The boundary layer thickness on a compressor blade suction surface increases rapidly under a adverse pressure gradient and even separates from the blade surface. This paper proposes a novel method for developing the slot inside the blade, with the inlet of the slot located at the leading edge of the blade and the outlet located at the suction surface, using the momentum of the incoming flow to form a high velocity jet to control the boundary layer on the suction surface. For a plane cascade with a diffusion factor of 0.45, the effects of the main slot parametres (such as the shape of the slot and the positions of the slot inlet and outlet) on the flow in the slot, the flow field and the aerodynamic performance of the cascade were investigated with a numerical method. When the aerodynamic performance of cascades with slotted and unslotted blades was compared, it was found that a reasonable slot structure can effectively inhibit the development of the boundary layer on the blade suction surface and greatly improve the aerodynamic performance of the cascade. Based on the influence of the slot parametres of the above cascade, the slot of a plane cascade with a diffusion factor of 0.60 was designed. The numerical calculation results show that the slotted cascade with a diffusion factor of 0.60 outperformed the slotted cascade with a diffusion factor of 0.45. This result showed that the higher the cascade load, the greater the performance improvement from slotting. Furthermore, the unslotted and slotted cascades were tested, and the test results agreed well with the calculations. The aerodynamic performance of the slotted cascade was better than that of the unslotted cascade, which verifies the accuracy of the calculation method and the feasibility of blade slotting for suppressing the development of boundary layers on suction surfaces and reducing flow loss.

With the severity and frequency of significant weather events increasing, methods for alleviating unsteady wind loading for high-rise buildings are gaining interest. This study numerically investigates the three-dimensional flow structures around a canonical high-rise building immersed in an atmospheric boundary layer at different oncoming wind angles, using wall-resolved large eddy simulations. A synthetic jet located on the top surface is used as open-loop active actuation with the aim of suppressing the building's side-force fluctuations when exposed to oncoming wind variations. Three different frequencies of jet forcing are considered, all half an order of magnitude larger than the vortex shedding frequency. The behaviour of the synthetic jet and its effect on the building's unsteady side force, time-averaged flow fields and unsteady flow structures are investigated numerically. The synthetic jet actuation is found to reduce the side-force fluctuation of the building, enhance the downwash flow and successfully attenuate the antisymmetric vortex shedding. This was achieved to different extents across the range of oncoming wind angles considered and may motivate future attempts to explore experimental active control strategies for attenuation of unsteady wind loading.

We design an open-loop active flow control for separated flows around a plunging circular cylinder based on resolvent analysis. The cylinder is plunging at a Strouhal number of 0.36 and a Reynolds number of 500. A linear time-periodic system for control is obtained by linearizing the non-inertial incompressible vorticity equation in the cylinder-fixed frame about a time-averaged base flow. Using the Lyapunouv–Floquet transformation, the linear time-periodic system is transformed into a similar linear time-invariant system, whose resolvent is analysed to obtain an optimal actuating Strouhal number of 0.1464 for the transformed linear system. Simulations show that the active control with tangential actuations is capable of reducing the lift fluctuation by up to 25.7 % when the flow is actuated near the predicted harmonic and subharmonic frequencies.

The flow dynamics of small-width wall-attached jets generated by a Coand-effect nozzle is investigated by unsteady Reynolds-averaged Navier–Stokes simulations. The data are validated by comparison with hot-wire velocity measurements performed on the same flow configurations. The jets exhibit a complex topology strongly influenced not only by the spanwise vorticity (as usually observed in wall jets) but also by a vorticity component normal to the wall and induced by the shear layer developing on the jet sides. This results in an original U-shaped jet whose characteristics are studied in detail for three different mass flow rates. The robustness of the flow topology on a larger range of injected mass flow rates is finally presented and discussed in terms of the injected momentum near the wall. The resulting flow profiles point out that our injector is expected to be a promising candidate for active flow control in gas-turbine compressors for aeronautical and energy applications.

