Validation strategy of reduced-order two-fluid flow models based on a hierarchy of direct numerical simulations

Abstract : Whereas direct numerical simulation (DNS) have reached a high level of description in the field of atomization processes, they are not yet able to cope with industrial needs since they lack resolution and are too costly. Predictive simulations relying on reduced order modeling have become mandatory for applications ranging from cryotechnic to aeronautic combustion chamber liquid injection. Two-fluid models provide a good basis in order to conduct such simulations, even if recent advances allow to refine subscale modeling using geometrical variables in order to reach a unified model including separate phases and disperse phase descriptions based on high order moment methods. Such models must be resolved using dedicated numerical methods and still lack assessment of their predictive capabilities. The present paper constitutes a building block of the investigation of a hierarchy of test-cases designed to be amenable to DNS while close enough to industrial configurations, for which we propose a comparison of two-fluid compressible simulations with DNS databases. We focus in the present contribution on an air-assisted water atomization using a planar liquid sheet injector. Qualitative and quantitative comparisons with DNS allow us to study strength and weaknesses of the reduced-order modeling and numerical approach in this specific configuration and set a framework for more refined models since they already provide a very interesting level of comparison on averaged quantities.
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https://hal.archives-ouvertes.fr/hal-02350200
Contributor : Pierre Cordesse <>
Submitted on : Wednesday, November 6, 2019 - 12:29:16 PM
Last modification on : Friday, November 8, 2019 - 1:20:40 AM

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  • HAL Id : hal-02350200, version 1
  • ARXIV : 1911.08950

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Pierre Cordesse, Alberto Remigi, Benjamin Duret, Angelo Murrone, Thibaut Ménard, et al.. Validation strategy of reduced-order two-fluid flow models based on a hierarchy of direct numerical simulations. 2019. ⟨hal-02350200⟩

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