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Optimized Design for the Plow of a Submarine Plowing Trencher 被引量:1
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作者 Hanyang Gong Ruhua Yuan +3 位作者 Xiaodong Xing Liquan Wang Zhipeng Wang Haixia Gong 《Journal of Marine Science and Application》 2013年第1期98-105,共8页
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 to... 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. 展开更多
关键词 submarine plowing trencher moldboard surface plow surface optimized design multi-objective genetic algorithm surface smoothness
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Combined Size and Shape Optimization of Structures with DOE,RSM and GA 被引量:1
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作者 Jie Song Hongliang Hua +2 位作者 Zhenqiang Liao Tao Wang Ming Qiu 《Journal of Beijing Institute of Technology》 EI CAS 2018年第2期267-275,共9页
In this paper,size and shape optimization problem of a machine gun system is addressed with an efficient hybrid method,in which a novel and flexible mesh morphing technique is employed to achieve fast parameterization... In this paper,size and shape optimization problem of a machine gun system is addressed with an efficient hybrid method,in which a novel and flexible mesh morphing technique is employed to achieve fast parameterization and modification of complexity structure without going back to CAD for reconstruction of geometric models or to finite element analysis( FEA) for remodeling. Design of experiments( DOE) and response surface method( RSM) are applied to approximate the constitutive parameters of a machine gun system based on experimental tests. Further FEA,secondary development technique and genetic algorithm( GA) are introduced to find all the optimal solutions in one go and the optimal design of the demonstrated machine gun system is obtained. Results of the rigid-flexible coupling dynamic analysis and exterior ballistics calculation validate the proposed methodology,which is relatively time-saving,reliable and has the potential to solve similar problems. 展开更多
关键词 finite element method(FEA) shape optimization mesh morphing response surface method(RSM) design of experiments(DOE) rigid-flexible coupling machine gun system
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