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Three-dimensional flow dynamics of a DC-RF hybrid thermal plasma
A strong and useful plasma field is obtained by combining a radio-frequency (RF) inductively coupled thermal plasma and a direct current (DC) thermal plasma jet. However, a thermal plasma is a unique fluid with intense light emission, high temperature (over 10,000 K), a complicated flow caused by electromagnetic forces and thermal expansion. This feature prevents direct measurements in experiments; therefore, the details of the thermofluid field are still poorly understood. A time-dependent 3-D simulation based on magnetohydrodynamics (MHD) has been attempted to clarify the thermofluid field of the plasma, which is governed by the conservation equations of mass, momentum (Navie-Stokes) and energy coupled with the electromagnetic equations (Maxwell). Simultaneously, the simulation takes into account the temperature-dependent large variations of the thermodynamic and transport properties as a plasma "fluid". Right figure and Left figure show the dynamic behaviors of the thermofluid field and the vortex structure interacting with the electromangeitc field, respectively (Play speed of Left is 1/6 of Right). The colors indicate the temperatures. Such a complicated flow has been predicted from experimental studies; however, it has never been obtained by any axisymmetric 2-D simulations which have been carried out. The present time-dependent 3-D simulation has first successfully obtained these realistic results and revealed the plasma flow dynamics. (Note: Some careful treatments are required to capture vortex structures of thermal plasma flows by numerical simulation. See the next section.) For more information, please see ... Three-dimensional flow dynamics of an argon RF plasma with DC jet assistance: a numerical study, Journal of Physics D: Applied Physics, Vol. 46, No. 1, (January, 2013) 015401 (12 pages). Masaya Shigeta |
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Fundamental problem in numerical simulation of thermal plasmas
As mentioned the above section, simulation of thermal plasma is generally difficult. The entire flow field, in which the plasma at a high temperature and a cold gas at room temperature co-exist, must be treated simultaneously. Widely varied temperatures of 300-12,000 K cause large variations of the transport properties and the density. Meanwhile, the Mach numbers are very small in and around the plasma. Consequently, when a numerical method for a compressible flow simulation is used, the computation takes an extremely long time to obtain a numerical solution for a practical time scale. Therefore, a thermal plasma is treated as an incompressible flow with the density as a temperatur-edependent variable. This condition, which is severe for numerical flow simulations, usually destabilizes the computation (= the computation easily diverges). That is why thermal plasma simulations have often used differencing schemes which suppress numerical instability effectively. However, those schemes also suppress the actual physical instability simultaneously. In consequence, the numerical result does not simulate any realistic flow with vortices as shown in Left figure. On the other hand, schemes that are effective for vortex capture often cause destabilization of computations. Although these two aspects mutually conflict, thermal plasma flows should also be calculated as "simulation" somehow using such schemes to obtain realistic results. As a result, the effort gives a more realistic flow as shown in Right figure. Experiments have predicted that a thermal plasma jet entrains surrounding cold gas by Kelvin-Helmholtz instability for more than 20 years ago. Nevertheless, such a flow has never been simulated because of the numerically severe conditions. Meanwhile, the present effort broke through this problem and gave a successful result. For more information, please see ... Journal of Physics D: Applied Physics, Vol. 49, No. 49, (November, 2016), pp. 493001 (18 pages). Masaya Shigeta Plasma Chemistry and Plasma Processing, (2020), available online. Masaya Shigeta [ New!! ] 3D simulation => Click! |
Simple equations to describe aerosol growth
often-used equations of moments our new equations
Both sets of equations give almost the same results for the time evolutions of the particle number density and mean size of aerosol. Aerosol growth through nucleation, condensation/evaporation and coagulation has usually been described by the simultaneous equations of the moments of the particle size distribution function (PSDF) with its profile assumption (Left) in numerical calculations. This method solves the four complex ordinary differential equations. For this problem, we derived a set of two ordinary differential equations and one algebraic equation (Right) without any profile assumption for the PSDF. In spite of its much simpler formulation and lower computational costs, it gives reasonable a numerical result which is almost the same as that obtained with a more complex set of equations (Left). This mathematical model can be expected to be applied to numerical predictions for not only plasma-aided nanopowder syntheses but also water-droplet generation in a steam turbine (causing erosion), meteorological problems with cloud/fog generation, space design requiring humidity control, etc. Note that the paper below presents the sets of equations applicable to the continuum size regime as well as the free molecular size regime shown above. For more information, please see ... Modelling and Simulation in Materials Science and Engineering, Vol. 20, No. 4, (May, 2012), pp. 045017 (11 pages). Valerian A. Nemchinsky and Masaya Shigeta Plasma Chemistry and Plasma Processing, (2020), available online. Masaya Shigeta [ New!! ] 3D simulation => Click! |
