Abstract
As the nuclear data are from either the experiment measurements or the estimation models, uncertainties would arise from the insufficient measurements and/or modeling uncertainties. The uncertainties in nuclear data would have effects on the best-estimated prediction results of the reactor system. In this paper, our home-developed code UNICORN, which has the capability of uncertainties analysis for the neutron physics calculations, has been applied to quantify the response uncertainties of the PWR burnup calculation introduced by the uncertainties of multigroup microscopic cross-section libraries. The burnup benchmark proposed by UAM (“Uncertainty Analysis in Modeling”) is selected for the demonstration purpose. Relative uncertainties of k ∞ , two-group constants and isotope concentrations with the fuel burnup introduced by the nuclear data uncertainties are quantified. It is observed that the relative uncertainty of the eigenvalue is 0.5%; the relative uncertainties of the two-group constants vary between 0.3% (for the Σ t,2) and 1.9% (for the vΣ f,2); the relative uncertainties for the isotope concentrations can reach 30%. These relative uncertainties introduced by the nuclear data are significant for the neutron physics calculations and cannot be ignored.
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References
K. Ivanov, M. Avramova, S. Kamerow, et al. 2013. Benchmarks for Uncertainty Analysis in Modelling (UAM) for the Design, Operation and Safety Analysis of LWRs. OECD Nuclear Energy Agency. NEA/NSC/DOC(2013)7.
M. Pusa, 2012. Incorporating Sensitivity and Uncertainty Analysis to a Lattice Physics Code with Application to CASMO-4. Annals of Nuclear Energy 40, 153–162.
W. Wieselquist, A. Vasiliev, H. Ferroukhi, 2012. Nuclear Data Uncertainty Propagation in a Lattice Physics Code Using Stochastic Sampling. PHYSOR 2012, Tennessee, USA.
B. T. Rearden, L. M. Petrie, M. A. Jessee, 2009. SAMS: Sensitivity Analysis Nodule for SCALE. Nuclear Science and Technology Division, Vol. II, Sect. F22.
A. J. Koning, D. Rochman, 2008. Towards sustainable nuclear energy: putting nuclear physics to work. Ann. Nucl. Energy 35 (11), 2024–2030.
F. Leszczynski, D. L. Aldama, A. Trkov, 2007. WIMS-D Library Update: Final Report of a Coordinated Research Project. International Atomic Energy Agency.
G. Marleau, A. Hébert, R. Roy, 2014. A User Guide for DRAGON Version 4. Technical Report, IGE-294.
C. Wan, L. Cao, H. Wu, et al. 2015. Code development for eigenvalue total sensitivity analysis and total uncertainty analysis. Ann. Nucl. Energy 85, 788–797.
C. J. Díez, O. Buss, A. Hoefer, et al. 2015. Comparison of nuclear data uncertainty propagation methodologies for PWR burnup simulations.
Acknowledgments
This work is supported by the National Natural Science Foundation of China (Grant No. 11522544).
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Wan, C., Cao, L., Wu, H., Zu, T., Shen, W. (2017). Propagation of Nuclear Data Uncertainties for PWR Burnup Calculation. In: Jiang, H. (eds) Proceedings of The 20th Pacific Basin Nuclear Conference. PBNC 2016. Springer, Singapore. https://doi.org/10.1007/978-981-10-2314-9_76
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DOI: https://doi.org/10.1007/978-981-10-2314-9_76
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