The Nuclear Regulatory Commission (NRC) has considered revision of 10-CFR-50.46C rule (Borchard and Johnson, 2013, “10 CFR 50.46c Rulemaking: Request to Defer Draft Guidance and Extension Request for Final Rule and Final Guidance,” U.S. Nuclear Regulatory Commission, Washington, DC.) to account for burn-up rate effects in future analysis of reactor accident scenarios so that safety margins may evolve as dynamic limits with reactor operation and reloading. To find these limiting conditions, both cladding oxidation and maximum temperature must be cast as functions of fuel exposure. To run a plant model through a long operational transient to fuel reload is computationally intensive, and this must be repeated for each reload until the time of the accident scenario. Moreover for probabilistic risk assessment (PRA), this must be done for many different fuel reload patterns. To perform such new analyses in a reasonable amount of computational time with good accuracy, Idaho National Laboratory (INL) has developed new multiphysics tools by combining existing codes and adding new capabilities. The parallel highly innovative simulation INL code system (PHISICS) toolkit (Rabiti et al., 2016, “New Simulation Schemes and Capabilities for the PHISICS/RELAP5-3D Coupled Suite,” Nucl. Sci. Eng., 182(1), pp. 104–118; Alfonsi et al., 2012, “PHISICS Toolkit: Multi-Reactor Transmutation Analysis Utility—MRTAU,” PHYSOR 2012 Advances in Reactor Physics Linking Research, Industry, and Education, Knoxville, TN, Apr. 15–20.) for neutronic and reactor physics is coupled with the reactor excursion and leak analysis program—three-dimensional (RELAP5-3D) (The RELAP5-3D© Code Development Team, 2014, “RELAP5-3D© Code Manual Volume I: Code Structure, System Models, and Solution Methods,” Rev. 4.2, Idaho National Laboratory, Idaho Falls, ID, Technical Report No. INEEL-EXT-98-00834.) for the loss of coolant accident (LOCA) analysis and reactor analysis and virtual-control environment (RAVEN) (Alfonsi et al., 2013, “RAVEN as a Tool for Dynamic Probabilistic Risk Assessment: Software Overview,” 2013 International Conference on Mathematics and Computational Methods Applied to Nuclear Science and Engineering, Sun Valley, ID, May 5–9, pp. 1247–1261.) for the probabilistic risk assessment (PRA) and margin characterization analysis. For RELAP5-3D to process a single sequence of cores in a continuous run required a sequence of restarting input decks, each with different neutronics or thermal-hydraulic (TH) flow region and culminating in an accident scenario. A new multideck input processing capability was developed and verified for this analysis. The combined RAVEN/PHISICS/RELAP5-3D tool is used to analyze a typical pressurized water reactor (PWR).

References

References
1.
Borchard
,
R.
, and
Johnson
,
M.
,
2013
, “
10 CFR 50.46c Rulemaking: Request to Defer Draft Guidance and Extension Request for Final Rule and Final Guidance
,” U.S. Nuclear Regulatory Commission, Washington, DC.
2.
Alfonsi
,
A.
,
Rabiti
,
C.
,
Mandelli
,
D.
,
Cogliati
,
J.
, and
Kinoshita
,
R.
,
2013
, “
RAVEN as a Tool for Dynamic Probabilistic Risk Assessment: Software Overview
,”
International Conference on Mathematics and Computational Methods Applied to Nuclear Science and Engineering
, Sun Valley, ID, May 5–9, pp.
1247
1261
.
3.
The RELAP5-3D© Code Development Team
,
2014
, “
RELAP5-3D© Code Manual Volume I: Code Structure, System Models, and Solution Methods
,” Rev. 4.2, Idaho National Laboratory, Idaho Falls, ID, Technical Report No.
INEEL-EXT-98-00834
.
4.
Mesina
,
G. L.
,
Aumiller
,
D. L.
,
Buschman
,
F. X.
, and
Kyle
,
M. R.
,
2016
, “
Modeling Moving Systems With RELAP5-3D
,”
J. Nucl. Sci. Eng.
,
182
(
1
), pp.
83
95
.
5.
Weaver
,
W. L.
,
Aumiller
,
D. L.
, and
Tomlinson
,
E. T.
,
2003
, “
A Generic Semi-Implicit Coupling Methodology for Use in RELAP5-3D
,”
J. Nucl. Eng. Des.
, 211(1), pp.
13
26
.
6.
