DNS of turbulent flow with hemispherical wall roughness

Abstract

The present study of the effect of roughness density on the mean flow turbulence parameters is motivated by the need for new generation of boundary conditions for multiphase computational multiphase fluid dynamics (CMFD) models applied to boiling flows. Effect of roughness element density on the turbulent flow in a channel is quantified through direct numerical simulations (DNSs). The Navier--Stokes equations are solved using finite element method and bubbles are approximated as rigid near-hemispherical obstacles at the wall. Six different cases were analysed including channel flow with smooth wall and channel flow with rough wall for five different bubble nucleation site densities. Friction factor and the law of the wall was calculated and compared with the previously published results. Existing correlations for nucleating bubble site density dependency on a wall heat flux were used to obtain a relation between the heat flux and the friction factor, leading to the law of the wall dependency on the heat flux. This separate effect study provides new guidelines on how the heat flux in subcooled boiling regime affects the turbulence behaviour near the wall and guides the computational fluid dynamics model development for boiling two-phase flows.

Keywords:

• turbulence
• roughness
• DNS

Acknowledgements

The solution presented herein made use of the Acusim linear algebra solution library provided by Altair Engineering Inc. and meshing and geometric modelling libraries by Simmetrix Inc. The authors would like to acknowledge Jacopo Buongiorno (MIT) and Robert Lowrie (LANL) for fruitful discussions.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This research was supported by the Consortium for Advanced Simulation of Light Water Reactors (http://www.casl.gov), an Energy Innovation Hub (http://www.energy.gov/hubs) for Modeling and Simulation of Nuclear Reactors under U.S. Department of Energy [grant number DE-AC05-00OR22725]. Computational resources were provided by the National Center for Computational Sciences at Oak Ridge National Laboratory, which is supported by the Office of Science of the Department of Energy [grant number DE-AC05-00OR22725].