650.11 test.
4.2.3.2.Results during the LOCA transient
For the following Figs, time reference was set at the beginning of the transient. A
comparison of the calculated plenum temperature is indicated in Fig. 91. A clustering in two
group of results was emerged. The difference was probably caused by the specific modellingassumptions selected by the participants for the calculation of the plenum temperature (theclustering did not depend on the code used for the simulation).
A comparison of the calculated total fission gas release is indicated in Fig. 92. The
scattering among the predicted values was significant, as the kinetic evolution of the fission gas
78

release along the transient were deviated significant. The number of participants able tocalculate this quantity was limited. This observation indicated the importance of further model
development for the prediction of fission gas behaviour during the transients.
A comparison of the calculated internal pressure is indicated in Fig. 93. Instead of theballooning phase (pressure decrease before burst), several participants predict an increase in thepressure prior to the burst. As described by CIEMAT, a specific algorithm was used by
FRAPTRAN to evaluate the inner pressure in the plenum. The qualitative agreement among
the participants was reasonable.
A comparison of the cladding outer temperature (at the position of the burst) is indicatedin Fig. 94. Results was reasonably close to each other, with a similar time evolution. The
predicted cladding temperature would depend on the boundary conditions adopted by theparticipants.
A comparison of the cladding elongation is indicated in Fig. 95. The scattering of results
among various participants was significant. This could be ascribed to the material properties of
the cladding used in different codes, since the thermal boundary conditions are similar among
the partners.
A comparison of the cladding radial displacement (at the position of the burst) is indicatedin Fig. 96. Similar considerations and comments as for the elongation could be made.

FIG. 91. Comparison of the plenum temperature during the LOCA transient of the IFA-650.11
test.

79

FIG. 92. Comparison of the total fission gas release during the LOCA transient of the IFA650.11 test.

FIG. 93. Comparison of the internal pressure during the LOCA transient of the IFA-650.11 test.

80

FIG. 94. Comparison of the clad outer temperature at burst position during the LOCA transientof the IFA-650.11 test.

FIG. 95. Comparison of the clad axial elongation during the LOCA transient of the IFA-650.11
test.

81

FIG. 96. Comparison of the clad radial displacement at burst position during the LOCA
transient of the IFA-650.11 test.
4.2.3.3.Results at the end of the LOCA transient
The scatter in the predicted failure times among the different participant was lesssignificant than in the other IFA-650 tests (see Fig. 97).
The axial profile of the cladding diameter (and in general indicating the position of the
burst) and the diametral gap are shown Figs 98 and 101, respectively. The scattering of thecalculated deformation was related to the burst criteria used in various codes. The experimental
data (i.e. maximum strain or stress criteria) were quite scattered that led to different results.
The cladding oxide thickness calculated by the participants was also scattered (Fig. 99),
despite the cladding temperature used as an input for the code was similar for all participants.
The same level of scattering was observed for the equivalent cladding reacted (as illustrated inFig. 100). Potentially different oxidation models were existed for different participants.

82

FIG. 97.

FIG. 98.

Comparison of the time of failure of the IFA-650.11 test.

Comparison of the cladding outer diameter after the IFA-650.11 test.

83

FIG. 99.

Comparison of the cladding oxidation thickness after the IFA-650.11 test.

FIG. 100. Comparison of the equivalent cladding reacted after the IFA-650.11 test.

84

FIG. 101. Comparison of the diametral gap after the IFA-650.11 test.
4.3. STUDSVIK LOCA TEST (NRC-192)
Seven organizations from seven different countries provided results for this Studsvik 192
test:
CNEA (Argentina), DIONISIO 2.0 code;
CEA (France), ALCYONE V1.4 code;
VTT (Finland), FRAPCON 4.0 & FRAPTRAN 2.0 codes;
CIEMAT (Spain), FRAPCON 3.5 & FRAPTRAN 1.5 codes;
SST-CNRS (Ukraine), TRANSURANUS v1m1j17 code ;MTA-EK (Hungary), FRAPTRAN 1.4 code;
SSM/ Quantumtech (Sweden), FRAPCON 3.5 & FRAPTRAN-QT-1.5 codes.
4.3.1. Results at the end of the base irradiation
Most of the participants used the base irradiation conditions (power history) provided by
US NRC to simulate the initial state of the rod before the transient.
MTA-EK did not calculate the behaviour of the rod after the base irradiation, but rather
the end-of-life measured data was used as the initial state of the rod before the LOCA test.
The calculated burnup of the rod was close to the average measured discharge burnup of
the fuel rod (Fig. 102). The residual pellet to cladding gap was scattered depending on the codeand user (Fig. 103). Even if there was no experimental data for the gap after base irradiation, avalue of a few microns seemed more reasonable than a wide gap because of fuel swelling andcladding creep at high burnup. Some participants had overpredicted this quantity.
The calculated diametral clad strain reported by participants was very different dependingon the code used (Fig. 104). The calculated values, although, remain small. Experimentally, thediameter was slightly increased during the base irradiation (0.13%). Most codes provided areasonable cladding elongation for the rod irradiated up to 70 GWd/tM (Fig. 105).
The corrosion layer calculated (Fig. 106) was between 10 and 40 µm, which was in agood agreement with the experimental data (between 25 and 30µm).
Only 3 participants calculated the radial distribution of fission gas inventory before thetransient (Fig. 107). This quantity could be compared to EPMA or SIMS measurement, but the85experimental data were not provided. Calculation showed that fission gas release during thebase irradiation occurred in the center part of the rod, as expected.

FIG. 102. Calculated average burn-up of the Studsvik 192 test rod segment.

FIG. 103. Calculated gap at mid segment of the Studsvik 192 test rod segment before test.

86

FIG. 104. Calculated average clad strain of the Studsvik 192 test rod segment before test.

FIG. 105. Calculated cladding elongation of the Studsvik 192 test rod segment before test.

FIG. 106. Calculated average corrosion layer thickness of the Studsvik 192 test rod segment
before test.

87

FIG. 107. Calculated fission gas inventory of the Studsvik 192 test rod segment before test at
mid segment.
4.3.2. Results during the LOCA test
For the following Figs, time reference was set at the beginning of heat up (the transient).
Inner rod pressure evolution (Figs 108 and 109) indicated that all participants
overestimated the burst time between 10 and 30 s. The pressure evolution during the test showeda ballooning phase (pressure decrease before burst). The modelling of plenum temperature wasleft to the participants, as the experiment was complex and not all temperatures were measured.
Most participants considered a quasi-constant temperature in the plenum, except CEA (Fig.
110). Even CEA considered a high temperature in the plenum, it did not result in an overestimation of the pressure in the rod.
Participants used the cladding temperature data provided by US-NRC in the data sheet tomodel the outer cladding temperature profile. All data calculated at the burst node wereconsistent (Fig. 111).
According to the participants, the calculated cladding axial and radial displacements
during the test could be very different (Figs 112 and 113). Results were mainly obtained fromthe cladding creep behaviour law used in the code, and all codes had a different one. Someparticipants used a higher creep rate (mainly FRAPTRAN code users) than others(TRANSURANUS, DIONISIO, ALCYONE) as illustrated in these Figs. The effect ofboundary conditions (cladding temperature profile) was negligible as all participants practicallyused the same assumptions.
Only CEA could calculate fission gas release during the test (Fig. 114). The main
mechanism modelled in the ALCYONE code was gas release by intergranular fragmentation.
This fragmentation could occur after the cladding burst (ALCYONE). In some codes(FRAPTRAN-QT), fuel fragmentation and relocation were calculated but extra fission gas
release was not introduced. The evolutions of the corresponding models were detailed in theparticipants’ reports.

88

FIG. 108. Rod inner pressure calculated during test (Studsvik 192 LOCA test).

FIG. 109. Rod inner pressure calculated around the burst (Studsvik 192 LOCA test).

89

FIG. 110. Plenum temperature calculated during test (Studsvik 192 LOCA test).

FIG. 111. Clad temperature at burst node calculated during test (Studsvik 192 LOCA test).

90

FIG. 112. Cladding axial elongation calculated during test (Studsvik 192 LOCA test).

FIG. 113. Cladding radial displacement at burst node calculated during test (Studsvik 192
LOCA test).

91

FIG. 114. Calculated fission gas release during test (Studsvik 192 LOCA test).
4.3.3. Results at the end of the LOCA test
All participants slightly over-estimated the time of failure of the rod segment (Fig. 115)
between 10 and 25 s, except CIEMAT with FRAPTRAN code.
Practically all participants located the burst node at mid-length of the rod segment (Fig.
116), whereas the experimental burst node was a bit further down the length. Two explanations
for the experimental result: either there was an axial gradient of temperature that made theexperimental burst node further down, or a localized overpressure in the rod due to local
fragmentation (and so fission gas release) before the burst.
As per other tests, the scattering of the calculated maximum cladding deformation was
related to the difference in burst criteria (i.e. the maximum strain or stress criteria) used invarious codes. As the experimental data available to build this criterion were very muchscattered, different approaches would lead to different results.
The cladding oxide thickness calculated by the participants was also scattered (Fig. 117),
despite the cladding input temperature was approximately the same for all participants. The
deviation was even more for participants who used FRAPTRAN. The same observation could
be made for the equivalent cladding reacted (Fig. 118) and the hydrogen content in the cladding.
Different oxidation models might have been used for the participants.
For all the participants, the calculated maximum pellet-cladding gap was observed at midlength (Fig. 119).
Two participants provided an assessment of fuel fragmentation volume fraction along therod segment (Fig. 120). SSM/ QuantumTech’s used the fragmentation and relocation model
implemented in FRAPTRAN, whereas MTA-EK’s used the HBS volume fraction in the pellet
before the test. It was assumed that only the rim structure could be fragmented during this test.
Although a model for intergranular fragmentation was implemented in CEA’s code
ALCYONE, this model was considered for calculating gas release than fuel fragmentation.

92

FIG. 115. Calculated time-of-failure (Studsvik 192 LOCA test).

FIG. 116. Cladding outer diameter calculated at end-of-test (Studsvik 192 LOCA test).

93FIG. 117. Cladding oxidation thickness calculated at end-of-test (Studsvik 192 LOCA test).

FIG. 118. Equivalent cladding reacted calculated at end-of-test (Studsvik 192 LOCA test).

94

FIG. 119. Calculated pellet-cladding gap at end-of-test (Studsvik 192 LOCA test).

FIG. 120. Fraction of fragmented fuel (Studsvik 192 LOCA test).
4.4. QUENCH-LOCA L1
Four organizations provided results for this test case:
CNEA (Argentina), DIONISIO 2.0 code;
INL (USA), BISON 1.4 code;
JRC (European Commission), TRANSURANUS v1m2j17 code ;GRS (Germany), ATHLET-CD 3.1A code.
Although participants had simulated different rods from the out-of-pile bundle test
provided by KIT, it was agreed that results from different codes would only be compared withthe experimental data from rod# 4 reported in this section.
95

The results provided by INL and GRS were shifted (corrected) since they applied a
different time for the start of their simulations. Their results were started at the onset of thetemperature increase at around 100.6 s, corresponding to the increase of the electrical powerthat lead to the LOCA event. Hence the time-dependent curves were shifted by 100.6 s (andaccordingly the predicted time for burst).
4.4.1. Results during the QUENCH-LOCA test
The results obtained from different codes were compared with experimental data
provided by KIT. Member States decided to compare the calculated internal gas pressure (MPa)and the cladding outer temperature (oC) at the burst location, as a function of time (s) for rod #4. Results are illustrated in Figs 121 to 123.
The internal gas pressure evolution (see Fig. 121) indicated that, apart from the
DIONISIO prediction, the codes closely followed the on-line measured pressure values prior to
burst. BISON and TRANSURANUS used the measured data as input values for theirsimulations, rather than using the code calculated values, as if it was a sealed rod in a reactor.
ATHLET-CD also used an initial internal pressure and calculated the pressure evolution.
ATHLET-CD code, as a system code, used groups of rods during the simulation. Rod# 4 wasan object representing the rods# 2, 4, 6, 8 that had the same thermal hydraulic and mechanicalbehaviour within the system code.
Results around the burst time for rod# 4 is indicated in Fig. 122. The difference between
code predictions and the measured data stemmed from the fact that simulation tools simply
considered an instantaneous drop in rod pressure upon burst and stopped the calculation(BISON). The measured value revealed that the pressure drop was not instantaneous.
Given that many thermocouple readings were available in the KIT bundle test, mostparticipants used the measured values as the boundary conditions for the benchmark exercisethat focused on the fuel rod behaviour. DIONISIO and ATHLET-CD relied on their own
thermal hydraulic models for estimating the temperature profile along the cladding during thetest. ATHLET-CD predicted the same temperature behaviour as the measured values, but thepeak temperature at 350 s was lower than the experiment (see Fig. 123).

FIG. 121. Comparison of the rod internal pressure (MPa) versus time (s) in rod 4 of the
QUENCH-LOCA L1 experiment at KIT, with predicted values obtained from DIONISIO,
TRANSURANUS, BISON and ATHLET-CD.

96

FIG. 122. Comparison of the rod internal pressure (MPa) versus time (s) around the burst
location in rod 4 of the QUENCH-LOCA L1 experiment at KIT, with predicted values obtained
from DIONISIO, TRANSURANUS, BISON and ATHLET-CD.

FIG. 123. Comparison of the cladding outer temperature (oC) at the axial position of the burst
versus time (s) in rod 4 of the QUENCH-LOCA L1 experiment at KIT, with predicted values
obtained from DIONISIO, TRANSURANUS, BISON and ATHLET-CD.
4.4.2. Results after the QUENCH-LOCA test
At the end of the LOCA test, participants were asked to compare their simulated values
for:
The cladding outer diameter (mm), the cladding oxidation thickness (microns), theequivalent cladding reacted (%) and the hydrogen content (ppm), as a function of the axial
position (mm), are illustrated from Figs 124 and 127.

97

Failure time (s), burst pressure (MPa), average cladding hoop stress (MPa) at the burst
location, axial location (mm) of the burst, clad outer temperature (oC) at the burst location,clad average hoop strain (%) at the burst location are illustrated from Figs 128 to 133.
The axial profiles of the cladding diameters after the test (see Fig. 124) indicated somescattering, although the overall agreement was reasonable for all predictions. The position of
the burst opening was in relatively good agreement, considering the dissimilarities in theboundary conditions as outlined above, along with the differences in the axial discretizationthat was also visible in the plot. The peak position obtained with BISON agreed with theballooning of the cladding at 916 mm (without burst); whereas the peak position predicted by
TRANSURANUS lied between this value and a maximum ballooning of 982 mm (with burst).
The burst position should normally occur at the highest temperature. However hot spot could
accommodate rod bending and the contact location between the pellets and the cladding could
then be changed. This phenomenon is stochastic and could not be modelled easily. The
scattering of the calculated maximum deformation was also related to the difference in burst
criteria (such as maximum strain or stress criteria) and the predicted cladding temperature (asindicated in Fig. 123) used in various codes.
The measured tangential strain from PIE included the opening after burst, whereas thecomputer codes did not account for this opening. After subtracting this opening, the maximum
strain values would be 11–15 % smaller for all rods. It was evident that the BISON code
underpredicted the tangential strain, whereas all other codes overpredicted the maximum strain
after burst. However, the deviation between the predicted and measured maximum strain values
was within the experimental uncertainty.

FIG. 124. Cladding outer diameter calculated at the end-of-test for rod 4 (QUENCH-LOCA
L1 test).

98

FIG. 125. Cladding oxide thickness calculated at the end-of-test for rod 4 (QUENCH-LOCA
L1 test).

FIG. 126. Equivalent cladding reacted calculated at the end-of-test for rod 4 (QUENCHLOCA L1 test).

99

FIG. 127. Hydrogen content in cladding at the end-of-test for rod 4 (QUENCH-LOCA L1test).
The cladding oxidation thicknesses along the rod after the LOCA experiment calculatedby the participants are reported in Fig. 125, while the experimental values are reported in
Section 2.4. Taking into account that the values obtained with the codes for the oxidized layer
thickness are only for the ZrO2 layer thickness, whereas the experimental values represent asum of the thickness of ZrO2 and α–Zr(O), and the large experimental scatter, it is fair toconclude that the values obtained with the codes are close to the measured values of ZrO2.
The predicted code values are also scattered, despite the cladding temperature used as
input of the code is close for all participants, being probably very sensible to this parameter.
The same observation can be made about the equivalent cladding reacted depicted in Fig. 126.
It is very likely that specific differences in the parametrization of the models exist for thedifferent participants. Finally, it should be pointed out that only predictions for the hydrogencontent in the cladding at the end of the test were provided by the DIONISIO code and depicted
in Fig. 127 for the sake completeness.
Rod failure times are reported in Fig. 128. The calculated values were scattered ascompare to the experimental burst time, but the several factors should be considered:
There was a spread on the axial temperature profiles, as indicated in Section 2.4 above;
There was a radial temperature gradient in the bundle;
The observed bending of the fuel rods (related to azimuthal temperature variations) was
not simulated by the codes;
The observed clad ballooning was not symmetric.
The TRANSURANUS code indicated the largest over-predicted burst time for this rod.
To assess the effect of some known uncertainties, a few additional calculations were carriedout. For instance, the impact of a ±10% spread on the cladding temperature was analyzed. The
effect of this coolant temperature variation on the burst time was consistent with the spread of
the burst time observed. Hence the coolant temperature would have an impact on the burst time.
This was consistent with the conclusions from the uncertainty analysis reported in Section 5.
One could conclude that the measured and calculated burst times were in reasonable agreement.
The difference between the predicted and the experimental values was not significant, when
considering the experimental uncertainties and the azimuthal temperature that could not be
typically captured by the 1.5D fuel performance codes.

