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The sharp-interface limit of the Cahn–Hilliard/Navier–Stokes model for binary fluids

Published online by Cambridge University Press:  02 January 2013

F. Magaletti
Dipartimento di Ingegneria Meccanica e Aerospaziale, Università di Roma La Sapienza, Via Eudossiana 18, 00184 Roma, Italy
F. Picano
Dipartimento di Ingegneria Meccanica e Aerospaziale, Università di Roma La Sapienza, Via Eudossiana 18, 00184 Roma, Italy Linné Flow Center, KTH Mechanics, Osquars Backe 18, SE-100 44 Stockholm, Sweden
M. Chinappi
Dipartimento di Fisica, Università di Roma La Sapienza, P. le Aldo Moro 5, 00185 Roma, Italy
L. Marino
Dipartimento di Ingegneria Meccanica e Aerospaziale, Università di Roma La Sapienza, Via Eudossiana 18, 00184 Roma, Italy
C. M. Casciola*
Dipartimento di Ingegneria Meccanica e Aerospaziale, Università di Roma La Sapienza, Via Eudossiana 18, 00184 Roma, Italy
Email address for correspondence:


The Cahn–Hilliard model is increasingly often being used in combination with the incompressible Navier–Stokes equation to describe unsteady binary fluids in a variety of applications ranging from turbulent two-phase flows to microfluidics. The thickness of the interface between the two bulk fluids and the mobility are the main parameters of the model. For real fluids they are usually too small to be directly used in numerical simulations. Several authors proposed criteria for the proper choice of interface thickness and mobility in order to reach the so-called ‘sharp-interface limit’. In this paper the problem is approached by a formal asymptotic expansion of the governing equations. It is shown that the mobility is an effective parameter to be chosen proportional to the square of the interface thickness. The theoretical results are confirmed by numerical simulations for two prototypal flows, namely capillary waves riding the interface and droplets coalescence. The numerical analysis of two different physical problems confirms the theoretical findings and establishes an optimal relationship between the effective parameters of the model.

©2013 Cambridge University Press

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