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Particle Characterization and Dynamics
Published in Wen-Ching Yang, Handbook of Fluidization and Fluid-Particle Systems, 2003
There are two primary objectives for investigating the particle segregation phenomenon in gas fluidized beds. In one respect, the fluidized beds are studied to determine the operating conditions required to promote bed mixing and eliminate or minimize particle segregation. A mixing index can generally be defined in this case to measure the closeness to perfect mixing. On the contrary, the other objective is to study the optimum conditions under which clean separation can be accomplished between different materials (or components) in the bed. For this case, both the degree and the rate of particle separation are important aspects of investigation.
Distillation
Published in John J. McKetta, Unit Operations Handbook, 2018
Holland and co-workers [45, 98] went beyond previously cited studies in representing tray phenomena. Perfect mixing is not assumed. Rather, the effects of transfer lag, channeling, mass transfer, and mixing, are all considered. The numerical technique used for solution is an adaption of the θ convergence method developed for steady-state simulation. The book [45] represents one of the most comprehensive sources of information on distillation dynamics.
Enhanced algorithm for randomised model structure selection
Published in International Journal of Systems Science, 2022
L. P. Fagundes, A. S. Morais, L. C. Oliveira-Lopes, J. S. Morais
Assuming a perfect mixing, i.e. there is no position dependence in the temperature, concentration, or reaction rate inside the CSTR, and applying a mass balance, the system can be described by Equations (36a) and (36b), where is the feed flow rate of product, the reactor volume is V = 700 l, is the nominal concentration of A in the feed and was set to 10 mol , and are the concentrations in the reactor, and the reaction rate constants for the three reactions , and are respectivelly 5/6 , 5/3 and 1/6 l mol.
Modeling of heat and mass transfer in fluidized bed dryers using the volumetric heat transfer coefficient. Part 1: Equations describing the simultaneous heat and mass transfer
Published in Drying Technology, 2021
Figure 1 shows a sketch of a short section of the fluidized bed dryer and a single particle. Figure 1a shows the gas flow in a short section of the dryer. Figure 1b shows the direction of the heat and mass transfer of a single particle. During convectional drying, simultaneous heat and mass transfer occur between the wet material and the drying gas. Determination of the contact surface of the particle has a number of uncertainties, therefore, the quantification of this value should be avoided in the model. Due to perfect mixing, there are no changes in the temperature and the moisture content of the material along the height of the dryer; these values change only in the function of the drying time. The temperature and the absolute humidity of the drying gas vary along the height of the dryer.
Transport of indoor aerosols to hidden interior spaces
Published in Aerosol Science and Technology, 2020
Mengjia Tang, Ningling Zhu, Kerry Kinney, Atila Novoselac
The CO2 concentration profiles measured during Experiments M2–M7 show that the DMV system had no impact on the dispersion of the tracer gas and corresponding particles between rooms. Specifically, statistical analysis indicates there was no significant difference between the air change rates (ACHs) measured in hidden spaces (Equation (1)) when the DMV system was on versus when it was off (p = 0.80 for the master bedroom closet, and p = 0.09 for the kitchen drawer/cabinet space). However, the temperature field in the house did have a major impact. Depending on the temperature differences between rooms in the house, it took from 0.5 to 1.5 h until uniform concentration of CO2 throughout the house was achieved. This time is often called the mixing time, which is the time required to achieve a uniform concentration in all rooms that is equivalent to the concertation that occurs with perfect mixing. For example, in Experiment M3 – which had the DMV system on and only a 0.4 °C temperature difference between the injection point in the control room and the adjacent kitchen – the mixing time was approximately 1.5 h. Conversely, in Experiments M5 which also had the DMV system on but a much higher temperature difference (1.0 °C) between these two rooms, the mixing time was approximately 0.5 h. In both of these experiments, the AHU was off, indicating that buoyancy-driven flow (reflected in the temperature difference between rooms) had a major impact on the distribution and movement of air throughout the house.