Induction Heating of Dispersed Metallic Particles in a Turbulent Flow

Nov 1, 2020
Particle clustering and gas temperature field during induction heating

Motivation

Induction heating of particles in flight is relevant to advanced combustion and energy conversion systems. This DNS study reveals how rapid heating reduces particle clustering and alters turbulent structures, informing the design of more efficient heating systems.

Overview

Inductively heated solid particles dispersed within a decaying isotropic turbulent carrier gas are investigated via Direct Numerical Simulation (DNS). The multiphase simulations account for the compressibility and temperature-dependent viscosity of the carrier gas.

We develop a semi-empirical model for solid particle heating through hysteresis and Joule mechanisms, as these dispersed particles are heated by an external high-frequency alternating magnetic field.

Validation of the semi-empirical induction heating model against the experimental data of Bae et al. (2015). Symbols are measurements for four particle loadings (5 to 20 phr); solid lines are the model, each with its own induction heating timescale. Higher loading heats faster and reaches a higher equilibrium temperature.
Validation of the semi-empirical induction heating model against the experimental data of Bae et al. (2015). Symbols are measurements for four particle loadings (5 to 20 phr); solid lines are the model, each with its own induction heating timescale. Higher loading heats faster and reaches a higher equilibrium temperature.
Gas temperature field (colors) and particle positions (black dots) in a 2D slice of the domain at t = 10, for increasing particle thermal response time (left to right). Hotter gas develops around the particle-laden regions as the thermal fluctuations grow.
Gas temperature field (colors) and particle positions (black dots) in a 2D slice of the domain at t = 10, for increasing particle thermal response time (left to right). Hotter gas develops around the particle-laden regions as the thermal fluctuations grow.

Key results

  • The growth of the Kolmogorov length scale is due to a simultaneous increase in viscosity and decrease in the dissipation rate.
  • The temperature-dependent viscosity of the gas leads to a faster decay of the gas turbulent kinetic energy, mainly through a loss of energy at intermediate wavenumbers.
  • The gas and particle thermal fluctuations are inversely correlated, set by the relative thermodynamic timescales.
  • Two regimes appear in the temperature spectrum: while thermal fluctuations grow, thermal energy increases monotonically in the low-wavenumber range; once they decay, the decay occurs across the entire spectrum.
  • Aggressive heating (shorter induction heating timescales) reduces particle clustering, whereas the particle thermal response time shows no such effect.

Heating de-clusters the particles

Preferential concentration is measured with the radial distribution function. The unheated case shows the strongest clustering at small separations, and the clustering weakens monotonically as the induction heating becomes more aggressive, while changing the particle thermal response time leaves the distribution essentially unchanged.

Radial distribution function of the particles at t = 30 for all cases, with a zoom on the small-separation limit. The unheated reference (I∞T0) clusters the most; shorter induction heating timescales (I10T10 to I01T10) progressively reduce clustering, while varying the thermal response time (I1T10, I1T100, I1T1000) has little effect.
Radial distribution function of the particles at t = 30 for all cases, with a zoom on the small-separation limit. The unheated reference (I∞T0) clusters the most; shorter induction heating timescales (I10T10 to I01T10) progressively reduce clustering, while varying the thermal response time (I1T10, I1T100, I1T1000) has little effect.

Reference

Mouallem, J. and Hickey, J.-P.: Induction heating of dispersed metallic particles in a turbulent flow, International Journal of Multiphase Flow, 132, 103414, 2020. https://doi.org/10.1016/j.ijmultiphaseflow.2020.103414

DNS Turbulence Multiphase Flows Heat Transfer
Joseph Mouallem
Joseph Mouallem
Computational Scientist & Research Software Engineer

Publications

Induction heating of dispersed metallic particles in a turbulent flow
Direct Numerical Simulation of inductively-heated solid particles dispersed in a decaying isotropic turbulent carrier gas.
Joseph Mouallem, Jean-Pierre Hickey
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