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See detailThe effect of liquid bridge model details on the dynamics of wet fluidized beds
Wu, Mingqiu UL; Khinast, Johannes; Radl, Stefan

in AIChE Journal (2018), 64(2), 437-456

Wet fluidized beds of particles in small periodic domains are simulated using the CFD-DEM approach. A liquid bridge is formed upon particle-particle collisions, which then ruptures when the particle ... [more ▼]

Wet fluidized beds of particles in small periodic domains are simulated using the CFD-DEM approach. A liquid bridge is formed upon particle-particle collisions, which then ruptures when the particle separation exceeds a critical distance. The simulations take into account both surface tension and viscous forces due to the liquid bridge. We perform a series of simulations based on different liquid bridge formation models: (1) the static bridge model of Shi and McCarthy, (2) a simple static version of the model of Wu et al., as well as (3) the full dynamic bridge model of Wu et al. We systematically compare the differences caused by different liquid bridge formation models, as well as their sensitivity to system parameters. Finally, we provide recommendations for which systems a dynamic liquid bridge model must be used, and for which application this appears to be less important [less ▲]

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See detailA Model to Predict Liquid Bridge Formation Between Wet Particles Based on Direct Numerical Simulations
Wu, Mingqiu UL; Khinast, Johannes; Radl, Stefan

in AIChE Journal (2016), 62(6), 1877-1987

We study dynamic liquid bridge formation, which is relevant for wet granular flows involving highly viscous liquids and short collisions. Specifically, the drainage process of liquid adhering to two ... [more ▼]

We study dynamic liquid bridge formation, which is relevant for wet granular flows involving highly viscous liquids and short collisions. Specifically, the drainage process of liquid adhering to two identical, non-porous wet particles with different initial film heights is simulated using Direct Numerical Simulations (DNS). We extract the position of the interface, and define the liquid bridge and its volume by detecting a characteristic neck position. This allows us building a dynamic model for predicting bridge volume, and the liquid remaining on the particle surface. Our model is based on two dimensionless mobility parameters, as well as a dimensionless time scale to describe the filling process. In the present work model parameters were calibrated with DNS data. We find that the proposed model structure is sufficient to collapse all our simulation data, indicating that our model is general enough to describe liquid bridge formation between equally sized particles [less ▲]

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