Suscripción a Biblioteca: Guest
Multiphase Science and Technology

Publicado 4 números por año

ISSN Imprimir: 0276-1459

ISSN En Línea: 1943-6181

SJR: 0.144 SNIP: 0.256 CiteScore™:: 1.1 H-Index: 24

Indexed in

VISCOUS OIL-WATER FLOW THROUGH AN INCLINED PIPELINE: EXPERIMENTATION AND PREDICTION OF FLOW PATTERNS

Volumen 27, Edición 1, 2015, pp. 1-26
DOI: 10.1615/MultScienTechn.v27.i1.10
Get accessGet access

SINOPSIS

We identify and predict the flow patterns observed during concurrent flow of viscous oil (viscosity 107 m Pa s, density 889 kg/m3) and water through a +5 deg inclined circular Perspex pipe with internal diameter of 0.025 m. Flow patterns have been identified with the help of visual and photographic techniques in a wide range of superficial velocities of both the fluids (USO = 0.052−1.38 m/s and USW = 0.068−1.23 m/s). Seven different flow patterns (namely, plug, slug, wavy stratified, stratified mixed, annular, dispersion of oil in water, and dispersion of water in oil flow) have been identified and a flow pattern map has been developed for the present system. Flow pattern transition boundaries have been predicted by analytical models and probabilistic neural network (PNN) technique. Transition of wavy stratified to stratified mixed flow pattern has been predicted following the drop formation mechanism at interface proposed by Al-wahibi, Smith, and Angeli, (Transition between Stratified and Non-Stratified Horizontal Oil-Water Flows: Part II. Mechanism of Drop Formation, Chem. Eng. Sci., vol. 62, pp. 2929−2940, 2007). During the development of PNN, superficial velocities of oil and water, pipe diameter, viscosity ratio, density ratio, interfacial tension, and pipe inclination have been considered as governing parameters of the flow patterns. The trained PNN gives a better prediction over the analytical models with accuracy of ∼90%.

CITADO POR
  1. Haase S., Marschner S., Ayubi M.M., Lange M., Gas-liquid flow in small channels: Artificial neural network classifiers for flow regime prediction, Chemical Engineering and Processing - Process Intensification, 180, 2022. Crossref

Portal Digitalde Biblioteca Digital eLibros Revistas Referencias y Libros de Ponencias Colecciones Precios y Políticas de Suscripcione Begell House Contáctenos Language English 中文 Русский Português German French Spain