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Acoustically induced thermal effects on Rayleigh streaming

Article dans une revue avec comité de lecture
Author
WEISMAN, Catherine
1041968 Laboratoire d'Informatique pour la Mécanique et les Sciences de l'Ingénieur [LIMSI]
BALTEAN-CARLÈS, Diana
1041968 Laboratoire d'Informatique pour la Mécanique et les Sciences de l'Ingénieur [LIMSI]
BAILLIET, Hélène
118112 Institut Pprime [UPR 3346] [PPrime [Poitiers]]
ccDARU, Virginie
134975 Laboratoire de Dynamique des Fluides [DynFluid]

URI
http://hdl.handle.net/10985/21438
DOI
10.1017/jfm.2020.996
Date
2021
Journal
Journal of Fluid Mechanics

Abstract

The present study focuses on acoustically induced thermal effects on Rayleigh streaming inside a resonator. Firstly, we consider the effect of the transverse (or wall-normal) mean temperature gradient on the acoustic streaming flow generated by a standing wave between two parallel plates. Analytical expressions for acoustic quantities are developed and used to express the sources of linear streaming. The influence of a transverse temperature variation on the streaming velocity is clearly identified through a term proportional to the temperature difference and to the square of the half-width of the guide. This term modifies the Rayleigh streaming pattern and may generate an additional vortex. On the other hand, the longitudinal (or wall-parallel) temperature difference is calculated as a cumulated effect of thermoacoustic heat transport in the fluid, heat conduction in the wall and heat convection of the air outside the resonator. At high acoustic levels, heat is significantly convected by the streaming flow and the resulting transverse temperature difference is proportional to the longitudinal temperature difference. Combining these expressions brings out a new criterion parameter for the nonlinear Reynolds number (ReNL) characterizing the transition in streaming patterns at high acoustic levels. This result explains previous experimental and numerical observations of the streaming flow dynamics at high acoustic amplitudes, under different temperature boundary conditions, and can provide a powerful prediction tool for streaming pattern transitions.

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