arXiv subjects

Mahendra K Verma

Publications and source records attributed to Mahendra K Verma.

4 recordsLinked to original sources

arXiv2025

Relative accuracy of turbulence simulations using pseudo-spectral and finite difference solvers

For a single timestep, a spectral solver is known to be more accurate than its finite-difference counterpart. However, as we show in this paper, turbulence simulations using the two methods have nearly the same accuracy. In this paper, we simulate forced hydrodynamic turbulence on a uniform 256$^3$ grid for Reynolds numbers 965, 1231, 1515, and 1994. We show that the two methods yield nearly the same evolution for the total energy and the flow profiles. In addition, the steady-state energy spectrum, energy flux, and probability distribution functions of the velocity and its derivatives are very similar. We argue that within a turbulence attractor, the numerical errors are likely to get cancelled (rather than get added up), which leads to similar results for the finite-difference and spectral methods. These findings are very valuable, considering that a parallel finite-difference simulation is more versatile and efficient (for large grids) than its spectral counterpart.

physics.flu-dyn↗

arXiv2022

Predictions of Reynolds and Nusselt numbers in turbulent convection using machine-learning models

In this paper, we develop a multivariate regression model and a neural network model to predict the Reynolds number (Re) and Nusselt number in turbulent thermal convection. We compare their predictions with those of earlier models of convection: Grossmann-Lohse~[Phys. Rev. Lett. \textbf{86}, 3316 (2001)], revised Grossmann-Lohse~[Phys. Fluids \textbf{33}, 015113 (2021)], and Pandey-Verma [Phys. Rev. E \textbf{94}, 053106 (2016)] models. We observe that although the predictions of all the models are quite close to each other, the machine learning models developed in this work provide the best match with the experimental and numerical results.

physics.flu-dyn↗

arXiv2018

Large eddy simulations using renormalized viscosity

In this paper, we have used renormalized viscosity for performing large eddy simulations (LES) of decaying homogeneous and isotropic turbulence inside a periodic cube on coarse grids ($32^3$, $64^3$ and $128^3$) at initial Taylor Reynolds number ${\mathrm{Re}_λ \approx 315} $. The LES results were compared with direct numerical simulation (DNS) results on $512^3$ grid. We observe good agreement between LES and DNS results on the temporal evolution of turbulence kinetic energy ${E(t)}$, kinetic energy spectrum ${E_{u}(k)}$, kinetic energy flux ${Π_u(k)}$. The isosurfaces of velocity magnitude at a given time are similar for DNS and LES. This establishes the suitability of using renormalized viscosity for performing large eddy simulations.

physics.flu-dyn↗

arXiv2016

Near isotropic behaviour of turbulent thermal convection

We investigate the anisotropy in turbulent convection in a 3D box using direct numerical simulation. We compute the anisotropic parameter $A = u_\perp^{2}/(2u_{\parallel}^{2})$, where $u_{\perp}$ and $u_{\parallel}$ are the components of velocity perpendicular and parallel to the buoyancy direction, the shell and ring spectra, and shell-to-shell energy transfers. We observe that the flow is nearly isotropic for the Prandtl number $\mathrm{Pr} \approx 1$, but the anisotropy increases with the Prandtl number. For $\mathrm{Pr}=\infty$, $A \approx 0.3$, thus anisotropy is not very significant even in extreme cases. We also observe that $u_{\parallel}$ feeds energy to $u_{\perp}$ via pressure. The computation of shell-to-shell energy transfers reveals that the energy transfer in turbulent convection is local and forward, similar to hydrodynamic turbulence. These results are consistent with the Kolmogorov's spectrum observed by Kumar et al.~[Phys. Rev. E {\bf 90}, 023016 (2014)] for turbulent convection.

physics.flu-dyn↗