Yunlei Mei , Fengmei Jing , Xinru Wang , Bin Guo , Song Wang , Qiang Lu
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引用次数: 0
Abstract
This paper constructs a multi-objective optimization design method for ducted turbines by combining Computational Fluid Dynamics with Response Surface Methodology and NSGA-II algorithm. The optimization objectives is to achieve the maximum power coefficient. The design variables include the duct angle, duct length, tip clearance, and rotor axial position. Firstly, a simulation model of the ducted turbine was established and validated through experimental data from a towing tank. Secondly, a regression equation between the duct structure design variables and the optimization objectives was constructed using response surface methodology. Finally, the NSGA-II algorithm was employed to optimize the objectives, and the hydrodynamic and flow field characteristics of the ducted turbine were analyzed. The results indicate that the maximum CP value of the ducted turbine reached 0.791, representing a 104.9% increase compared to the open turbine. In addition, the kinetic energy of the wake of the ducted turbine is lower, and its near-field wake velocity deficit is 44.05% higher than that of the open turbine. Due to the interaction between the duct-shedding vortex and the blade tip vortex, the diffusion range of the ducted turbine wake is broader, and the wake recovery is faster. At the downstream 7D, the degree of wake recovery is basically consistent with that of the open turbine. Finally, the duct alters the operating conditions of the blades. In the future, the blades can be optimized based on the radial flow distribution within the duct, which will further enhance the output power.
期刊介绍:
The journal Energy Conversion and Management provides a forum for publishing original contributions and comprehensive technical review articles of interdisciplinary and original research on all important energy topics.
The topics considered include energy generation, utilization, conversion, storage, transmission, conservation, management and sustainability. These topics typically involve various types of energy such as mechanical, thermal, nuclear, chemical, electromagnetic, magnetic and electric. These energy types cover all known energy resources, including renewable resources (e.g., solar, bio, hydro, wind, geothermal and ocean energy), fossil fuels and nuclear resources.