Direct numerical simulations of dynamic gas‐solid suspensions

Abstract

We report direct numerical simulation results for gas flow through dynamic suspensions of spherical particles. The simulations are performed using an immersed boundary method (IBM), with careful correction for the grid resolution effect. The flow systems we have studied vary with mean flow Reynolds number, solids volume fraction, as well as particle/gas density ratio. On the basis of the simulation results, the effect of particle mobility on the gas-solid drag force is analyzed and introduced into the existing drag correlation that was derived from simulations of stationary particles. This mobility effect is characterized by the granular temperature, which is a result of the particle velocity fluctuation. The modified drag correlation is considered so-far the most accurate expression for the interphase momentum exchange in computational fluid dynamics models, in which the gas-solid interactions are not directly resolved.

Momentum, heat and mass transfer simulations of bounded dense mono-dispersed gas-particle systems

“…In our work we will consider particle-based interphase transfer coefficients, i.e., quantities that take the effect of individual fluidparticle relative speeds into account. Hence, our approach incorporates aready some (but not all) of the effects studied by Tang et al [25]. What we will leave out in our present study is the effect that the speed of neighbouring particles has on these particle-individual transfer coefficients.…”

“…Such fluctuations have been recently shown to play a significant role in the correct evaluation of the drag coefficient [25]. Specifically, the effect of particle velocity fluctuations can be accounted for by introducing an additional term in the drag expression that depends on the "particle temperature Reynolds number" (defined using the square root of the fluctuating kinetic energy of the particle cloud).…”

Effect of granular temperature and solid concentration fluctuation on the gas-solid drag force: A CFD test

“…Here we test two different correlations available in literature: one is obtained from a theoretical study (Wylie et al, 2003), the other is recently obtained from direct numerical simulation using immersed boundary method (Tang, 2015;Tang et al, 2016b). The drag force correlation of Ergun (1952) is chosen as the starting point to formulate a drag correlation considering the effect of granular temperature following a previous study (Wylie et al, 2003).…”

“…With the rapid development of high-fidelity direct numerical simulation techniques, the accuracy and reliability of various drag models have been examined (van der Hoef et al, 2008;Deen and Kuipers, 2014;Tenneti and Subramaniam, 2014). One of the conclusions is that modification of currently-used drag correlations is needed, to consider the effects of the fluctuation of state variables (Benyahia, 2008;Kriebitzsch, 2011;Kriebitzsch et al, 2013aKriebitzsch et al, , 2013bTang, 2015;Tang et al, 2016b). Models or correlations have also been proposed (Wylie et al, 2003;Zhang and Reese, 2003;Tang et al, 2016b;Third et al, 2016), however, no CFD test has been carried out except that Zhang and Reese has tested the effect of granular temperature on the hydrodynamics of circulating fluidized beds (Zhang and Reese, 2003).…”

“…One of the conclusions is that modification of currently-used drag correlations is needed, to consider the effects of the fluctuation of state variables (Benyahia, 2008;Kriebitzsch, 2011;Kriebitzsch et al, 2013aKriebitzsch et al, , 2013bTang, 2015;Tang et al, 2016b). Models or correlations have also been proposed (Wylie et al, 2003;Zhang and Reese, 2003;Tang et al, 2016b;Third et al, 2016), however, no CFD test has been carried out except that Zhang and Reese has tested the effect of granular temperature on the hydrodynamics of circulating fluidized beds (Zhang and Reese, 2003). To this end, CFD simulations are performed to study the effects of solid concentration fluctuation and granular temperature on the interphase drag force and the resultant CFD results, where the results of DNS are assumed to be perfect and are worked as the benchmark data.…”