Cardiff University | Prifysgol Caerdydd ORCA
Online Research @ Cardiff 
WelshClear Cookie - decide language by browser settings

Prediction of the transition from stratified to slug flow or roll-waves in gas-liquid horizontal pipes

Kadri, Usama, Mudde, R. F., Oliemans, R. V. A., Bonizzi, M. and Andreussi, P. 2009. Prediction of the transition from stratified to slug flow or roll-waves in gas-liquid horizontal pipes. International Journal of Multiphase Flow 35 (11) , pp. 1001-1010. 10.1016/j.ijmultiphaseflow.2009.07.002

Full text not available from this repository.


In stratified gas–liquid horizontal pipe flow, growing long wavelength waves may reach the top of the pipe and form a slug flow, or evolve into roll-waves. At certain flow conditions, slugs may grow to become extremely long, e.g. 500 pipe diameter. The existence of long slugs may cause operational upsets and a reduction in the flow efficiency. Therefore, predicting the flow conditions at which the long slugs appear contributes to a better design and management of the flow to maximize the flow efficiency. In this paper, we introduce a wave transition model from stratified flow to slug flow or roll-wave regimes. The model tracks the wave crest along the pipe. If the crest overtakes the downstream wave end before hitting the top of the pipe, a roll-wave is formed, otherwise a slug. For model validation we performed measurements in air–water horizontal pipe flow facilities with internal diameters of 0.052 and 0.06 m. Furthermore, we made numerical calculations using a transient one-dimensional multiphase flow simulator (MAST) which adopts a four-field model. The model presented in this paper successfully predicts the evolution of waves and their transition into either slugs or roll-waves. It also predicts the formation time of slugs and roll-waves with a satisfactory agreement.

Item Type: Article
Status: Published
Schools: Mathematics
Uncontrolled Keywords: Waves; Roll-waves; Slug flow; Gas–liquid pipe flow; Flow regime transition
Publisher: Elsevier
ISSN: 0301-9322
Last Modified: 04 Jun 2017 09:28

Citation Data

Cited 28 times in Scopus. View in Scopus. Powered By Scopus® Data

Actions (repository staff only)

Edit Item Edit Item