Premium
Using discrete distributions to analyze CSD data from MSMPR crystallizers
Author(s) -
Jones Christopher M.
Publication year - 2002
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.690480709
Subject(s) - nucleation , dispersion (optics) , distribution (mathematics) , population , statistics , growth rate , mathematics , statistical physics , suspension (topology) , representation (politics) , biological system , thermodynamics , physics , mathematical analysis , optics , demography , geometry , homotopy , sociology , biology , pure mathematics , politics , political science , law
Abstract A novel technique for treating continuous mixed‐suspension, mixed‐product removal (MSMPR) crystal‐size distribution (CSD) data uses a discrete probability distribution to represent the growth rate distribution of crystals in a crystallizer. It is based on the premise that individual crystals in a population each have their own intrinsic growth rate, but the growth rates of crystals in the population may vary. Treatment of CSD data using this discrete distribution technique enables the calculation of crystallizer kinetics data, including the nucleation rate and characterization of the nuclei growth rate distribution and using both graphical representation and descriptive statistics. Previously published data for a system exhibiting growth rate dispersion is used to demonstrate the efficacy of the technique. Furthermore, the results of the data analysis using the discrete distribution technique are compared to the results of data analysis using the continuous distribution technique.