Pressurized Water Reactor Core Parameter Prediction Using an Artificial Neural Network

1993 ◽  
Vol 113 (1) ◽  
pp. 70-76 ◽  
Author(s):  
Han Gon Kim ◽  
Soon Heung Chang ◽  
Byung Ho Lee
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Reactor Core ◽  
Pressurized Water Reactor ◽  
Pressurized Water ◽  
Water Reactor ◽  
Artificial Neural ◽  
Core Parameter ◽  
Parameter Prediction

CFD Analysis of the Coolant Mixing within the Upper Plenum of a Pressurized Water Reactor (PWR)

2013 ◽  
Vol 444-445 ◽  
pp. 411-415 ◽  
Author(s):  
Fu Cheng Zhang ◽  
Shen Gen Tan ◽  
Xun Hao Zheng ◽  
Jun Chen
Keyword(s):  
Temperature Distribution ◽  
Fluid Dynamic ◽  
Characteristic Temperature ◽  
Reactor Core ◽  
Flow Distribution ◽  
Sensitivity Study ◽  
Cfd Model ◽  
Pressurized Water Reactor ◽  
Pressurized Water ◽  
Water Reactor

In this study, a Computational Fluid Dynamic (CFD) model is established to obtain the 3-D flow characteristic, temperature distribution of the pressurized water reactor (PWR) upper plenum and hot-legs. In the CFD model, the flow domain includes the upper plenum, the 61 control rod guide tubes, the 40 support columns, the three hot-legs. The inlet boundary located at the exit of the reactor core and the outlet boundary is set at the hot-leg pipes several meters away from upper plenum. The temperature and flow distribution at the inlet boundary are given by sub-channel codes. The computational mesh used in the present work is polyhedron element and a mesh sensitivity study is performed. The RANS equations for incompressible flow is solved with a Realizable k-ε turbulence model using the commercial CFD code STAR-CCM+. The analysis results show that the flow field of the upper plenum is very complex and the temperature distribution at inlet boundary have significant impact to the coolant mixing in the upper plenum as well as the hot-legs. The detailed coolant mixing patterns are important references to design the reactor core fuel management and the internal structure in upper plenum.

Prediction of safety parameters of pressurized water reactor based on feature fusion neural network

2022 ◽  
Vol 166 ◽  
pp. 108803
Author(s):  
Yinghao Chen ◽  
Dongdong Wang ◽  
Cao Kai ◽  
Cuijie Pan ◽  
Yayun Yu ◽  
...  
Keyword(s):  
Neural Network ◽  
Feature Fusion ◽  
Pressurized Water Reactor ◽  
Pressurized Water ◽  
Water Reactor ◽  
Safety Parameters
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