A method to predict particle collision speeds in fluidized beds. (31st December 2022)

• Record Type: Journal Article
• Authors: Runstedtler, Allan; Duchesne, Marc A.
• Is Part Of: Chemical engineering science. Volume 264(2022)
• Publication Date: 2022-12-31
• Subjects: Kinetic theory -- Gas -- Solid -- Agglomeration; Chemical engineering -- Periodicals; Génie chimique -- Périodiques; Chemical engineering; Periodicals; Electronic journals; 660
• DOI: 10.1016/j.ces.2022.118157
• Languages: English
• ISSNs: 0009-2509

Abstract

Highlights: New analytical expression for particle (collision) speed in collision-dominated fluidized beds. Combines kinetic theory of particle collisions with fluid-particle drag. Accommodates collective/correlated particle motion in the bed. Validated by comparing to computational fluid dynamics (CFD) - discrete element method (DEM) Provides rapid prediction as well as a basis for understanding particle speed. Abstract: The target of this method is gas–solid fluidized beds, in which the particles progressively become coated with liquid or generally become sticky for any reason. Previous studies have shown that the restitution coefficient of wet particle collisions depends on the speed at which the particles collide. Moreover, below a critical collision speed, the particles fail to rebound at all. Therefore, predicting particle collision speeds is important. Current methods to predict collision speeds are computationally expensive. The present method provides an analytical expression for particle collision speed, making it convenient for evaluating the potential for agglomeration. Moreover, it provides a basis for understanding the speed of particle motion in fluidized beds—usually only accessible through time-consuming numerical simulations—by anticipating the outcome of what is largely a repetitive computation of particle–particle collision and re-acceleration by the gas flow. The method combines the mean free time between inelastic particle collisions (with provision for collective particle motion), which cause them to lose kinetic energy, and the drag force by the turbulent gas flow on the particles, which accelerates them prior to their next collision. To validate the method, the results are compared to corresponding computational fluid dynamics (CFD) - discrete element method (DEM) calculations.