Root Mean Square Temperature Fluctuations Research Articles

Large eddy simulation of rotating turbulent flows and heat transfer by the lattice Boltzmann method

Due to its advantage in parallel efficiency and wall treatment over conventional Navier-Stokes equation-based methods, the lattice Boltzmann method (LBM) has emerged as an efficient tool in simulating turbulent heat and fluid flows. To properly simulate the rotating turbulent flow and heat transfer, which plays a pivotal role in tremendous engineering devices such as gas turbines, wind turbines, centrifugal compressors, and rotary machines, the lattice Boltzmann equations must be reformulated in a rotating coordinate. In this study, a single-rotating reference frame (SRF) formulation of the Boltzmann equations is newly proposed combined with a subgrid scale model for the large eddy simulation of rotating turbulent flows and heat transfer. The subgrid scale closure is modeled by a shear-improved Smagorinsky model. Since the strain rates are also locally determined by the non-equilibrium part of the distribution function, the calculation process is entirely local. The pressure-driven turbulent channel flow with spanwise rotation and heat transfer is used for validating the approach. The Reynolds number characterized by the friction velocity and channel half height is fixed at 194, whereas the rotation number in terms of the friction velocity and channel height ranges from 0 to 3.0. A working fluid of air is chosen, which corresponds to a Prandtl number of 0.71. Calculated results are demonstrated in terms of mean velocity, Reynolds stress, root mean square (RMS) velocity fluctuations, mean temperature, RMS temperature fluctuations, and turbulent heat flux. Good agreement is found between the present LBM predictions and previous direct numerical simulation data obtained by solving the conventional Navier-Stokes equations, which confirms the capability of the proposed SRF LBM and subgrid scale relaxation time formulation for the computation of rotating turbulent flows and heat transfer.

Tracking of large-scale structures in turbulent channel with direct numerical simulation of low Prandtl number passive scalar

Channel flow DNS (Direct Numerical Simulation) at friction Reynolds number 180 and with passive scalars of Prandtl numbers 1 and 0.01 was performed in various computational domains. The “normal” size domain was ∼2300 wall units long and ∼750 wall units wide; size taken from the similar DNS of Moser et al. The “large” computational domain, which is supposed to be sufficient to describe the largest structures of the turbulent flows was 3 times longer and 3 times wider than the “normal” domain. The “very large” domain was 6 times longer and 6 times wider than the “normal” domain. All simulations were performed with the same spatial and temporal resolution. Comparison of the standard and large computational domains shows the velocity field statistics (mean velocity, root-mean-square (RMS) fluctuations, and turbulent Reynolds stresses) that are within 1%-2%. Similar agreement is observed for Pr = 1 temperature fields and can be observed also for the mean temperature profiles at Pr = 0.01. These differences can be attributed to the statistical uncertainties of the DNS. However, second-order moments, i.e., RMS temperature fluctuations of standard and large computational domains at Pr = 0.01 show significant differences of up to 20%. Stronger temperature fluctuations in the “large” and “very large” domains confirm the existence of the large-scale structures. Their influence is more or less invisible in the main velocity field statistics or in the statistics of the temperature fields at Prandtl numbers around 1. However, these structures play visible role in the temperature fluctuations at low Prandtl number, where high temperature diffusivity effectively smears the small-scale structures in the thermal field and enhances the relative contribution of large-scales. These large thermal structures represent some kind of an echo of the large scale velocity structures: the highest temperature-velocity correlations are not observed between the instantaneous temperatures and instantaneous streamwise velocities, but between the instantaneous temperatures and velocities averaged over certain time interval.

DNS of turbulent channel flow with conjugate heat transfer at Prandtl number 0.01

Direct Numerical Simulation (DNS) of the fully developed velocity and temperature fields in a turbulent channel flow coupled with the unsteady conduction in the heated walls was carried out. Simulations were performed with passive scalar approximation at Prandtl number 0.01, which roughly corresponds to the Prandtl number of liquid sodium. DNSs were performed at friction Reynolds numbers 180, 395 and 590. The obtained statistical quantities like mean temperatures, profiles of the root-mean-square (RMS) temperature fluctuations for various thermal properties of wall and fluid, and various wall thicknesses were obtained from a pseudo-spectral channel-flow code. Even for the highest implemented Reynolds number the temperature profile in the fluid does not exhibit log-law region and the near-wall RMS temperature fluctuations show Reynolds number dependence. Conjugate heat transfer simulations of liquid sodium–steel system point to a relatively intensive penetration of turbulent temperature fluctuations into the heated wall. Database containing the results is available in a digital form.