New strategies for quantifying and propagating nuclear data uncertainty in CUSA

2016 ◽  
Vol 307 ◽  
pp. 328-338 ◽  
Author(s):  
Qiang Zhao ◽  
Chunyan Zhang ◽  
Chen Hao ◽  
Fu Li ◽  
Dongyong Wang ◽  
...  
Keyword(s):  
Nuclear Data ◽  
Data Uncertainty ◽  
New Strategies

scholarly journals Nuclear Data Uncertainty Quantification in Criticality Safety Evaluations for Spent Nuclear Fuel Geological Disposal

2021 ◽  
Vol 11 (14) ◽  
pp. 6499
Author(s):  
Matthias Frankl ◽  
Mathieu Hursin ◽  
Dimitri Rochman ◽  
Alexander Vasiliev ◽  
Hakim Ferroukhi
Keyword(s):  
Uncertainty Quantification ◽  
Nuclear Fuel ◽  
Evaluation Method ◽  
Spent Nuclear Fuel ◽  
Nuclear Data ◽  
Data Uncertainty ◽  
Evaluation Methodology ◽  
Geological Disposal ◽  
Fuel Assemblies ◽  
Criticality Safety

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.

Nuclear Data Uncertainty Propagation for a Sodium Fast Reactor

2011 ◽  
Vol 59 (2(3)) ◽  
pp. 1191-1194 ◽  
Author(s):  
D. Rochman ◽  
A. J. Koning ◽  
D. F. Dacruz ◽  
S. C. van der Marck
Keyword(s):  
Fast Reactor ◽  
Uncertainty Propagation ◽  
Nuclear Data ◽  
Data Uncertainty ◽  
Sodium Fast Reactor

Nuclear data uncertainty for criticality-safety: Monte Carlo vs. linear perturbation

2016 ◽  
Vol 92 ◽  
pp. 150-160 ◽  
Author(s):  
D. Rochman ◽  
A. Vasiliev ◽  
H. Ferroukhi ◽  
T. Zhu ◽  
S.C. van der Marck ◽  
...  
Keyword(s):  
Monte Carlo ◽  
Nuclear Data ◽  
Data Uncertainty ◽  
Linear Perturbation ◽  
Criticality Safety

scholarly journals Nuclear Data Uncertainty Propagation to Reactivity Coefficients of a Sodium Fast Reactor

2014 ◽  
Vol 118 ◽  
pp. 535-537
Author(s):  
J.J. Herrero ◽  
R. Ochoa ◽  
J.S. Martínez ◽  
C.J. Díez ◽  
N. García-Herranz ◽  
...  
Keyword(s):  
Fast Reactor ◽  
Uncertainty Propagation ◽  
Nuclear Data ◽  
Data Uncertainty ◽  
Sodium Fast Reactor ◽  
Reactivity Coefficients

scholarly journals Trends on major actinides from an integral data assimilation

2020 ◽  
Vol 239 ◽  
pp. 13002
Author(s):  
Gerald Rimpault ◽  
Gilles Noguère ◽  
Cyrille de Saint Jean
Keyword(s):  
Data Assimilation ◽  
Energy Range ◽  
Cross Section ◽  
Capture Cross Section ◽  
Critical Mass ◽  
Nuclear Data ◽  
Data Uncertainty ◽  
Capture Cross ◽  
Plateau Region ◽  
Integral Data

The objective of this work is to revisit integral data assimilation for a better prediction of the characteristics of SFR cores. ICSBEP, IRPhE and MASURCA critical masses, PROFIL irradiation experiments and the FCA-IX experimental programme (critical masses and spectral indices) with well-mastered experimental technique have been used. As calculations are performed without modelling errors (with as-built geometries) and without approximations with the TRIPOLI4 MC code, highly reliable C/E are achieved. Assimilation results suggest a 2.5% decrease for 238U capture from 3 keV to 60 keV, and a 4-5% decrease for 238U inelastic in the plateau region. For this energy range, uncertainties are respectively reduced to 1-2% and to 2-2.5% for 238U capture and 238U inelastic respectively. The increase trends on 239Pu capture cross section of around 3% in the [2 keV-100 keV] energy range come from a low PROFIL 240Pu/239Pu ratio C/E. For 240Pu capture cross section, the increase trend of around 4% in the [3 keV-100 keV] energy range goes in the same direction as the recent ENDF/B.VIII evaluation though at a much lower level. The nuclear data uncertainty associated to SFR ASTRID critical mass is reduced to 470 pcm.

Enhancement of Stochastic Sampling Capability in RMC Code

2018 ◽  
Author(s):  
Guanlin Shi ◽  
Yishu Qiu ◽  
Kan Wang
Keyword(s):  
Uncertainty Analysis ◽  
Sampling Method ◽  
Nuclear Data ◽  
Data Uncertainty ◽  
Monte Carlo Code ◽  
Tabular Data ◽  
Stochastic Sampling ◽  
First Order ◽  
Fission Spectrum ◽  
Sensitivity And Uncertainty Analysis

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].

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