Nuclear-data uncertainty analysis for the start-up physics test of CPR1000 reactor

2021 ◽  
Vol 156 ◽  
pp. 108197
Author(s):  
Liming Zhang ◽  
Hongyun Xie ◽  
Wanchao Mao ◽  
Jialin Ping
Author(s):  
Guanlin Shi ◽  
Yishu Qiu ◽  
Kan Wang

As people pay more attention to nuclear safety analysis, sensitivity and uncertainty analysis has become a research hotspot. In our previous research, we had developed an integrated, built-in stochastic sampling module in the Reactor Monte Carlo code RMC [1]. Using this module, we can perform nuclear data uncertainty analysis. But at that time the uncertainty of fission spectrum was not considered. So, in this work, the capability of computing the uncertainty of keff induced by the uncertainty of fission spectrum, including tabular data form and formula form, is implemented in RMC code based on the stochastic sampling method. The algorithms and capability of computing keff uncertainty induced by uncertainty of fission spectrum in RMC are verified by comparison with the results calculated by the first order uncertainty quantification method [2].


2021 ◽  
Vol 11 (14) ◽  
pp. 6499
Author(s):  
Matthias Frankl ◽  
Mathieu Hursin ◽  
Dimitri Rochman ◽  
Alexander Vasiliev ◽  
Hakim Ferroukhi

Presently, a criticality safety evaluation methodology for the final geological disposal of Swiss spent nuclear fuel is under development at the Paul Scherrer Institute in collaboration with the Swiss National Technical Competence Centre in the field of deep geological disposal of radioactive waste. This method in essence pursues a best estimate plus uncertainty approach and includes burnup credit. Burnup credit is applied by means of a computational scheme called BUCSS-R (Burnup Credit System for the Swiss Reactors–Repository case) which is complemented by the quantification of uncertainties from various sources. BUCSS-R consists in depletion, decay and criticality calculations with CASMO5, SERPENT2 and MCNP6, respectively, determining the keff eigenvalues of the disposal canister loaded with the Swiss spent nuclear fuel assemblies. However, the depletion calculation in the first and the criticality calculation in the third step, in particular, are subject to uncertainties in the nuclear data input. In previous studies, the effects of these nuclear data-related uncertainties on obtained keff values, stemming from each of the two steps, have been quantified independently. Both contributions to the overall uncertainty in the calculated keff values have, therefore, been considered as fully correlated leading to an overly conservative estimation of total uncertainties. This study presents a consistent approach eliminating the need to assume and take into account unrealistically strong correlations in the keff results. The nuclear data uncertainty quantification for both depletion and criticality calculation is now performed at once using one and the same set of perturbation factors for uncertainty propagation through the corresponding calculation steps of the evaluation method. The present results reveal the overestimation of nuclear data-related uncertainties by the previous approach, in particular for spent nuclear fuel with a high burn-up, and underline the importance of consistent nuclear data uncertainty quantification methods. However, only canister loadings with UO2 fuel assemblies are considered, not offering insights into potentially different trends in nuclear data-related uncertainties for mixed oxide fuel assemblies.


2011 ◽  
Vol 59 (2(3)) ◽  
pp. 1191-1194 ◽  
Author(s):  
D. Rochman ◽  
A. J. Koning ◽  
D. F. Dacruz ◽  
S. C. van der Marck

2019 ◽  
Vol 129 ◽  
pp. 308-315
Author(s):  
Abdulaziz Ahmed ◽  
H. Boukhal ◽  
T. El Bardouni ◽  
M. Makhloul ◽  
E. Chakir ◽  
...  

1984 ◽  
Vol 11 (3) ◽  
pp. 387-395 ◽  
Author(s):  
Edward McBean ◽  
Jacques Penel ◽  
Kwok-Lui Siu

The delineation of floodplains involves, in most circumstances, solving the one-dimensional energy equation. However, uncertainties in the identified floodplain arise from both computational and data uncertainties; data uncertainties are concluded to be generally more significant than computational uncertainties.A method is developed to calculate the uncertainty in floodplain delineation arising from data uncertainties. The proposed method requires only HEC-2 computer output and a small computer program. Application of the method to two case studies and comparison with another uncertainty method suggest that the proposed uncertainty theory is applicable to practical situations within the given constraints. Key words: data uncertainty, floodplain, uncertainty analysis, water profile computation.


Sign in / Sign up

Export Citation Format

Share Document