基于多块动态混合网格的AUV自航类物理数值模拟
Physics-based Numerical Simulation of AUV Self-propulsion Using Multi-block Hybrid Dynamic Mesh Method
查看参考文献16篇
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文摘
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提出了一种采用多块动态混合网格进行AUV(自主水下机器人)自航试验的类物理数值模拟的方法.对AUV带舵翼和螺旋桨的全附体进行建模,采用UDF(用户自定义函数)实现推进器和AUV之间的力和速度传递,结合6DOF(自由度)运动方程求解AUV的运动参数,采用动态层方法进行网格更新,最终实现AUV从静止到匀速的直航运动的自航推进数值模拟.相对MFR(多参考系坐标)法,自航速度误差为2.6%,伴流分数误差为3.7%,推力减额误差为6.8%.与非结构动网格法和重叠网格法相比,该方法的计算收敛快.同时,数值模拟获得了AUV自航推进过程中的速度曲线,推力和阻力变化曲线,自航推进的尾迹和压力云图,以及相应的动画,揭示了自航推进过程中船、桨、舵相互作用的内在机理,为进行更复杂的载体操纵运动提供类物理数值模拟方法. |
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其他语种文摘
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A multi-block hybrid dynamic mesh method for physics-based numerical simulation of AUV (autonomous underwater vehicle) self-propulsion motion is presented. The method models a fully appended AUV with rudders and propeller, uses UDF (user defined function) to transmit force and velocity between AUV and its propeller, adopts 6DOF (degree of freedom) motion equations to solve the motion parameters, and employs the dynamic layer method to update meshes. Finally, the numerical simulation of AUV self-propulsion motion is achieved which models the straight ahead run from the static state to the uniform velocity. The differences of the self-propulsion velocity, the wake fraction and the thrust deduction factor compared with MFR (multiple frames of reference) are 2.6%, 3.7%, and 6.8%, respectively. And the computation convergence is speeded up compared with the unstructured dynamic mesh method and the dynamic overset mesh method. By numerical simulation, the velocity curve, curves of thrust and resistance, contours of wake velocity and pressure, and related animations during AUV self-propulsion are obtained. The physical reasons of interaction among the hull, the propeller and the rudders are investigated, which provides a physics-based numerical simulation method for more complex maneuvering motions of marine vehicles. |
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来源
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机器人
,2019,41(6):706-712 【核心库】
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DOI
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10.13973/j.cnki.robot.180683
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关键词
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自主水下机器人
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自航推进
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动网格
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螺旋桨
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类物理数值模拟
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地址
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1.
大连海事大学船舶与海洋工程学院, 辽宁, 大连, 116026
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中国科学院沈阳自动化研究所, 机器人学国家重点实验室, 辽宁, 沈阳, 110016
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语种
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中文 |
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文献类型
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研究性论文 |
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ISSN
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1002-0446 |
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学科
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自动化技术、计算机技术 |
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基金
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中国科学院沈阳自动化研究所机器人学重点实验室基金
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国家重点研发计划
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中央高校基本科研业务费专项资金
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国家自然科学基金
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文献收藏号
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CSCD:6625902
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