 Award ID(s):
 1832976
 NSFPAR ID:
 10296808
 Date Published:
 Journal Name:
 Entropy
 Volume:
 22
 Issue:
 10
 ISSN:
 10994300
 Page Range / eLocation ID:
 1126
 Format(s):
 Medium: X
 Sponsoring Org:
 National Science Foundation
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The transition from laminar to turbulent flow is of great interest since it is one of the most difficult and unsolved problems in fluids engineering. The transition processes are significantly important because the transition has a huge impact on almost all systems that come in contact with a fluid flow by altering the mixing, transport, and drag properties of fluids even in simple pipe and channel flows. Generally, in most transportation systems, the transition to turbulence causes a significant increase in drag force, energy consumption, and, therefore, operating cost. Thus, understanding the underlying mechanisms of the laminartoturbulent transition can be a major benefit in many ways, especially economically. There have been substantial previous studies that focused on testing the stability of laminar flow and finding the critical amplitudes of disturbances necessary to trigger the transition in various wallbounded systems, including circular pipes and square ducts. However, there is still no fundamental theory of transition to predict the onset of turbulence. In this study, we perform direct numerical simulations (DNS) of the transition flows from laminar to turbulence in a channel flow. Specifically, the effects of different magnitudes of perturbations on the onset of turbulence are investigated. The perturbation magnitudes vary from 0.001 (0.1%) to 0.05 (5%) of a typical turbulent velocity field, and the Reynolds number is from 5,000 to 40,000. Most importantly, the transition behavior in this study was found to be in good agreement with other reported studies performed for fluid flow in pipes and ducts. With the DNS results, a finite amplitude stability curve was obtained. The critical magnitude of perturbation required to cause transition was observed to be inversely proportional to the Reynolds number for the magnitude from 0.01 to 0.05. We also investigated the temporal behavior of the transition process, and it was found that the transition time or the time required to begin the transition process is inversely correlated with the Reynolds number only for the magnitude from 0.02 to 0.05, while different temporal behavior occurs for smaller perturbation magnitudes. In addition to the transition time, the transition dynamics were investigated by observing the time series of wall shear stress. At the onset of transition, the shear stress experiences an overshoot, then decreases toward sustained turbulence. As expected, the average values of the wall shear stress in turbulent flow increase with the Reynolds number. The change in the wall shear stress from laminar to overshoot was, of course, found to increase with the Reynolds number. More interestingly was the observed change in wall shear stress from the overshoot to turbulence. The change in magnitude appears to be almost insensitive to the Reynolds number and the perturbation magnitude. Because the change in wall shear stress is directly proportional to the pumping power, these observations could be extremely useful when determining the required pumping power in certain flow conditions. Furthermore, the stability curve and wall shear stress changes can be considered robust features for future applications, and ultimately interpreted as evidence of progress toward solving the unresolved fluids engineering problem.more » « less

Wellresolved direct numerical simulations (DNS) have been performed of the flow in a smooth circular pipe of radius
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null (Ed.)Abstract Coherent structures are critical for controlling turbulent boundary layers due to their roles in momentum and heat transfer in the flow. Turbulent coherent structures can be detected by measuring wall shear stresses that are footprints of coherent structures. In this study, wall shear stress fluctuations were measured simultaneously in a zero pressure gradient turbulent boundary layer using two housemade wall shear stress probes aligned in the spanwise direction. The wall shear stress probe consisted of two hotwires on the wall aligned in a Vshaped configuration for measuring streamwise and spanwise shear stresses, and their performance was validated in comparison with a direct numerical simulation result. Relationships between measured wall shear stress fluctuations and streamwise velocity fluctuations were analyzed using conditional sampling techniques. The peak detection method and the variableinterval timeaveraging (VITA) method showed that quasistreamwise vortices were inclined toward the streamwise direction. When events were simultaneously detected by the two probes, stronger fluctuations in streamwise velocity were detected, which suggests that stronger coherent structures were detected. In contrast to the former two methods, the hibernating event detection method detects events with lower wall shear stress fluctuations. The ensembleaveraged mean velocity profile of hibernating events was shifted upward compared to the law of the wall, which suggests low drag status of the coherent structures related with hibernating events. These methods suggest significant correlations between wall shear stress fluctuations and coherent structures, which could motivate flow control strategies to fully exploit these correlations.more » « less

Nearwall flow simulation remains a central challenge in aerodynamics modelling: Reynoldsaveraged Navier–Stokes predictions of separated flows are often inaccurate, and largeeddy simulation (LES) can require prohibitively small nearwall mesh sizes. A deep learning (DL) closure model for LES is developed by introducing untrained neural networks into the governing equations and training in situ for incompressible flows around rectangular prisms at moderate Reynolds numbers. The DLLES models are trained using adjoint partial differential equation (PDE) optimization methods to match, as closely as possible, direct numerical simulation (DNS) data. They are then evaluated outofsample – for aspect ratios, Reynolds numbers and bluffbody geometries not included in the training data – and compared with standard LES models. The DLLES models outperform these models and are able to achieve accurate LES predictions on a relatively coarse mesh (downsampled from the DNS mesh by factors of four or eight in each Cartesian direction). We study the accuracy of the DLLES model for predicting the drag coefficient, nearwall and farfield mean flow, and resolved Reynolds stress. A crucial challenge is that the LES quantities of interest are the steadystate flow statistics; for example, a timeaveraged velocity component $\langle {u}_i\rangle (x) = \lim _{t \rightarrow \infty } ({1}/{t}) \int _0^t u_i(s,x)\, {\rm d}s$ . Calculating the steadystate flow statistics therefore requires simulating the DLLES equations over a large number of flow times through the domain. It is a nontrivial question whether an unsteady PDE model with a functional form defined by a deep neural network can remain stable and accurate on $t \in [0, \infty )$ , especially when trained over comparatively short time intervals. Our results demonstrate that the DLLES models are accurate and stable over long time horizons, which enables the estimation of the steadystate mean velocity, fluctuations and drag coefficient of turbulent flows around bluff bodies relevant to aerodynamics applications.more » « less

Turbulent boundary layers subject to severe acceleration or strong favorable pressure gradient (FPG) are of fundamental and technological importance. Scientifically, they elicit great interest from the points of view of scaling laws, the complex interaction between the outer and inner regions, and the quasilaminarization phenomenon. Many flows of industrial and technological applications are subject to strong acceleration such as convergent ducts, turbines blades and nozzles. Our recent numerical predictions (J. Fluid Mech., vol. 775, pp. 189200, 2015) of turbulent boundary layers subject to very strong FPG with high spatial/temporal resolution, i.e. Direct Numerical Simulation (DNS), have shown a meaningful weakening of the Reynolds shear stresses with an evident logarithmic behavior. In the present study, assessment of three different turbulence models (Shear Stress Transport, kw and SpalartAllmaras, henceforth SST, kw and SA, respectively) in Reynoldsaveraged NavierStokes (RANS) simulations is performed. The main objective is to evaluate the ability of popular turbulence models in capturing the characteristic features present during the quasilaminarization phenomenon in highly accelerating turbulent boundary layers. Favorable pressure gradient is prescribed by a top converging surface (sink flow) with an approximately constant acceleration parameter of K = 4.0 x 10^(6). Furthermore, the quasilaminarization effect on the temperature field is also examined by solving the energy equation and assuming the temperature as a passive scalar. Validation of RANS results is carried out by means of a large DNS dataset.more » « less