For a description of the heat and mass transfer occurring during the drying of grain in a spouted
bed dryer with a draft tube, a CFD modeling technique was used. The Eulerian−Eulerian
multifluid modeling approach was applied to predict gas−solid flow behavior. A heat- and mass-transfer model was added as compiled executable code by means of UDF programming to
FLUENT 6.1, expanding its abilities. Moisture was treated as UDS, and its transport in each
phase and exchange between phases were predicted. The kinetics of drying was described by
classical and diffusional models for periods I and II of drying, respectively. Results of the
simulations were compared with experimental data and with values obtained from various
correlations. CFD simulations predict very well the mass-transfer rate but underpredict the
heat-transfer rate. Predicted values of the Nusselt and Sherwood numbers are above 2, in
agreement with theory. The heat- and mass-transfer rates obtained from the correlations and
CFD simulations were usually of the same order of magnitude, but the values obtained from
the simulations were closer to the experimental data.
We describe a high-performance implementation of the lattice Boltzmann method (LBM) for sparse 3D geometries on graphic processors (GPU). The main contribution of this work is a data layout that allows to minimise the number of redundant memory transactions during the propagation step of LBM. We show that by using a uniform mesh of small three-dimensional tiles and a careful data placement it is possible to utilise more than 70% of maximum theoretical GPU memory bandwidth for D3Q19 lattice and double precision numbers. The performance of our implementation is thoroughly examined and compared with other GPU implementations of LBM. The proposed method performs the best for sparse geometries with good spatial locality.
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