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Chord length distribution to particle size distribution
Author(s) -
Pandit Ajinkya V.,
Ranade Vivek V.
Publication year - 2016
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.15338
Subject(s) - chord (peer to peer) , particle size distribution , particle size , materials science , distribution (mathematics) , computational physics , simple (philosophy) , particle (ecology) , biological system , optics , particle number , ceramic , statistical physics , mechanics , analytical chemistry (journal) , mathematics , plasma , physics , chemistry , composite material , computer science , mathematical analysis , chromatography , geology , distributed computing , philosophy , epistemology , biology , oceanography , quantum mechanics
A simple model is presented to extract the particle size distribution (PSD) from the chord length distribution measured using a focused beam reflectance measurement probe. The model can be implemented using simple spread sheeting tools and does not require the description of additional parameters as opposed to previous models. The model was validated for two systems consisting of spherical ceramic beads by comparing model predicted PSD against the PSD obtained through image analysis (IA). Then, the model was evaluated by considering various systems consisting of irregularly shaped particles (sand/zinc dust/plasma alumina). Model predictions accurately predicted the mean but over‐predicted the variance of the PSD in comparison with the PSD obtained from IA. However, overall, a reasonable agreement was observed. Finally, the model was shown to be accurate in predicting PSD in comparison with the measured PSD for systems of practical relevance such as for paracetamol and p‐aminophenol crystals. © 2016 American Institute of Chemical Engineers AIChE J , 62: 4215–4228, 2016