scholarly journals Nuclear Power Plant Construction Scheduling Problem with Time Restrictions: A Particle Swarm Optimization Approach

2016 ◽  
Vol 2016 ◽  
pp. 1-9 ◽  
Author(s):  
Shang-Kuan Chen ◽  
Yen-Wu Ti ◽  
Kuo-Yu Tsai

In nuclear power plant construction scheduling, a project is generally defined by its dependent preparation time, the time required for construction, and its reactor installation time. The issues of multiple construction teams and multiple reactor installation teams are considered. In this paper, a hierarchical particle swarm optimization algorithm is proposed to solve the nuclear power plant construction scheduling problem and minimize the occurrence of projects failing to achieve deliverables within applicable due times and deadlines.

2021 ◽  
Vol 23 (3) ◽  
pp. 99
Author(s):  
Yoyok Dwi Setyo Pambudi

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.


2011 ◽  
Vol 486 ◽  
pp. 41-44 ◽  
Author(s):  
Yu Qing Xu ◽  
Zhi Yang

The design criteria, operational frequency, operational order and compatibility are proposed and analyzed for nuclear power plant main control room. A layout optimization mathematic model is created based on these rules. Objective function of the mathematic model is developed, in which the distance of hands’ moving is added in order to measure the workload of operators. An example of 12 components on panel is implemented by particle swarm optimization.


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