100FIG. 128. Failure time (s) of rod 4 in QUENCH-LOCA L1 test at KIT.
The predicted burst pressures were compared with the experimental value, as summarized
in Fig. 129. Except for the DIONISIO code that underpredicted the measured burst pressure,the other codes tend to be overpredicted. However, BISON and TRANSURANUS imposed a
rod internal pressure based on the measured values that could explain the degree ofoverprediction. DIONISIO and ATHLET-CD codes used the calculated coolant temperatures.
Nevertheless, the cladding temperature at the time-of-failure in DIONISIO was quite close to
the measured value as show in Fig. 132 below. DIONISIO used FEM to discretize the halfpellet of each sector and an average value on stress to calculate the burst criteria (rather thanthe maximum value in a single element). This was done to avoid abnormal (extreme) values,
but could underestimate the value on burst or the maximum stress.

FIG. 129. Burst pressure (MPa) at failure in rod 4 in QUENCH-LOCA L1 test at KIT.
Fig. 130 indicated the average cladding hoop stress at burst elevation. The values obtained
from TRANSURANUS and ATHLET-CD were almost two time those from DIONISIO andBISON codes. This could reflect on the experimental uncertainty on the burst stress, which wasusually reported as a function of temperature in a logarithmic scale.

101

FIG. 130. Average cladding hoop stress (MPa) at burst elevation in rod 4 (QUENCH-LOCA
L1 test) at KIT.
The predicted burst elevations are indicated in Fig. 131. Although the results wereconsistent with the axial plots for the outer diameter, results would also depend on the axial
discretisation used in different simulations. The low value obtained by DIONISIO code wasmost likely affected by the axial distribution of the coolant temperature which was calculated,
whereas the other codes simply applied the measured temperatures (as the boundary condition)
during the test. This is consistent with the lower axial elevation of the burst position revealedin Fig. 131.

FIG. 131. Axial position of the centre of the burst (mm) of rod 4 in QUENCH-LOCA L1 test
at KIT.
The clad temperatures at burst are indicated in Fig. 132, which are consistent with thetrends as shown in Fig. 123. TRANSURANUS code predicted a low temperature, as theimposed clad temperature was decreased with an overpredicted burst time. The opposite wastrue for the BISON code. The ATHLET-CD code on the other hand indicated a lower
temperature because of the lower burst elevation at 850 mm. The temperature predicted by
ATHLET-CD at 950 mm, representing the measured burst elevation, was approximately 30 K
higher than at 850 mm, which was comparable to the experimental value.

102

FIG. 132. Clad outer temperature (oC) at burst elevation of rod 4 in QUENCH-LOCA L1 test
at KIT.
The predicted maximum tangential strains after the tests, compared with the measured
value, are as indicated in Fig. 133. The overall picture was consistent with those results
illustrated in Fig. 124, i.e. the BISON code underpredicted while the other codes overpredicted
the maximum deformation. One should note that the experimental value included the burst
opening size. The measured strain would be reduced by about 11–14%, if the burst opening size
was not included.

FIG. 133. Clad average hoop engineering strain (%) at burst elevation of rod 4 in QUENCH
LOCA L1 test at KIT.
4.5. CORA-15
Two organizations provided results for this case:
GRS (Germany), ATHLET-CD code;
IBRAE (Russia), SOCRAT code.
For both codes, the rod bundle was simulated by four concentric rings according toTable 10, an inner ring (ROD1) containing the central unheated rod, a second ring containing

103

four heated rods (ROD2), a third ring containing six unheated rods and two absorber rods
(ROD3) and an outer ring with twelve heated rods (ROD4).
TABLE 10. CORA-15 ROD GROUPS FOR MODELLING
Rod group in code

Number of rod in the CORA-15 test bundle

Rod 1

Central unheated rod (4.4)

Rod 2
Rod 3

Inner heated rods (3.3), (3.5), (5.5), (5.3)
Unheated rods (4.2), (2.2), (2.4), (2.6), (6.6), (6.4);
Absorber rods (4.6), (6.2) in ATHLET-CD
Outer heated rods (1.1), (1.3), (1.5), (1.7), (3.7), (5.7),(7.7), (7.5), (7.3), (7.1), (5.1), (3.1)

Rod 4

The reference time (0 s) was established for the beginning of the experiment. The
reference bundle elevation (0 mm) corresponded to the bottom of the heated length in the rod
simulator.
4.5.1. Cladding burst parameters for the CORA-15 bundle
Table 11 shows results of both codes concerning the burst parameters. Experimental
average values of the burst time for corresponding rod groups are included.

TABLE 11. BURST DATA CALCULATED BY ATHLET CD (GRS), SOCRAT(IBRAE) (in comparison with experimental results)
Description

Rod 1
3595
3619

Rod 2
3571
3559

Rod 3
3612
3626

Rod 4
3570
3593

Source
GRS
IBRAE

3601

3559e
3548-3564f

3609e
3565-3645f

3580e
3494-3618f

Experiment

6.90
6.15
6.15
750
783

6.92
5.85
5.44 (rod 3.3)
750
717Time of burst (s)Internal rod
pressurea (MPa)
Axial elevation(mm)b
Cladding outer
temperaturec (°С)
Maximum hoopstraina (%)
Average hoop
stressa (Mpa)
a

767
842
43.64
36
133.3

6.68
6.81
6.0
5.85
5.73 (rod 6.6) 5.84 (rod 7.7)
750
750
783
750
—g
762
766
754
827
847
847
Between 650 and 850 (estimated)
40.97
40.55
38.87
36
36
38
h
—
82.2
82.2
79.6
—h

At predicted burst time.
b
Of middle of clad burst opening.
c
At the middle of the burst at predicted burst time.
dAzimuthal average hoop stress (Mpa) σb in cladding at predicted burst time.
e
Mean.
f
Time span.
g—: Not available because of the bundle melting.
h—: Not available.

104

GRS
IBRAE
Experiment
GRS
IBRAE
Experiment
GRS
IBRAE
Experiment
GRS
IBRAE
Experiment
GRS
Experiment

The corresponding comparison diagrams together with experimental data are presented
in Fig. 134.
GRS
IBRAE
experiment

4

Rod group

Rod group

4

3

2

1
3500

3550
3600
Burst time, s

3650

3700

600

GRS
IBRAE
experiment

3

2

650

700
750
800
850
Burst temperature, °C

1

900

GRS

4

Rod group4

Rod group

GRS
IBRAE
experiment

2

1

3450

IBRAE

3

2

1
4

5
6
7
Burst pressure, MPa

8

25

GRS
IBRAE
exp.

3

2
1

30

35
40
Burst strain, %4
Rod group4
Rod group

3

45

GRS

3

2

1
600

650

700
750
800
Burst elevation, mm

850

70

80

90 100 110 120
Burst stress, MPa

130

140

FIG. 134. Burst parameters. Transparent bars show uncertainty ranges. Transparent red
corresponds to the measurement uncertainties, transparent green and blue - predictions withthe axial node size of 100 mm (GRS) and 33 mm (IBRAE), respectively.
Measured data that characterized the cladding burst were the burst time and the burst
pressure derived from the pressure evolutions. The burst elevations were not available becauseof the bundle melting in the expected ballooning zone. The burst time depended mainly on thetemperature distribution within the cross-section since the initial inner pressure was small. The
test exhibited a large burst time span of 150 s (from 3494 to 3644 s). This indicated a large
cladding temperature difference in the burst cross-sections that could be estimated as 150 K
based on the measured burst time span and the heat up rate (1 K/s). The temperature differences
could be resulted from the heat losses (outer heated claddings were colder than inner ones),105presence of unheated rods and absorbers as well as from a local temperature non-uniformity.
Table 11 indicated the following burst sequence in the test: heated inner claddings (rod 2) –outer heated claddings (rod 4) – unheated central cladding (rod 1) – inner unheated cladding(rod 3). The burst time span was calculated within the experimental scattering of ATHLET aswell as SOCRAT. Burst pressure was captured by both codes with a tendency of slightoverestimated (the measured burst pressure values, provided for the groups 2–4 in Fig. 134,
were derived from the pressure evolutions of individual rods as indicated in the Table 11, notaveraged over the groups).
The burst elevation could be estimated assuming that the ballooning and rupture occurredat the hottest elevation. Fig. 135 displays vertical temperature profiles at the beginning (3500 s),
the middle (3600 s) and the end (3650 s) of the burst time span derived from the available TC
readings. This facilitated the estimation of the hottest zone location between 250 mm and
850 mm at the beginning, and between 600 and 850 mm at the middle and the end of burst time
span. The hottest zone was calculated at around an elevation of 750 mm. Considering the node
sizes, the axial elevations of the clad burst openings in all rods predicted both by ATHLET and
SOCRAT were located between 700 and 800 mm (Fig. 134).
The burst temperatures of the unheated cladding were estimated to rise from 650 to 800°C during the burst time span. The heated rods were estimated to be 50 K hotter than theunheated ones based on the difference of 50 s between the mean values of the burst times. So,
the estimated temperature range for both the heated and unheated rods would be approximately
650 to 850 C.
Maximum hoop strain achieved at the opening of the burst was calculated by both codes
as εb = 100·(Dact – D0)/D0, where Dact = (Dext + Din)/2 was the mean diameter of cladding, Dext
and Din were external and internal cladding diameters at the opening at the burst time, and D0
was the initial mean cladding diameter. Both codes used a simple failure criterion based on the
maximum strain.

FIG. 135. Vertical temperature distribution at the burst time span.

106

4.5.2. Time dependences and axial dependences of LOCA events for central rod 4.4 of
the CORA-15 bundle
ATHLET and SOCRAT gave reasonable temperature predictions (see Figs 136 and 137).
However, there were discrepancies in the pressure modelling: higher burst pressure for
ATHLET (GRS) than for SOCRAT (IBRAE) (Fig. 137).
2500

8

2250

7

2000

6

Pressure, MPa

9Temperature, K

2750

1750

5
Tc GRS

1500

4

Tc IBRAE
exp. T 750U4.4

1250

3

pi GRSpi IBRAE

1000

2exp. p rod 4.4

750

1

500
0

1000

2000

3000
Time, s

4000

5000

0
6000

FIG. 136. Comparison of temperature (Tc) and internal pressure (pi) histories during the test
(at an elevation of 750 mm).
1500

7.25

Tc GRS
Tc IBRAE

1250

pi GRS

1125

exp. p rod 4.4

7.00

exp. T 750U4.4

6.75

pi IBRAE

6.50

Pressure, MPa

Temperature, K

1375

1000

6.25

875

6.00

750

5.75

625

5.50

500
2900

5.25
3100

3300
Time, s

3500

3700

FIG. 137. Comparison of temperature (Tc) and internal pressure (pi) histories during the
LOCA transient (at an elevation of 750 mm).
There was a remarkable coincidence in the location and extent of the ballooning zone
predicted by both codes as indicated in Fig. 138, though ATHLET revealed a stronger
ballooning in comparison with SOCRAT. The reason of a sharp decrease of the residual metal
thickness between 450 and 950 mm was the thinning of the cladding due to ballooning. The
influence of the oxide layer was minimal at the time of the burst due to low oxide thickness(Fig. 139). SOCRAT indicated more oxidation (in narrower region) due to higher burst
temperatures.

107

750

15.0
14.5

700
Metal layer thickness, µm

14.0

Diameter, mm

13.5
13.0

650
Clad_Diam GRS

12.5

Clad_Diam IBRAE

12.0

600

TRMb GRS

11.5

TRMb IBRAE

11.0

550

10.5
10.0
0

200

400

600
Elevation, mm

800

1000

500
1200

FIG. 138. Axial distributions of cladding external diameter and residual metal at burst time.
3.0
TOLb GRS

Oxide layer thickness, µm

2.5

TOLb IBRAE

2.0

1.5

1.0

0.5

0.0
0

200

400

600
Elevation, mm

800

1000

1200

FIG. 139. Axial distributions of oxide layer ZrO2 at the outer cladding surface.
4.5.3. Post-test outer oxide layer thickness of the CORA-15 claddings
The thickness of ZrO2 films at different elevations for different element groups isindicated in Fig. 140. Debris from ZrO2 relocated with the melt or any information about
oxidized part of the melt were not provided.

108

Unheated Control Rod Group 1

Heated Rod Group 2

Unheated Rod Group 3

Heated Rod Group 4

FIG. 140. Results on calculated final axial distribution of oxide layer thickness at the end of
the test.
Concerning the GRS data, it should be mentioned that for the central unheated rod 1 andinner heated rod group 2, the cladding metal between 650–950 mm was completely relocatedto lower elevations during the time interval from 4190–4250 s. Thereafter, the thickness ofresidual metal at those elevations was calculated to be zero. Oxide layer at elevation 950 mm
was 251 µm, afterwards it was kept constant. This was the reason why it was less than thecorresponding thickness at elevation 1150 mm, where the oxidation continues with the coolingphase.
The IBRAE data showed axial variation of residual ZrO2 thickness connected with themodelling of the start of the melt formation and its relocation through breaches of claddings.
The degradation of ZrO2 cladding were governed by set of different phenomena: ballooning
and burst, dissolution of oxides by molten Zr, and loss of cladding integrity due totransformation into debris.

109

4.5.4. Post-test blockage of the CORA-15 bundle
The bundle blockage is defined as a reduction of the area of the original fluid channel by
an increase in material area 𝐴 :⁄𝐴 ,𝐵 = 100% ∙ 𝐴 − 𝐴 ,where the area of the initial fluid channel 𝐴 = 𝐴 − 𝐴 ,= 𝐴 − 23𝐴
− 2𝐴
= 0.00673  0.00209  0.0003 = 0.00434 m² with area inside the shroud 𝐴 = 0.00673 m².
Please note that the cross-sectional areas for one of those 23 fuel rods 𝐴𝑟𝑜𝑑 = 90.87 mm2 andone of 2 absorber rods 𝐴= 150 mm2.
grid
75
0.007
Blockage GRS
spacers
Blockage IBRAE
Material area GRS
Material area IBRAE
Materail area, exp.

45

0.006
0.005

30

0.004

15

0.003

0

0.002

-15

0.001

-30
-50

50

150

250

350

450 550 650
Elevation, mm

750

850

Area of materials, m²

Bundle blockage B, %60

0950 1050 1150

FIG. 141. Results on material distribution (𝐴 ) and bundle blockage B at the end of the test.
As indicated in Fig. 141, IBRAE calculation predicted the relocation of molten materials
from upper elevations to the middle grid spacer (about 500 mm). For GRS, the lack ofmodelling melt retention by spacer grids leads to an overestimation of the temperatures atelevations below the spacer grid at 450 mm. To artificially simulate this retention effect, a very
low relocation velocity for the metallic (Zr) melt was used, which shifted the axial profile ofthe blockage to higher elevations.
4.5.5. Hydrogen release during the CORA-15 test
Comparison of the hydrogen flowrate and total mass calculated at the outlet of the test
section, with data measured by two mass spectrometers located in the gas lines, were presented
in Figs 142 and 143. Both codes predicted the total hydrogen mass at the end of the test
sampling line, within the measurement uncertainties illustrated.

110

350

H2 rate, mg/s

300
250

200

GRS H2 rateexp. H2 rate before condenser
exp. H2 rate after condenser
GRS integral H2
exp. integral H2 before condenser
exp. integral H2 after condenser

175
150
125

Integral H2, g

400

200

100

150

75

100

50

50

25

0
3500

3750

4000

4250

4500

4750 5000
Time, s

5250

5500

5750

0
6000

FIG. 142. Comparison of GRS calculation results with experimental data of two mass
spectrometers.

250

H2 rate, mg/s

200

200

IBRAE H2 rateexp. H2 rate before condenser
exp. H2 rate after condenser
IBRAE integral H2
exp. integral H2 before condenser
exp. integral H2 after condenser

175
150
125

150

100
75

100

50
50

0
3500

Integral H2, g

300

25

3750

4000

4250

4500

4750 5000
Time, s

5250

5500

5750

0
6000

FIG. 143. Comparison of IBRAE calculation results with experimental data of two mass
spectrometers.
A correction of hydrogen evolution should be performed, considering the peculiarities of
the gas lines with the spectrometer (effects of transport delay, dilution, mixing and so on). For
instance, as indicated in Fig. 144, the measured hydrogen curves after the condenser in the othertest (CORA-W2) were corrected to reproduce the hydrogen curves at the outlet of the test
section. This correction facilitated a direct comparison between the measured and calculated
values.
111

FIG. 144. Effect of measurement - hydrogen production measured by spectrometer andcorrected to a test section outlet in CORA-W2 test [98].

