Parameter estimation of a jet flow model using genetic algorithms and maximum likelihood formulation

PAULO CECILIA; HORACIO A. PETIT

Eliva press

Año: 2022 p. 42

978-1-63648-525-6

The scarcity of natural sands has triggered a considerable increase in theconsumption of manufactured sands for concrete production. In this regard,the flakiness of the particles and the excess of fines are the main problems thatshould be addressed when utilizing manufactured sands. The throat classifier isan air classifier designed for the elimination of fine particles (smaller than 75micrometers) from manufactured sands. The main features of the classifier havebeen presented in the literature but the mechanism that drives the classificationhas not been studied in detail. Therefore, this work explores the mechanismof classification of the throat classifier by using CFD-DPM and CFD-DEMsimulations. The accuracy and limitations of the methodologies were evaluatedby comparing the results against experimental data obtained at pilot scale.The simulations presented fair results in the representation of the airflow andthe particle classification inside the throat classifier. Differences between thepredictions using the CFD-DPM and the CFD-DEM methodologies under thesimulated conditions were found to be negligible. The results of the simulationsallowed for a more detailed understanding of the classification mechanismthat occurs inside the device and the influence of operational variables on theequipment performance.