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Improved droplet breakup models for spray applications

Stefanitsis, D., Strotos, G., Nikolopoulos, N., Kakaras, E. and Gavaises, M. ORCID: 0000-0003-0874-8534 (2019). Improved droplet breakup models for spray applications. International Journal of Heat and Fluid Flow, 76, pp. 274-286. doi: 10.1016/j.ijheatfluidflow.2019.02.010


The current study examines the performance of two zero-dimensional (0D) aerodynamically-induced breakup models, utilized for the prediction of droplet deformation during the breakup process in the bag, multi-mode and sheet-thinning regimes. The first model investigated is an improved version of the widely used Taylor analogy breakup (TAB) model, which compared to other models has the advantage of having an analytic solution. Following, a model based on the modified Navier–Stokes (M-NS) is examined. The parameters of both models are estimated based upon published experimental data for the bag breakup regime and CFD simulations with Diesel droplets performed as part of this work for the multi-mode and sheet-thinning regimes, for which there is a scarcity of experimental data. Both models show good accuracy in the prediction of the temporal evolution of droplet deformation in the three breakup regimes, compared to the experimental data and the CFD simulations. It is found that the best performance of the two is achieved with the M-NS model. Finally, a unified secondary breakup model is presented, which incorporates various models found in the literature, i.e. TAB, non-linear TAB (NLTAB), droplet deformation and breakup (DDB) and M-NS, into one equation using adjustable coefficients, allowing to switch among the different models.

Publication Type: Article
Publisher Keywords: Droplet breakup models, Droplet deformation, TAB, CFD
Subjects: T Technology > TJ Mechanical engineering and machinery
T Technology > TL Motor vehicles. Aeronautics. Astronautics
Departments: School of Mathematics, Computer Science & Engineering > Engineering > Mechanical Engineering & Aeronautics
Date Deposited: 06 Mar 2019 11:47
Text - Accepted Version
Available under License Creative Commons Attribution Non-commercial No Derivatives.

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