Algorithm to determine flow regimes, transition zones, and pressure gradient of two-phase pipe-flow.

OLUSOLA, Oloruntoba and KARA, Fuat (2019). Algorithm to determine flow regimes, transition zones, and pressure gradient of two-phase pipe-flow. International Journal of Scientific & Engineering Research, 10 (10), 739-747.

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Abstract

Existing two-phase phenomenological models for predicting pressure gradient in flowlines and risers are flow regime specific, and rely on pre-knowledge of flow regime. In practical two-phase pipe flow design, several flow regimes occur in typical flowlines and risers which require different flow regime and pressure gradient phenomenological models. Several exiting flow regime prediction methods employ switching between different models with discontinuous boundaries. Therefore, a consistent method to predict flow regime transition zone and selection of appropriate pressure gradient phenomenological model is required. This work aims to provide an algorithm to predict flow regimes and transitions zones, as well as pressure gradient in a two-phase pipe flow, and to validate the developed algorithm using published experimental data. The proposed algorithm is obtained by combining existing and modified flow regimes, and pressure gradient phenomenological models. Validation of the developed algorithm shows that stratified and annular/mist flow regimes experimental data are identified as transitions flows. Results also showed that 87.87 % of slug data were correctly determined, with the remaining data identified as stratified (0.37 %), dispersed-bubble (9.51 %), and transition (2.24 %) flows. Pressure gradient predictions are within 27.36 % average absolute error. The proposed algorithm is able to determine flow regimes and transition zones for unified flowregime phenomenological prediction models, and select appropriate pressure gradient phenomenological prediction models

Item Type:	Article
Page Range:	739-747
SWORD Depositor:	Symplectic Elements
Depositing User:	Symplectic Elements
Date Deposited:	08 Apr 2022 16:19
Last Modified:	08 Apr 2022 16:19
URI:	https://shura.shu.ac.uk/id/eprint/29969

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