Parametric study and Multi-Objective optimization of a ductless Archimedes screw hydrokinetic Turbine: Experimental and numerical investigation

•A ductless Archimedes screw turbine is proposed for low-speed current application.•The number of turns plays a dominant role in improving the power coefficient.•The lead angle predominates in optimizing the static torque coefficient.•Multi-objective optimization was performed by applying the Geneti...

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Veröffentlicht in:Energy conversion and management Jg. 273; S. 116423
Hauptverfasser: Zhang, Dayu, Guo, Penghua, Hu, Qiao, Li, Jingyin
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Elsevier Ltd 01.12.2022
Schlagworte:
administrative management
algorithms
energy conversion
hydraulic flumes
hydrodynamics
Hydrokinetic turbine
lead
Low current speed
Optimization
Startup performance
torque
Hydrokinetic turbine
Startup performance
Low current speed
Optimization
ISSN:0196-8904, 1879-2227
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Zusammenfassung:•A ductless Archimedes screw turbine is proposed for low-speed current application.•The number of turns plays a dominant role in improving the power coefficient.•The lead angle predominates in optimizing the static torque coefficient.•Multi-objective optimization was performed by applying the Genetic Algorithm. Aiming to prolong the duration of detection equipment deployed in deep water, a new type of hydrokinetic turbine with good self-starting ability should be developed to harness low-speed current energy in such deep-water scenarios. In this study, a novel ductless Archimedes screw turbine is proposed to improve the system’s startup performance for low-speed current applications. An experimentally verified numerical method was used to investigate the parametric sensitivity of several key geometrical parameters. Strong interaction effects between the lead angle and number of turns were observed. The turbine performance enhancement by increasing the number of turns can only be achieved at a large lead angle. A tradeoff between the lead angle and number of turns is necessary for the optimization design of the ductless Archimedes screw turbine. Multi-objective optimization was performed on the ductless Archimedes screw turbine to improve its self-starting ability and power coefficient by using the central composite design, the radial basis function neural network, and the non-dominated sorting genetic algorithm. Water flume experiment results showed that the maximum power coefficient and static torque coefficient of the optimized ductless Archimedes screw turbine can be improved by 36.7% and 143%, respectively, with respect to the initial design. These results indicate ductless Archimedes screw turbines are suitable for low-speed current applications in deep water.
Bibliographie:ObjectType-Article-1
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ISSN:0196-8904
1879-2227
DOI:10.1016/j.enconman.2022.116423