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Stochastic modeling of particle motion along a sliding conveyor
Author(s) -
Cronin Kevin,
Catak Muammer,
Dempsey Sean,
Ollagnier Remi
Publication year - 2010
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.11975
Subject(s) - randomness , mechanics , particle (ecology) , displacement (psychology) , magnetosphere particle motion , particle displacement , stochastic process , brownian motion , statistical physics , control theory (sociology) , classical mechanics , mathematics , physics , computer science , geology , statistics , amplitude , psychology , oceanography , control (management) , quantum mechanics , artificial intelligence , magnetic field , psychotherapist
The sliding conveyor consists of a plane surface, known as the track, along which particles are induced to move by vibrating the bed sinusoidal with respect to time. The forces on the particle include gravity, bed reaction force and friction. Because friction coefficients are inherently variable, particle motion along the bed is erratic and unpredictable. A deterministic model of particle motion (where friction is considered to be known and invariant) is selected and its output validated by experiment. Two probabilistic solution techniques are developed and applied to the deterministic model, in order to account for the randomness that is present. The two methods consider particle displacement to be represented by discrete time and continuous time random processes, respectively, and permits analytical solutions for mean and variance in displacement versus time to be found. These are compared with experimental measurements of particle motion. Ultimately this analysis can be employed to calculate residence‐time distributions for such items of process equipment. © 2009 American Institute of Chemical Engineers AIChE J, 2010