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A novel, structure‐tracking monte carlo algorithm for spray fluidized bed agglomeration
Author(s) -
Dernedde Mathias,
Peglow Mirko,
Tsotsas Evangelos
Publication year - 2012
Publication title -
aiche journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.958
H-Index - 167
eISSN - 1547-5905
pISSN - 0001-1541
DOI - 10.1002/aic.13709
Subject(s) - economies of agglomeration , monte carlo method , tracking (education) , discretization , process (computing) , monte carlo algorithm , algorithm , statistical physics , particle (ecology) , agglomerate , fluidized bed , computer science , a priori and a posteriori , mathematics , materials science , engineering , physics , thermodynamics , psychology , mathematical analysis , pedagogy , philosophy , statistics , oceanography , epistemology , chemical engineering , composite material , geology , operating system
A stochastic modeling approach to fluidized bed agglomeration is presented. First, the fundamentals of a general Monte Carlo algorithm are discussed, namely the correlation of real with simulation time and the size of the simulation box. Two different approaches regarding the morphological description of particle structure development are then compared for different theoretical test cases. The first approach (concept of positions) is a fast and effective geometrical discretization to follow properties such as primary particle number per agglomerate throughout the simulation. The second approach is a new three‐dimensional (3‐D) structure algorithm, which allows a complete, unrestricted description of the spatial evolution of particles related to physical microprocesses. The 3‐D algorithm enables to apply distributed particle and droplet sizes, which is not possible in the concept of positions. In the perspective, the structural growth of particles can be connected to process conditions, opening new possibilities for process and product design. © 2011 American Institute of Chemical Engineers AIChE J, 58: 3016–3029, 2012