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Wear prediction in a fluidized bed

Authors: Boyle, E. J.; Rogers, W. A.;

Wear prediction in a fluidized bed

Abstract

A procedure to model the wear of surfaces exposed to a fluidized bed is formulated. A stochastic methodology adapting the kinetic theory of gases to granular flows is used to develop an impact wear model. This uses a single-particle wear model to account for impact wear from all possible-particle collisions. An adaptation of a single-particle abrasion model to describe the effects of many abrading particles is used to account for abrasive wear. Parameters describing granular flow within the fluidized bed, necessary for evaluation of the wear expressions, are determined by numerical solution of the fluidized bed hydrodynamic equations. Additional parameters, describing the contact between fluidized particles and the wearing surface, are determined by optimization based on wear measurements. The modeling procedure was used to analyze several bubbling and turbulent fluidized bed experiments with single-tube and tube bundle configurations. Quantitative agreement between the measured and predicted wear rates was found, with some exceptions for local wear predictions. This work demonstrates a methodology for wear predictions in fluidized beds.

Country
United States
Related Organizations
Keywords

And Peat, Experimental Data 014000, Mathematical Models, 36 Materials Science, Combustion, Fluidized Beds, Corrosion And Erosion, 01 Coal, Particulates, Granular Materials, Wear, Fluidized-Bed Combustion, Hydrodynamics, Collisions, Bubbles, Lignite, Forecasting, 360105

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average