Missouri University of Science and Technology
Hydrodynamics of trickle bed reactors (TBRS) packed with industrial catalyst using advanced measurement techniques
Abstract
dc:description.abstract"The impacts of the packing characteristics on the hydrodynamics od a trickle bed reactor (TBR) have been investigated using advanced measurements techniques of Gamma-ray densitometry (GRD) and Optical fiber probe and conventional measurement techniques of high-frequency differential pressure transducer and load cell. Two different reactor sizes of bench and pilot plant scale were used. Bench-scale TBR carried out the experiments to assess phase distribution and catalyst utilization with 1.18 cm inside diameter and 72 cm length at ambient pressure and temperature. The mixture of catalyst and fine particles displayed considerable improvements in the phase distribution, liquid holdup profile, and catalyst utilization efficiency. In the pilot plant scale reactor, the catalyst shape showed a significant impact on the hydrodynamics, pressure drop, local gas and liquid velocities, and flow regime transition. The currently used trilobe and quadrilobe in hydrotreating processes showed lower pressure drop, increased liquid holdup, enhanced local gas and liquid saturation and velocities, and lower flow regime transition compared with spherical and cylindrical shapes of catalysts. Meanwhile, mechanistic model named slit model predicted the pressure drop and liquid holdup better than selected correlations where equivalent diameter is used and the bed characteristic is quantitated properly by measured Ergun constants"--Abstract, page iv.
Degree
thesis:*- Name thesis:degree_name
- Ph. D. in Chemical Engineering
- Grantor
- Missouri University of Science and Technology
Author and committee
dc:creator, dc:contributor.*- Author dc:creator
-
- Al-Ani, Mohammed Jaber
Subjects
dc:subject × 7Identifiers
dc:identifier.*- Repository record dc:identifier
- https://scholarsmine.mst.edu/doctoral_dissertations/2819
- OAI identifier oai:identifier
- oai:scholarsmine.mst.edu:doctoral_dissertations-3824