Twin vortex computer in fluid flow
Twin vortex computer in fluid flow
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DOI：
10.1088/1367-2630/ac024d
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发表时间：
2021-06-01
影响因子：
3.3
通讯作者：
Notsu, Hirofumi
中科院分区：
文献类型：
--
作者：
Goto, Ken;Nakajima, Kohei;Notsu, Hirofumi
流体普遍存在于自然界和技术中。在许多类型的流体流动中，众所周知的是旋涡脱落，其发生在流体流过海崖体时。随着雷诺数的增加，可以在这种流动中发现不同类型的涡。在这项研究中，我们发现，这些旋涡可以用于进行某些类型的计算。从计算流体动力学模拟的结果表明，最佳的计算性能达到临界雷诺数附近，在那里的流动表现出一个双涡开始之前的卡门涡脱落与霍普夫分叉。结果表明，随着雷诺数的增加，双涡运动的输入灵敏度也随之增加，表明了系统内部的信息处理方式。我们的发现为理解流体动力学与其计算能力之间的关系铺平了一条新的道路。
Fluids exist universally in nature and technology. Among the many types of fluid flows is the well-known vortex shedding, which takes place when a fluid flows past a bluff body. Diverse types of vortices can be found in this flow as the Reynolds number increases. In this study, we reveal that these vortices can be employed for conducting certain types of computation. The results from computational fluid dynamics simulations showed that optimal computational performance is achieved near the critical Reynolds number, where the flow exhibits a twin vortex before the onset of the Karman vortex shedding associated with the Hopf bifurcation. It is revealed that as the Reynolds number increases toward the bifurcation point, the input sensitivity of the twin vortex motion also increases, suggesting the modality of information processing within the system. Our finding paves a novel path to understand the relationship between fluid dynamics and its computational capability.