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Citation:
　Hanyang Gong,Ruhua Yuan,Xiaodong Xing,et al.Optimized Design for the Plow of a Submarine Plowing Trencher[J].Journal of Marine Science and Application,2013,(1):98-105.[doi:10.1007/s11804-013-1170-0]
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Optimized Design for the Plow of a Submarine Plowing Trencher

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Title:
Optimized Design for the Plow of a Submarine Plowing Trencher
Author(s):
Hanyang Gong;  Ruhua Yuan;  Xiaodong Xing;  Liquan Wang;  Zhipeng Wang and Haixia Gong
Affilations:
Author(s):
Hanyang Gong;  Ruhua Yuan;  Xiaodong Xing;  Liquan Wang;  Zhipeng Wang and Haixia Gong
1. College of Mechanical and Electrical Engineering, Harbin Engineering University, Harbin 150001, China 2. China Offshore Oil Engineering Co. Ltd., Tianjin 300000, China
Keywords:
submarine plowing trencher;  moldboard surface;  plow surface optimized design;  multi-objective genetic algorithm;  surface smoothness
分类号:
-
DOI:
10.1007/s11804-013-1170-0
Abstract:
The plow of the submarine plowing trencher is one of the main functional mechanisms, and its optimization is very important. The design parameters play a very significant role in determining the requirements of the towing force of a vessel. A multi-objective genetic algorithm based on analytical models of the plow surface has been examined and applied in efforts to obtain optimal design of the plow. For a specific soil condition, the draft force and moldboard surface area which are the key parameters in the working process of the plow are optimized by finding the corresponding optimal values of the plow blade penetration angle and two surface angles of the main cutting blade of the plow. Parameters such as the moldboard side angle of deviation, moldboard lift angle, angular variation of the tangent line, and the spanning length are also analyzed with respect to the force of the moldboard surface along soil flow direction. Results show that the optimized plow has an improved plow performance. The draft forces of the main cutting blade and the moldboard are 10.6% and 7%, respectively, less than the original design. The standard deviation of Gaussian curvature of moldboard is lowered by 64.5%, which implies that the smoothness of the optimized moldboard surface is much greater than the original.

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Memo

Memo:
Supported the National Natural Science Foundation of China (No. 51179040) and Natural Science Foundation of Heilongjiang Province (No. E200904).
Last Update: 2013-03-14