Assembling a bubble-induced turbulence model incorporating physical understanding from DNS. (July 2019)

• Record Type: Journal Article
• Authors: Magolan, Benjamin; Baglietto, Emilio
• Is Part Of: International journal of multiphase flow. Volume 116(2019)
• Page Start: 185
• Page End: 202
• Publication Date: 2019-07
• Subjects: Bubble-Induced turbulence -- k−ε Models -- Bubbly flow -- Multiphase CFD; Multiphase flow -- Periodicals; Écoulement polyphasique -- Périodiques; Multiphase flow; Periodicals; 620.1064
• DOI: 10.1016/j.ijmultiphaseflow.2019.04.009
• Languages: English
• ISSNs: 0301-9322

Abstract

Highlights: New Bubble-Induced Turbulence (BIT) model incorporates physical understanding. Turbulent viscosity formulation derived from turbulent kinetic energy budgets. Time-scale formulation relates to bubble characteristics. Modulation parameter and dissipation coefficient optimized on BIT turbulent regimes. BIT model considerably improves liquid turbulent kinetic energy predictions. Abstract: Bubble-induced turbulence (BIT) is a two-phase flow phenomenon characterized by complex interfacial interactions that fundamentally alter the resulting liquid turbulent kinetic energy distribution, budgets, and scales. Incorporating this complexity into a BIT model remains a formidable challenge, as existing two-equation BIT closures struggle with accurately predicting the turbulent kinetic energy and mean flow profiles. The present work assembles a BIT model that incorporates additional physical understanding into its formulation by leveraging insights garnered from experiments, DNS, and previous assessment. The model comprises new turbulent viscosity and time-scale formulations, in addition to optimized values for the modulation parameter, dissipation coefficient, and newly proposed turbulent viscosity multiplier. Improved model performance is demonstrated through simulation of air/water experimental cases and direct comparison with existing closures, which includes qualitative inspection of individual sets as well as quantitative assessment of the turbulent kinetic energy error distribution. Future work delving into momentum closure development, new experimental campaigns, and DNS parametric studies is motivated and linked to BIT model improvements.