Online

Pond, Ian

Mechanical Engineering

2015

MS

Reynolds average Navier-Stokes (RANS) modeling has established itself as a critical design tool in many engineering applications, thanks to its superior computational efficiency. The drawbacks of RANS models are well known, but not necessarily well understood: poor prediction of transition, non-equilibrium flows, mixing and heat transfer, to name the ones relevant to our study. In the present study, we use a direct numerical simulation (DNS) of a reciprocating channel flow driven by an oscillating pressure gradient to test several low- and high-Reynolds' RANS models. Temperature is introduced as a passive scalar to study heat transfer modeling. Low-Reynolds' models manage to capture the overall physics of wall shear and heat flux well, yet with some phase discrepancies, whereas high-Reynolds' models fail. We have derived an integral method for wall shear and wall heat flux analysis, which reveals the contributing terms for both metrics. This method shows that the qualitative agreement appears more serendipitous than driven by the ability of the models to capture the correct physics. The integral method is shown to be more insightful in the benchmarking of RANS models than the typical comparisons of statistical quantities. This method enables the identification of the sources of discrepancies in energy budget equations. For instance, in the wall heat flux, one model is shown to have an out of phase dynamic behavior when compared to the benchmark results, demonstrating a significant issue in the physics predicted by this model. Our study demonstrates that the integral method applied to RANS modeling yields information not previously available that should guide the derivation of physically more accurate models.