Particle Swarm Optimization applied to the nuclear reload problem of a Pressurized Water Reactor

2009 ◽  
Vol 51 (2) ◽  
pp. 319-326 ◽  
Author(s):  
Anderson Alvarenga de Moura Meneses ◽  
Marcelo Dornellas Machado ◽  
Roberto Schirru
Keyword(s):  
Particle Swarm Optimization ◽  
Particle Swarm ◽  
Pressurized Water Reactor ◽  
Pressurized Water ◽  
Swarm Optimization ◽  
Water Reactor

scholarly journals Numerical Modeling and Hydraulic Optimization of a Surge Tank Using Particle Swarm Optimization

Water ◽  
2019 ◽  
Vol 11 (4) ◽  
pp. 715 ◽  
Author(s):  
Khem Prasad Bhattarai ◽  
Jianxu Zhou ◽  
Sunit Palikhe ◽  
Kamal Prasad Pandey ◽  
Naresh Suwal
Keyword(s):  
Particle Swarm Optimization ◽  
Particle Swarm ◽  
Pressure Head ◽  
Transient Behavior ◽  
Maximum Pressure ◽  
Surge Tank ◽  
Hydraulic Transients ◽  
Pressurized Water ◽  
Swarm Optimization ◽  
Prime Concern

In a pressurized water conveyance system, such as a hydropower system, during hydraulic transients, maximum and minimum pressures at various controlling sections are of prime concern for designing a safe and efficient surge tank. Similarly, quick damping of surge waves is also very helpful for the sound functioning of the hydro-mechanical system. Several parameters like diameter of the surge tank, diameter of the orifice, operating discharge, working head, etc., influence the maximum/minimum surge, damping of surge waves in the surge tank, and the difference of maximum pressure head at the bottom tunnel and maximum water level in the surge tank. These transient behaviors are highly conflicting in nature, especially for different diameters of orifices (DO) and diameters of surge tanks (DS). Hence, a proper optimization method is necessary to investigate the best values of DO and DS to enhance the safety and efficiency of the surge tank. In this paper, these variables are accurately determined through numerical analysis of the system by the Method of Characteristics (MOC). Furthermore, the influence on the transient behavior with changing DO and DS is investigated and finally, optimum values of DO and DS are determined using Particle Swarm Optimization (PSO) to minimize the effects of hydraulic transients on the system without compromising the stability and efficiency of the surge tank. The obtained results show significant improvements over the contemporary methods of finding DO and DS for surge tank design.

Smart teaching mode based on particle swarm image recognition and human-computer interaction deep learning

2020 ◽  
Vol 39 (4) ◽  
pp. 5699-5711
Author(s):  
Shirong Long ◽  
Xuekong Zhao
Keyword(s):  
Feature Extraction ◽  
Particle Swarm Optimization ◽  
Deep Learning ◽  
Real Time ◽  
Image Recognition ◽  
Particle Swarm ◽  
Learning Technology ◽  
Search Performance ◽  
Swarm Optimization ◽  
Teaching Mode

The smart teaching mode overcomes the shortcomings of traditional teaching online and offline, but there are certain deficiencies in the real-time feature extraction of teachers and students. In view of this, this study uses the particle swarm image recognition and deep learning technology to process the intelligent classroom video teaching image and extracts the classroom task features in real time and sends them to the teacher. In order to overcome the shortcomings of the premature convergence of the standard particle swarm optimization algorithm, an improved strategy for multiple particle swarm optimization algorithms is proposed. In order to improve the premature problem in the search performance algorithm of PSO algorithm, this paper combines the algorithm with the useful attributes of other algorithms to improve the particle diversity in the algorithm, enhance the global search ability of the particle, and achieve effective feature extraction. The research indicates that the method proposed in this paper has certain practical effects and can provide theoretical reference for subsequent related research.

Sign in / Sign up

Export Citation Format

Share Document