This work proposes a machine-learning or artificial intelligence (AI) control of a low-drag Ahmed body with a rear slant angle φ = 35° with a view to finding strategies for efficient drag reduction (DR). The Reynolds number Re investigated is 1.7 × 105 based on the square root of the body cross-sectional area. The control system comprises of five independently operated arrays of steady microjets blowing along the edges of the rear window and vertical base, twenty-six pressure taps on the rear end of the body and a controller based on an ant colony algorithm for unsupervised learning of a near-optimal control law. The cost function is designed such that both DR and control power input are considered. The learning process of the AI control discovers forcing that produces a DR up to 18 %, corresponding to a drag coefficient reduction of 0.06, greatly exceeding any previously reported DR for this body. Furthermore, the discovered forcings may provide alternative solutions, i.e. a tremendously increased control efficiency given a small sacrifice in DR. Extensive flow measurements performed with and without control indicate significant alterations in the flow structure around the body, such as flow separation over the rear window, recirculation bubbles and C-pillar vortices, which are linked to the pressure rise on the window and base. The physical mechanism for DR is unveiled, along with a conceptual model for the altered flow structure under the optimum control or biggest DR. This mechanism is further compared with that under the highest control efficiency.

Machine learning frameworks such as genetic programming and reinforcement learning (RL) are gaining popularity in flow control. This work presents a comparative analysis of the two, benchmarking some of their most representative algorithms against global optimization techniques such as Bayesian optimization and Lipschitz global optimization. First, we review the general framework of the model-free control problem, bringing together all methods as black-box optimization problems. Then, we test the control algorithms on three test cases. These are (1) the stabilization of a nonlinear dynamical system featuring frequency cross-talk, (2) the wave cancellation from a Burgers’ flow and (3) the drag reduction in a cylinder wake flow. We present a comprehensive comparison to illustrate their differences in exploration versus exploitation and their balance between ‘model capacity’ in the control law definition versus ‘required complexity’. Indeed, we discovered that previous RL control attempts of controlling the cylinder wake were performing linear control and that the wide observation space was limiting their performances. We believe that such a comparison paves the way towards the hybridization of the various methods, and we offer some perspective on their future development in the literature of flow control problems.

We stabilize an open cavity flow experiment to 1 % of its original fluctuation level. For the first time, a multi-modal feedback control is automatically learned for this configuration. The key enabler is automatic in situ optimization of control laws with machine learning augmented by a gradient descent algorithm, named gradient-enriched machine learning control (Cornejo Maceda et al., J. Fluid Mech., vol. 917, 2021, A42, gMLC). The physical interpretation of the feedback mechanism is assisted by a novel cluster-based control law visualization for the flow dynamics and corresponding actuation commands. Starting points of the control experiment are two unforced open cavity benchmark configurations: a narrow-bandwidth regime with a single dominant frequency and a mode-switching regime where two frequencies compete. The flow is forced by a dielectric barrier discharge actuator located at the leading edge and is monitored by a downstream hot-wire sensor over the trailing edge. The feedback law is optimized with respect to the monitored fluctuation level. As reference, the self-oscillations of the mixing layer are mitigated with steady actuation. Then, a feedback controller is optimized with gMLC. As expected, feedback control outperforms steady actuation by achieving a better amplitude reduction with approximately 1 % of the actuation energy required for similarly effective steady forcing. Intriguingly, optimized laws learned for one regime perform well for the other untested regime as well. The proposed control strategy can be expected to be applicable for many other shear flow experiments.

The role played by patterned heating in reducing pressure losses within vertical conduits is investigated. The heating generates flow separation structures which reduce the direct contact between the stream and the sidewalls, thereby limiting the frictional resistance. This also modifies the temperature field thereby inducing a net buoyancy force which may either assist or oppose the pressure gradient required to maintain a fixed flow rate. If the flow Reynolds number is increased sufficiently, the separation structures may be washed away, which means that the pressure-gradient-reducing mechanism is eliminated. The details of the system response are a function of the form of spatial heating distribution, its intensity, the flow Reynolds number and the fluid Prandtl number. Carefully chosen heating of the two walls can induce a pattern interaction effect and a judicious choice of the two patterns can have as much as an order of magnitude effect on the system response.

This experimental study investigated the control induced by a spanwise surface wire on a rigid circular cylinder undergoing vortex-induced vibration (VIV) under the conditions of low mass damping in the lower synchronization branch. Being motivated by the idea of VIV-based energy harvesting from ocean and river flows, this elastically mounted cylinder was immersed in a water channel, leaving a free end at its bottom spanwise end, while the free water surface bounded its top. The cylinder was constrained to vibrate in the cross-stream direction. The wire diameter was 6.25 % of the cylinder diameter. Experimental research was conducted by attaching this large-scale wire along the span of the cylinder at various angular positions ranging from 0° to 180° (with respect to the most upstream point of the cylinder) at a fixed Reynolds number of 104 (based on the cylinder diameter). Simultaneous to measuring the trajectory of the cylinder motion via a laser distance sensor, the instantaneous velocity field in the near wake of the cylinder was obtained using particle image velocimetry. Several VIV response categories were identified depending on the angular position of the wire, which led to the classification of distinct angular ranges for the wire application. Associated with the structural vibrations in these categories, different vortex-formation modes induced by the wire were revealed. For specific wire positions, decreases of up to 98 % and increases of up to 102 % were identified in the oscillation amplitude of the cylinder compared with the amplitude of the clean cylinder under similar conditions.

