Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.14279/33732
Title: A mechanistic model for the prediction of flow pattern transitions during separation of liquid-liquid pipe flows
Authors: Evripidou, Nikola 
Avila, Carlos 
Angeli, Panagiota 
Major Field of Science: Engineering and Technology
Field Category: Chemical Engineering
Keywords: Two-phase flow;Dispersion;Oil-water;Separation;Mechanistic model
Issue Date: Oct-2022
Source: International Journal of Multiphase Flow, 2022, vol. 155
Volume: 155
Journal: International Journal of Multiphase Flow 
Abstract: A one-dimensional mechanistic model that predicts the flow pattern transitions during the separation of dispersed liquid-liquid flows in horizontal pipes was developed. The model is able to capture the evolution along the pipe of the four characteristic layers that develop from initially dispersed flows of either oil-in-water or water-in-oil at a range of mixture velocities: a pure water layer at the bottom, a settling (flotation/sedimentation) layer, a dense-packed zone, and a pure oil layer on the top. Coalescence correlations from literature were included in the model to predict the drop growth due to binary drop coalescence and the coalescence rate of drops with their corresponding interface. The model predictions on the evolution of the heights of the different layers were partly compared against available experimental data obtained in a pilot scale two-phase flow facility in a test section of 0.037 m inner diameter using tap water and an oil of density 828 kg m−3 and viscosity 5.5 mPa s as test fluids, and in a 0.1 m inner diameter test section using water and an oil of density 857 kg m−3 and viscosity 13.6 mPa s. It was shown that the evolution of the four characteristic layers depends on the rates of drop settling and drop-interface coalescence. Oil-in-water dispersions separated faster than water-in-oil ones, while dispersions with smaller drop-sizes were more likely to exhibit depletion of the dense-packed zone.
URI: https://hdl.handle.net/20.500.14279/33732
ISSN: 03019322
DOI: 10.1016/j.ijmultiphaseflow.2022.104172
Type: Article
Affiliation : University College London 
Avila Multiphase Flow Consulting 
Funding: Chevron Corporation University College London
Publication Type: Peer Reviewed
Appears in Collections:Άρθρα/Articles

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