1125. UNCERTAINTY AND SENSITIVITY ANALYSIS FOR IFA-650.10
5.1. INTRODUCTION
As part of the FUMAC project, an uncertainty and sensitivity analysis (UASA) was
performed on the modelling of the Halden LOCA test IFA-650.10 (PWR rod, without
significant axial relocation) with different fuel rod codes.
The objective was to verify the key physical phenomena (such as clad and fueltemperatures, rod internal pressure, clad elongation, and clad outside diameter) which were wellbound by the measured data. As an optional activity for some participants, sensitivity analysis
for these phenomena was also completed through global sensitivity analysis (GSA).
This chapter describes the fuel codes and the statistical uncertainty and sensitivity
analysis tools; the specifications for the uncertainty and sensitivity analysis tools; and thecomparison and discussion of the uncertainty and sensitivity analysis results provided by theparticipants.
5.2. PARTICIPANTS AND USED CODESAs shown in Table 12, seven participants performed the uncertainty analysis, and six
participants performed the sensitivity analysis.
TABLE 12. PARTICIPANTS OF UNCERTAINTY AND SENSITIVITY ANALYSIS
Participant
CNEA
CEA
CIAE
CIEMAT
IPEN
Tractebel
JRC

Code
DIONISIO-2.0
ALCYONE-1D
FTPAC
FRAPTRAN-1.5
FRAPTRANFRAPTRAN-TE-1.5
TRANSURANUS

UA/SA Tool
DAKOTAURANIEDAKOTADAKOTA
Excel
DAKOTA
Built-in (M-C)

UA
Y
Y
Y
Y
Y
Y
Y

SA
Y
Y
Y
Y
Y
Y

Five different fuel rod codes (DIONISIO, ALCYONE, FTPAC, FRAPTRAN,
TRANSURANUS) and four different statistical uncertainty and sensitivity analysis tools(DAKOTA, URANIE, Excel, and built-in Monte Carlo function) were used. The analyses were
performed according to the specifications (see Annex I).
Results submitted by the participants were analyzed and compared with the available
experimental data in this chapter. A detailed discussion of the results from each participant
could be found in their respective reports, as compiled in the Annex II.
5.3. SPECIFICATIONS
5.3.1. Methodology
The following uncertainty analysis approach was adopted amd a common list of input
uncertainty parameters was defined, covering:
Fuel manufacturing data;
Operating and test conditions;
Material properties and models;
The uncertainties on the output parameters of interest were quantified using the input
uncertainty propagation method through Monte-Carlo simulations [99].
The non-parametric order statistics [100] was a well established and shared methodology
in the nuclear community [101–102], and hence the methodology was recommended for this113

activity. Methodologies for sampling and for the uncertainty and sensitivity analysis [99–109]
are described in Section 2 of Annex I.
If a participant does not have his own tool, a statistical UASA analysis tool (DAKOTA[110]) may be used, which may be obtained freely from ANL.
The participant, however, has the freedom to use other alternative method or tool toperform the UASA, or to perform only the uncertainty analysis.
A common list of output parameters was defined for this CRP, the results were provided
for comparison.
5.3.2. Definition of input uncertainty parameters
The input uncertainty parameters to be considered are defined in Table 13 for Halden
LOCA test IFA-650.10 [111]. For simplicity, a normal distribution was assumed for all input
uncertainty parameters. Note also that the uncertainty on the model input parameters is defined
as a multiplier (the mean value of 1.00 is thus the calculated best estimate value), theuncertainty on the measured or calculated temperature (cladding, coolant or plenum) is defined
as an adder (the mean value of T is thus the measured or calculated best estimate value).
TABLE 13. LIST OF INPUT UNCERTAINTY PARAMETERS FOR IFA-650.10
Distribution

Input Uncertainty Parameters

Cladding outside diameter (mm)9.50Standard
Deviation
0.01

Cladding inside diameter (mm)

8.36

0.01

Normal8.34

8.38

Pellet outside diameter
Fuel theoretical density (kg/m3
at 20°C)
U235 enrichment (%)

8.2

0.01

Normal

8.18

8.22

10457

50

Normal

10357

10557

4.487

0.05

Normal

4.387

4.587

Filling gas pressure (MPa)

4.0

0.05

Normal3.9

4.1

Relative power during base irradiation

1

0.01

Normal0.98

1.02

Relative power during test

1

0.025

Normal0.95

1.05

Test rod power profile

1

0.01

Normal0.98

1.02

Cladding temperature (°C)

T (Measured)

10

-

T-20

T+20

Coolant temperature (°C)
Clad-to-coolant heat transfer
coefficient multiplier (same Coef.
applied for all flow regimes)
Fuel thermal conductivity model
multiplier
Clad thermal conductivity model
multiplier
Fuel thermal expansion model
multiplier
Clad thermal expansion model
multiplier
Fuel densification model multiplier

T (Calculated)

5

-

T-10

T+10

1.00
(Calculated)

0.125

Normal

0.75

1.25

1.00

5%

Normal

0.90

1.10

1.00

5%

Normal

0.90

1.10

1.00

5%

Normal

0.90

1.10

1.00

5%

Normal

0.90

1.10

1.00

5%

Normal0.90

1.10

Fuel solid swelling model multiplier

1.00

5%

Normal

0.90

1.10

Mean

114

Normal

Lower
bound
9.48

Upper
bound
9.52

Type

Distribution

Input Uncertainty Parameters
Mean

Standard
Deviation

Type

Lower
bound

Upper
bound

Fuel gaseous swelling model
multiplier
Clad Yield stress multiplier

1.00

5%

Normal

0.90

1.10

1.00

5%

Normal0.90

1.10

Fuel heat capacity multiplier

1.00

1.5%

Normal0.97

1.03

Cladding heat capacity multiplier

1.00

1.5%

Normal0.97

1.03

Cladding elastic modulus multiplier
Cladding corrosion model multiplierduring steady-state operation
Cladding hydrogen pickup fraction
multiplier during steady-state
operation
Cladding oxidation model multiplierat high temperature
Thermal conductivity multiplier of theoxide layer
Fission gas release (or gas diffusion
coefficient) multiplier
Gap gas conductivity multiplier

1.00

5%

Normal

0.90

1.10

1.00

12.5%

Normal

0.75

1.25

1.00

15%

Normal

0.7

1.30

1.00

15%

Normal

0.7

1.30

1.00

10%

Normal

0.80

1.20

1.00

25%

Normal

0.50

1.50

1.00

12.5%

Normal0.75

1.25

Fuel/cladding emissivity multiplier

1.00

5%

Normal0.90

1.10

Fuel radial relocation multiplier
Fuel fragment packing fraction
multiplier (if applicable)
Cladding strain threshold multiplierfor fuel mobility (if applicable)
Cladding Meyer hardness multiplier

1.00

10%

Normal

0.80

1.20

1.00

10%

Normal

0.80

1.20

1.00

10%

Normal

0.80

1.20

1.00

5%

Normal0.90

1.10

Cladding annealing multiplier

1.00

5%

Normal0.90

1.10

Cladding burst criteria multiplier
Cladding burst strain criteria
multiplier

1.00

10%

Normal

0.80

1.20

1.00

10%

Normal0.80

1.20

Plenum gas temperature (°C)

T (measured or
calculated)

5

-

T-10

T+10

5.3.3. Modelling assumptions
Due to complexity to simulate the thermal hydraulic behaviours and the differences that
may appear from various assumptions and/or models, it was recommended to use the thermal
hydraulic boundary conditions calculated from SOCRAT [112], namely:
Coolant temperatures;
Clad to coolant heat transfer coefficients (HTCs).
The clad to coolant heat transfer coefficients should be determined from the total heat
flux (radiative and convective), namely HTC = Qtot / (Tclad –Tcool), for each axial node. This willallow the fuel rod code to calculate the cladding temperatures Tclad.
Alternatively, the measured or calculated cladding temperatures could be imposed
directly as the boundary conditions.

115

The rodlet plenum temperature (Tplenum) should be taken from the measurement, or fromany appropriate empirical plenum gas temperature model.
A steady state of 100 s should be simulated before the beginning of blowdown. The
transient calculation should stop at 600 s (after the scram at 517 s).
The recommended maximum time step is 0.1 s during the steady-state and 0.001 s during
the transient and 0.0002 s during the burst period, but short time steps can be used for stabilityof calculations.
5.3.4. Output parameters
For the uncertainty analysis, each participant is requested to provide lower and upperbounds (LB, UB) associated with all the time trend of output parameters listed in Table 14 (therecommended frequency is 10 s). In addition, the results of the calculation with the nominal
value of the input parameters, also called reference calculation (REF) should be provided.
For the sensitivity analysis, the partial rank correlation coefficients (PRCC, or
Spearman’s RCC if PRCC is not available) of the above output parameter vs. each of the input
uncertainty, at the times defined in Table 15, and the maximal value for each correspondence
parameter should be provided.
TABLE 14. LIST OF OUTPUT PARAMETERS TO BE PROVIDED
Parameter

Unit

Description

Fuel rod internal pressure (RIP)

MPa

Fuel rod internal pressure

Fuel centreline temperature (TFC)°C

Temperature of fuel centreline at peak power/burst
node

Fuel surface temperature (TFO)°C

Fuel surface temperature at peak power/burst node

Cladding inside surface temperature (TCI)°C

Cladding outside surface temperature(TCO)
Cladding outside surface oxide layer
thickness (TOL)°C
mm

Cladding inside surface temperature at peak
power/burst node
Cladding outside surface temperature at peak
power/burst node
Cladding outside surface oxide layer thickness at
peak power/burst node
Equivalent cladding reacted at peak power/burst
node
Cladding outside diameter at peak power/burst
node

Equivalent cladding reacted (ECR)%

Cladding outside diameter (DCO)mm

Cladding effective stress (CES)MPa

Cladding effective stress at peak power/burst node

Cladding elongation (ECT)mm

Clad total axial elongation

Fuel elongation (EFT)mm

Fuel column total axial elongation (expansion)

116

TABLE 15. LIST OF DIFFERENT TIMES FOR SENSITIVITY ANALYSIS OUTPUT
Time/
parameters

t1

t2

Definition

End ofnaturalcirculation

Beginning of
blowdown

End ofcooldown

Burst

End ofcalculation

Value

100.0 s

110 s

170 s

350 s

600 s

t3

t4

t5

5.4. COMPARISON OF UNCERTAINTY ANALYSIS RESULTS
The calculation results of the 200 successful runs were collected. The 5th and 196th ranks
were chosen to estimate the upper/lower (95%/5%) uncertainty bounds (LB, UB) of the output
parameter of interest, according to the order statistics (except that JRC used directly Monte
Carlo method to obtain the upper/lower (95%/5%) uncertainty bounds (LB, UB)). The resultsof the reference case (REF) were also provided.
The uncertainty of the following main output parameters were compared and discussed
in this report:
Rod internal pressure (RIP);
Cladding outer surface temperature (TCO) at burst node;
Fuel outer surface temperature (TFO) at burst node;
Cladding total elongation (ECT);
Cladding outside diameter (DCO) at burst node.
Comparison of the experimental data within the reference and upper bound values, foreach of the main output parameters, allowed an assessment of the adequacy of the model andthe conservatism of the upper bound value.
Comparison of the uncertainty bands, obtained by different participants for each of themain output parameters with measurements, allowed to quantify the accuracy of the model.
Comparison of the position of the reference case within the uncertainty bands, by different
participants for each of the main out parameters, allowed detection of bias (if any) in the model.
Finally, comparison of the differences between the maximum UB values and minimum
LB values (the global uncertainty width) and the maximum REF values and minimum REF
values (the global reference dispersion) allowed identification of the proportion of the model
difference in the global uncertainty width, as well as the position of the experimental data.
5.4.1. Rod internal pressure (RIP)
The calculated reference rod internal pressure is indicated in Fig. 145. Reasonably
agreements with the experimental data were obtained. With the exception for Tractebel and
JRC, all participants predicted an early burst. CEA’s results after the burst were discarded since
they are not physical. The results between CIEMAT, IPEN and Tractebel were different,
although the same FRAPTRAN code, with different versions, options, and assumptions (cladand plenum gas temperatures) were used.
The calculated upper bound for rod internal pressure is indicated in Fig. 146, which does
not bound the experimental data, except for Tractebel (trend and burst time) and JRC (bursttime). This was not surprising as only Tractebel and JRC predicted well for the burst time (seeFig. 145).
The calculated uncertainty band for rod internal pressure is indicated in Fig. 147. The
uncertainty bounds were between 0.25–0.45 MPa (about 4%) close to the burst time, except for
those lower values predicted by JRC and IPEN.

117

Fig. 148 indicated the position of the reference within the uncertainty band for rod internalpressure. The reference values were closer to the lower bound before the burst(R = (REF  LB)/(UB  LB) < 0.5), and closer to the upper bound at the burst (R > 0.5).
Interesting observation could be made from Fig. 149. The experimental data werebounded by both the minimum and maximum reference values (reference dispersion) and theminimum and maximum uncertainty values (uncertainty width). This indicated that there wasno bias in the rod internal pressure model, whose uncertainty band could be quantified by thestatistical approach.
14

Rod internal pressue
reference value (MPa)

12
10
EXP

8

CEA
CIAE
CIEMAT

6

CNEA
Tractebel
IPEN

4

JRC

2
0
0

100

200

300
Time (s)

400

500

600

FIG. 145. IFA-650.10: Reference values for the rod internal pressure.
14

Rod internal pressre
upper bound (MPa)

12
10
8

EXP
CEA
CIAE
CIEMAT

6

CNEA
Tractebel
IPEN

4

JRC

2
0
0

100

200

300
Time (s)

400

500

600

FIG. 146. IFA-650.10: Upper bounds for the rod internal pressure.

118

0,50
0,45
Rod internal pressure
uncertainty band (MPa)

0,40
0,35
0,30

CEA
CIAE

0,25

CIEMAT
CNEA

0,20

Tractebel
IPEN

0,15

JRC

0,10
0,05
0,00
0

100

200

300
Time (s)

400

500

600

FIG. 147. IFA-650.10: Uncertainty bands for the rod internal pressure.

1,0

Rod internal pressure
position of the reference

0,9
0,8
0,7
0,6

CEA
CIAE

0,5

CIEMAT
CNEA

0,4

Tractebel
IPEN

0,3

JRC

0,2
0,1
0,0
0

100

200

300
Time (s)

400

500

600

FIG. 148. IFA-650.10: Position of the reference values within the uncertainty band for therod internal pressure.

119

14

12
EXP
Rod Internal Pressure (MPa)10

Min(LB_all_participants)
Max(UB_all_participants)
Min(Ref_all_participants)

8

Max(Ref_all_participants)
6

4

2

0
0

100

200

300
Time (s)

400

500

600

FIG. 149. IFA-650.10: The global reference dispersion and uncertainty width of allparticipants for the rod internal pressure.
5.4.2. Clad outer surface temperature (TCO)
The calculated reference clad outer surface temperature is indicated in Fig. 150, which isslightly higher than the experimental data. Instead of using the SOCRAT calculated coolant
temperature, heat transfer coefficient and the associated uncertainties, as requested in theSpecifications, IPEN used the measured clad temperature directly.
The location of the calculated cladding surface temperature at burst node was notprecisely the one that was measured, hence the results could be slightly different and morerefined nodalization and measurements were recommended. Results obtained from CIEMAT,IPEN and Tractebel were different, although the same FRAPTRAN code, but with different
versions, options and assumptions, was used.
The calculated upper bound clad outer surface temperature is indicated in Fig. 151, which
does bound the experimental data. Note again that IPEN used the measured clad temperature
directly, instead of using the SOCRAT calculated coolant temperature and heat transfer
coefficient and the associated uncertainties as requested in the Specifications.
The calculated uncertainty band for clad outer surface temperature is indicated in Fig.
152. The uncertainty bounds were between 0–80°C, which was about 10% of the reference
value. In general, the uncertainty bands were higher after burst.
The position of the reference within the uncertainty band for clad outer surface
temperature is indicated in Fig. 153. The reference values were closer to the middle of theuncertainty band (R = (REF  LB)/(UB  LB) = 0.5), except for CIEMAT (which was closer
to upper band after burst) and IPEN (from which the uncertainty band was not considered).

120

Clad outer surface temperaturereference value (°C)

1200
1000
800
EXP
CEA

600

CIAE
CIEMAT
CNEA
Tractebel

400

IPEN
JRC

200
0
0

100

200

300
Time (s)

400

500

600

FIG. 150. IFA-650.10: Reference values for clad outer surface temperature.

Clad outer surface temperature
upper bound (°C)

1200
1000
800
EXP
CEA

600

CIAE
CIEMAT
CNEA
Tractebel

400

IPEN
JRC

200
0
0

100

200

300
Time (s)

400

500

600

FIG. 151. IFA-650.10: Upper bounds for clad outer surface temperature.

121

100

Clad outer surface temperature
uncertainty band (°C)

90
80
70
60

CEA
CIAE

50

CIEMAT
CNEA

40

Tractebel
IPEN

30

JRC

20
10
0
0

100

200

300
Time (s)

400

500

600

FIG. 152. IFA-650.10: Uncertainty bands for clad outer surface temperature.

Clad temperature uncertainty coverage

1,0
0,9
0,8
0,7
0,6

CEA
CIAE

0,5

CIEMAT
CNEA

0,4

Tractebel
IPEN

0,3

JRC

0,2
0,1
0,0
0

100

200

300
Time (s)

400

500

600

FIG. 153. IFA-650.10: Position of the reference within the uncertainty band for clad outersurface temperature.

122

1200

Clad Outer Surface Temperature (°C)

1000

800

600
EXP

400

Min(LB_all_participants)
Max(UB_all_participants)
Min(Ref_all_participants)

200

Max(REF_all_participants)

0
0

100

200

300
Time (s)

400

500

600

FIG. 154. IFA-650.10: The global reference dispersion and uncertainty width of allparticipants for clad outer surface temperature.
The experimental data are bounded by both the maximum reference and the UB values,
as indicated in Fig. 154. Both the minimum reference and LB values were close to theexperimental data, this indicated that a significant bias in the thermal hydraulic boundary
conditions could exist.
5.4.3. Fuel outer surface temperature (TFO)
The calculated reference fuel outer surface temperature is indicated in Fig. 155. No
experimental data was available for comparison. However, all but the CNEA results wereconsistent with the clad outer surface temperature (Fig. 150). As noted previously, thedifference of results was obtained between CIEMAT, IPEN and Tractebel, using the same
FRAPTRAN code but with different versions, options and assumptions.
The calculated upper bound, uncertainty band, and the position of the reference values
for fuel outer surface temperature are indicated from Figs 156 to 158. The uncertainty band
(Fig. 157) was greater than that for the clad outer surface temperature (Fig. 152), due to theinvolvement of modelling uncertainties (such as clad/fuel thermal conductivity, gap
conductance, etc.). The reference values were closer to the middle of the uncertainty band (R =(R = (REF  LB)/(UB  LB) = 0.5), except for CIEMAT (which is closer to upper band after
burst) and IPEN (which uncertainty band was not considered).
The reference dispersion and uncertainty width presented by all participants were quite
close, as indicated in Fig. 159. The difference between the reference values was dominant in
the uncertainty width.

