Impact of Bifurcation Angle and Inlet Reynolds Number on Local Pressure Recovery in Biologically-Inspired Flow Networks

Abstract

This work computationally investigates local flow behavior in tree-like flow networks of varying scale, bifurcation angle, and inlet Reynolds number. The performance of the tree-like flow networks were evaluated based on pressure drop and wall temperature distributions. Microscale, mesoscale, and macroscale tree-like flow networks, composed of a range of symmetric bifurcation angles (15, 30, 45, 60, 75, and 90°) and subject to a range of inlet Reynolds numbers (1000, 2000, 4000, 10000, and 20000) were evaluated. Local pressure recoveries were evident at bifurcations, regardless of scale and bifurcation angle which may result in a lower total pressure drop when compared with traditional parallel channel networks. Similarly, wall temperature spikes were also present immediately following bifurcations due to flow separation and recirculation. The magnitude of the wall temperature increases at bifurcations was dependent upon both bifurcation angle and scale. When compared with mesoscale and macroscale flow networks, microscale flow networks resulted in the largest local pressure recoveries and the smallest temperature jumps at bifurcations. Thus, while biologically-inspired flow networks offer the same advantages at all scales, the greatest performance increases are achieved at microscale.

Frequency Response and Transfer Functions of Large Self-similar Networks

“…For natural networks, a thermal conductivity model of biological tissue which includes the effects of the vascular network's geometry and the blood flow's convection is proposed in [12]. The effects on flow behavior brought by changing the geometry and the operating condition of biologically inspired networks are studied in [10]. For robotic swarms, an approach to adapt their aggregation behavior to the variations in the swarm density and the external environment is present in [23].…”