Issue |
EPJ Web Conf.
Volume 264, 2022
EFM21 – 15th International Conference “Experimental Fluid Mechanics 2021”
|
|
---|---|---|
Article Number | 01007 | |
Number of page(s) | 7 | |
Section | Contributions | |
DOI | https://doi.org/10.1051/epjconf/202226401007 | |
Published online | 11 July 2022 |
https://doi.org/10.1051/epjconf/202226401007
Spray in cross–flow: comparison of experimental and numerical approach
1
Energy Institute, Faculty of Mechanical Engineering, Brno University of Technology, Technická 2896/2, 616 69 Brno, Czech Republic
2
Provyko s.r.o., Vinařská 558/3a, Pisárky, 603 00 Brno, Czech Republic
* Corresponding author: Ondrej.Cejpek@vutbr.cz
Published online: 11 July 2022
The spray behaviour and droplet trajectories in realistic conditions are of crucial importance in many industrial, agricultural and chemical applications. Droplet characteristics and spray trajectory in chemical applications (e. g. flue gas scrubbing, CO2 capture in spray column) determine the amount of mass involved in the gas scrubbing process, mass trapped by the flow or attached to the walls. Knowledge of the droplet behaviour can improve a nozzle design and scaling, increase the process efficiency, minimize the process liquid and blow away the fraction. In this study, experiments with pressure swirl nozzle in cross–flow of air were performed at one nozzle injection pressure (0.5 MPa) and several cross–flow velocities (8, 16, 32 m/s). The results on droplet trajectories are compared with numerical results obtained by ANSYS Fluent. Two Lagrange approaches for spray modelling were used. Injection of droplet groups and Linearized Instability Sheet Atomization (LISA) model incorporated within ANSYS Fluent were used to represent the spray. The CFD results of spray penetration and droplet trajectories are compared with experimental data. A simple analytical model is able to well predict trajectories of large droplets, but fails to predict trajectories of small droplets. The LISA model yields a better accuracy for spray in cross-flow prediction.
© The Authors, published by EDP Sciences, 2022
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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