123

Fuel outer surface temperaturereference value (°C)

1200
1000
800
CEA
CIAE

600

CIEMAT
CNEA
Tractebel
IPEN

400

JRC

200
0
0

100

200

300
Time (s)

400

500

600

FIG. 155. IFA-650.10: Reference values for fuel outer surface temperature.

Fuel outer surface temperature
upper bound (°C)

1200
1000
800
CEA
CIAE

600

CIEMAT
CNEA
Tractebel
IPEN

400

JRC

200
0
0

100

200

300
Time (s)

400

500

600

FIG. 156. IFA-650.10: Upper bound for fuel outer surface temperature.

124

100

Fuel outer surface temperature
uncertainty band (°C)

90
80
70
60

CEA
CIAE

50

CIEMAT
CNEA

40

Tractebel
IPEN

30

JRC

20
10
0
0

100

200

300
Time (s)

400

500

600

FIG. 157. IFA-650.10: Uncertainty bands for fuel outer surface temperature.

Fuel temperature uncertainty coverage

1,0
0,9
0,8
0,7
0,6

CEA
CIAE

0,5

CIEMAT
CNEA

0,4

Tractebel
IPEN

0,3

JRC

0,2
0,1
0,0
0

100

200

300
Time (s)

400

500

600

FIG. 158. IFA-650.10: The position of the reference within the uncertainty band for fuel outersurface temperature.

125

1200

Fuel Outer Surface Temperature (°C)

1000

800

600
Min(LB_all_participants)

400

Max(UB_all_participants)
Min(Ref_all_participants)
Max(Ref_all_participants)

200

0
0

100

200

300
Time (s)

400

500

600

FIG. 159. IFA-650.10: The global reference dispersion and uncertainty width of allparticipants for fuel outer surface temperature.
5.4.4. Clad elongation (ECT)The calculated reference clad elongation in comparison with the experimental data is
indicated in Fig. 160. Despite the different in initial states, the heatup period before burst weregenerally well predicted by all participants. However, FRAPTRAN predicted a reduction after
burst. The difference between CIEMAT, Tractebel and IPEN was noted again, when difference
versions of the FRAPTRAN code were used.
The calculated upper bound clad elongation is indicated in Fig. 161, which does boundthe experimental data except for the much lower results after burst predicted by the
FRAPTRAN (CIEMAT, IPEN and Tractebel). The large initial uncertainty could be due to thedifferent in starting points between the calculations and the experiment. A correction could
probably be applied but it would depend on several input uncertainty parameters.
The calculated uncertainty band for clad elongation is indicated in Fig. 162. The
uncertainty bounds were generally small, except for the large bands after burst with
FRAPTRAN. With FRAPTRAN code, with BALON2 model being activated, FRACAS-1 was
not able to correctly predict the behaviour of the cladding elongation after the burst. FEA model
should be able to do a better job but was not used in this case. The uncertainty band followed
the same trend as the reference case. This implied that the mechanical deformation model was
not sufficiently good and should be improved. Those improvements could be made directly tothe code (such as calibration, input data, meshing etc.) or the modification of the models (suchas improved ballooning model or use of FEA).
The position of the reference was within the uncertainty band for clad elongation asshown in Fig. 163. The reference values were closer to the middle of the uncertainty band
(R = (REF  LB)/(UB  LB) = 0.5).

126

4,0

Clad elongationreference value (mm)

2,0
0,0
0

100

200

300

400

500

600
EXP

-2,0

CEA
CIAE
CIEMAT-4,0

CNEA
Tractebel
IPEN

-6,0

JRC

-8,0
-10,0

Time (s)FIG. 160. IFA-650.10: Reference values for clad elongation.

4

Clad elongation
upper bound (mm)

2
0
0

100

200

300

400

500

600

-2

EXP
CEA
CIAE
CIEMAT-4

CNEA
Tractebel
IPEN

-6

JRC

-8
-10

Time (s)FIG. 161. IFA-650.10: Upper bounds for clad elongation.

127

2,0
1,8

Clad elongation
uncertainty band (mm)

1,6
1,4
1,2

CEA
CIAE

1,0

CIEMAT
CNEA

0,8

Tractebel
IPEN

0,6

JRC

0,4
0,2
0,0
0

100

200

300
Time (s)

400

500

600

FIG. 162. IFA-650.10: Uncertainty bands for clad elongation.

1,0

Clad elongation
position of the reference value

0,9
0,8
0,7
0,6

CEA
CIAE

0,5

CIEMAT
CNEA

0,4

Tractebel
IPEN

0,3

JRC

0,2
0,1
0,0
0

100

200

300
Time (s)

400

500

600

FIG. 163. Position of the reference within the uncertainty band for clad elongation.
Fig. 164 indicated the reference dispersion and uncertainty width for all participants werequite large. The difference between the reference values dominated the global uncertainty
width.

128

4
2
0

Clad Elongation

0

100

200

300

-2

400

500

600

EXP
Min(LB_all_participants)-4

Max(UB_all_participants)
Min(Ref_all_participants)-6

Max(Ref_all_participants)
-8
-10
-12

Time (s)FIG. 164. IFA-650.10: Global reference dispersion and uncertainty width of all participants
for clad elongation.
5.4.5. Clad outside diameter (COD) at burst node
Except for IPEN, the calculated reference clad outside diameter is indicated in Fig. 165.
CEA and CNEA results after burst were discarded. However, the difference between CIEMAT(highest in COD) and Tractebel (lowest in COD), both using the FRAPTRAN code but withdifferent versions and options, was noted again.
The calculated upper bound clad outside diameter is indicated in Fig. 166. Participant
results bounded the experimental data, except for the Tactebel results that could be improvedby using the FEA model.
The calculated uncertainty band for clad outside diameter is indicated in Fig. 167. The
uncertainty bounds were between 0–3.5 mm (up to 40%).
The position of the reference within the uncertainty band for clad outside diameter isindicated in Fig. 168. The reference values are closer to the middle of the uncertainty band
(R = (REF  LB)/(UB  LB) = 0.5) before the burst.
It is interesting to note that the reference dispersion and uncertainty width of allparticipants were quite large, as indicated in Fig. 169. The differences between the reference
values of all participants dominated the global uncertainty width. The minimum LB and REF
values were quite close, indicating that the model contained a significant bias and was notadequate for uncertainty analysis. This was due to the use of FRACAS-1 model in the
FRAPTRAN code used by Tractebel, which could be improved by using the FEA model.

129

18
17

Cladd outer diameter
reference value (mm)

16
15
14

EXP
CEA

13

CIAE
CIEMAT

12

CNEA

11

JRC

Tractebel

10
9
8
0

100

200

300
Time (s)

400

500

600

FIG. 165. IFA-650.10: Reference values for clad outside diameter.

18
17

Clad outer diameter
upper bound (mm)

16
15
14

EXP
CEA

13

CIAE
CIEMAT

12

CNEA
Tractebel
JRC

11
10
9
8
0

100

200

300
Time (s)

400

500

600

FIG. 166. IFA-650.10: Upper bounds for clad outside diameter.

130

4,0

Clad outer diameter
uncertainty band (mm)

3,5
3,0
2,5
CEA

2,0

CIAE
CIEMAT
CNEA

1,5

Tractebel
JRC

1,0
0,5
0,0
0

100

200

300
Time (s)

400

500

600

FIG. 167. IFA-650.10: Uncertainty bands for clad outside diameter.

1,0

Clad outer diameter
position of reference value

0,9
0,8
0,7
0,6
CEA

0,5

CIAE
CIEMAT

0,4

CNEA
Tractebel
JRC

0,3
0,2
0,1
0,0
0

100

200

300
Time (s)

400

500

600

FIG. 168. IFA-650.10: Position of the reference within the uncertainty band for clad outside
diameter.

131

18
EXP

17

Min(LB_all_participants)
Max(UB_all_participants)

16

Min(Ref_all_participants)

Clad Outer Diameter (mm)15

Max(Ref_all_participants)

14
13
12
11
10
9
8
0

100

200

300
Time (s)

400

500

600

FIG. 169. IFA-650.10: Global reference dispersion and uncertainty width of all participants
Clad outside diameter.
5.5. COMPARISON OF SENSITIVITY ANALYSIS RESULTS
The global sensitivity analysis (GSA) is a powerful tool to identify the most influential
input uncertainty parameters on each output parameter of interest. They can be identified byusing various sensitivity indices like correlation coefficients and well-defined significancethresholds. Specific guidance and interpretation of the significance depends on the number ofsamples, number of variables, and analysis tolerance.
In the current work, the Partial Rank Correlation Coefficients (PRCCs) were used andarbitrary significance threshold of 0.5 were chosen for identification of the high influence of
the input uncertainty parameters on the output parameter (i.e., PRCC > 0.5). Lower values
imply low (PRCC < 0.25) or medium influence (0.25 ≤ PRCC ≤ 0.5).
An example of calculating PRCCs by Tractebel, using FRAPTRAN-TE-1.5 and
DAKOTA, is shown in Table 16. The PRCC for each output parameter of interest as a functionof all the input parameters change during the transient was summarized. The values shown inthis table were the maximum during the transient. The red cells were those of high influence,with at least one instant (of PRCC > 0.5), during the transient.
Comparison of the PRCCs by different participants for each of the main output parameters
facilitated the identification of a common list of high influential input parameters or
phenomena. A common list of high influential input parameters for each output is summarized
in Fig. 171, based on the PRCCs at their maximum absolute values of all participants. The redcells with ‘1’ implied that a high influence parameter being identified by at least 1 participant.

132

Input uncertainty parameter

RIP

Cladding outside diameter (mm)Cladding inside diameter (mm)Pellet outside diameter
Fuel theoretical density (kg/m3 at 20 °C)

TCO

TOL

ECR

DCO CES

ECT

13%

12%

11%

83%

19%

83%

17%

8%

50%

50%

6%

82%

81%

90%

79%

50%

40%

40%

7%

17%

83%

77%

79%

43%

TFC

TFO TCI

18%

9%

12%

70%

63%

64%

65%

56%

60%

EFT

10%

39%

36%

38%

38%

9%

9%

13%

10%

15%

21%

U235 enrichment (%)

10%

10%

12%

12%

12%

9%

8%

11%

12%

11%

14%

Filling gas pressure (MPa)

98%

15%

30%

28%

28%

8%

17%

35%

92%

26%

11%

Relative power during base irradiation
Relative power during test
Test rod power profile
Cladding temperature (°C)
Coolant temperature (°C)
Clad-to-Coolant heat transfer coefficientFuel thermal conductivity model
Clad thermal conductivity model
Fuel thermal expansion model
Clad thermal expansion model
Fuel densification model
Fuel solid swelling model
Fuel gaseous swelling model
Clad Yield stress
Fuel heat capacity

10%

8%

9%

9%

9%

6%

10%

7%

8%

10%

9%

53%

94%

93%

94%

94%

52%

54%

80%

33%

39%

84%

10%

25%

7%

8%

7%

11%

8%

85%

9%

10%

6%

39%

95%

96%

100% 100%

58%

60%

73%

27%

87%

90%

85%

100%

98%

99%

99%

90%

91%

96%

64%

77%

94%

16%

80%

26%

29%

29%

14%

15%

10%

7%

44%

42%

11%

9%

8%

44%

8%

9%

8%

7%

5%

9%

4%

18%

19%

17%

13%

13%

8%

17%

51%

43%

61%

99%

11%

11%

12%

14%

15%

7%

6%

96%

19%

97%

9%

24%

36%

38%

18%

18%

7%

10%

61%

51%

54%

35%

25%

40%

41%

24%

24%

11%

16%

62%

55%

60%

31%

39%

38%

38%

24%

24%

10%

11%

65%

56%

61%

30%

44%

25%

59%

67%

66%

15%

37%

77%

36%

55%

21%

20% 69% 67% 69%

69%

14%

13% 31% 16% 17% 48%

6%
Cladding heat capacity
Cladding elastic modulus
10%
Cladding corrosion model during steady-state
operation
10%

Cladding hydrogen pickup
steady-state operation

fraction

15%

19%

20%

20%

7%

9%

7%

6%

9%

14%

9%

9%

11%

11%

9%

7%

13%

17%

10%

13%

11%

29%

22%

22%

100% 100%

21%

57%

15%

11%

11%

10%

10%

7%

7%

11%

6%

10%

6%

11%

11%

13%

7%

7%

18%

18%

83%

84%

10%

11%

11%

4%

6%

5%

5%

10%

10%

8%

8%

7%

7%

6%

6%

8%

5%

7%

6%

10%

9%

9%

9%

13%

9%

2%

17%

59%

91%

48%

47%

15%

17%

47%

14%

19%

44%

8%

7%

19%

13%

13%

9%

7%

17%

11%

10%

10%

10%

6%

8%

17%

15%

8%

8%

6%

7%

7%

8%

14%

7%

7%

10%

10%

12%

12%

8%

6%

12%

11%
8%

duringCladding oxidation model at high temperature
Thermal conductivity of the oxide layer
Fission gas release (or gas diffusion coefficient)
Gap gas conductivity
Fuel/cladding emissivity
Fuel radial relocation
Fuel fragment packing fraction (if applicable)

Cladding strain threshold for fuel mobility (ifapplicable)
12%
Cladding Meyer hardness
8%
Cladding annealing
65%
Cladding burst criteria
9%
Cladding burst strain criteria
6%
Plenum gas temperature (°C)
95%

4%

5%

15%

15%

15%

13%

8%

10%

15%

11%

11%

16%

16%

9%

9%

13%

12%

7%

4%

51%

79%

82%

82%

28%

56%

90%

47%

63%

35%
6%

4%

9%

5%

5%

7%

5%

14%

9%

10%

10%

9%

10%

9%

5%

12%

10%

11%

6%

5%

5%

16%

23%

23%

9%

13%

21%

86%

15%

12%

FIG. 170. High Influential input uncertainty parameters based on PRCC at their maximum
for each output from Tractebel, as an example is illustrated.

133Input uncertainty parameter

RIP TFC TFO TCI TCO TOL ECR DCO CES ECT EFT

Cladding outside diameter (mm)Cladding inside diameter (mm)Pellet outside diameter

0
1
1

0
1
1

0
1
1

1
1
1

0
0
0

0
0
0

1
1
0

1
1
1

1
1
1

0
1
1

0
1
1

0
0
1

0
0
0

0
0
0

0
0
0

0
0
0

0
0
0

0
0
0

0
0
1

0
0
1

0
0
1

0
0
0

0
1
0
1
1

0
1
0
1
1

0
1
0
1
1

0
1
0
1
1

0
1
0
1
1

0
1
0
1
1

0
1
0
0
1

0
1
1
1
1

0
0
0
1
0

0
0
0
1
1

0
1
0
1
1

1
1
0
1
1
0
0
0
0
0
0
0

1
1
0
1
1
0
0
0
0
1
0
0

1
0
0
1
1
0
0
0
1
1
0
0

1
0
1
0
0
0
0
0
1
1
0
0

1
0
0
0
0
0
0
0
1
1
0
0

1
0
0
0
0
0
0
0
0
0
0
0

1
0
0
0
0
0
0
0
0
0
0
0

1
1
0
1
1
1
1
1
1
0
0
1

1
0
0
1
1
1
1
1
1
0
0
0

1
0
0
1
1
1
1
1
1
0
0
1

1
1
0
1
1
0
0
0
0
0
0
0

0

0

0

0

0

1

1

0

1

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

1

1

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0
1
0
0

0
1
0
0

0
1
0
0

0
1
0
0

0
0
0
0

0
0
0
0

0
0
0
0

0
0
0
0

0
1
0
0

0
0
0
0

0
1
0
0

0

0

0

0

0

0

0

0

0

0

0

0
0
1
0
0
1

0
0
1
0
0
0

0
0
1
0
0
0

0
0
1
0
0
0

0
0
1
0
0
0

0
0
0
0
0
0

0
0
1
0
0
0

0
0
1
0
0
1

0
0
0
0
0
1

0
0
1
0
0
0

0
0
0
0
0
0

Fuel theoretical density (kg/m3 at 20 °C)
U235 enrichment (%)
Filling gas pressure (MPa)
Relative power during base irradiation
Relative power during test
Test rod power profile
Cladding temperature (°C)
Coolant temperature (°C)
Clad-to-Coolant heat transfer coefficientFuel thermal conductivity model
Clad thermal conductivity model
Fuel thermal expansion model
Clad thermal expansion model
Fuel densification model
Fuel solid swelling model
Fuel gaseous swelling model
Clad Yield stress
Fuel heat capacity
Cladding heat capacity
Cladding elastic modulus
Cladding corrosion model during steady-state operation
Cladding hydrogen pickup fraction during steady-state
operation
Cladding oxidation model at high temperature
Thermal conductivity of the oxide layer
Fission gas release (or gas diffusion coefficient)
Gap gas conductivity
Fuel/cladding emissivity
Fuel radial relocation
Fuel fragment packing fraction (if applicable)
Cladding strain threshold for fuel mobility (if applicable)
Cladding Meyer hardness
Cladding annealing
Cladding burst criteria
Cladding burst strain criteria
Plenum gas temperature (°C)

FIG. 171. Common list of high influential input uncertainty parameters based on PRCC attheir maximum for each output.

