A Monte Carlo Method to Quantify the Effect of Reactor Residence Time Distribution on Polyolefins Made with Heterogeneous Catalysts: Part I-Catalyst/Polymer Particle Size Distribution Effects

2017 ◽  
Vol 12 (1) ◽  
pp. 1700031 ◽  
Author(s):  
João B. P. Soares ◽  
Jazmín Romero
Keyword(s):  
Particle Size ◽  
Monte Carlo ◽  
Monte Carlo Method ◽  
Particle Size Distribution ◽  
Size Distribution ◽  
Residence Time ◽  
Time Distribution ◽  
Residence Time Distribution ◽  
Heterogeneous Catalysts ◽  
Polymer Particle

Modelling of Fluidized Bed Reactors

2003 ◽  
Vol 1 (1) ◽  
Author(s):  
Joachim Werther ◽  
Ernst-Ulrich Hartge
Keyword(s):  
Particle Size ◽  
Particle Size Distribution ◽  
Fluidized Bed ◽  
Residence Time ◽  
Time Distribution ◽  
Residence Time Distribution ◽  
Scale Up ◽  
Fluidized Bed Reactor ◽  
Fluidized Bed Reactors ◽  
Model Calculations

The fluidized bed reactor has a lot of advantages: excellent gas-solid contacting, no hot spots even with highly exothermal reactions, good gas-to-particle and bed-to-wall heat transfer and the ease of solids handling which is particularly important if the catalyst is quickly ageing. However, the list of disadvantages is as long: broad residence time distribution of the gas due to dispersion and gas-bypass in the form of bubbles, broad residence time distribution of solids due to intense mixing, erosion of bed internals and the attrition of the catalyst particles. A particular disadvantage of the fluidized bed reactor is its difficult scale-up. The historical experience with the FCC process is that in the early 40's of the last century this process was successfully scaled up from a 5 cm dia. pilot-scale unit to a 4.5 m dia. bed in the production unit. On the other hand, around 1950 the scale up of the Fischer-Tropsch synthesis in the fluidized bed failed completely. Modern process design should be able to avoid such disasters by making use of modeling and simulation tools. However, a modeling tool which is really helpful in planning and designing of an industrial fluidized bed reactor has to fulfill a lot of requirements. It should be able to describe the influence of the several changes which are typical for the scale-up process, for example enlargement of bed diameter, bed height and fluidizing velocity, changes of gas distributor design, introduction of in-bed heat exchanger tubes and baffles. In the present work a modelling approach is presented which is able to handle the most important aspects of industrial fluidized bed reactors. A particular focus is to describe the relationship between catalyst attrition, solids recovery in the reactor system and chemical performance of the fluidized bed reactor. The competing influences of attrition of the catalyst particles and efficiency of the solids recovery lead to the establishment of a catalyst particle size distribution (PSD) in the bed inventory which in turn influences via the hydrodynamic characteristics of the fluidized bed the performance of the chemical reactor. The usefulness of this approach is illustrated with model calculations for a fictituous first order reaction where the fluidized bed is equipped with different solids recovery systems including one single stage cyclone, several cyclones in parallel, two- and three-stage cyclone systems, respectively. Model calculations illustrate the significance of a high efficiency of the solids recovery in order to keep the fines in the system which is decisive for a high performance of the reactor. The calculations reveal that it may take months until a quasi steady state of the bed particle size distribution is obtained.

scholarly journals Monte Carlo simulation for soot dynamics

2012 ◽  
Vol 16 (5) ◽  
pp. 1391-1394 ◽  
Author(s):  
Kun Zhou
Keyword(s):  
Particle Size ◽  
Monte Carlo ◽  
Particle Size Distribution ◽  
Size Distribution ◽  
Gas Phase ◽  
Volume Fraction ◽  
Soot Formation ◽  
Bimodal Distribution ◽  
Number Density ◽  
Stochastic Error

A new Monte Carlo method termed Comb-like frame Monte Carlo is developed to simulate the soot dynamics. Detailed stochastic error analysis is provided. Comb-like frame Monte Carlo is coupled with the gas phase solver Chemkin II to simulate soot formation in a 1-D premixed burner stabilized flame. The simulated soot number density, volume fraction, and particle size distribution all agree well with the measurement available in literature. The origin of the bimodal distribution of particle size distribution is revealed with quantitative proof.

Role of emulsifier on the particle size and polymer particle size distribution using multiwavelength spectroscopy measurements

2017 ◽  
Vol 38 (11) ◽  
pp. 1600-1606 ◽  
Author(s):  
María-Teresa Celis ◽  
Billmary Contreras ◽  
Patricia Rosenzweig Levy ◽  
Lucero Méndez ◽  
Francys Vejar ◽  
...  
Keyword(s):  
Particle Size ◽  
Particle Size Distribution ◽  
Size Distribution ◽  
Polymer Particle
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