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  • 标题:Optimization of thrust propeller design for an ROV (Remotely Operated Vehicle) consideration by Genetic Algorithms
  • 本地全文:下载
  • 作者:Aldias Bahatmaka ; Dong-Joon Kim ; Deddy Chrismianto
  • 期刊名称:MATEC Web of Conferences
  • 电子版ISSN:2261-236X
  • 出版年度:2017
  • 卷号:138
  • 页码:1-8
  • DOI:10.1051/matecconf/201713807003
  • 语种:English
  • 出版社:EDP Sciences
  • 摘要:Remotely Operated Vehicle (ROV) is one of the technology that can facilitate for observing and exploring the underwater condition (sea). The design and manufacturing process of underwater robots needs many support and increase the performance of the underwater robot to do some missions. Thruster is one of main component which has function as an actuator during the operation. In the present study, propeller design the most important for solving the problem of an ROV. For the optimization of thrust, Genetic Algorithms (GA) can powerfully search for parameters in large multidimensional design space. Thus, the principle can be applied for determining the initial dimension of the propeller for producing optimum thrust of ROV. GA was successfully shown able to obtain an optimal set of parameters leading to propeller characteristics and best performances.
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