scholarly journals Improvement of solar flat‐plate collector performance by optimum tilt angle and minimizing top heat loss coefficient using particle swarm optimization

2020 ◽  
Vol 8 (8) ◽  
pp. 2771-2783 ◽  
Author(s):  
Fathollah Pourfayaz ◽  
Reza Shirmohammadi ◽  
Akbar Maleki ◽  
Alibakhsh Kasaeian
Keyword(s):  
Particle Swarm Optimization ◽  
Flat Plate ◽  
Heat Loss ◽  
Tilt Angle ◽  
Particle Swarm ◽  
Loss Coefficient ◽  
Swarm Optimization ◽  
Flat Plate Collector

Optimization of Tandem Blade Based on Improved Particle Swarm Algorithm

2016 ◽  
Author(s):  
Song Zhaoyun ◽  
Bo Liu ◽  
Mao Xiaochen ◽  
Lu Xiaofeng
Keyword(s):  
Particle Swarm Optimization ◽  
Pressure Loss ◽  
Total Pressure ◽  
Particle Swarm ◽  
Loss Coefficient ◽  
Total Pressure Loss ◽  
Swarm Optimization ◽  
Improved Particle Swarm Optimization ◽  
Pressure Loss Coefficient ◽  
Total Pressure Loss Coefficient

To improve the design quality of high-turning tandem blade, a coupling optimization system for the shape and relative position of tandem blades was developed based on an improved particle swarm optimization algorithm and NURBS parameterization. First of all, to increase convergence speed and avoid local optima of particle swarm optimization (PSO), an improved particle swarm optimization (IPSO) is formulated based on adaptive selection of particle roles, adaptive control of parameters and population diversity control. Then experiments are carried out using test functions to illustrate the performance of IPSO and to compare IPSO with some PSOs. The comparison indicates IPSO can obtain excellent convergence speed and simultaneously keep the best reliability. In addition, the coupling optimization system is validated by optimizing a large-turning tandem blade. Optimization results illustrate IPSO can obviously increase the optimization speed and reduce the time and cost of optimization. After optimization, at design condition, the total pressure loss coefficient of the optimized blade is decreased by 40.4%, and the static pressure ratio of optimized blade is higher and the total pressure loss coefficient is smaller at all incidence angles. In addition, properly reducing the gap area of tandem blade can effectively reduce the friction loss of the blade boundary layer and the mixing loss created by mixing the gap fluid and the mainstream fluid.

Determination of Losses & Loss Coefficients of Solar Flat Plate Collector when Wind Velocity & Tilt Angle at Zero Value – An Experimental Study

2013 ◽  
Vol 376 ◽  
pp. 294-298
Author(s):  
M.K. Bhatt ◽  
B.M. Sutaria ◽  
S.N. Gaderia ◽  
S.A. Channiwala
Keyword(s):  
Experimental Study ◽  
Solar Energy ◽  
Flat Plate ◽  
Heat Loss ◽  
Tilt Angle ◽  
Major Part ◽  
Energy Measurement ◽  
Loss Coefficients ◽  
Flat Plate Collector

The flat plate collector is one of the most widely used device for harnessing solar energy. Measurement of various losses occurring in a flat plate collector is important for design as well as evaluation for efficiency under different conditions. The major part of overall heat loss is the top heat loss. The various losses such as bottom loss, side loss, edge loss, corner loss, sealing loss & top loss etc, are measured as well as recorded. There are forty eight thermocouples located at different points.

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.

Sistem Kontrol Optimal Fuzzy-Particle Swarm Optimization

2018 ◽  
Vol 9 (1) ◽  
pp. 1-5
Author(s):  
Fachrudin Hunaini ◽  
Imam Robandi ◽  
Nyoman Sutantra
Keyword(s):  
Fuzzy Logic ◽  
Particle Swarm Optimization ◽  
Control System ◽  
Membership Function ◽  
Fuzzy Logic Control ◽  
Particle Swarm ◽  
Optimization Method ◽  
Swarm Optimization ◽  
Motion Error ◽  
Logic Control

Fuzzy Logic Control (FLC) is a reliable control system for controlling nonlinear systems, but to obtain optimal fuzzy logic control results, optimal Membership Function parameters are needed. Therefore in this paper Particle Swarm Optimization (PSO) is used as a fast and accurate optimization method to determine Membership Function parameters. The optimal control system simulation is carried out on the automatic steering system of the vehicle model and the results obtained are the vehicle's lateral motion error can be minimized so that the movement of the vehicle can always be maintained on the expected trajectory

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