(123d) Application of CPFD Method in the Simulation of Horizontal Dense Phase Pneumatic Conveying of Pulverized Coal | AIChE

(123d) Application of CPFD Method in the Simulation of Horizontal Dense Phase Pneumatic Conveying of Pulverized Coal

Authors 

Jin, Y. - Presenter, Key Laboratory of Coal Gasification and Energy Chemical Engineering of Ministry of Education, Shanghai Engineering Research Center of Coal Gasification, East China University of Science and Technology
Gong, X., Key Laboratory of Coal Gasification and Energy Chemical Engineering of Ministry of Education, Shanghai Engineering Research Center of Coal Gasification, East China University of Science and Technology
Lu, H., Key Laboratory of Coal Gasification and Energy Chemical Engineering of Ministry of Education, Shanghai Engineering Research Center of Coal Gasification, East China University of Science and Technology
Guo, X., Key Laboratory of Coal Gasification and Energy Chemical Engineering of Ministry of Education, Shanghai Engineering Research Center of Coal Gasification, East China University of Science and Technology
Flow stability is a key question to be solved for the development of dense phase pneumatic conveying. Flow patterns are closely related with flow stability. From the view of experimental materials, angle of repose, packing density and tapped density were determined by PT-X powder tester. And flowability was determined by FT4 Powder Rheometer. The experimental results shew that the tested pulverized coal was a kind of Geldart’s group C powder with strong cohesion. This study contributes with a computational particle fluid dynamic (CPFD) simulation which is based on the numerical solution of continuity and momentum balance equations in a three-dimensional (3-D) horizontal pipeline. A novel correction model was developed, describing interaction among particles and between fluid and particles decided by the experiment mentioned before. CPFD approach predicted the particle velocity and pressure drop were generally below 5% for the stable cases. What’s more, the six different flow patterns were predicted by the CPFD approach embedded in the correction model, which was confirmed by the electrical capacitance tomography (ECT) in the experiment facility set up by our own. With the help of our correction model, it could reveal the mechanism of the change of flow patterns.

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