Monte Carlo Modeling of the Portuguese Research Reactor Core and Comparison with Experimental Measurements

2003 ◽  
Vol 143 (3) ◽  
pp. 358-363 ◽  
Author(s):  
Ana C. Fernandes ◽  
Isabel C. Gonçalves ◽  
Nuno P. Barradas ◽  
António J. Ramalho
Keyword(s):  
Monte Carlo ◽  
Research Reactor ◽  
Reactor Core ◽  
Experimental Measurements ◽  
Monte Carlo Modeling

Validation of the Monte Carlo Model of the Greek Research Reactor Core

2010 ◽  
Vol 170 (3) ◽  
pp. 460-464 ◽  
Author(s):  
D. Kontogeorgakos ◽  
I. E. Stamatelatos
Keyword(s):  
Monte Carlo ◽  
Research Reactor ◽  
Monte Carlo Model ◽  
Reactor Core

Monte Carlo Modeling of the Texas A&M University Research Reactor

2004 ◽  
Vol 145 (1) ◽  
pp. 1-10 ◽  
Author(s):  
Chan-Hyeong Kim ◽  
Siyoung Jang ◽  
Warren Dan Reece
Keyword(s):  
Monte Carlo ◽  
Research Reactor ◽  
University Research ◽  
Monte Carlo Modeling

A Neutron Transport Calculation Method for Deep Penetration and its Preliminary Verification

2018 ◽  
Author(s):  
Wankui Yang ◽  
Baoxin Yuan ◽  
Songbao Zhang ◽  
Haibing Guo ◽  
Yaoguang Liu ◽  
...  
Keyword(s):  
Monte Carlo ◽  
Research Reactor ◽  
Neutron Transport ◽  
Reactor Core ◽  
Deep Penetration ◽  
Monte Carlo Code ◽  
Deterministic Theory ◽  
Continuous Energy ◽  
Transport Calculation ◽  
Good Agreement

Deep penetration problems exist widely in reactor applications, such as SPRR300 (Swimming Pool Research Reactor 300), a light water moderated, enriched uranium fueled research reactor in China. Deterministic transport theory is intrinsically suitable for deep penetration. But there exist some problems when it’s applied in SPRR-300research reactors. First, the reactor core is complicated for geometry description in deterministic theory codes. Monte Carlo method has advantages in complex geometry modeling. And it uses continuous energy cross sections which are independent with specific reactor types and research objections. But usually it’s difficult to converge well enough to deal with deep penetration problems, even though there are a number of variance reduction techniques. Based on the advantages and disadvantages of Monte Carlo and Deterministic method, we proposed a coupled neutron transport calculation method for deep penetration. It combines advantages of these two methods. Firstly, we use Monte Carlo code to finish fine modeling and do the whole reactor core calculation. Domestically developed Monte Carlo code JMCT is used to do the neutron transport calculation. Then homogenized group constants in each mesh are calculated from JMCT output by a self-developed script. Afterwards, we do the whole reactor calculation with deterministic theory code TORT. It directly uses group constants generated by Monte Carlo code. Finally, we can get the deep penetration calculation results from TORT output. Verification is carried out by comparing the group constants of benchmark problem, and by comparing keff calculated by this method with continuous energy Monte Carlo method. Benchmark calculation is conducted with OECD/NEA slab benchmark problem. The comparison shows that group constants generated by this study are in good agreement with results from published references. Then above group constants are applied to 3-dimensional discrete ordinates deterministic theory transport code TORT. But keff calculated by TORT is a little lower than that calculated by Monte Carlo code JMCT. To minimize other influence factors, different Sn/Pn order, and different mesh size in TORT has been tried. Unfortunately the keff difference between these two methods remains. Even though the keff results in this benchmark are less than keff calculated by continuous energy MC method, Benchmark results show that all the group constants generated by this method are in good agreement with existing references. So it can be expected that after further verification and validation, this coupled method can be effectively applied to the deep penetration problem in such kind of research reactors.

Monte Carlo modeling of the Pakistan Research Reactor-1 (PARR-1)

2016 ◽  
Vol 87 ◽  
pp. 584-590 ◽  
Author(s):  
M. Rizwan Ali ◽  
R. Khan ◽  
K.S. Chaudri ◽  
T. Stummer
Keyword(s):  
Monte Carlo ◽  
Research Reactor ◽  
Monte Carlo Modeling

Genetic-based Monte Carlo Modeling of geothermal prospects: Indian examples

2021 ◽  
Author(s):  
Anirbid Sircar ◽  
Kriti Yadav ◽  
Kamakshi Rayavarapu ◽  
Namrata Bist
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Modeling
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