Numerical simulation on temperature in wood crib fires

Temperature from burning wood cribs will be simulated in this paper by sub-grid scale model in FDS. A baseline gas phase uncertainty is determined for simulating wood crib fire spread scenarios. This uncertainty is based on a sensitivity analysis of key input parameters and their subsequent effect on key output variables that are important for fire spread. Effects of different grid systems, computing domains and moisture contents on the predictions were studied first and then used to study the gaseous phase sensitivity. The gaseous phase input variables considered are: Smagorinsky constant, Prandtl number, and Schmidt number. The results show that the predictions for temperature have good agreement with experiment with the values of 0.25, 0.7, 0.4 and 5 for Smagorinsky constant, turbulent Schmidt number and turbulent Prandtl number respectively.

Large Eddy Simulation with Energy-Conserving Schemes and the Smagorinsky Model: A Note on Accuracy and Computational Efficiency

Despite advances in turbulence modelling, the Smagorinsky model remains a popular choice for large eddy simulation (LES) due to its simplicity and ease of use. The dissipation in turbulence energy that the model introduces, is proportional to the Smagorinsky constant, of which many different values have been proposed. These values have been derived for certain simulated test-cases while using a specific set of numerical schemes, to obtain the correct dissipation in energy simply because an incorrect value of the Smagorinsky constant would lead to an incorrect dissipation. However, it is important to bear in mind that numerical codes may suffer from numerical or artificial dissipation, which occurs spuriously through a combination of spatio-temporal and iterative errors. The latter can be controlled through more iterations, the former however, depends on the grid resolution and the time step. Recent research suggests that a complete energy-conserving (EC) spatio-temporal discretisation guarantees zero numerical dissipation for any grid resolution and time step. Therefore, using an EC scheme would ensure that dissipation occurs primarily through the Smagorinsky model (and errors in its implementation) than through the discretisation of the Navier-Stokes (NS) equations. To evaluate the efficacy of these schemes for engineering applications, the article first discusses the use of an EC temporal discretisation as regards to accuracy and computational effort, to ascertain whether EC time advancement is advantageous or not. It was noticed that a simple non-EC explicit method with a smaller time step not only reduces the numerical dissipation to an acceptable level but is computationally cheaper than an implicit-EC scheme for wide range of time steps. Secondly, in terms of spatial discretisation on uniform grids (popular in LES), a simple central-difference scheme is as accurate as an EC spatial discretisation. Finally, following the removal of numerical dissipation with any of the methods mentioned above, one is able to choose a Smagorinsky constant that is nearly independent of the grid resolution (within realistic bounds, for OpenFOAM and an in-house code). This article provides impetus to the efficient use of the Smagorinsky model for LES in fields such as wind farm aerodynamics and atmospheric simulations, instead of more comprehensive and computationally demanding turbulence models.

On the self-sustained nature of large-scale motions in turbulent Couette flow

Large-scale motions in wall-bounded turbulent flows are frequently interpreted as resulting from an aggregation process of smaller-scale structures. Here, we explore the alternative possibility that such large-scale motions are themselves self-sustained and do not draw their energy from smaller-scale turbulent motions activated in buffer layers. To this end, it is first shown that large-scale motions in turbulent Couette flow at $Re=2150$ self-sustain, even when active processes at smaller scales are artificially quenched by increasing the Smagorinsky constant $C_{s}$ in large-eddy simulations (LES). These results are in agreement with earlier results on pressure-driven turbulent channel flows. We further investigate the nature of the large-scale coherent motions by computing upper- and lower-branch nonlinear steady solutions of the filtered (LES) equations with a Newton–Krylov solver, and find that they are connected by a saddle–node bifurcation at large values of $C_{s}$. Upper-branch solutions for the filtered large-scale motions are computed for Reynolds numbers up to $Re=2187$ using specific paths in the $Re{-}C_{s}$ parameter plane and compared to large-scale coherent motions. Continuation to $C_{s}=0$ reveals that these large-scale steady solutions of the filtered equations are connected to the Nagata–Clever–Busse–Waleffe branch of steady solutions of the Navier–Stokes equations. In contrast, we find it impossible to connect the latter to buffer-layer motions through a continuation to higher Reynolds numbers in minimal flow units.