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Silicide Nanopowder Growth in Thermal Plasma Synthesis
These movies show the time evolutions of the particle size-composition distributions of the silicide nanoparticles (nanopowder) synthesized in thermal plasma processing. We have successfully clarified the formation mechanisms including binary nucleation and binary co-condensation of two components (Mo&Si, Co&Si, etc.) by our original mathematical model and solution algorithm "Two-Directional Nodal Method". In Mo-Si system (Initial vapor ratio Mo:Si = 1:1), the molybdenum-rich nanoparticles first grow up and subsequently silicon condenses on the nanoparticles, which results in the significant growth of the nanopowder. On the other hand, in Co-Si system (Initial vapor ratio Co:Si = 1:1), silicon-rich nuclei are first generated and immediately make a rapid growth into nanoparticles due to simultaneous co-condensation of cobalt and silicon. These results show that the nanopowders synthesized in thermal plasma processing have widely ranging sizes and compositions inevitably even under a simple condition (Initial vapor ratio Metal:Si = 1:1). These numerical results agree with the experiment results, which endorses the validity of our model. In addition to molybdenum-silicide (Mo-Si) and cobalt-silicide (Co-Si), the nanoparitcles' formation mechanisms are being studied for titanium-silicide (Ti-Si), iron-silicide (Fe-Si), borides (boron-based intermetallic compound), and binary metal alloys (Fe-Co, Fe-Pt etc.). For more information, please see ... Journal of Applied Physics, Vol. 108, Issue 4, (August, 2010), pp. 043306 (15 pages). Masaya Shigeta and Takayuki Watanabe Powder Technology, Vol. 288, (January 1, 2016), pp. 191-201. Masaya Shigeta, Takayuki Watanabe Nanomaterials, Vol. 6, (March 7, 2016), pp. 43 (10 pages). (Impact factor = 3.553, 5-year impact factor = 4.100) Masaya Shigeta, Takayuki Watanabe |
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Platinum nanopowder growth in the cooling counterflow region of thermal plasma
It is possible to mass-produce nanoparticles (Right figure) by quenching a thermal plasma flow including material vapor (here, platinum vapor) with counterflow cooling (Left figure) promoting nucleation. These numerical results can be obtained by solving the mathematical models coupling the sequential physics of a plasma flow dynamics, material vaporization, and nanopowder growth. Nanoparticles are created through homogeneous nucleation and subsequent heterogeneous condensation growth. The nanoparticles simultaneously grow up by Brownian coagulation between themselves. However, it is still impossible to calculate this collective growth of many nanoparticles for a practical time scale by the "Molecular dynamics" approach even with powerful computers. Meanwhile, an "Aerosol dynamics" equation effectively expresses the growth. Although the equation cannot be solved even numerically yet, it can be calculated by combining with a statistical method. In addition, the calculation also takes into account diffusion, thermophoresis, and convection of nanoparticles as well as transport of material vapor. Many nuclei are generated at the interface between the plasma flow and the counterflow. Being transported downstream, the nuclei grow up into nanoparticles gaining the material vapor. The nanoparticles also increase their sizes by coagulation with each other, and consequently the number of nanoparticles decreases. For more information, please see ... Numerical investigation of cooling effect on platinum nanoparticle formation in inductively coupled thermal plasmas, Journal of Applied Physics, Vol. 103, Issue 7, (April, 2008), pp. 074903 (15 pages). Masaya Shigeta and Takayuki Watanabe |
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Arc plasma dynamics in a TIG welding condition
This movie shows a simulation result of arc plasma in a TIG welding condition. (Left: Temperature, Right: Flow vectors) The arc plasma has Max. temperature ~18000 K and Max. speed ~200 m/s beneath the electrode tip. However, their positions do not coincide. It is also interesting that the sizes of the high-temperature region and the high-speed region are different. The shielding gas supplied from the top is entrained partially into arc plasma, ionized, and then becomes arc plasma. The high-temperature region is almost stationary whereas the low-to-middle-temperature region fluctuates by fluid dynamic instability. |
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Dynamics of two non-neutral plasma rings in a unifrom magnetic field
Fixed coordinate system
Rotating coordinate system
A dynamic motion of two non-neutral plasma rings in a uniform magnetic field was simulated. Finite Larmor radius effect and Transient electric field effect were taken into account as well. Here, electron plasma or positron plasma was supposed as a non-neutral plasma. Colors indicate the speeds in each system |
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