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Aerobreakup of drops is a fundamental two-phase flow problem that is essential to many spray applications. A parametric numerical study was performed by varying the gas stream velocity, focusing on the regime of moderate Weber numbers, in which the drop deforms to a forward bag. When the bag is unstable, it inflates and disintegrates into small droplets. Detailed numerical simulations were conducted using the volume-of-fluid method on an adaptive octree mesh to investigate the aerobreakup dynamics. Grid-refinement studies show that converged three-dimensional simulation results for drop deformation and bag formation are achieved by the refinement level equivalent to 512 cells across the initial drop diameter. To resolve the thin liquid sheet when the bag inflates, the mesh is refined further to 2048 cells across the initial drop diameter. The simulation results for the drop length and radius were validated against previous experiments, and good agreement was achieved. The high-resolution results of drop morphological evolution were used to identify the different phases in the aerobreakup process, and to characterize the distinct flow features and dominant mechanisms in each phase. In the early time, the drop deformation and velocity are independent of the Weber number, and a new internal-flow deformation model, which respects this asymptotic limit, has been developed. The pressure and velocity fields around the drop were shown to better understand the internal flow and interfacial instability that dictate the drop deformation. Finally, the impact of drop deformation on the drop dynamics was discussed.
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Data-driven modeling of the aerodynamic deformation and drag for a freely moving drop in the sub-critical Weber number regime
Accurate prediction of the dynamics and deformation of freely moving drops is crucial for numerous droplet applications. When the Weber number is finite but below a critical value, the drop deviates from its spherical shape and deforms as it is accelerated by the gas stream. Since aerodynamic drag on the drop depends on its shape oscillation, accurately modeling the drop shape evolution is essential for predicting the drop's velocity and position. In this study, 2D axisymmetric interface-resolved simulations were performed to provide a comprehensive dataset for developing a data-driven model. Parametric simulations were conducted by systematically varying the drop diameter and free-stream velocity, achieving wide ranges of Weber and Reynolds numbers. The instantaneous drop shapes obtained in simulations are characterized by spherical harmonics. Temporal data of the drag and modal coefficients are collected from the simulation data to train a {Nonlinear Auto-Regressive models with eXogenous inputs} (NARX) neural network model. The overall model consists of two multi-layer perceptron networks, which predict the modal coefficients and the drop drag, respectively. The drop shape can be reconstructed with the predicted modal coefficients. The model predictions are validated against the simulation data in the testing set, showing excellent agreement for the evolutions of both the drop shape and drag.
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- Award ID(s):
- 2321396
- PAR ID:
- 10510665
- Publisher / Repository:
- Elsevier
- Date Published:
- Journal Name:
- International Journal of Multiphase Flow
- Volume:
- 177
- ISSN:
- 0301-9322
- Page Range / eLocation ID:
- 104859
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1016/j.ijmultiphaseflow.2024.104859
