Turbulence Modeling of Complex Flows in CFD

In the last two decades of the 20th century, the world had witnessed the enormous increase in the computational resources. This has brought in the tremendous increase in human knowledge and understanding of complex phenomenon, like turbulence and its modeling among others. The technical development has brought new challenges in engineering design. Whether we limit ourselves to the earthly matters or indulge in space exploration, the simulation of turbulence has become a routine task. Turbulence is a phenomenon in nature comprising of complex eddy structures which can greatly improve heat and mass transfer. The simplistic approach for the computation of turbulent flows is to compute them by Reynolds Averaged Navier-Stokes (RANS) equations based models. But due to the averaging procedure, the inherent unsteadiness of the flow is compromised. On the other hand, Direct Numerical Simulation (DNS) is the best approach for turbulent flow computations, in which no modeling assumptions are invoked and turbulent eddies as small as of the order of Kolmogorov scale are computed. The middle approach between these extremes is the Large Eddy Simulation (LES), in which part of the turbulence is modeled and rest is computed. However, the computational costs and memory requirement are still too large to take it as a general purpose engineering design tool. In this thesis, the effect of changes in inflow conditions on the heat transfer by an impinging jet is investigated using LES. The Dynamic Smagorinsky model proposed by Germano et al. has been used as a subgrid model. Results of several Large Eddy Simulations are reported in the thesis, which are conducted with use of total 244 processors on high performance computing clusters. The inflow conditions explored are: • The fully developed turbulent jet