Investigation of packed bed and moving bed reactors with benchmarking using advanced measurement and computational techniques

Trickle bed reactors (TBR), as typical packed bed reactors (PBR), are widely used in various fields. Very limited information regarding the flow behaviors, hydrodynamic, and mathematical models in extrudate catalyst shapes, such as cylinders, trilobes, and quadrilobes, can be found in literatures because the major focus was on spherical shape. Therefore, a hybrid pressure drops and liquid holdup phenomenological model for extrudate catalyst shapes was developed based on two-phase volume averaged equations, which showed high accuracy against experimental data. The maldistribution and dynamic liquid holdup were investigated in quadrilobe catalyst using gamma-ray computed tomography. A pseudo-3D empirical model was developed and compared with deep neural network predictions. Both models were in good agreement with experimental data. The accretion locations of heavy metal contaminants entrained with flow were tracked by the dynamic radioactive particle tracking technique in the packed beds of sphere, cylinder, trilobe, and quadrilobe, respectively. Kernel density estimator was used to indicate the accretion probability distribution, showing that pressure drop played an important role in heavy metal accretions. CFD simulations of random packed trilobe catalyst bed were conducted to obtain the local information and were validated by experimental data. Moving bed reactors (MBR), as a relatively new type of reactor, encounter many challenges due to the bed expansion because of the concurrent gas-liquid upflow. DEM simulation was used to generate expanded bed. A porosity distribution correlation was developed and implemented in CFD simulations to investigate the hydrodynamics --Abstract, page iv