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The Scientific World Journal
Volume 2014, Article ID 519654, 12 pages
http://dx.doi.org/10.1155/2014/519654
Research Article

Parallel Simulation of HGMS of Weakly Magnetic Nanoparticles in Irrotational Flow of Inviscid Fluid

1Department of Physics, Faculty of Science, Silpakorn University, Nakhon Pathom 73000, Thailand
2Department of Computing, Faculty of Science, Silpakorn University, Nakhon Pathom 73000, Thailand
3Department of Computer Engineering, Faculty of Engineering, Kasetsart University, Bangkok 10900, Thailand

Received 19 December 2013; Accepted 27 March 2014; Published 11 May 2014

Academic Editors: B. Sun and F. Yu

Copyright © 2014 Kanok Hournkumnuard et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

The process of high gradient magnetic separation (HGMS) using a microferromagnetic wire for capturing weakly magnetic nanoparticles in the irrotational flow of inviscid fluid is simulated by using parallel algorithm developed based on openMP. The two-dimensional problem of particle transport under the influences of magnetic force and fluid flow is considered in an annular domain surrounding the wire with inner radius equal to that of the wire and outer radius equal to various multiples of wire radius. The differential equations governing particle transport are solved numerically as an initial and boundary values problem by using the finite-difference method. Concentration distribution of the particles around the wire is investigated and compared with some previously reported results and shows the good agreement between them. The results show the feasibility of accumulating weakly magnetic nanoparticles in specific regions on the wire surface which is useful for applications in biomedical and environmental works. The speedup of parallel simulation ranges from 1.8 to 21 depending on the number of threads and the domain problem size as well as the number of iterations. With the nature of computing in the application and current multicore technology, it is observed that 4–8 threads are sufficient to obtain the optimized speedup.