Beta-effective sensitivity and uncertainty analysis of MYRRHA reactor for possible use in nuclear data validation and improvement

2018 ◽  
Vol 113 ◽  
pp. 425-435 ◽  
Author(s):  
Ivan A. Kodeli
Keyword(s):  
Uncertainty Analysis ◽  
Nuclear Data ◽  
Data Validation ◽  
Sensitivity And Uncertainty Analysis ◽  
Effective Sensitivity

Sensitivity and uncertainty analysis on keff due to nuclear data in the KRITZ-2:19 – Comparison between JENDL-4.0 and ENDF/B-VII.1

2019 ◽  
Vol 129 ◽  
pp. 308-315
Author(s):  
Abdulaziz Ahmed ◽  
H. Boukhal ◽  
T. El Bardouni ◽  
M. Makhloul ◽  
E. Chakir ◽  
...  
Keyword(s):  
Uncertainty Analysis ◽  
Nuclear Data ◽  
Sensitivity And Uncertainty Analysis

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].

scholarly journals Sensitivity and uncertainty analysis of βeff for MYRRHA using a Monte Carlo technique

2018 ◽  
Vol 4 ◽  
pp. 42 ◽  
Author(s):  
Hiroki Iwamoto ◽  
Alexey Stakovskiy ◽  
Luca Fiorito ◽  
Gert Van den Eynde
Keyword(s):  
Monte Carlo ◽  
Uncertainty Analysis ◽  
Nuclear Data ◽  
Ratio Method ◽  
Delayed Neutron ◽  
Continuous Energy ◽  
A Value ◽  
Transport Code ◽  
Sensitivity And Uncertainty Analysis ◽  
Data Sensitivity

This paper presents a nuclear data sensitivity and uncertainty analysis of the effective delayed neutron fraction βeff for critical and subcritical cores of the MYRRHA reactor using the continuous-energy Monte Carlo N-Particle transport code MCNP. The βeff sensitivities are calculated by the modified k-ratio method proposed by Chiba. Comparing the βeff sensitivities obtained with different scaling factors a introduced by Chiba shows that a value of a = 20 is the most suitable for the uncertainty quantification of βeff. Using the calculated βeff sensitivities and the JENDL-4.0u covariance data, the βeff uncertainties for the critical and subcritical cores are determined to be 2.2 ± 0.2% and 2.0 ± 0.2%, respectively, which are dominated by delayed neutron yield of 239Pu and 238U.

scholarly journals Perturbation-Theory-Based Sensitivity and Uncertainty Analysis with CASMO-4

2012 ◽  
Vol 2012 ◽  
pp. 1-11 ◽  
Author(s):  
Maria Pusa
Keyword(s):  
Perturbation Theory ◽  
Uncertainty Analysis ◽  
Adjoint System ◽  
Nuclear Data ◽  
Theoretical Background ◽  
Reactor Physics ◽  
Deterministic Transport ◽  
Practical Guidelines ◽  
Rate Ratios ◽  
Sensitivity And Uncertainty Analysis

The topic of this paper is the development of sensitivity and uncertainty analysis capability to the reactor physics code CASMO-4 in the context of the UAM (Uncertainty Analysis in Best-Estimate Modelling for Design, Operation, and Safety Analysis of LWRs) benchmark. The sensitivity analysis implementation is based on generalized perturbation theory, which enables computing the sensitivity profiles of reaction rate ratios efficiently by solving one generalized adjoint system for each response. Both the theoretical background and the practical guidelines for modifying a deterministic transport code to compute the generalized adjoint solutions and sensitivity coefficients are reviewed. The implementation to CASMO-4 is described in detail. The developed uncertainty analysis methodology is deterministic, meaning that the uncertainties are computed based on the sensitivity profiles and covariance matrices for the uncertain nuclear data parameters. The main conclusions related to the approach used for creating a covariance library compatible with the cross-section libraries of CASMO-4 are presented. Numerical results are given for a lattice physics test problem representing a BWR, and the results are compared to the TSUNAMI-2D sequence in SCALE 6.1.

Improvement of sensitivity and uncertainty analysis capabilities of generalized response in Monte Carlo code RMC

2021 ◽  
Vol 154 ◽  
pp. 108099
Author(s):  
Guanlin Shi ◽  
Yuchuan Guo ◽  
Conglong Jia ◽  
Zhiyuan Feng ◽  
Kan Wang ◽  
...  
Keyword(s):  
Monte Carlo ◽  
Uncertainty Analysis ◽  
Monte Carlo Code ◽  
Sensitivity And Uncertainty Analysis
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