Weaver
,
W. L.
,
2014
, “
RELAP5-3D Code Manual, Volume 1, Appendix B: User Guide for the PVM Coupling Interface in the RELAP5-3D© Code
,” Rev. 4.2, Idaho National Laboratory, Idaho Falls, ID, Technical Report No. INEEL-EXT-98-00834.
7.
Rabiti
,
C.
,
Alfonsi
,
A.
, and
Epiney
,
A. S.
,
2016
, “
New Simulation Schemes and Capabilities for the PHISICS/RELAP5-3D Coupled Suite
,”
Nucl. Sci. Eng.
,
182
(
1
), pp.
104
118
.
8.
Alfonsi
,
A.
,
Rabiti
,
C.
,
Epiney
,
A. S.
,
Wang
,
Y.
, and
Cogliati
,
J.
,
2012
, “
PHISICS Toolkit: Multi-Reactor Transmutation Analysis Utility—MRTAU
,” Advances in Reactor Physics Linking Research, Industry, and Education (
PHYSOR 2012
), Knoxville, TN, Apr. 15–20.
9.
Strydom
,
G.
,
Epiney
,
A. S.
,
Alfonsi
,
A.
, and
Rabiti
,
C.
,
2016
, “
Comparison of the PHISICS/RELAP5-3D Ring and Block Model Results for Phase I of the OECD/NEA MHTGR-350 Benchmark
,”
J. Nucl. Technol.
,
193
(
1
), pp.
15
35
.
10.
Horelik
,
N.
,
Herman
,
B.
,
Forget
,
B.
, and
Smith
,
K.
,
2013
, “
Benchmark for Evaluation and Validation for Reactor Simulations (BEAVRS) v1.01
,”
International Conference on Mathematics and Computational Methods Applied to Nuclear Science and Engineering
, Sun Valley, ID, May 5–9, pp.
2986
2999
.
11.
Szilard
,
R.
,
Frepoli
,
C.
,
Yurko
,
J.
,
Youngblood
,
R.
,
Zoino
,
A.
,
Alfonsi
,
A.
,
Rabiti
,
C.
,
Zhang
,
H.
,
Bayless
,
P.
,
Zhao
,
H.
,
Swindlehurst
,
G.
, and
Smith
,
C.
,
2015
, “
Industry Application Emergency Core Cooling System Cladding Acceptance Criteria Early Demonstration
,” Idaho National Laboratory, Idaho Falls, ID, Technical Report No.
INL/EXT-15-36541
.
12.
Zoino
,
A.
,
Alfonsi
,
A.
,
Rabiti
,
C.
,
Slizard
,
R. H.
,
Giannetti
,
F.
, and
Caruso
,
G.
,
2017
, “
Performance-Based ECCS Cladding Acceptance Criteria: A New Simulation Approach
,”
Ann. Nucl. Energy
,
100
(
2
), pp.
204
216
.
13.
Mesina
,
G. L.
,
2013
, “
RELAP5-3D Restart and Backup Verification Testing
,” Idaho National Laboratory, Idaho Falls, ID, Technical Report No.
INL/EXT-13-29568
.
14.
Mesina
,
G.
,
Aumiller
,
D.
, and
Buschman
,
F.
,
2016
, “
Extremely Accurate Sequential Verification of RELAP5-3D
,”
ANS J. Nucl. Sci. Eng.
,
182
(
1
), pp.
1
12
.
15.
Mesina
,
G.
, and
Anderson
,
A.
,
2016
, “
Enhanced Verification for RELAP5-3D Parameter and Sensitivity Studies
,”
ASME
Paper No. ICONE24-61040.
16.
Alfonsi
,
A.
,
Rabiti
,
C.
,
Mandelli
,
D.
,
Cogliati
,
J.
,
Kinoshita
,
R.
, and
Naviglio
,
A.
,
2013
, “
Dynamic Event Tree Analysis Through RAVEN
,”
International Topical Meeting on Probabilistic Safety Assessment and Analysis (PSA 2013)
, on CD-ROM, Columbia, SC, Sept. 22–26, Report No. INL/CON-14-32595.
17.
Alfonsi
,
A.
,
Rabiti
,
C.
,
Mandelli
,
D.
,
Cogliati
,
J.
, and
Kinoshita
,
R.
,
2014
, “
RAVEN: Development of the Adaptive Dynamic Event Tree Approach
,” Idaho National Laboratory, Idaho Falls, ID, Technical Report No. INL/MIS-14-33246.
You do not currently have access to this content.