134Input uncertainty parameter
Cladding outside diameter (mm)Cladding inside diameter (mm)Pellet outside diameter
Fuel theoretical density (kg/m3 at 20 °C)
U235 enrichment (%)
Filling gas pressure (MPa)
Relative power during base irradiation
Relative power during test
Test rod power profile
Cladding temperature (°C)
Coolant temperature (°C)
Clad-to-Coolant heat transfer coefficientFuel thermal conductivity model
Clad thermal conductivity model
Fuel thermal expansion model
Clad thermal expansion model
Fuel densification model
Fuel solid swelling model
Fuel gaseous swelling model
Clad Yield stress
Fuel heat capacity
Cladding heat capacity
Cladding elastic modulus
Cladding corrosion model during steady-state operation
Cladding hydrogen pickup fraction during steady-state
operation
Cladding oxidation model at high temperature
Thermal conductivity of the oxide layer
Fission gas release (or gas diffusion coefficient)
Gap gas conductivity
Fuel/cladding emissivity
Fuel radial relocation
Fuel fragment packing fraction (if applicable)
Cladding strain threshold for fuel mobility (if applicable)
Cladding Meyer hardness
Cladding annealing
Cladding burst criteria
Cladding burst strain criteria
Plenum gas temperature (°C)

Fuel Thermal+RIP

Clad thermal+ECR

Fuel/Clad
Mechanical

Overall

0
1
1

1
1
1

1
1
1

1
1
1

0
0
1

0
0
0

0
0
1

0
0
1

0
1
0
1
1

0
1
0
1
1

0
1
1
1
1

0
1
1
1
1

1
1
0
1
1
0
0
0
1
1
0
0

1
0
1
0
0
0
0
0
1
1
0
0

1
1
0
1
1
1
1
1
1
0
0
1

1
1
1
1
1
1
1
1
1
1
0
1

0

1

1

1

0

0

0

0

0

1

0

1

0

0

0

0

0
1
0
0

0
1
0
0

0
1
0
0

0
1
0
0

0

0

0

0

0
0
1
0
0
1

0
0
1
0
0
0

0
0
1
0
0
1

0
0
1
0
0
1

FIG. 172. Common list of high influential input uncertainty parameters for each fuelmodelling aspect.
Based on the current sensitivity study results, a common list of high influential input
uncertainty parameters could be identified for each aspect of the fuel rod code, as shown in
Fig. 172. Again, the red cells with ‘1’ implied that a high influence parameter being identified
by at least 1 participant.
In summary, the following input uncertainty parameters were of high influence on theoverall fuel code models, including fuel and cladding thermal and mechanical modelling:

135

Fuel rod geometries: clad outside/inside diameter, fuel pellet diameter;
Test conditions: filling gas pressure, power and clad-to-coolant heat transfer (coolant
temperature and clad-to-coolant heat transfer coefficients, or clad temperature) during thetest. The axial power profile was also important for mechanical modelling;
Material properties and models related to fuel-to-clad heat transfer: fuel thermal
conductivity and heat capacity; gap conductivity; fuel thermal expansion, densificationand swelling; cladding thermal expansion, yield stress, annealing; cladding steady-state
corrosion and high-temperature oxidation;
Plenum gas temperature.
On the contrary, the following input uncertainty parameters appeared to have only low or
medium influence:
Fuel manufacturing data (Fuel density, Enrichment);
Operation conditions: Relative power during base irradiation;
Material properties: models related to clad heat capacity, Meyer hardness, burst strain
criteria or burst stress and strain criteria, fuel radial relocation, fuel/cladding emissivity,
fission gas release. The axial relocation related parameters (fuel fragmentation fraction,strain threshold for fuel mobility) had no influence as the axial relocation model is not
used.
The non-significance of some input uncertainty parameters was surprising. For example,
in FRAPTRAN (without the axial relocation model), the ballooning and burst were predictedby the BALON2 model which calculated the extent and shape of the localized large cladding
deformation (ballooning) that occurred between the time that the cladding effective strain
exceeds the instability strain and the time of cladding rupture. The BALON2 model predicted
failure (burst) in the ballooning node when the cladding true hoop stress exceeded an empiricallimit that was a function of cladding temperature, or when the predicted cladding permanent
hoop strain exceeds the strain limit that was a function of cladding temperature. It was expectedthat there should be at least an impact of the ‘cladding burst stress criteria’ or ‘cladding burst
strain criteria’.
One should not forget the limitations of using the correlation coefficients. Indeed, theimpact of a single input uncertainty parameter on a specific output parameter could be nonlinear and non-monotonic and thus not captured by the correlation coefficients like PRCC.
Another explanation would be that those parameters affect only the burst time, but not the otherparameters. This would make their effect harder to notice.
5.6. CONCLUSIONS
An uncertainty and sensitivity analysis was performed on the simulation of the Halden
LOCA test IFA-650.10, according to detailed Specifications. Seven participants submitted theiruncertainty analysis results, and six participants submitted their sensitivity analysis results. The
provided results were compared and discussed, in comparison with the available experimental
data.
The comparison of the uncertainty analysis showed that the uncertainty bands were
acceptable for the fuel and clad thermal behaviour (RIP, TCO and TFO), but quite large for theclad mechanical behaviour prediction (ECT and DCO). The mechanical models for the claddeformation still required improvement, at least for certain fuel rod codes (i.e., FRAPTRAN).
The comparison of the sensitivity analysis results helped to identify a common list of highinfluential input uncertainty parameters for each output parameter, and for each aspect (fuel andclad thermal and mechanical modelling) and phenomena within the fuel rod codes.
It should be noted that a significant user-effect existed, as illustrated by the differences inthe three results using FRAPTRAN.
136

5.7. SUMMARY AND RECOMMENDATIONS
Within the FUMAC project, the following achievements were made:Verified experimental data set on fuel characteristics in accident conditions, supporting
codes development and validation for potential extension of the IFPE database;
Better predictive capabilities of fuel performance codes: improved models, material
properties and numerical algorithms for the simulation of nuclear fuel under DBA and
DEC, with consideration of uncertainties;
Extended collaboration between some Member State organizations (examples: INLPOLIMI-JRC collaboration agreement; IFE-IBRAE collaboration and joint presentation
at the Enlarged Halden Programme Group Meeting, 2017) beyond the FUMAC project
timeframe.
Many participants acknowledged the IAEA for organizing this CRP, which provided an
ideal platform to compare their code results with others and especially with experimental data,
to which they otherwise would not have access.
All experimental data revealed a relatively large spread of the measured burst strains,which was determined by the local conditions of temperature and pressure, and by theheterogeneities and composition or micro-structural variations in the materials underinvestigations. An uncertainty analysis of the experimental data was therefore recommended,
including those data that were used for the development and validation of the codes applied.
It has been reiterated that this CRP triggered new collaborations, led to the development
and improvement of common models, for those that have been used by a larger user group (e.g.
FRAPTRAN, TRANSURANUS). It has also enabled to point out differences in theinterpretation of some experiments and therefore in the use of the codes, the so-called user
effects.
The active participation of organizations that provided the experimental data has also
been very instrumental in clarifying various questions raised during the project.
The following recommendations were made:More analysis and cases for VVER fuel would be needed, especially in view of recent
advanced fuel developments;
A general interest has been expressed to consider a similar analysis for advanced fuels
and cladding materials, including some of the so-called accident tolerant fuels;
For a successful CRP that involves so many cases and participants, the duration of the
project meetings may be extended, enabling for instance to analyze better model details
and code changes as well as their comparison with more detailed experimental data;
Deeper analysis of failure criteria with advanced tools, and uncertainty analysis on
experimental data would be beneficial;
Need more quantitative information about fuel fragmentation.
Participants also recommended that the future CRP should focus on fuel modelling withmore practical applications to support the sustainability of nuclear technology, diversificationof fuel supply, and innovation in fuel technology development.

137

REFERENCES[1]MISFELDT, I., “The D-COM Blind Problem on Fission Gas Release: Experimental
Description and Results, Summary report,” in OECD-NEA-CSNI/IAEA Specialists'
Meeting on Water Reactor Fuel Safety and Fission Product Release in Off-Normal and
Accident Conditions, IAEA-IWGFPT/16, p. 411, Roskilde, Denmark, 16–20 May 1983.
[2] KILLEEN, J., TURNBULL, J. A., SARTORI, E., “Fuel Modelling at Extended Burnup:
IAEA Coordinated Research Project FUMEX-II”, Proceedings of International LWR
Fuel Performance Meeting, American Nuclear Society, San Francisco, California, USA,
30 September–3 October, 2007.
[3] INTERNATIONAL ATOMIC ENERGY AGENCY, “Fuel Modelling at Extended
Burnup (FUMEX-II)”, IAEA TECDOC-1687, IAEA, Vienna, Austria, 2012.
[4] INTERNATIONAL ATOMIC ENERGY AGENCY, “Improvement of computer codesused for fuel behaviour simulation (FUMEX-III)”. IAEA-TECDOC-1697, IAEA,
Vienna, Austria, 2013.
[5] HÓZER, Z., GYŐRI, C., HORVÁTH, M., NAGY, I., MARÓTI, L., MATUS, L.,
WINDBERG, P., FRECSKA J.,” Ballooning Experiments with VVER Cladding”,
Nuclear Technology 152(3), 273, 2005.
[6] PEREZ-FERÓ, E., GYŐRI, C., MATUS, L., VASÁROS, L., HÓZER, Z., WINDBERG,
P.,MARÓTI, L., HORVÁTH, M., NAGY, I., CSORDÁS, A.P, NOVOTNY T.,“Experimental database of E110 claddings exposed to accident conditions”, J. Nucl.
Mater., 397, 48, 2010.
[7] FLANAGAN, M., et al., Post-test examination results from integral, high-burnup, fueled
LOCA tests at Studsvik Nuclear Laboratory, Report NUREG-2160, U.S. Nuclear
Regulatory Commission, Washington, DC, USA, 2013.
[8] HELIN, M. and J. FLYGARE, NRC LOCA tests at Studsvik: Design and construction oftest train device and tests with unirradiated cladding material, Report STUDSVIK/N11/130, Studsvik Nuclear AB, Studsvik, Sweden, 2013.
[9] FLANAGAN, M. and P. ASKELJUNG. Observations of fuel fragmentation, mobility andre-lease in integral high-burnup, fueled LOCA tests. OECD Halden Reactor Project
LOCA Workshop, May 29–30, 2012, Lyon, France: OECD Halden Reactor Project,
Halden, Norway, 2012.
[10] ZWICKY, H.-U., Re-fabrication of ramp rodlet Z-3 from Westinghouse father rod
irradiated in North Anna. Report N-05/131 Rev. 1, Studsvik Nuclear AB, Nyköping,
Sweden, 2006.
[11] ZWICKY, H.-U., Re-fabrication of ramp rodlet Z-4 from Westinghouse father rod
irradiated in North Anna. Report N-05/133 Rev. 1, Studsvik Nuclear AB, Nyköping,
Sweden, 2006.
[12] RAYNAUD, P.A.C., NRC Studsvik LOCA test 192, 2014, MS Excel data file contributed
to the IAEA CRP FUMAC on December 8, 2014, U.S. Nuclear Regulatory Commission,
Washington, DC, USA, 2014.
[13] JERNKVIST, L.O., Computational assessment of LOCA simulation tests on high burnup
fuel rods in Halden and Studsvik. Report SSM 2017:12, Swedish Radiation Safety
Authority, Stockholm, Sweden, 2017.
[14] ERBACHER, F. J., H. J. NEITZEL, AND K. WIEHR. Effects of thermohydraulics on
clad ballooning, flow blockage and coolability in a LOCA. NO. IWGFPT--16. 1983.

139

[15] STUCKERT, J., GROßE, M., RÖSSGER, C., KLIMENKOV, M., STEINBRÜCK, M.,
WALTER, M. QUENCH-LOCA program at KIT on secondary hydriding and results ofthe commissioning bundle test QUENCH-L0. Nucl. Eng. Des. 255 (2013) 185–201.
[16] VESHCHUNOV, M.S., SHESTAK. V.E., Modelling of Zr alloy burst cladding internaloxidation and secondary hydriding under LOCA conditions. J. Nucl. Mater., 461 (2015)
129–142.
[17] NUREG/CR-7023, Vol. 1, Revision 1: “FRAPTRAN 1.5: A Computer Code for theTransient Analysis of Oxide Fuel Rods”, USNRC, May 2014.
[18] NUREG/CR-7023, Vol. 2, Revision 1: “FRAPTRAN 1.5: Integral assessment”, USNRC,May 2014.
[19] JERNKVIST, L. O., MASSIH A. R., and ALVESTAV A., Axial relocation of fragmented
and pulverized fuel and its effects on fuel rod heat load during LOCAs, Top Fuel 2015,
paper A0059, 2015.
[20] GOVERS K., VERWERFT M., “Simulation of ballooning & relocation in the Halden
LOCA tests with FRAPTRAN”, EHPG meeting, 2014.
[21] JERNKVIST, L. O., MASSIH, A. R., ALVESTAV, A., “Computational assessment ofaxial fuel relocation in Halden IFA-650 LOCA tests. In Proceedings of Enlarged Halden
Program Group Meeting, Sandefjord, Norway, OECD Halden Reactor Project, May 8–
13, 2016.
[22] JERNKVIST L. O., and MASSIH, A. R., “Models for axial relocation of fragmented andpulverized fuel pellets in distending fuel rods and its effects on fuel rod heat load,” SSM
research report 2015:37, Swedish Radiation Safety Authority (SSM), Stockholm,
Sweden, September 2015.
[23] JERNKVIST, L. O., “Observed and corrected errors in source code and algorithms of
FRAPTRAN-1.5,” Report TR15-002V2, Quantum Technologies AB, March 2016.
[24] ZHANG, J., “Code modification requirements specifications (CMRS) for extension andadaptation of FRAPTRAN-1.5 for LOCA fuel behaviour modelling,” Internal report
FUELROD/4DO/0437004/000/00, Tractebel, February 2016.
[25] JERNKVIST, L. O., “The FRAPTRAN-TE-1.5 computer program”, Report TR16-001,
Quantum Technologies AB, March 2016.
[26] LASSMANN, K., URANUS -- A computer programme for the thermal and mechanicalanalysis of the fuel rods in a nuclear reactor, Nucl. Eng. Des. 45 (1978) 325.
[27] LASSMANN, K., TRANSURANUS: a fuel rod analysis code ready for use, J. Nucl.
Mater. 188 (1992) 295.
[28] LASSMANN, K., RONCHI, C., SMALL, G. J., The development of fuel performancemodels at the European institute for transuranium elements, J. Nucl. Mater. 166 (1989)
112.
[29] LASSMANN, K., O'CARROL, C., DE LAAR, J.V., WALKER, C. T., The radial
distribution of plutonium in high burnup UO2 fuels, J. Nucl. Mater. 208 (1994) 223.
[30] LASSMANN, K., WALKER, C. T., DE LAAR, J.V., LINDSTRÖM, F., Modelling thehigh burnup UO2 structure in LWR fuel, J. Nucl. Mater. 226 (1995) 1.
[31] LASSMANN, K., DE LAAR, J.V., “The Transient TRANSURANUS version”,
Proceedings of IAEA RER/4/019, Licensing Fuel and Fuel Modelling Codes for WWER
Reactors, Seminar " Implementation of the WWER version of the TRANSURANUS codeand its application to safety criteria", Sofia, Bulgaria, 7–11 December 1998.

140

[32] UFFELEN, V.P, GYORI, Cs., SCHUBERT, A., DE LAAR, J.V., HOZER, Z.,SPYKMAN, G., Extending the application range of a fuel performance code from normal
operating to design basis accident conditions, J. Nucl. Mater. 383 (2008) 137.
[33] GYORI, Cs., HÓZER, Z., LASSMANN, K., SCHUBERT, A., DE LAAR, J.V.,
HATALA, B., CVAN, M., "Extension of Transuranus code applicability with Niobium
containing cladding models (EXTRA) ", Final Report, EVOL-EXTRA-D5 / FIKSCT2001-00173, 2004.
[34] SPYKMAN, G., MÄRTENS, D., BOUR, D., KOCK, P., LASSMANN, K.,
SCHUBERT, A., DE LAAR, J.V., "Implementation of a Cladding Failure Model for a
Loss of Coolant Accident (LOCA)-Analysis in Transuranus", Proceedings of Enlarged
Halden Programme Group Meeting on High Burn-up Fuel Performance, Safety andReliability, Sandefjord, Norway, 9–14 May 2004.
[35] DI MARCELLO, V., SCHUBERT, A., DE LAAR, J.V., VAN UFFELEN, P., The
TRANSURANUS mechanical model for large strain analysis, Nucl. Eng. Des. 276 (2014)19.
[36] PASTORE, G., Luzzi, L., Di Marcello, V.,VAN UFFELEN, Physics-based modelling offission gas swelling and release in UO2 applied to integral fuel rod analysis, Nucl. Eng.
Des. 256 (2013) 75.
[37] DI MARCELLO, V., RONDINELLO, V., SCHUBERT, A., DE LAAR, J.V., VAN
UFFELEN, P., Modelling actinide redistribution in mixed oxide fuel for sodium fast
reactors, Progress in Nuclear Energy 72 (2014) 83.
[38] DI MARCELLO, V., SCHUBERT, A., DE LAAR, J.V., VAN UFFELEN, P., Extensionof the TRANSURANUS plutonium redistribution model for fast reactor performance
analysis, Nucl. Eng. Des. 248 (2012) 149.
[39] LASSMANN, K., HOHLEFELD, F., The revised URGAP model to describe the gap
conductance between fuel and cladding, Nucl. Eng. Des. 103 (1987) 215.
[40] SCHUBERT, A., VAN UFFELEN, P., DE LAAR, J.V., Walker, C. T., HAECK, W.,
Extension of the TRANSURANUS burn-up model, J. Nucl. Mater. 376 (2008) 1[41] MARELLE, V. et al., Thermo-mechanical modelling of PWR fuel with ALCYONE. inproceedings of Top Fuel 2011, Chengdu, China, 2011.
[42] MARELLE, V. et al., New developments in ALCYONE 2.0 fuel performance code. inproceedings of Top Fuel Boise Idaho USA, 2016.
[43] STRUZIK, C. et al., Validation of fuel performance CEA code ALCYONE, scheme 1D,
on extensive data base. in proceedings of Top Fuel 2012, Manchester, United Kingdom,
2012.
[44] SERCOMBE, J. et al., Stress concentration during pellet cladding interaction:
Comparison of closed-form solutions with 2D (r,theta) finite element simulations. Nucl.
Eng. Des. 260, 175, 2013.
[45] MICHEL, B. et al., 3D fuel cracking modelling in pellet cladding mechanical interaction.
Engineering Fracture Mechanics 75, 3581, 2008.
[46] MARELLE, V., Validation of PLEIADES/ALCYONE 2.0 fuel performance code.
WRFPM2017, Jeju Island Corea, 2017.
[47] JOMARD, G. et al., CARACAS: an industrial model for the description of fission gas
behaviour in LWR-UO2 fuel. in Proceedings WRFPM 2014, Sendaï (Japan), 2014.
[48] NOIROT, L. et al., MARGARET: A comprehensive code for the description of ﬁssion
gas behaviour. Nuclear Enginering and design 241, 2011.

