The OECD UAM Benchmark was launched in 2005 with the objective of determining the uncertainty in the simulation of Light Water Reactors (LWRs) system calculations at all the stages of the coupled reactor physics—thermal hydraulics modeling. Within the framework of the “Neutronics Phase” of the Benchmark the solutions of some selected test cases at the cell physics and lattice physics levels are presented. The SCALE 6.1 code package has been used for the neutronics modeling of the selected exercises. Sensitivity and Uncertainty analysis (S/U) based on the generalized perturbation theory has been performed in order to assess the uncertainty of the computation of some selected reactor integral parameters due to the uncertainty in the basic nuclear data. As a general trend, it has been found that the main sources of uncertainty are the 238U (n, ) and the 239Pu nubar for the UOX- and the MOX-fuelled test cases, respectively. Moreover, the reference solutions for the test cases obtained using Monte Carlo methodologies together with a comparison between deterministic and stochastic solutions are presented. 1. Introduction In recent years there has been an increasing demand from nuclear research, industry, safety, and regulation bodies for best estimate predictions of Light Water Reactors (LWRs) performances to be provided with their confidence bounds. In addition to the establishment of LWRs best-estimate calculations for design and safety analysis, understanding uncertainties of evaluated reactor parameters is important for introducing appropriate design margins and deciding where additional efforts should be undertaken to reduce those uncertainties. In order to address those issues, an in-depth discussion on “Uncertainty Analysis in Modeling” started to take place in 2005 within the OECD/NEA Nuclear Science Committee, which led to the creation of a dedicated Expert Group and to the launching of a Benchmark exercise, the OECD UAM (Uncertainty Analysis in Modeling) LWR Benchmark [1]. The proposed technical approach is to establish a benchmark for uncertainty analysis in best-estimate modeling and coupled multiphysics and multiscale LWR analysis, using as bases a series of well-defined problems with complete sets of input specifications and reference experimental data. The objective is to determine the uncertainty in LWR system calculations at all stages of coupled reactor physics/thermal hydraulics calculation. The UAM benchmark has been conceived to be structured in three different phases, being Phase I the “Neutronics Phase,” Phase II the “Core Phase,” and
References
[1]
K. Ivanov, et al., “Benchmark for Uncertainy Analysis in Modeling (UAM) for Design, Operation and Safety Analysis of LWRs,” NEA/NSC/DOC, 2012.
[2]
J. Solis, K. Ivanov, B. Sarikaya, A. Olson, and K. Hunt, “BWR TT Benchmark. Volume I: Final Specifications,” NEA/NSC/DOC, 2001.
[3]
K. Ivanov, T. Beam, A. Baratta, A. Irani, and N. Trikouros, “PWR MSLB Benchmark. Volume 1: Final Specifications,” NEA/NSC/DOC(99), 1999.
[4]
B. Ivanov, K. Ivanov, P. Groudev, M. Pavlova, and V. Hadjiev, “VVER-1000 Coolant Transient Benchmark (V1000-CT). Phase 1—Final Specification,” NEA/NSC/DOC, 2002.
[5]
“Benchmark on the KRITZ-2 LEU and MOX Critical Experiments—Final Report,” NEA/NSC/DOC, 2005.
[6]
C. Vaglio and A. Santamarina, “Assembly and core specification of generation 3 PWR,” CEA Report, 2010.
[7]
B. Rearden, C. M. Hopper, K. R. Elam, et al., “Applications of the TSUNAMI sensitivity and uncertainty analysis methodology,” in Proceedings of the 7th International Conference on Nuclear Criticality Safety (ICNC '03), Tokai-mura, Japan, October 2003.
[8]
G. Palmiotti and M. Salvatores, “Developments in sensitivity methodologies and the validation of reactor physics calculations,” Science and Technology of Nuclear Installations, vol. 2012, Article ID 529623, 14 pages, 2012.
[9]
H. Brooks, “Perturbation Theory for Boltzmann Equation,” KAPL-304, 1950.
[10]
G. Aliberti, L. Mercatali, G. Palmiotti, and M. Salvatores, “A systematic approach to nuclear data uncertainties and their impact on transmutation strategies,” in Proceedings of the International Workshops on Nuclear Data for Transmutation, Darmstadt, Germany, September 2003.
[11]
A. Gandini, “Uncertainty analysis and experimental data transposition methods based on perturbation theory,” in Uncertainty Analysis, Y. Ronen, Ed., CRC Press, Boca Raton, Fla, USA, 1988.
[12]
E. Greenspan, “Developments in perturbation theory,” in Advances in Nuclear Science and Technology, J. Lewins and A. Becker, Eds., vol. 14, Plenum Press, 1982.
[13]
M. L. Williams, B. L. Broadhead, and C. V. Parks, “Eigenvalue sensitivity theory for resonance-shielded cross sections,” Nuclear Science and Engineering, vol. 138, no. 2, pp. 177–191, 2001.
[14]
“SCALE: A Comprehensive Modeling and Simulation Suite for Nuclear Safety Analysis and Design,” ORNL/TM-2005/39, Version 6.1. Oak Ridge National Laboratory. Radiation Safety Information Computational Center at Oak Ridge National Laboratory as CCC-785, 2011.
[15]
M. B. Chadwick, P. Oblo？insky, M. Herman, et al., “ENDF/B-VII.0: next generation evaluated nuclear data library for nuclear science and technology,” Nuclear Data Sheets, vol. 107, pp. 2931–3060, 2006.
[16]
B. T. Rearden, M. L. Williams, M. A. Jessee, D. E. Mueller, and D. A. Wiarda, “Sensitivity and uncertainty analysis capabilities and data in SCALE,” Nuclear Technology, vol. 174, no. 2, pp. 236–288, 2011.
[17]
M. L. Williams, “Resonance self-shielding methodologies,” Nuclear Technology, vol. 174, pp. 149–168, 2011.
[18]
N. M. Greene, L. M. Petrie, and M. L. Williams, “XSDRNPM: A One-Dimensional Discrete-Ordinates Code for Transport Analysis,” ORNL/TM-2005/39, 2011.
[19]
B. T. Rearden, L. M. Petrie, M. A. Jessee, and M. L. Williams, “SAMS: Sensitivity Analysis Module for SCALE,” ORNL/TM-2005/39, 2011.
[20]
M. L. Williams, D. Wiarda, G. Arbanas, and B. L. Broadhead, “SCALE Nuclear Data Covariance library,” ORNL/TM-2005/39, 2011.
[21]
A. Trkov, G. L. Molnár, Z. Révay et al., “Revisiting the 238U thermal capture cross section and gamma-ray emission probabilities from 239Np decay,” Nuclear Science and Engineering, vol. 150, no. 3, pp. 336–348, 2005.
[22]
J. Lepp？nen, Development of a new Monte Carlo reactor physics code [D. Sc. Thesis], Helsinki University of Technology, 2007.
[23]
E. Fridman and J. Lepp？nen, “On the use of the Serpent Monte Carlo code for few-group cross section generation,” Annals of Nuclear Energy, vol. 38, no. 6, pp. 1399–1405, 2011.
[24]
“The JEFF-3.1.1 Nuclear Data Library,” NEA JEFF Report 22, OECD, 2009.
[25]
X-5 Monte Carlo Team, “MCNP—A General Monte Carlo N-Particle Transport Code (Version 5),” Los Alamos National Laboratory. LA-CP-03-0245, 2003.
