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Significance Statement
Currently the Ergun equation as developed in 1952 is one of the most popular equations used to predict the pressure drop in fixed beds of granular materials. In many cases the users of the equation do not consider the conditions under which it was developed; i.e. small, uniform-sized, spherical particles with diameter less than 1.5 mm (mainly glass spheres, sand and pulverized coke). Another limitation in the use of this equation is that two packed beds may have the same average particle diameter and the calculated pressure drop values will be the same, but one may have a narrow particle size distribution and the other a wide distribution which affects the void fraction and associated differences in pressure drop.
The significance of the current development is that it focusses on the use of large coal, char and ash particles (1.7−45 mm), their sphericity and also considers the interaction and contribution of different particle sizes and their distribution to the bed voidage and associated pressure drop.
In industrial practice it is important to understand the variables that affect packed bed pressure drop and also to be able to accurately calculate such pressure drop. The importance is related to both the design of new packed bed reactors and the troubleshooting of existing reactors. In the case of new designs the capacity of auxiliary equipment such as blowers or compressors depends on the system pressure drop, of which the packed bed reactor may be a major contributor. For existing packed bed reactors the accurate knowledge of the expected bed pressure drop may contribute to early detection of changes in bed packing and undesired gas flow patterns that negatively affect reactor stability.
Figure Legend: Typical example of how three particle size distributions of the same material with same Ergun index can have different void fractions and pressure drop per bed length.
Journal Reference
Fuel, Volume 158, 15 October 2015, Pages 232-238.
Andrei Koekemoer, Adam Luckos
Sasol Group Technology, R&T Division, P.O. Box 1, Sasolburg 1947, South Africa
Abstract
The dependence of packed bed pressure drop on variables such as particle size distribution (PSD) and material type are of vital importance in the design of industrial equipment including fixed- and fluidized-bed reactors, blast furnaces and fixed-bed gasifiers. The pressure drop across a packed bed is commonly calculated using the Ergun equation that was developed using experimental data from laboratory-scale beds comprised of small, mono-sized, smooth, non-porous, spherical or nearly spherical particles. In the industrial applications much larger poly-dispersed particles are used, raising the need for a correlation based on more relevant measurements. This study deals with an extension of the Ergun equation to packed beds of large coal, char and ash particles with different average particle diameters and different PSD widths. The research presented here has shown the influence of material type and PSD on both particle properties (sphericity) and packed bed properties (voidage and Sauter mean diameter). In turn these have a significant impact on the subsequent bed pressure drop. It was determined that a bed of ash particles has the highest voidage, followed by the char bed and then coal bed with the lowest voidage. The difference may be attributed to differences in particle sphericity as well as the surface roughness of the particles. In all cases the particle diameter had a lesser effect on bed voidage compared to PSD width, as wider PSD was associated with a lower bed voidage due to smaller particles filling the spaces between the larger particles. New values of the Ergun equation constants were obtained via regression analysis from pressure drop data generated for coal, ash and char particles. The values applicable to coal (77.4 and 2.8), char (160.4 and 2.8) and ash (229.7 and 2.3) particles were found to better approximate bed pressure drop compared to those used in the original form of the Ergun equation (150 and 1.75). The modified Ergun equation can successfully be used to predict pressure drop in a composite packed bed of coal, char and ash particles mimicking the bed structure in an industrial packed-bed gasifier.
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