141

[49] WILLIAMSON, R.L., HALES, J.D., NOVASCONE, S. R., TONKS, M.R., GASTON,
D.R., PERMANN, C.J., ANDRS, D., MARTINEAU. R.C., Multidimensional
multiphysics simulation of nuclear fuel behaviour. J. Nucl. Mater. 423, 149, 2012.
[50] GASTON, D., NEWMAN, C., HANSEN, G., LEBRUN-GRANDIÉ, D., MOOSE: A
parallel computational framework for coupled systems of nonlinear equations, Nucl. Eng.
Des., 239, 1768, 2009.
[51] RASHID, M.M., Incremental kinematics for finite element applications, International
Journal of Numerical Methods and Engineering 36, 3937, 1993.
[52] HALES, J.D., WILLIAMSON, R.L., NOVASCONE, S.R., PASTORE, G., SPENCER,
B.W., STAFFORD, D.S., GAMBLE, K.A., PEREZ, D.M., GARDNER, R.J., LIU, W.,
BISON theory manual: The equations behind nuclear fuel analysis. Technical Report
INL/EXT-13-29930, Rev.1. Idaho National Laboratory, 2014.
[53] PASTORE, G., SWILER, L.P., HALES, J.D., NOVASCONE, S.R., PEREZ, D.M.,
SPENCER, B.W., LUZZI, L., VAN UFFELEN, P., WILLIAMSON R.L., . Uncertainty
and sensitivity analysis of fission gas behaviour in engineering-scale fuel modelling. J.
Nucl. Mater. 465, 398, 2015.
[54] WILLIAMSON R.L., GAMBLE, K.A., PEREZ, D.M., NOVASCONE, S.R., PASTORE,
G., GARDNER, R.J., HALES, J.D., LIU, W., MAI, A., Validating the BISON fuelperformance code to integral LWR experiments. Nucl. Eng. Des. 301, 232, 2016.
[55] Assessment of BISON: A Nuclear Fuel Performance Analysis Code. BISON Release 1.3,
Technical Report INL/MIS-13-30314 Rev. 3, Idaho National Laboratory, 2016.
[56] PASTORE, G., NOVASCONE, S.R., WILLIAMSON R.L., HALES, J.D., SPENCER,
B.W., STAFFORD, D.S., Modelling of fuel behaviour during loss-of-coolant accidents
using the BISON code. In: Proc. of the LWR Fuel Performance Meeting, Zurich,
Switzerland, September 13–17, 2015.
[57] PASTORE, G., WILLIAMSON R.L., NOVASCONE, S.R., SPENCER, B.W., HALES,
J.D., Modelling of LOCA tests with the BISON fuel performance code. In: Enlarged
Halden Programme Group Meeting, Fornebu, Norway, May 8-13, 2016.
[58] WILLIAMSON R.L., FOLSOM, C.P., PASTORE, G., VEEARAGHAVAN, S.,
Reactivity insertion accident (RIA) capability status in the BISON fuel performance code.
Technical Report CASL-X-2016-1104-000, Consortium for Advanced Simulation of
LWRs, July 2016.
[59] PASTORE, G., FOLSOM, C.P., WILLIAMSON R.L., HALES, J.D., LUZZI, L.,PIZZOCRI, D., BARANI T., Modelling fission gas behaviour with the BISON fuelperformance code. In Enlarged Halden Programme Group Meeting, Lillehammer,
Norway, September 24-29, 2017.
[60] HALES, J.D., WILLIAMSON R.L., NOVASCONE, S.R., PEREZ, D.M., SPENCER,
B.W., PASTORE, BG., Multidimensional Multiphysics Simulation of TRISO Particle
Fuel, J. Nucl. Mater. 443, 531, 2013.
[61] PASTORE, G., PIZZOCRI, D., NOVASCONE, S.R., PEREZ, D.M., SPENCER, B.W.,
WILLIAMSON R.L., VAN UFFELEN, P., LUZZI, L., Modelling of transient fission gas
behaviour in oxide fuel and application to the BISON code. In Enlarged Halden
Programme Group Meeting, Røros, Norway, September 7–12, 2014.
[62] BARANI, T., BRUSCHI, E., PIZZOCRI, D., PASTORE, G., VAN UFFELEN, P.,
WILLIAMSON R.L., LUZZI, L., Analysis of transient fission gas behaviour in oxide fuelusing BISON and TRANSURANUS, J. Nucl. Mater. 486, 96, 2017.

142

[63] SOBA, A., DENIS, A., DIONISIO 2.0: New version of the code for simulating a whole
nuclear fuel rod under extended irradiation, Nucl. Eng. and Des. 292, 213, 2015.
[64] SOBA, A., DENIS, A., ROMERO, L., VILLARINO, E., SARDELLA, F., A high burnup model developed for the DIONISIO code, J. Nucl. Mater., 433(1), 160, 2013.
[65] SOBA, A., LEMES, M., DENIS, A., An empirical formulation to describe the evolutionof the high burnup structure, J. Nucl. Mater., 456, 174, 2015.
[66] SOBA, A., LEMES, M., GONZÁLEZ, M.E., DENIS, A., ROMERO, L., Simulation of
the behaviour of nuclear fuel under high burnup conditions, Ann. Nucl. Energy. 70, 147,
2014.
[67] LEMES, M., SOBA, A., DAVERIO, H., DENIS, A., Inclusion of models to describe
severe accident conditions in the fuel simulation code DIONISIO, Nucl. Eng. and Des.
315, 1, 2017.
[68] GEELHOOD, K.J., LUSCHER, W.G., CUTA, J.M., FRAPTRAN-1.5: A Computer Codefor the Transient Analysis of Oxide Fuel Rods. U.S. Nuclear Regulatory Commission,
2014.
[69] WILLIAMSON R.L., PASTORE G., NOVASCONE. S.R., et al. Modelling of LOCA
Tests with the BISON Fuel Performance Code. Idaho National Laboratory, Idaho Falls,
United States, 2016.
[70] ROSINGER H.E., NEITZEL H.J., ERBACHER F.J., Development of a Burst Criterion
for Zircaloy Fuel Cladding under LOCA Conditions. In Proc. IAEA Specialist Meetingon Fuel Element Performance Computer Modelling, Blackpool, UK, pp. 21–35. 1980.
[71] GEELHOOD, K.J., LUSCHER, W.G., FRAPTRAN-1.5: Integral Assessment. U.S.
Nuclear Regulatory Commission, 2014.
[72] RAPTA-5.2 software tool. ROSTECHNADZOR (Federal Environmental, Industrial andNuclear Supervision Service), SEC NRS (Scientific and Engineering Centre of Nuclear
and Radiation Safety), Certificate of Computer Code № 399 of 14.07.2016.
[73] FEDOTOV, P., Analytical functions used for description of the plastic deformation
process in zirconium alloys VVER type fuel rod cladding under designed accident
conditions. Proceedings of the Fifth International Conference. VVER Fuel Performance,
Modelling and Experimental Support. 29 September – 3 October 2003, Albena, Bulgaria.
p. 417–429.
[74] FEDOTOV P., NECHAEVA O., SALATOV A., LOSHMANOV L., Universal model ofzirconium alloys plastic deformation under VVER design basis accident (DBA)
conditions. 6-th International Conference on VVER Fuel Performance, Modelling andExperimental Support. 19-23 September 2005, Bulgaria.
[75] FEDOTOV, P.V., GONCHAROV, A.A., KUMACHEV, A.V., MEDVEDEV, A.V.,
NECHAEVA, O.A., NOVIKOV, V.V., ONUFRIEV, A.V.,SALATOV, A.V.,
MOLCHANOV, V.L., PIMENOV, YU.V., ALEKSEEV, A.V., KISELEVA, I.V.,
SHULIMOV, V.N., FEDIK, I.I., NALIVAEV, V.I., PARSHIN, N.YA.,
KONSTANTINOV. V.S., Estimation of Water-Water Energy Reactor Fuel Rod Failurein Design Basis Accidents, Proceeding of 2005 Water Reactor Fuel Performance
Meeting, Kyoto, Japan, 2-6 October 2005, p.p. 835–847.
[76] VESHCHUNOV, M.S., BOLDYREV, A. V., OZRIN, V.D., SHESTAK, V.E.,
TARASOV, V.I., A new mechanistic code SFPR for modelling of single fuel rod
performance under various regimes of LWR operation, Nucl. Eng. Des. 241, 2822–2830(2011).

143

[77] VESHCHUNOV, M.S., OZRIN, V.D., SHESTAK, V.E., TARASOV, V.I., DUBOURG,
R., NICAISE, G., Development of the mechanistic code MFPR for modelling fission
products release from irradiated UO2 fuel. Nucl. Eng. Des. 236, 179–200 (2006).
[78] VESHCHUNOV, M.S., DUBOURG, R., OZRIN, V.D., SHESTAK, V.E., TARASOV,
V.I., Mechanistic modelling of Urania fuel evolution and fission product migration during
irradiation and heating. J. Nucl. Mater. 362, 327 (2007).
[79] HOFMANN, P., NOACK, V., VESHCHUNOV, M.S., BERDYSHEV, A.V.,
BOLDYREV, A.V., MATWEEV, L.V., PALAGIN, A.V., SHESTAK, V.E., PhysicoChemical Behaviour of Zircaloy Fuel Rod Cladding Tubes During LWR Severe Accident
Reflood, Report FZKA 5846, Karlsruhe, Germany (1997).
[80] HOFMANN, P., MIASSOEDOV, A., STEINBOCK, L., STEINBRUECK, M.,
BERDYSHEV, A.V., BOLDYREV, A.V., PALAGIN, A.V., SHESTAK, V.E.,
VESHCHUNOV, M.S., Quench Behaviour of Zircaloy Fuel Rod Cladding Tubes. SmallScale Experiments and Modelling of the Quench Phenomena. Report FZKA 6208, INVCOBE (98)-D018, Karlsruhe, Germany (1999).
[81] VESHCHUNOV M.S., SHESTAK, V.E., Model for Melt Blockage (Slug) Relocation
and Physico-Chemical Interactions during Core Degradation under Severe Accident
Conditions. Nucl. Eng. Des. 238 (2008) 3500–3507[82] KIM H.C., et al., Development of fully coupled MARS-KS/FRAPTRAN code system forsimulation of fuel behaviour during LOCA, Transactions of the Korea Nuclear Society
Autumn meeting, Gyeongju, Korea, October 26, 2017.
[83] GEELHOOD, K.J., LUSCHER, W.G., BEYER, C.E., CUTA, J.M., FRAPTRAN 1.4: A
Computer Code for the Transient Analysis of Oxide Fuel Rods, NUREG/CR-7023, Vol.1,
2011.
[84] MARS Code manual, Volume I: Code Structure, System Models, Solution Methods,
KAERI/TR-2812, 2004.
[85] GEELHOOD, K.J., LUSCHER, W.G., BEYER, C.E., CUTA, J.M., FRAPTRAN 1.4: A
Computer Code for the Transient Analysis of Oxide Fuel Rods, NUREG/CR-7023, Vol.
1, PNNL-19400, 2011.
[86] HÄMÄLÄINEN, A., STENGÅRD, J.-O., MIETTINEN, J., KYRKI-RAJAMÄKI, R.,
Coupled Code FRAPTRAN - GENFLO for Analysing Fuel Behaviour During PWR andBWR Transients and Accidents. Proceeding of: Technical Committee meeting, 10
September 2001, Halden, Norway, IAEA-TECDOC-1320, 2001.
[87] MIETTINEN, J., HÄMÄLÄINEN, A., 2002. GENFLO - A General Thermal Hydraulic
Solution for Accident Simulation. VTT Research Notes 2163, ISBN 951-38-6083-3,
ISSN 1455-0865. www.vtt.fi/inf/pdf/tiedotteet/2002/T2163.pdf (visited 5 May 2017).
[88] ORGANISATION FOR ECONOMIC CO-OPERATION AND DEVELOPMENT,NUCLEAR ENERGY AGENCY, Benchmark Calculations on Halden IFA-650 LOCA
Test Results, NEA/CSNI/R6, 2010.
[89] MIETTINEN, J., Thermohydraulic Model SMABRE for Light Water Reactor
Simulations. Thesis for the degree of Licentiate of Technology, Helsinki University ofTechnology, 2000.
[90] ARKOMA, A., IKONEN, T., Sensitivity analysis of local uncertainties in large breakloss-of-coolant accident (LB-LOCA) thermo-mechanical simulations. Nucl. Eng. Des.,
305, 293, 2016.

144

[91] ARKOMA, A., HÄNNINEN, M., RANTAMÄKI, K., KURKI, J., and HÄMÄLÄINEN,
A., Statistical analysis of fuel failures in large break loss-of-coolant accident (LBLOCA)
in EPR type nuclear power plant. Nucl. Eng. Des., 285, 1, 2015.
[92] AUSTREGESILO, H., BALS, C. AND TRAMBAUER, K., 2007. Post-Test Calculationand Uncertainty Analysis of the Experiment Quench-07 with the System Code ATHLETCD. Nucl. Eng. Des., 237(15–17), PP.1693-1703.
[93] BOLSHOV, L.A., DOLGANOV, K.S., KISELEV, A.E. STRIZHOV, V.F., 2019. Resultsof SOCRAT code development, validation and applications for NPP safety assessment
under severe accidents. Nucl. Eng. Des., 341, pp.326–345.
[94] DI MARCELLO, V., SCHUBERT, A., DE LAAR, J.V., VAN UFFELEN, P., The
TRANSURANUS mechanical model for large strain analysis. Nucl. Eng. Des. 276, 19,
2014.
[95] ERBACHER, F. J., NEITZEL, H. J., ROSINGER, H., SCHMIDT, H., WIEHR, K., Burst
criterion of Zircaloy fuel claddings in a loss-of-coolant accident. In Zirconium in the
Nuclear Industry, Fifth Conference, ASTM STP 754, D.G. Franklin Ed., pages 271.
American Society for Testing and Materials, 1982.
[96] ERBACHER, F.J., NEITZEL, H.J., WIEHR, K., Technical Report 4781,
Kernforschungszentrum Karlsruhe (KfK), Germany, 1990.
[97] LAVOIL, A., LOCA Testing at Halden; The Tenth Experiment IFA-650.10. Technical
Report HWR-974, OECD Halden Reactor Project, 2010.
[98] HAGEN, S., HOFMANN, P., NOACK, V., SCHANZ G., et al. “Behaviour of VVER1000 Fuel Element with Boron Carbide/Steel Absorber Tested under Severe Fuel Damage
Conditions in the CORA Facility. Results of Experiment CORA-W2”. KfK 5363, 1994.
[99] GENTLE, E., “Monte-Carlo Methods,” Encyclopaedia of Statistics, 5, pp. 612-617, John
Wiley and Sons, New-York, 1985.
[100] CONOVER, W., Practical non-parametric statistic, Wiley, New York, 1999.
[101] GLAESER, H., “GRS Method for Uncertainty and Sensitivity Evaluation of Code Results
and Applications,” Science and Technology of Nuclear Installations, Volume 2008,
Article ID 798901, 2008.
[102] ZHANG, J., SEGURADO J., SCHNEIDESCH, C., “Towards an Industrial Applicationof Statistical Uncertainty Analysis Methods to Multi-physic Modelling and Safety
Analyses,” Proc. OECD/CSNI Workshop on Best Estimate Methods and Uncertainty
Evaluations, Barcelona, Spain, 16–18 November 2011.
[103] WILKS, S.S., Determination of sample sizes for setting tolerance limits, Ann. Math. Stat.
12, 91, 1941.
[104] GUBA, A., MAKAI, M., PAL L., “Statistical aspects of best estimate method-I”;
Reliability Engineering and System Safety, 80, 217, 2003.
[105] DE CRÉCY, A., et al., “The BEMUSE Programme: Results of the First Part Concerning
the LOFT L2-5 Test,” Proceedings of 14th International Conference on Nuclear
Engineering, Miami, Florida, USA, 17 July, 2006.
[106] GLAESER, H., “BEMUSE Phase VI Report, Status report on the area, classification of
the methods, conclusions and recommendations,” OECD/NEA/CSNI/R (2011) 4, March
2011.
[107] MCKAY, M. D., “Sensitivity and uncertainty analysis using a statistical sample of input
values,” Ch. 4, “Uncertainty Analysis”, Ronen, Y. Editor, CRC Press, Florida, USA,
1988.

