Microconfined High-Pressure Transcritical Channel Flow Database: Laminar, Transitional & Turbulent Regimes

Abstract

The potential of comprehending and managing microscale flows to enhance energy processes, especially in heat transfer and propulsion applications, remains largely untapped particularly for supercritical fluids, which have gained increased interest over the past years due to the higher power and thermodynamic efficiencies they provide. This work, therefore, presents the first comprehensive, open-source dataset carefully curated and structured for studying microconfined high-pressure transcritical fluid channel flows under various regimes. Particularly, the dataset contains 18 direct numerical simulations of carbon dioxide at different bulk pressures and velocities confined between differentially-heated walls. For all cases, the thermodynamic conditions selected impose the fluid to undergo a transcritical trajectory across the pseudo-boiling region. The data collection comprises an array of physical quantities that enable comprehensive parametric analyses spanning laminar, transitional, and turbulent flow regimes. This data repository is poised to provide access to the detailed study and modeling of the complex flow physics observed in high-pressure transcritical fluids, especially those closely linked to improving microfluidics performance.

Fig. 1

Schematic of a microconfined channel flow domain with cold (cw) and hot (hw) isothermal walls. The illustration also shows the domain dimensions and the mean flow direction.

Fig. 2

Snapshots of instantaneous streamwise velocity in wall units μ⁺ on a $z/\delta$-$y/\delta$ slice for the 18 cases.

Fig. 3

Comparison between NIST data and RHEA results of density normalized by critical density $\rho /{\rho }_c$ (a) and dynamic viscosity normalized by critical dynamic viscosity $\mu /{\mu }_c$ (b) for CO₂ at $P/P_c=2$ in the range $T/T_c\approx 0.8-1.6$.

Fig. 4

Local mesh resolution in the three directions $\mathrm{\Delta }{x}_i$ normalized by mean Kolmogorov ${\overline{\eta }}_u$ (a) and Batchelor ${\overline{\eta }}_{\theta }$ (b) scales along the wall-normal direction $y/\delta$.

Fig. 5

Schematic of a microconfined channel flow mesh domain with detail of the spatial discretization approach.

Fig. 6

Snippet from the Python code accessing data and calculating the bulk Reynolds number from output data files.