Journal of Flow Control, Measurement & Visualization

Volume 6, Issue 2 (April 2018)

ISSN Print: 2329-3322   ISSN Online: 2329-3330

Numerical Study of Axial Magnetic Effects on a Turbulent Thermal Plasma Jet for Nanopowder Production Using 3D Time-Dependent Simulation

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DOI: 10.4236/jfcmv.2018.62010    1,187 Downloads   2,545 Views  Citations
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ABSTRACT

3D time-dependent simulations are performed using a computational method suitable for thermal plasma flows to capture a turbulent field induced by a thermal plasma jet and steep gradients in nanopowder distributions. A mathematical model with a simple form is developed to describe effectively simultaneous processes of growth and transport of nanopowder in/around a thermal plasma flow. This growth-transport model obtains the spatial distributions of the number density and mean diameter of nanopowder with a lower computational cost. The results show that an argon thermal plasma jet induces multi-scale vortices even far from itself. A double-layer structure of high-temperature thicker vortex rings surrounded by low-temperature thinner vortex rings is generated in the upstream region. As the vortex rings flow downstream, the high-temperature thicker vortex rings deform largely whereas the low-temperature thinner vortex rings break up into smaller vortices. Nanopowder is generated at the fringe of plasma and transported widely outside the plasma region. The nanopowder grows up collectively by coagulation decreasing particle number as well as homogeneous nucleation and heterogeneous condensation. When a uniform magnetic field is applied in the axial direction, a longer and straighter thermal plasma jet is obtained because of Lorentz force and Joule heating. Larger nanopowder is produced around the plasma because turbulent diffusions of silicon vapor and nanoparticles by vortices are suppressed as well.

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Shigeta, M. (2018) Numerical Study of Axial Magnetic Effects on a Turbulent Thermal Plasma Jet for Nanopowder Production Using 3D Time-Dependent Simulation. Journal of Flow Control, Measurement & Visualization, 6, 107-123. doi: 10.4236/jfcmv.2018.62010.

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