145

[108] HELTON, J.C., JOHNSON, J.D., SALLABERRY, C.J., STORLIE, C.B., “Survey ofsampling-based methods for uncertainty and sensitivity analysis,” Reliability Engineeringand System Safety, 91,10, 2006.
[109] IOOSS B., LEMAITRE, P., “A review on global sensitivity analysis methods,” in
Uncertainty management in Simulation-Optimization of Complex Systems: Algorithms
and Applications (C. Meloni and G.
Dellino, Eds), Springer, 2015,
http://www.springer.com/business.
[110] ADAMS, B., et al., "DAKOTA, A Multilevel Parallel Object-Oriented Framework for
Design Optimization, Parameter Estimation, Uncertainty Quantification, and Sensitivity
Analysis: Version 5.1 User's Manual", Sandia Technical Report SAND2010-2183,
Updated Version 5.3, December 2013. (http://www.cs.sandia.gov/dakota).
[111] LAVOIL, A., “LOCA Testing at Halden, the Tenth Experiment IFA-650.10”, HWR-974,
OECD Halden Reactor Project, December 2010.
[112] KISELEV, A., “Short Information on the Results Of IFA-650.9, IFA-650.10 and IFA650.11 Calculations with Socrat Code”, Technical Note, Version 3, IBRAE RAN,
December 2016.

146

ANNEX I:SPECIFICATIONS FOR UNCERTAINTY ANALYSIS ON MODELLING OF
THE HALDEN LOCA TEST IFA-650.10
I–1. INTRODUCTION
During the 2nd RCM of the FUMAC project, it was agreed to perform an uncertainty andsensitivity analysis (UASA) based on one chosen IFA-650 test using simplified T/H boundary
conditions (i.e., coolant temperature and heat transfer coefficients calculated by SOCRAT, or
the measured or calculated cladding temperatures).
The objective is to verify if the quantified uncertainties on the predicted key physicalparameters (cladding temperature, plenum gas temperature, plenum gas pressure, burst time,strain, elongation, equivalent cladding reacted, hydriding, etc.) well bound the measured data
during the test, and as an optional activity for the interested participants, to identify theimportant input parameters through global sensitivity analysis (GSA).
Considering the complexity of IFA-650.9 (very high burnup, completed T/H conditions,need axial relocation model), it was proposed to choose either IFA-650.10 (for PWR) or IFA650.11 (for VVER) with moderate burnup and without significant axial relocation, as the casefor the UASA.
The following approach was proposed:
Using input uncertainty propagation method, based on non-parametric order statistics;
Sample number is chosen to 200;
A common list of input uncertainty parameters will be agreed, covering fuelmanufacturing data, properties and models, operating and test conditions;
A common list of output uncertainties will be agreed;
If the participant has no own tool, a statistical UASA analysis tool (DAKOTA) may be
used, which may be obtained freely from SNL.
The participant, however, has the freedom to use other alternative method or tool toperform the UASA, or perform only the uncertainty analysis.
This report gives:
A short description of the proposed uncertainty and sensitivity analysis methodology(§2);
A specification of the test case IFA-650.10 (§3) (which can be adapted to IFA650.11);
A list of input uncertainties to be considered for IFA650.10 (§4) (can be adapted to
IFA650.11);
A list of output uncertainties to be provided (§5);
A process and schedule (§6).
This specification follows the same approach as for the OECD RIA benchmark Phase II.
I–2. METHODOLOGY
I–2.1.

Uncertainty analysis: input uncertainty propagation method

Among all the available uncertainty analysis methods, the probabilistic input uncertainty
propagation method is so-far the most widely used in the nuclear safety analysis [I–1].
147

In this method, the fuel codes are treated as ‘black boxes’, and the input uncertainties arepropagated to the simulation model output uncertainties via the code calculations with sampled
input data from the known distributions [I–2].
The method consists in the following steps (Fig. I–1):(a) Specification of the problem: All relevant code outputs and corresponding uncertain
parameters for the codes, plant modelling schemes, and plant operating conditions are
identified;(b) Uncertainty modelling: the uncertainty of each uncertain parameter is quantified by aprobability density function (pdf) based on engineering judgment and experience
feedback from code applications to separate and integral effect tests and to full plants
simulation. If dependencies between uncertain parameters are known and judged to bepotentially important, they are quantified by correlation coefficients;(c) Uncertainty propagation through the computer code: the propagation is performed using
Monte-Carlo simulations [I–3]. In Monte-Carlo simulation, the computer code is run
repeatedly, each time using different values for each of the uncertain parameters. These
values are drawn from the probability distributions and dependencies chosen in theprevious step. In this way, one value for each uncertain parameter is sampled
simultaneously in each repetition of the simulation. The results of a Monte-Carlosimulation lead to a sample of the same size for each output quantity;(d) Statistical uncertainty analysis of the results: with sufficient large number of MonteCarlo simulations, the output sample can be used to get any typical statistics of the code
response such as mean or variance, the upper or lower bounds, and to determine thecumulative distribution function (CDF). The CDF allows to derive the percentiles of the
distribution (if X is a random variable and FX its CDF, the 𝛼-percentile,   [ 0 ;1] , is thedeterministic value 𝑋𝛼 such that 𝐹 (𝑋𝛼) = 𝑃(𝑋 ≤ 𝑋𝛼) = 𝛼.

FIG. I–1. The four steps of an input uncertainty propagation method.

148

A simple way to get information on percentiles is to use order statistics [I–4], which is awell-established and shared methodology in the nuclear community and hence is recommended
for this activity [I–5] [I–6] [I–7].
The principle of order statistics is to derive results from the ranked values of a sample. If(𝑋 , … , 𝑋 ) denotes a sample of any random variable, 𝑋, and (𝑋 , … , 𝑋 ) the corresponding
ranked one, order statistics first provides an estimation of the percentile of interest since the 𝛼-percentile can be estimated by 𝑋 ( , ) . Moreover, it turns out that the CDF of 𝑋 ( ) , 𝐹 𝑋 ( ) ,follows the Beta law 𝛽(𝑘, 𝑁 − 𝑘 + 1), which does not depend on the distribution of 𝑋. This
key result allows quantifying the probability that any ranked value is smaller than any percentile
by the following formula:𝑃 𝑋 ( ) ≤ 𝑋𝛼 = 𝐹 ( ,where 𝐹 ( ,

(I1)

) (𝛼)

) denotes the CDF of the Beta law 𝛽(𝑘, 𝑁 − 𝑘 + 1).

Equation (I1) can then be used to derive:
1) Lower and upper bounds of a percentile of interest, given the sample size 𝑁 and theconfidence level 𝛽 that controls the probability that 𝑋 ( ) ≤ 𝑋𝛼. It requires to solve the equation
𝐹( ,) (𝛼) = 𝛽;2) The minimal sample size (and therefore the minimal number of computer runs) to obtain alower or upper bound of a given percentile with a given confidence level. It leads to the socalled Wilk’s formula [I–4]:(I2)

𝑁 = ln(1 − 𝛽)⁄lnα
and Guba’s estimate in Case of multiple output parameters in [I–5].

Order statistics are widely used since nothing should be known about the distribution of
the random variable except that it is assumed continuous. Moreover, this method is very simple
to implement, which makes it extremely interesting for licensing applications to nuclear safety
analyses.
Due to its simplicity, robustness and transparency, this method will be used in thisbenchmark. The highly recommended sample size is set to 200 (i.e. 200 code runs will be
performed). Strong justifications should be given if a lower number of code runs is performed.
The sample is constructed according to the selected pdfs coming from the uncertainty modelling
step and assuming independence between input parameters following a Simple Random
Sampling (SRS) as recommended for the use of order statistics in BEMUSE [I–6] [I–7].
Moreover, we focus on the estimation of a lower, resp. upper, bound of the 5%, resp. 95%,
percentiles α at confidence level β higher than 95%. For 𝑁 = 200, 𝛽 = 0.95 and 𝛼 = 0.05 or
0.95, Equation (I1) leads to:
𝑃 𝑋 ( ) ≤ 𝑋 % >0.95,
𝑃 𝑋(

)

≤𝑋

%

>0.95

the lower, resp. upper, bound is defined in this benchmark by 𝑋 ( ) , resp. 𝑋 (

)

.

149

For a proper use of order statistics, all code runs should be successfully terminated. If not,it is therefore recommended to correct the failed code runs. As noticed during the BEMUSE
project [I–7], some failures can come from a too large time step and the run can be continued
after time step reduction. If there is no possible correction, a careful checking of the output
evolution is be performed in the failed runs to keep the results before the failures occur and use
the previous methodology to analyse them. When the number of failures is relatively low, aconservative treatment can also be considered by assuming that the n failed runs produced then most adverse values of the output of interest.
Participants are requested to clearly describe in their contribution their approach to handle this
topic.
I–2.2.

Sensitivity analysis: Global sensitivity analysis method

Besides the uncertainty analysis, and as an optional activity for the interested participants,
a complementary study may be performed to get qualitative insights on the most influential
input parameters.
This work can be done based on a global sensitivity analysis using the 200 code runs
previously obtained. This is usually done together with the statistical uncertainty analysis, using
the same tool.
More precisely, if Y denotes the response of interest and {Xi}i=1,…,p the set of p uncertain
input parameters (also called regressors), it will require to compute the following classicalcorrelation coefficients:
Linear (or Pearson’s) simple correlation coefficients (SCC): for each i,
𝜌 =

( ,

)

(I3)

where 𝜎 and 𝜎 are the empirical standard deviations of X and Y.
They correspond to the p correlation coefficients between the response and the pregressors. They measure the degree of linear dependence between the response and the pregressors taken separately.
A better measure of linear relation between the response and one of the p regressors is theso-called partial correlation coefficient (PCC), in which the correlation between the twovariables under consideration is calculated and corrected for the linear contribution of theremaining variables. Indeed, since this correction removes linear trends associated with othervariables, the PCC would lead to higher number than the Pearson’s simple correlation
coefficient.
Spearman’s rank correlation coefficient (RCC): same definition as SCC but replacing
input and output values by their respective ranks. Working with ranks allows one to extend theprevious underlying linear regression model to a monotonic non-linear one. In the presence of
nonlinear but monotonic relationships between the response and each of the p regressors, useof the ranks can substantially improve the resolution of sensitivity analysis results [I–8].
The partial rank correlation coefficient (PRCC) provides an improved measure of themonotonic relation between the response and one of the p regressors by removing trends
associated with other variables. Again, the PRCC would lead to higher number than theSpearman’s rank correlation coefficient.
Based on this information (Pearson’s SCC or Spearman’s RCC, PCC or PRCC), the mostinfluential uncertain input parameters can be identified.

150

Note that the above correlation coefficients estimate the linear connection (SCC) or themonotonic one (RCC) between the input and the target output parameters. Moreover, nointeraction between input parameters is considered [I–9].
As the fuel rod codes are all complex models, and there are certain interactions between
input parameters, these coefficients can only be considered as qualitative and relative index isused for screening the non-important input parameters.
Other sensitivity measures, such as the Sobol’s indexes, could be obtained by using thevariance-based decomposition method [I–10]. The Sobol’s indexes provide quantitatively thecontribution of the uncertainty of each input parameter to the target output parameter
uncertainty. However, the variance-based decomposition method requires much morecalculations efforts, therefore is not recommended for the current benchmark.
I–2.3.

The tool

The participant can choose the tool that is available for him to perform the proposed
UASA.
The DAKOTA (Design Analysis Kit for Optimization and Terascale Applications) code
has been developed by the Sandia National Laboratory [I–11]. It can be freely downloaded
from the website http://www.cs.sandia.gov/dakota.
As shown in Fig. I–2, DAKOTA provides a flexible, extensible interface between
simulation codes and iterative analysis methods, via DAKOTA input files and executables.

FIG. I–2. DAKOTA uncertainty analysis process.
Among others, DAKOTA contains algorithms for uncertainty quantification (UQ) withsampling (Monte-Carlo or Latin Hypercube), epistemic uncertainty methods (Second orderprobability or Dempster-Shafer theory of evidence), and sensitivity analysis. These capabilities
may be used on their own or as components within advanced strategies.
For the applications presented in this activity, the input uncertainty parameters range anddistributions, as well as the uncertainty analysis method and number of samples are defined in
the DAKOTA Input File.
Based on the sampled or assigned input uncertainty parameters in the DAKOTA
Parameter File, various scripts can be developed to create the code input files, to execute thesimulation jobs, and to collect the code calculation output data into the DAKOTA Results File.
The DAKOTA Executable will then perform the requested statistical uncertainty and sensitivity
analysis, and provide the information in the DAKOTA Output Files.
151

I–3. SPECIFICATION OF THE CASE
I–3.1.

Test IFA-650.10

The objective of the Halden LOCA tests IFA-650 is to study fuel behaviours such as fuelfragmentation and relocation, cladding ballooning, burst (rupture) and oxidation during typical
LOCA transient for PWR, BWR and VVER high burnup fuels.
In the IFA-650 LOCA tests, a single fuel rodlet is in a high-pressure flask connected tothe heavy water loop 13 of the Halden reactor. The fuel power is controlled by reactor power.
Nuclear power generation in the fuel rod is used to simulate decay heat, whereas the electricalheater surrounding the rod is simulating the heat from surrounding rods.
As shown in Fig. 3 (Section 2.2), the rig and rod instrumentations consisted of three
cladding thermocouples at the bottom (TCC1) and upper (TCC2 & 3) part of the rod, threeheater thermocouples at different axial elevations (TCH1 at bottom, TCH2 at mid and TCH3 attop), a cladding extensometer (EC2) and a rod pressure sensor (PF1), rig coolant thermocouples(two at rig inlet, TI, and two at outlet, TO), three axially distributed vanadium neutron detectors(ND) to measure axial power distribution and two fast response cobalt NDs to monitor rapid
flux and power changes.
The detailed description of IFA-650.10 can be found in Section 2.2. The test segment was
cut from a standard PWR fuel rod test which had been irradiated in the PWR Gravelines 5 (900
MWe EDF, France) during five cycles from August 1988 to August 1995 to a burn-up of 61
MWd/kgU (average cycle powers 195, 230, 215, 185 and 150 W/cm). The length of the fuelstack was ~ 440 mm and no end pellets were inserted.
The rod was filled with a gas mixture of 95 % argon and 5 % helium at 40 bars. Argon
was chosen to simulate the fission gases, whereas a small amount of helium is required for theleak test of the rod. The rod plenum volume (free gas volume) was made relatively large tomaintain stable pressure conditions until cladding burst. The total free gas volume of ~16–17
cm³ was thus practically all located in the plenum, outside the heated region.
The test was conducted in May 2010. The evolution of the main test results is illustrated
in Figs 20 and 21 (Section 2.2).
The initial loop pressure was ~70 bar and the counter pressure in the blowdown tank was~2 bar. Shortly before the test start, the outer loop was by-passed, and after ~3 minutes withnatural circulation in the rig, the LOCA was initiated by opening the valves leading to theshielded blowdown tank.
The target peak cladding temperature was 850 °C. Cladding failure occurred ~249 s after
blowdown at ~755 °C (TCC1) as evidenced by pressure, cladding temperature measurements
as well as the gamma monitor on the blowdown line to the dump tank.
Spraying was started 12 s after the burst to ensure that the fission products are transportedout of the loop. The test was terminated by a reactor scram 417 s after the blowdown initiation.
At the end of the test, the rig was filled with helium for dry storage.
Slight clad ballooning and burst were detected and verified by the gamma scanning performed
at Halden. No fuel relocation was seen during the test, which was subsequently confirmed by
the gamma scanning.
I–3.2.

Modelling

The total length of the test fuel rod should be modelled by at least 17 radial nodes and 7
axial nodes.
The initial conditions of the test fuel rod can be modelled by a steady state simulation of
the base in-reactor irradiations. In both steady state and transient fuel rod input models, most152

of the data were set according to the specifications of IFA-650 tests or the code manual
recommended values. The refabricated rodlet input model should be validated by comparing
with available measured data. The refabricated rodlet initialization file should be the output ofsteady-state input model which contains gas data from the initial rod and subsequent Fission
Gas Release (FGR) history data. The number of moles of new gas mixture and the relative
amount of each gas species in the refabricated rodlet should be adapted to match the calculated
and measured initial rod internal pressure.
The provided measured data during tests include (see Fig. 20 and 21):Three measured cladding temperatures at the bottom (TCC1) and upper (TCC2 & 3);
Measured rod internal pressure (PF1);
Measured plenum temperature (Tplenum);Three measured heater temperatures at different axial elevations (TCH1 at bottom, TCH2
at mid and TCH3 at top);
Rig coolant temperatures (two at rig inlet, TIA, and two at outlet, TOA);
Rig pressure and flowrate,;rod power (Co) and axial power distribution (V);Heater power (LHR heater).
Ideally, if one knows the transient evolution of coolant pressure, inlet temperature andflow rate in the channel between the rod and the heater, on can use the built-in (if any) fuel rod
code heat transfer models to calculate the coolant temperatures, heat transfer coefficients, andcladding temperatures.
However, since most fuel rod codes do not simulate in detail the rig and the different
phases of the test, and due to complexity to simulate the thermal hydraulic behaviours and thedifferences that may appear from various assumptions and/or models, it is recommended to use
the thermal hydraulic boundary conditions calculated from SOCRAT [I–13], namely:
Coolant temperatures;
Clad to coolant heat transfer coefficients (HTCs).
The clad to coolant heat transfer coefficients should be determined from the total heat
flux (radiative + convective), namely HTC = Qtot / (Tclad – Tcool), for each axial node.
Alternatively, the measured or calculated cladding temperatures can be imposed directlyas the boundary conditions.
The rodlet plenum temperature (Tplenum) should be taken from the measurement, or fromany appropriate empirical plenum gas temperature model.
For the transient calculation, the rod axial power profile as shown in Fig. I–3 should be
used.
The default ‘best estimate’ properties and models in the participant’s fuel rod code should beselected, namely the:Fuel thermal conductivity, thermal expansion, specific heat models;Cladding thermal conductivity, thermal expansion, specific heat models;
Fuel initial radial deformation and relocation due to densification, solid swelling and gas
swelling;
Cladding initial radial deformation;
Rigid pellet and cladding deformation models (finite difference model) for fuel rod
mechanical response;
Default clad failure model;
Fission gas release mode;
Gap conductance model due to gap gas conductivity, fuel/cladding emissivity andcladding hardness;
153

Cathcart-Pawel (C-P) model for high temperature oxidation;
Non-protective initial oxide layer option.

