Fluid flow through a bed of solid particles is an important process that occurs in full-scale water treatment operations. The Carman–Kozeny model remains highly popular for estimating the resistance across the bed. It is common practice to use particle shape factors in fixed bed state to match the predicted drag coefficient with experimentally obtained drag coefficients. In fluidised state, however, where the same particles are considered, this particle shape factor is usually simply omitted from the model without providing appropriate reasoning. In this research, it is shown that a shape factor is not a constant particle property but is dependent on the fluid properties as well. This dynamic shape factor for irregularly shaped grains increases from approximately 0.6 to 1.0 in fluidised state.

We found that unstable packed beds in moderate up-flow conditions are pseudo-fixed and in a setting state. This results in a decreasing bed voidage and simultaneously in a decreasing drag coefficient, which seems quite contradictory. This can be explained by the collapse of local channels in the bed, leading to a more uniform flow distribution through the bed and improving the available surface for flow-through. Our experimental measurements show that the drag coefficient decreases considerably in the laminar and transition regions. This is most likely caused by particle orientation, realignment and rearrangement in particles’ packing position.

A thorough hydraulic analysis shows that up-flow filtration in rapid sand filters under backwash conditions causes the particle bed to collapse almost imperceptibly. In addition, an improved expression of the drag coefficient demonstrated that the Carman–Kozeny model constant, however often assumed to be constant, is in fact not constant for increasing flow rates. Furthermore, we propose a new pseudo-3D image analysis for particles with an irregular shape. In this way, we can explain the successful method using optimisation of the extended terminal sub-fluidisation wash (ETSW) filter backwashing procedure, in which turbidity and peaks in the number of particles are reduced with a positive effect on water quality.

A virtual lab (MOOC) for students chemical, civil or mechanical engineering. Students are introduced with a fluidised bed reactor (multiphase flow). This expansion column represents a liquid-solid fluidisation process applied in drinking water treatment processes. The knowledge you will gain will help you develop and improve your competence profile of a highly qualified chemical engineer. Students are informed with short lectures (films): https://doi.org/10.4121/12881009 and a manual (document). Several assignments must be completed based on recorded laboratory experiments.

We have successfully validated the Asphaltene Option in ECLIPSE, using an experimental data set from the literature. We compare our results with a previous Deep Bed Filtration simulation model of the same data. We find that the experimental data can be reproduced by using the surface deposition parameter α only. This provides an important simplification of the Asphaltene Option in ECLIPSE. Moreover, the values of α can be predicted from a pore scale colloid dynamics simulation model using the Stochastic Rotation Dynamics (SRD) technique. It turns out that the values for α obtained in the literature (Wang, 2001) and our own ECLIPSE results are consistent with the predictions from the SRD simulation model. This may give an advantage over other asphaltene deposition models available in the literature.