A large eddy simulation of flows around an underwater vehicle model using an immersed boundary method
A large eddy simulation of flows around an underwater vehicle model using an immersed boundary method
复制标题
使用浸入边界法对水下航行体模型周围流动的大涡模拟
DOI：
10.1016/j.taml.2016.11.004
复制
发表时间：
2016-11
影响因子：
3.4
通讯作者：
Guowei He
中科院分区：
文献类型：
--
作者：
Shizhao Wang;Beiji Shi;Yuhang Li;Guowei He
对中等雷诺数的水下航行器模型的绕流进行了大涡模拟。水下航行器模型采用带全附体的DARPA SUBOFF，基于船体长度的雷诺数为1.0×105。采用基于移动最小二乘重构的浸没边界方法处理复杂的几何边界。采用自适应网格加密技术对船体附近的流动进行求解。在单元数从5000万到32亿的网格上对流动求解器的并行可伸缩性进行了测试。对于水下航行器模型周围的流动，并行求解器达到了近线性的可伸缩性。模拟结果较好地反映了船体附近和尾流中涡系结构的基本特征。由大涡模拟得到的时均压力系数和流向速度分布均与附加轴对称物体的流动特征相一致。程序的效率和对流动特征的正确预测使我们能够对数万个岩心和数十亿个网格点进行全尺度模拟，以获得较高雷诺数的水下机器人绕流。
A large eddy simulation (LES) of the flows around an underwater vehicle model at intermediate Reynolds numbers is performed. The underwater vehicle model is taken as the DARPA SUBOFF with full appendages, where the Reynolds number based on the hull length is 1.0× 10 5. An immersed boundary method based on the moving-least-squares reconstruction is used to handle the complex geometric boundaries. The adaptive mesh refinement is utilized to resolve the flows near the hull. The parallel scalabilities of the flow solver are tested on meshes with the number of cells varying from 50 million to 3.2 billion. The parallel solver reaches nearly linear scalability for the flows around the underwater vehicle model. The present simulation captures the essential features of the vortex structures near the hull and in the wake. Both of the time-averaged pressure coefficients and streamwise velocity profiles obtained from the LES are consistent with the characteristics of the flows pass an appended axisymmetric body. The code efficiency and its correct predictions on flow features allow us to perform the full-scale simulations on tens of thousands of cores with billions of grid points for higher-Reynolds-number flows around the underwater vehicles.
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影响因子：
3.7
作者：
J. Jiménez;M. Hultmark;A. Smits
通讯作者：
J. Jiménez;M. Hultmark;A. Smits
影响因子：
4.6
作者：
P. B. Johansson;W. George;M. Gourlay
通讯作者：
P. B. Johansson;W. George;M. Gourlay
DOI：
10.1080/10618562.2014.1002484
发表时间：
2015-01
影响因子：
1.3
作者：
Chao Yan;Weixi Huang;G. Cui;Chunxiao Xu;Zhao-shun Zhang
通讯作者：
Chao Yan;Weixi Huang;G. Cui;Chunxiao Xu;Zhao-shun Zhang
影响因子：
2
作者：
J. Jiménez;R. Reynolds;A. Smits
通讯作者：
J. Jiménez;R. Reynolds;A. Smits
影响因子：
5
作者：
Xiao-cui Wu;Yiwei Wang;Chenguang Huang;Zhiqiang Hu;Rui-wen Yi
通讯作者：
Xiao-cui Wu;Yiwei Wang;Chenguang Huang;Zhiqiang Hu;Rui-wen Yi