FIG. I–3. Axial power profile at the start of the test of IFA-650.10 [I–12].
If axial fuel relocation is available and used, the fitting parameters for the cladding burst
strain, annealing rate, Yield stress, packing fraction, pellet-cladding gap width threshold forfuel fragment axial mobility should be set at their default values.
A steady state of 100 s should be simulated before the beginning of blowdown. The
calculation should stop at 600 s (after the scram at 517 s).
The maximum time step during the transient should be chosen appropriately to capture
the transient behaviours (e.g., < 0.1 s during the heat up phase).
I–4. DEFINITION OF INPUT UNCERTAINTIES
I–4.1.

Identification of uncertainty parameters

From the preliminary calculation results [I–14] and based on engineering judgements, thefollowing uncertainty parameters are identified. They may not be all relevant to the Halden
LOCA tests but are included to determine the important parameters through the sensitivity
analysis.
The participant can consider only the parameters applicable or relevant to his own code.
I–4.2.

Uncertainties in fuel rod design/manufacturing data

The following relevant uncertainty parameters can be considered:
Cladding outside/inside diameter;
Fuel pellet outside diameter;235
U enrichment;
Fuel theoretical density;
Rod gas-gap fill pressure.

154

I–4.3.

Uncertainties in fuel rod operation and test boundary conditions

The uncertainty parameters in the initial states of the fuel rod are mainly related to theuncertainties in the base irradiation operating conditions. As the base irradiation operating
conditions will be explicitly simulated, the uncertainties in the initial states of the fuel rod will
be propagated from steady state fuel rod code (e.g., FRAPCON) to transient fuel rod code (e.g.,
FRAPTRAN):
Cladding corrosion model (initial state);
Cladding hydrogen pickup model (initial state).
The following relevant uncertainty parameters are considered on the test boundary
conditions:
Rod average power;
Rod power profile;
Decay heat model.
If the T/H boundary conditions as calculated by SOCRAT are used, the following
uncertainties should be considered (if applicable):
Coolant temperature;
Clad to coolant heat transfer coefficient.
If the calculated or measured cladding temperatures are used as the boundary conditions,the measurement and/or the calculation uncertainties should be considered.
 Clad temperatures: measured or from SOCRAT calculations (if applicable).
I–4.4.

Uncertainties in physical properties and key models

If applicable, the following relevant uncertainty parameters are considered (the final list
depends on the selected code and the participant’s choice):
Fuel thermal conductivity;

Fission gas release (or gas diffusion
coefficient);

Cladding thermal conductivity;

Gap gas conductivity;

Fuel thermal expansion coefficient;

Fuel/cladding emissivity;

Cladding thermal expansion
coefficient;
Fuel specific heat capacity;

Fuel radial relocation;

Cladding specific heat capacity;

Cladding annealing;

Fuel densification model;

Cladding ballooning model;

Fuel solid swelling model;

Cladding mechanical deformation;

Fuel gaseous swelling model;

Cladding burst stress criteria;

Cladding Meyer hardness;155

I–4.5.

Cladding yield stress;

Cladding burst strain criteria;

Fuel axial relocation (fuel fragment
packing fraction and cladding strain
threshold for fuel mobility, if
applicable);
Cladding oxidation model at hightemperature;
Thermal conductivity of the oxide
layer;

Plenum gas temperature (empiricalcorrelation from measured data or
SOCRAT calculations);
Cladding elastic modulus.

Definition of INPUT uncertain parameters

Table 13 provides the recommended input parameters (if applicable) as well as theinformation related to their uncertainties. For each of them, it includes a mean value, a standard
deviation and a type of distribution.
To avoid unphysical numerical values, a range of variation (lower and upper bounds) isalso provided. The sampling will be performed (i.e., truncated) between the upper and lower
bounds. This information is then used to define a probability distribution for uncertainty
modelling.
For the current benchmark application, a normal distribution has been assigned forsimplicity to all the considered input parameters. Where applicable, the standard deviation has
been taken as the half of the maximum of the absolute value of the difference between theirnominal value and their upper or lower bound. In addition, the participants could performsensitivity studies by using other distributions, such as uniform or histogram. These results
could be reported at the RCM or the final report.
Depending on the code selected, it might be difficult to modify some recommended input
parameters. In this case, the parameters can be discarded but this information must be clearlymentioned in participants’ contributions.
I–5. OUTPUT SPECIFICATION
I–5.1.

Uncertainty analysis output

Each participant will give lower and upper bounds (LB, UB) for the output parameterslisted in Table 14. A frequency of 10 s was recommended as the trending time. In addition, theresults of the calculation with the nominal value of the input parameters, also called reference
calculation (REF) will be provided.
I–5.2.

Sensitivity analysis output

A list of times required for sensitivity analysis is proposed in Table 15. One formatted
Excel file was also expected for providing the sensitivity analysis results.
Based on this information, the most influential uncertain input parameters with respect to
the Fuel Thermal Behaviour (fuel pellet centreline and surface temperature), Clad Thermal
Behaviour (cladding surface temperatures and oxidation layer thickness), and MechanicalBehaviour (Cladding diameter, effective stress) could be identified and given in the lastcolumns of Table 13.
It is up to the participants to define the thresholds for measuring the importance (H, M or L),
based on the sensitivity analysis results and his own experience. The following empirical156

thresholds could be used to indicate the relative importance (as recommended in the DAKOTA
user’s guide and some previous studies):
H (High): absolute value of correlation coefficients ≥ 0.5;
M (Medium): 0.5 > absolute value of correlation coefficients > 0.25;
L (Low): absolute value of correlation coefficients ≤ 0.25.
Appropriate common thresholds for measuring the importance can be defined at a later stage.
I–5.3.

Proposed Process and Schedule As per agreements

Step 1 (J. Zhang): Proposal for a draft specification, and send to all participants forreview/comments (by end-of-December 2016);
Step 2 (all participants): Send comments/suggestions to J. Zhang (end-of-January 2017);
Step 3 (J. Zhang): Send final Specification with a common list of input uncertainty
parameters ranges and distributions and output (in Excel file) to all participants (end-ofJune, 2017);
Step 4 (all participants): Perform the uncertainty analysis according to the Specifications
and send the results to IAEA (end-of-September 2017);
Step 5 (IAEA and the Consulting team): Synthesis and compare uncertainty analysis
results (end-of-October 2017);
Step 6 (all participants): Prepare presentations, compare results and present conclusions(3rd RCM, November 13-17, 2017);
Step 7 (IAEA and the Consulting team): Prepare final report (Consulting meeting, 2018).

157

REFERENCES TO THE ANNEX I[I–1] GLAESER, H., “GRS Method for Uncertainty and Sensitivity Evaluation of CodeResults and Applications, Science and Technology of Nuclear Installations, Volume
2008, Article ID 798901, 2008.
[I–2] ZHANG, J., SEGURADO J., SCHNEIDESCH, C., “Towards an Industrial Applicationof Statistical Uncertainty Analysis Methods to Multi-physical Modelling and Safety
Analyses,” Proc. OECD/CSNI Workshop on Best Estimate Methods and Uncertainty
Evaluations, Barcelona, Spain, 16–18 November 2011.
[I–3] GENTLE, E., “Monte-Carlo Methods,” Encyclopaedia of Statistics, 5, pp. 612–617,
John Wiley and Sons, New-York, 1985.
[I–4] CONOVER, W., Practical non-parametric statistic, Wiley, New York, 1999.
[I–5] GUBA, A., MAKAI, M., PAL L., Statistical aspects of best estimate method-I;
Reliability Engineering and System Safety 80, 217–232, 2003.
[I–6] DE CRÉCY, A., et al., “The BEMUSE Programme: Results of the First Part Concerning
the LOFT L2-5 Test,” Proceedings of 14th International Conference on Nuclear
Engineering, Miami, Florida, USA, 17–20 July, 2006.
[I–7] GLAESER, H., “BEMUSE Phase VI Report, Status report on the area, classification of
the methods, conclusions and recommendations,” OECD/NEA/CSNI/R(2011)4, March
2011.
[I–8] MCKAY, M.D., “Sensitivity and uncertainty analysis using a statistical sample of input
values,” Ch. 4, Uncertainty Analysis, Ronen, Y. Editor, CRC Press, Florida, USA, 1988.
[I–9] HELTON, J.C., JOHNSON, J.D., SALLABERRY, C.J., STORLIE, C.B., “Survey ofsampling-based methods for uncertainty and sensitivity analysis,” Reliability
Engineering and System Safety, 91(10), 10/2006.
[I–10] IOOSS B., LEMAITRE, P., “A review on global sensitivity analysis methods,” in
Uncertainty management in Simulation-Optimization of Complex Systems: Algorithms
and Applications (C. Meloni and G.
Dellino, Eds), Springer, 2015,
http://www.springer.com/business.
[I–11] ADAMS, B., et al., "DAKOTA, A Multilevel Parallel Object-Oriented Framework for
Design Optimization, Parameter Estimation, Uncertainty Quantification, and Sensitivity
Analysis: Version 5.1 User's Manual", Sandia Technical Report SAND2010-2183,
Updated Version 5.3, December 2013, http://www.cs.sandia.gov/dakota.
[I–12] LAVOIL, A., “LOCA Testing at Halden, the Tenth Experiment IFA-650.10”, HWR974, OECD Halden Reactor Project, December 2010.
[I–13] KISELEV, A., “Short Information on the Results of IFA-650.9, IFA-650.10 and IFA650.11 Calculations with SOCRAT code”, Technical Note, version 3, IBRAE RAN,
December 2016.
[I–14] ZHANG, J., UMIDOVA, Z., DETHIOUX, A., “Simulation of fuel behaviours under
LOCA and RIA using FRAPTRAN and uncertainty analysis with DAKOTA”, in“Modelling of Water Cooled Fuel Including Design Basis and Severe Accidents,
Proceedings of a Technical Meeting Held in Chengdu, China, 28 October – 1 November
2013”, IAEA-TECDOC-CD-1775, 2015.

159

LIST OF PARTICIPANTS
Zhang, J.

Tractebel Engineering S.A.,
Avenue Ariane 7,1200 Brussels, BE, Belgium
Email: jinzhao.zhang@tractebel.engie.com

Abe, A.

Instituto de Pesquisas Energéticas e Nucleares(IPEN-CNEN/SP),
Avenida prodessor Lineu Prestes, 2242,
05508-000 São Paulo, Brazil
Email: ayabe@ipen.br

Boneva, S.

Institute for Nuclear Research and Nuclear Energy(INRNE), Bulgarian Academy of Science,
72 Tzarigradsko Chausee Blvd.
1784 Sofia, Bulgaria.
Email: boneva@inme.bas.bg

Ji, S.

China Institute of Atomic Energy,
ZinZhen
P.O. BOX: 275,
Beijing 102413,
FangShan District, China
Email: songtaoji@139.com

Ren, Q.

China Nuclear Power Technology Research Institute,
Yitian Road, Jiangsu Building, 13/F, Block A,
518026, Shenzhen City, China
E-mail: renqisen@cgnpc.com.cn

Van Uffelen, P.

European Commission,Materials Research Department Institute forTransuranium Elements,
Postfach 2340,
76125 Karlsruhe,
Germany
Email: paul.van-uffelen@ec.europa.eu

Stuckert, J.

Karlsruhe Institute of Technology,
Hermann-von-Helmholtz-Platz 1,
76344 Eggenstein Leopoldshafen,
Germany
Email: juri.stuckert@kit.edu

Tulkki, V.

VTT Technical Research Centre of Finland,
P.O. BOX 1000, Vuorimiehentie 3, Otaniemi,
02044 Espoo, Finland
Email: ville.tulkki@vtt.fi

Boulore, A.

Centre CEA de Saclay (Essonne)
Gif-sur-Yvette 91191,
FranceEmail: antoine.boulore@cea.fr

Kulacsy, K.

Hungarian Academy of Sciences, Centre of Energy
Research,
Konkoly Thege út 29-33, P.O. Box 49.
1121 Budapest, Hungary
Email: katalin.kulacsy@energia.mta.hu

161

162

Luzzi, L.

Politecnico di Milano,
Dipartimento di Energia,
Via Lambruschini 4 (Building 25),
20156 Milano, Italy
Email: lelio.luzzi@polimi.it

Fujioka, K.

Nuclear Regulatory Authority (NRA),
1-9-9 Roppongi,
106-8450 Minato-ku,
Tokyo, Japan
Email: kazuharu_fujioka@nsr.go.jp

Koo, Y.H.

Korean Atomic Energy Research Institute (KAERI),
111 Daedeok-daero 989 beon-gil, Yuseong-gu,
305353 Daejeon,
Republic of Korea
Email: yhkoo@kaeri.re.kr

Wiesenack, W.

OECD Halden Reactor Project; Institute for Energy
Technology
P.O. BOX 173, Os Alle 5,
N1751 Halden, Norway
Email: wolfgang.wiesenack@hrp.no

Fedotov, P.

Joint Stock Company (JSC), A.A. Bochvar HighTechnology Research Institute of Inorganic
Materials,
P.O. BOX. 369, JSC “VNIINM”, 5-a Rogova str.,
Moscow, Russian Federation
Email: fpvpetr@rambler.ru

Kiselev, A.

Nuclear Safety Institute of Russian Academy of
Sciences (IBRAE),
Bolshaya Tulskaya str. 52, 115191,
Moscow, Russian Federation
E-mail: ksv@ibrae.ac.ru

Herranz, L.

Centro de Investigaciones Energeticas,
Medioambientales y Tecnologicas (CIEMAT),
Avenida Complutense 40,
28040 Madrid, Spain
Email: luisen2013@gmail.com

Jernkvist, L.

Quantum Technologies AB,
Uppsala Science Park,
SE-75183 Uppsala, Sweden
Email: loje@quantumtech.se

Cherednichenko, O.

Energorisk Ltd.,
T. Strokacha 7,
P.O. Box. 141, 031448 Kiev,
UkraineEmail: cherezo@bigmir.net

Ieremenko, M.

State Scientific and Technical Center for Nuclear andRadiation Safety (SSTC NRS),
Stusa Vasilya Vul, 35/37,
03142 Kyiv, Ukraine
Email: ml_eremenko@sstc.com.ua

Williamson, R.

Battelle Energy Alliance LLC, Idaho National
Laboratory (INL)
2525 N. Fremont Avenue,
P.O. Box 1625,
83415-3840 Idaho Falls ID,
United States of America.
Email: Richard.williamson@inl.gov

Xu, P.

5801 Bluff Road
Postal Code: 29601, Hopkins,
South Carolina, USA
E-mail: xup@westinghouse.com

Porter, I.

Nuclear Regulatory Commission (US-NRC),
Washington 20555, District of Columbia,
United States of America.
Email: ian.porter@nrc.gov

Austregesilo, H.

Gesellschaft für Anlagen- und Reaktorsicherheit (GRS)GmbH
Cooling Circuit Department,
Reactor Safety Research Division,
Forschungszentrum, Boltzmannstr. 1485748 Garching,
Germany
E-Mail: henrique.austregesilo@grs.de(Active observer)

163

CONTRIBUTORS TO DRAFTING AND REVIEW
Boulore, A.

CEA, France

Chan, P.

International Atomic Energy Agency

Pastore, G.

Batelle INL, USA

Pizzocri, D.

Politecnico di Milano, Italy

Rathod, V.

International Atomic Energy Agency

Stuckert, J.

KIT, Germany

Van Uffelen, P.

EC/JRC, Germany

Veshchunov, M.

International Atomic Energy Agency

Wiesenack, W.

IFE-HRP, Norway

Zhang, J.

TRACTEBEL, Belgium

165

@

No. 26ORDERING LOCALLY
IAEA priced publications may be purchased from the sources listed below or from major local booksellers.
Orders for unpriced publications should be made directly to the IAEA. The contact details are given at
the end of this list.

NORTH AMERICA
Bernan / Rowman & Littlefield
15250 NBN Way, Blue Ridge Summit, PA 17214, USA
Telephone: +1 800 462 6420 • Fax: +1 800 338 4550
Email: orders@rowman.com • Web site: www.rowman.com/bernan
Renouf Publishing Co. Ltd
22-1010 Polytek Street, Ottawa, ON K1J 9J1, CANADA
Telephone: +1 613 745 2665 • Fax: +1 613 745 7660
Email: orders@renoufbooks.com • Web site: www.renoufbooks.com

REST OF WORLD
Please contact your preferred local supplier, or our lead distributor:
Eurospan Group
Gray’s Inn House
127 Clerkenwell Road
London EC1R 5DB
United Kingdom
Trade orders and enquiries:
Telephone: +44 (0)176 760 4972 • Fax: +44 (0)176 760 1640
Email: eurospan@turpin-distribution.com
Individual orders:www.eurospanbookstore.com/iaea
For further information:
Telephone: +44 (0)207 240 0856 • Fax: +44 (0)207 379 0609
Email: info@eurospangroup.com • Web site: www.eurospangroup.com

Orders for both priced and unpriced publications may be addressed directly to:Marketing and Sales Unit
International Atomic Energy Agency
Vienna International Centre, PO Box 100, 1400 Vienna, Austria
Telephone: +43 1 2600 22529 or 22530 • Fax: +43 1 26007 22529
Email: sales.publications@iaea.org • Web site: www.iaea.org/publications

19-00921

IAEA-TECDOC-1889

IAEA-TECDOC-1889

IAEA TECDOC SERIES

Fuel Modelling in Accident Conditions (FUMAC)

IAEA-TECDOC-1889

Fuel Modelling in Accident
Conditions (FUMAC)
Final Report of a Coordinated Research ProjectInternational Atomic Energy Agency
ViennaISBN 978–92–0–163919–6
ISSN 1011–4289@