
arXiv: 2111.15350
We derive a class of equations describing low Reynolds number steady flows of incompressible and viscous fluids in networks made of straight channels, with several sources and sinks, and adaptive conductivities. The flow is controlled by the fluxes at sources and sinks. The network is represented by a graph and the adaptive conductivities describe the transverse channel elasticities, mirroring several network structures found in physics and biology. Minimising the dissipated energy per unit time, we have found an explicit form for the adaptation equations and, asymptotically in time, a steady state tree geometry for the graph connecting sources and sinks is reached. A phase transition tuned by an order parameter for the adapted steady sate graph has been found.
6 pages, 5 figures
biological network, network Hagen-Poiseuille flow, flow flux control, Fluid Dynamics (physics.flu-dyn), FOS: Physical sciences, low Reynolds number incompressible viscous flow, Physics - Fluid Dynamics, Neural networks for/in biological studies, artificial life and related topics, Incompressible viscous fluids, Biological Physics (physics.bio-ph), microchannel flow, Physics - Biological Physics, Flow control and optimization for incompressible viscous fluids
biological network, network Hagen-Poiseuille flow, flow flux control, Fluid Dynamics (physics.flu-dyn), FOS: Physical sciences, low Reynolds number incompressible viscous flow, Physics - Fluid Dynamics, Neural networks for/in biological studies, artificial life and related topics, Incompressible viscous fluids, Biological Physics (physics.bio-ph), microchannel flow, Physics - Biological Physics, Flow control and optimization for incompressible viscous fluids
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 4 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
