A Statistical Analysis Towards Modelling the Fluctuating Torque on Particles in Particleladen Turbulent Shear Flow
Abstract
Dynamics of the particle phase in a particle laden turbulent flow is highly influenced by the fluctuating velocity and vorticity field of the fluid phase. The present work mainly focuses on exploring the possibility of applying a Langevin type of random torque model to predict the rotational dynamics of the particle phase. Towards this objective, direct numerical simulations (DNS) have been carried out for particle laden turbulent shear flow with Reynolds number, $Re_\delta=750$ in presence of subKolmogorov sized inertial particles (Stokes number >>1). The interparticle and wallparticle interactions have also been considered to be elastic. From the particle equation of rotational motion, we arrive at the expression where the fluctuating angular acceleration fluctuation $\alpha'_i$ of the particle is expressed as the ratio of a linear combination of fluctuating rotational velocities of particle $\omega'_i$ and fluid angular velocity $\Omega'_i$ to the particle rotational relaxation time $\tau_r$. The analysis was done using p.d.f plots and JensenShannon Divergence based method to assess the similarity of the particle net rotational acceleration distribution $f(\alpha'_i)$, with (i) the distributions of particle acceleration component arising from fluctuating fluid angular velocity computed in the particleLargrangian frame $f(\Omega'_i/\tau_r)_{pl}$, (ii) fluctuating particle angular velocity $f(\omega'_i/\tau_r)_{pl}$, and (iii) the fluid angular velocity $(\Omega'_i/\tau_r)_{e}$, computed in the fluid Eulerian grids. The analysis leads to the conclusion that $f(\alpha'_i)$ can be modeled with a Gaussian white noise using a preestimated strength which can be calculated from the temporal correlation of $(\Omega'_i/\tau_r)_{e}$.
 Publication:

arXiv eprints
 Pub Date:
 June 2021
 arXiv:
 arXiv:2106.02941
 Bibcode:
 2021arXiv210602941G
 Keywords:

 Physics  Fluid Dynamics;
 Physics  Data Analysis;
 Statistics and Probability
 EPrint:
 19 pages, 30 figures