Nuclear Power Plant Monitoring Method by Neural Network and its Application to Actual Nuclear Reactor

1996 ◽  
Vol 11 (4) ◽  
pp. VII
Keyword(s):  
Neural Network ◽  
Power Plant ◽  
Nuclear Power Plant ◽  
Nuclear Power ◽  
Nuclear Reactor ◽  
Monitoring Method ◽  
Plant Monitoring

Real-time Nuclear Power Plant Monitoring with Neural Network

1998 ◽  
Vol 35 (2) ◽  
pp. 93-100 ◽  
Author(s):  
Kunihiko NABESHIMA ◽  
Tomoaki SUZUDO ◽  
Katsuo SUZUKI ◽  
Erdinç TÜRKCAN
Keyword(s):  
Neural Network ◽  
Power Plant ◽  
Nuclear Power Plant ◽  
Real Time ◽  
Nuclear Power ◽  
Plant Monitoring

scholarly journals PARTICLE SWARM OPTIMIZATION BASED PROBABILISTIC NEURAL NETWORK FOR CLASSIFICATION OF SEVERE ACCIDENT OF NUCLEAR REACTOR

2021 ◽  
Vol 23 (3) ◽  
pp. 99
Author(s):  
Yoyok Dwi Setyo Pambudi
Keyword(s):  
Neural Network ◽  
Particle Swarm Optimization ◽  
Power Plant ◽  
Nuclear Power Plant ◽  
Nuclear Power ◽  
Nuclear Reactor ◽  
Probabilistic Neural Network ◽  
Particle Swarm ◽  
Severe Accident ◽  
Swarm Optimization

Due to its danger and complexity, the identification and prediction of major severe accident scenarios from an initiating event of a nuclear power plant remains a challenging task. This paper aims to classify severe accident at the Advanced Power Reactor (APR) 1400, which includes the loss of coolant accidents (LOCA), total loss of feedwater (TLOFW), station blackout (SBO), and steam generator tube rupture (SGTR) using a standard  probabilistic neural network (PNN)  and Particle Swarm Optimization Based Probabilistic Neural Network (PSO PNN). The algorithm has been implemented in MATLAB.  The experiment results showed that supervised PNN PSO could classify severe accident of nuclear power plant better than the standar PNN.

A High Effective Parallel Method for the Coupling Between Neutronics and Thermal-Hydraulic

2016 ◽  
Author(s):  
Xiaomeng Dong ◽  
Zhijian Zhang ◽  
Zhaofei Tian ◽  
Lei Li ◽  
Guangliang Chen
Keyword(s):  
Power Plant ◽  
Nuclear Power Plant ◽  
Nuclear Power ◽  
Large Scale ◽  
Nuclear Reactor ◽  
Reactor Core ◽  
Decisive Role ◽  
Reactor Power ◽  
Coupling Method ◽  
Outlet Temperature

Multi-physics coupling analysis is one of the most important fields among the analysis of nuclear power plant. The basis of multi-physics coupling is the coupling between neutronics and thermal-hydraulic because it plays a decisive role in the computation of reactor power, outlet temperature of the reactor core and pressure of vessel, which determines the economy and security of the nuclear power plant. This paper develops a coupling method which uses OPENFOAM and the REMARK code. OPENFOAM is a 3-dimension CFD open-source code for thermal-hydraulic, and the REMARK code (produced by GSE Systems) is a real-time simulation multi-group core model for neutronics while it solves diffusion equations. Additionally, a coupled computation using these two codes is new and has not been done. The method is tested and verified using data of the QINSHAN Phase II typical nuclear reactor which will have 16 × 121 elements. The coupled code has been modified to adapt unlimited CPUs after parallelization. With the further development and additional testing, this coupling method has the potential to extend to a more large-scale and accurate computation.

scholarly journals Neutronic safety analysis of proposed reactor technologies for Ghana’s nuclear power plant using the MCNP code

2019 ◽  
Vol 34 (3) ◽  
pp. 238-242
Author(s):  
Rex Abrefah ◽  
Prince Atsu ◽  
Robert Sogbadji
Keyword(s):  
High Pressure ◽  
Power Plant ◽  
Nuclear Power Plant ◽  
Nuclear Power ◽  
Nuclear Reactor ◽  
Atomic Energy Commission ◽  
Clean Energy ◽  
Safety Analysis ◽  
Operating Conditions ◽  
The Government

In pursuance of sufficient, stable and clean energy to solve the ever-looming power crisis in Ghana, the Nuclear Power Institute of the Ghana Atomic Energy Commission has on the agenda to advise the government on the nuclear power to include in the country's energy mix. After consideration of several proposed nuclear reactor technologies, the Nuclear Power Institute considered a high pressure reactor or vodo-vodyanoi energetichesky reactor as the nuclear power technologies for Ghana's first nuclear power plant. As part of technology assessments, neutronic safety parameters of both reactors are investigated. The MCNP neutronic code was employed as a computational tool to analyze the reactivity temperature coefficients, moderator void coefficient, criticality and neutron behavior at various operating conditions. The high pressure reactor which is still under construction and theoretical safety analysis, showed good inherent safety features which are comparable to the already existing European pressurized reactor technology.

Study on Sensor with Mechanical Properties in Nuclear Power Plant with Application of BP Neural Network to Fault Tolerant Control

2013 ◽  
Vol 644 ◽  
pp. 56-59
Author(s):  
Jin Yang Li ◽  
Hong Xia ◽  
Shou Yu Cheng
Keyword(s):  
Neural Network ◽  
Mechanical Properties ◽  
Power Plant ◽  
Nuclear Power Plant ◽  
Bp Neural Network ◽  
Nuclear Power ◽  
Control Method ◽  
Fault Tolerant ◽  
Fault Tolerant Control ◽  
Level Sensor

All kinds of sensor with mechanical properties often can go wrong in nuclear power plant. In this kind of situation, it puts forward a kind of active fault tolerant control method based on the improved BP neural network. Firstly, the method will train sensor by BP neural network. Secondly, it will be established dynamic model bank in all kinds of running state. The system will be detected by using BP neural network real time. When the sensor goes wrong, it will be controled by reconstruction. Taking pressurizer water-level sensor as the case, a simulation experiment was performed on the nuclear power plant simulator. The results showed that the proposed method is valid for the fault tolerant control of sensor in nuclear power plant.

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