Twin vortex computer in fluid flow

Abstract

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 Kármán 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.