scholarly journals Advanced Burnup Calculation Code System in a Subcritical State with Continuous-Energy Monte Carlo Code for Fusion-Fission Hybrid Reactor

2009 ◽  
Vol 46 (8) ◽  
pp. 776-786 ◽  
Author(s):  
Masayuki MATSUNAKA ◽  
Masayuki OHTA ◽  
Hiroyuki MIYAMARU ◽  
Isao MURATA
Keyword(s):  
Monte Carlo ◽  
Subcritical State ◽  
Hybrid Reactor ◽  
Monte Carlo Code ◽  
Code System ◽  
Continuous Energy ◽  
Calculation Code ◽  
Burnup Calculation

Validation of a Monte Carlo code system for grid evaluation with interference effect on Rayleigh scattering

2018 ◽  
Vol 63 (3) ◽  
pp. 03NT02 ◽  
Author(s):  
Abel Zhou ◽  
Graeme L White ◽  
Rob Davidson
Keyword(s):  
Monte Carlo ◽  
Interference Effect ◽  
Rayleigh Scattering ◽  
Monte Carlo Code ◽  
Code System

A collision history-based approach to sensitivity/perturbation calculations in the continuous energy Monte Carlo code SERPENT

2015 ◽  
Vol 85 ◽  
pp. 245-258 ◽  
Author(s):  
Manuele Aufiero ◽  
Adrien Bidaud ◽  
Mathieu Hursin ◽  
Jaakko Leppänen ◽  
Giuseppe Palmiotti ◽  
...  
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Code ◽  
Continuous Energy

Calculation of the exposure buildup factors for x-ray photons with continuous energy spectrum using Monte Carlo code

2018 ◽  
Vol 38 (1) ◽  
pp. 207-217 ◽  
Author(s):  
Mustafa Mohammad Rafiei ◽  
Hossein Tavakoli-Anbaran
Keyword(s):  
Monte Carlo ◽  
Energy Spectrum ◽  
Monte Carlo Code ◽  
X Ray ◽  
Continuous Energy ◽  
Continuous Energy Spectrum ◽  
Buildup Factors

Application of continuous-energy Monte Carlo code as a cross-section generator of BWR core calculations

2005 ◽  
Vol 32 (8) ◽  
pp. 857-875 ◽  
Author(s):  
Masayuki Tohjoh ◽  
Masato Watanabe ◽  
Akio Yamamoto
Keyword(s):  
Monte Carlo ◽  
Cross Section ◽  
Monte Carlo Code ◽  
Continuous Energy

scholarly journals Analyses of Assay Data of LWR Spent Nuclear Fuels with a Continuous-Energy Monte Carlo Code MVP and JENDL-4.0 for Inventory Estimation of 79Se, 99Tc, 126Sn and 135Cs

2011 ◽  
Vol 2 (0) ◽  
pp. 369-374 ◽  
Author(s):  
Keisuke OKUMURA ◽  
Shiho ASAI ◽  
Yukiko HANZAWA ◽  
Hideya SUZUKI ◽  
Masaaki TOSHIMITSU ◽  
...  
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Code ◽  
Nuclear Fuels ◽  
Continuous Energy

Adjoint neutron flux estimator implementation and verification in the continuous energy Monte Carlo code MONK

2020 ◽  
Vol 356 ◽  
pp. 110368
Author(s):  
Francesco Tantillo ◽  
Simon Richards
Keyword(s):  
Monte Carlo ◽  
Neutron Flux ◽  
Monte Carlo Code ◽  
Continuous Energy

scholarly journals GENERALIZED SENSITIVITY ANALYSIS CAPABILITY WITH THE DIFFERENTIAL OPERATOR METHOD IN RMC CODE

2021 ◽  
Vol 247 ◽  
pp. 15020
Author(s):  
Guanlin Shi ◽  
Conglong Jia ◽  
Kan Wang ◽  
Quan Cheng
Keyword(s):  
Sensitivity Analysis ◽  
Monte Carlo ◽  
Differential Operator ◽  
Response Function ◽  
Operator Method ◽  
Monte Carlo Code ◽  
Transport Mode ◽  
Continuous Energy ◽  
Relative Standard ◽  
Monte Carlo Transport

Sensitivity analysis is an important way for us to know how the input parameters will affect the output of a system. Therefore, recently, there is an increased interest in developing sensitivity analysis methods in continuous-energy Monte Carlo Code due to the fact that Monte Carlo method can perform high-fidelity simulations of nuclear reactor. Previous studies mainly focused on developing sensitivity analysis method suitable for analyze eigenvalue. There are relatively few researches for performing sensitivity analysis of generalized response function by using continuous-energy Monte Carlo code. So, in this work, the differential operator method (DOM) has been investigated and implemented in continuous-energy Reactor Monte Carlo code (RMC) to perform sensitivity analysis of generalized response function in the form of ratios of reaction rate. The DOM implemented in RMC is based on the analog Monte Carlo transport mode and non-analog Monte Carlo transport mode. The correctness of the newly implemented method has been verified by comparing the results with those calculated by using the collision history-based method through the Jezeble and Flattop benchmark problems. In general, the results given by the DOM agree well with those obtained by the collision history-based method with an accuracy of 5%. Moreover, it is also shown that the non-analog Monte Carlo transport mode can obtain lower relative standard deviation of the sensitivity coefficients than the analog Monte Carlo transport mode.

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