SFMC23

On the stability of wall-bounded flows at high-pressure transcritical fluid conditions

  • Bernades, Marc (Universitat Politècnica de Catalunya)
  • Capuano, Francesco (Universitat Politècnica de Catalunya)
  • Jofre, Lluís (Universitat Politècnica de Catalunya)

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High-pressure transcritical fluids operate within ther- modynamic spaces in which supercritical gas-like and liquid-like states can be differentiated across the pseudo-boiling line (Jofre & Urzay , 2020, 2021). As studied by Bernades & Jofre (2022), the thermophys- ical properties of these two regimes in the vicinity of the pseudoboiling region can be leveraged to signif- icantly increase the Reynolds numbers with respect to atmospheric conditions. Among other fields, this result is notably important in microfluidics as it may enable the achievement of microconfined turbulence to obtain enhanced mixing and heat transfer rates. In this regard, the recent direct numerical sim- ulations (DNS) performed by Bernades et al. (2022, 2023) demonstrate the feasibility of achiev- ing microconfined turbulence by means of utilizing high-pressure transcritical fluids. The resulting flow physics differ significantly from the typical behavior of turbulent wall-bounded flows, which is altered by the presence of localized baroclinic torques responsi- ble for remarkably increasing flow rotation. As a re- sult, the flow becomes unstable and rotation is trans- formed into a wide range of scales (i.e., turbulent flow motions) through vortex stretching mechanisms. However, the phenomena responsible for destabiliz- ing the flow are still not fully characterized. To that end, this work aims to conduct linear stability analy- sis of wall-bounded flows at high-pressure transcriti- cal fluid conditions to carefully identify and quantify the underlying flow mechanisms. In this regard, Ren et al. (2019) have recently developed a linear sta- bility analysis framework for highly non-ideal fluids from which this work will initially feed. In particular, focus will be placed on analyzing the principal modes for different values of the dimensionless numbers, and subsequently compare results to DNS data.