This paper evaluates and modifies the so-called suboptimal control technique for turbulent skin friction reduction through a combination of low-order modelling and direct numerical simulation (DNS). In a previous study, Nakashima et al. (J. Fluid Mech., vol. 828, 2017, pp. 496–526) employed resolvent analysis to show that the efficacy of suboptimal control was mixed across spectral space when the streamwise wall shear stress (case ST) was used as a sensor signal, i.e. specific regions of spectral space showed drag increment. This observation suggests that drag reduction may be attained if control is applied selectively in spectral space. DNS results presented in the present study, however, do not show a significant effect on the flow with selective control. A posteriori analyses attribute this lack of efficacy to a much lower actuation amplitude in the simulations compared to model assumptions. Building on these observations, resolvent analysis is used to design and provide a preliminary assessment of modified control laws that also rely on sensing the streamwise wall shear stress. Control performance is then assessed by means of DNS. The proposed control laws generate as much as $10\,\%$ drag reduction, and these results are broadly consistent with resolvent-based predictions. The physical mechanisms leading to drag reduction are assessed via conditional sampling. It is shown that the new control laws effectively suppress the near-wall quasi-streamwise vortices. A physically intuitive explanation is proposed based on a separate evaluation of clockwise and anticlockwise vortices.

Using the resolvent analysis, we investigate how the near-wall mode primarily responsible for the friction drag is amplified or suppressed depending on the shape of the mean velocity profile of a turbulent channel flow. Following the recent finding by Kühnen et al. (2018), who modified the mean velocity profile to be flatter and attained significant drag reduction, we introduce two types of artificially flattened turbulent mean velocity profiles: one is based on the turbulent viscosity model proposed by Reynolds and Tiederman (1967), and the other is based on the mean velocity profile of laminar flow. A special care is taken so that both the bulk and friction Reynolds numbers are unchanged, whereby only the effect of change in the mean velocity profile can be studied. These mean velocity profiles are used as the base flow in the resolvent analysis, and the response of the wavenumber-frequency mode corresponding to the near-wall coherent structure is assessed via the change in the singular value (i.e., amplification rate). The flatness of the modified mean velocity profiles is quantified by three different measures. In general, the flatter mean velocity profiles are found to result in significant suppression of near-wall mode. Further, increasing the mean velocity gradient in the very vicinity of the wall is found to have a significant importance for the suppression of near-wall mode through mitigation of the critical layer.

In the present study, we numerically manipulate the mean velocity profile of a turbulent channel flow and assess the friction drag reduction performance by using resolvent analysis. Building on the implication obtained from Kühnen et al. (Nat. Phys., Vol. 14, 2017, pp. 386–390) that modifying mean velocity profile flat leads to significant drag reduction, we first introduce two functions for turbulent mean velocity, which can express ‘flattened’ profiles: one is derived based on the turbulent viscosity model proposed by Reynolds & Tiederman (J. Fluid Mech., Vol. 658, 2010, pp. 336–382), and the other is based on the mean velocity profile of laminar flow. These functions are used as the mean velocity profile for the resolvent analysis, and the flatness of the resulting profiles is characterized by two different measures. As a result, we confirm that, friction drag reduction is achieved if the turbulent mean velocity profile is ‘flattened’. However, we also find that the flatness of the mean velocity profile in the center of the channel alone is not enough to evaluate the drag reduction performance.

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