On the experimental investigation of gas-liquid flow in bubble columns using ultrafast X-ray tomography and radioactive particle tracking. (12th October 2017)

• Record Type: Journal Article
• Authors: Azizi, Salar; Yadav, Ashutosh; Lau, Yuk Man; Hampel, Uwe; Roy, Shantanu; Schubert, Markus
• Is Part Of: Chemical engineering science. Volume 170(2017)
• Page Start: 320
• Page End: 331
• Publication Date: 2017-10-12
• Subjects: Gas-liquid flow -- Bubble column -- Radioactive particle tracking -- Ultrafast X-ray computed tomography; Chemical engineering -- Periodicals; Génie chimique -- Périodiques; Chemical engineering; Periodicals; Electronic journals; 660
• DOI: 10.1016/j.ces.2017.02.015
• Languages: English
• ISSNs: 0009-2509

Abstract

Highlights: A complementary bubble column study using Ultrafast X-ray Computed Tomography and Radioactive Particle Tracking is performed. Unique gas and liquid phase dynamics data for four experimental cases are extracted. Obtained gas phase structures of UXCT support the liquid phase flow patterns of RPT quite well. Mass flow balance and relative gas-liquid velocities are determined as a manner of complementary of both techniques. Abstract: Several techniques have been developed in the past to measure gas and liquid phase dynamics; however, reported data were mostly gathered individually for either liquid velocity, or volume fraction (phase holdup), but never when both are measured in the same system. In this work, arguably for the first time, bubble column hydrodynamics have been investigated using two complementary advanced non-invasive measurement techniques, namely Ultrafast X-ray Computed Tomography (UXCT) and Radioactive Particle Tracking (RPT). The UXCT experimental data in terms of gas phase structure is used in a supportive way to explain the liquid velocity profiles of the RPT data. Results of both experimental techniques are verified in a complementary manner using the mass conservation calculation. The results show good agreement. It is envisioned that the presented data would be helpful in the development and validation of numerical models for better predicting the flow profiles in bubble columns.