Abstract

We present a parallel algorithm and visualization for simulating mass transfer of weakly magnetic nanoparticles during the process of high gradient magnetic separation (HGMS). The dynamics of mass transfer is investigated statistically in terms of particle volume concentration and is described by the continuity equation which is solved numerically using the finite difference. For parallelization, the concentration data are divided into equal parts rowwise which are distributed to parallel processes. Parallel computations are performed by using communication schemes based on message passing interface (MPI) and it can interact with the visualization engine developed by Python. Also, we present the visualization engine that connects to the parallel simulation to view the capture process in real time. We show the performance of the parallel algorithm in terms of parallel speedup, efficiency, and the percentage of the communication overhead. The result shows that we gain almost linear speedup for every test case and the communication overhead per process is no more than 20%. We also show the various test case parameters and their visualizations.

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