A set of several exact coherent states in plane Couette flow is computed under spanwise wall oscillation control, with a range of wall oscillation amplitudes and periods $({A_w}, T)$. It is found that the wall oscillation generally stabilises the upper branch of the equilibrium solutions and achieves the corresponding drag reduction, while it influences modestly the lower branch. The stabilisation effect is found to increase with the oscillation amplitude with an optimal time period around ${T^{+}} \approx 100$. The exact coherent states reproduce some key dynamical behaviours of streaks observed in previous studies, while exhibiting the rich coherent structure dynamics that cannot be extracted from a phase average of turbulent states. Visualisation of state portraits shows that the size of the state space supporting turbulent solution is reduced by the spanwise wall oscillation, and the upper-branch equilibrium solutions become less repelling, with many of their unstable manifolds being stabilised. This change of the state space dynamics leads to a significant reduction in lifetime of turbulence. Finally, the main stabilisation mechanism of the exact coherent states is found to be the suppression of the lift-up effect of streaks, explaining why previous linear analyses have been so successful for turbulence stabilisation modelling and the resulting drag reduction.

The unsteady wind loading on high-rise buildings has the potential to influence strongly their structural performance in terms of serviceability, habitability and occupant comfort. This paper investigates numerically the flow structures around a canonical high-rise building immersed in an atmospheric boundary layer, using wall-resolved large eddy simulations. The switching between two vortex shedding modes is explored, and the influence of the atmospheric boundary layer on suppressing symmetric vortex shedding is identified. It is shown that the antisymmetric vortex shedding mode is prevalent in the near wake behind the building, with strong coherence between the periodic fluctuations of the building side force and the antisymmetric vortex shedding mode demonstrated. Two feedback control strategies, exploiting this idea, are designed to alleviate the aerodynamic side-force fluctuations, using pressure sensing on just a single building wall. The sensor response to synthetic jet actuation along the two ‘leading edges’ of the building is characterised using system identification. Both the designed linear controller and the least mean square adaptive controller attenuate successfully the side-force fluctuations when implemented in simulations. The linear controller exhibits a better performance, and its effect on the flow field is to delay the formation of dominant vortices and increase the extent of the recirculation region. Feedback control that requires a smaller sensing area is then explored, with a comparable control effect achieved in the attenuation of the unsteady loading. This study could motivate future attempts to understand and control the unsteady loading of a high-rise building exposed to oncoming wind variations.

This work studies the application of a reinforcement learning (RL)-based flow control strategy to the flow past a cylinder confined between two walls to suppress vortex shedding. The control action is blowing and suction of two synthetic jets on the cylinder. The theme of this study is to investigate how to use and embed physical information of the flow in the RL-based control. First, global linear stability and sensitivity analyses based on the time-mean flow and the steady flow (which is a solution to the Navier–Stokes equations) are conducted in a range of blockage ratios and Reynolds numbers. It is found that the most sensitive region in the wake extends itself when either parameter increases in the parameter range we investigated here. Then, we use these physical results to help design RL-based control policies. We find that the controlled wake converges to the unstable steady base flow, where the vortex shedding can be successfully suppressed. A persistent oscillating control seems necessary to maintain this unstable state. The RL algorithm is able to outperform a gradient-based optimisation method (optimised in a certain period of time) in the long run. Furthermore, when the flow stability information is embedded in the reward function to penalise the instability, the controlled flow may become more stable. Finally, according to the sensitivity analyses, the control is most efficient when the probes are placed in the most sensitive region. The control can be successful even when few probes are properly placed in this manner.

We address a challenge of active flow control: the optimization of many actuation parameters guaranteeing fast convergence and avoiding suboptimal local minima. This challenge is addressed by a new optimizer, called the explorative gradient method (EGM). EGM alternatively performs one exploitive downhill simplex step and an explorative Latin hypercube sampling iteration. Thus, the convergence rate of a gradient based method is guaranteed while, at the same time, better minima are explored. For an analytical multi-modal test function, EGM is shown to significantly outperform the downhill simplex method, the random restart simplex, Latin hypercube sampling, Monte Carlo sampling and the genetic algorithm. EGM is applied to minimize the net drag power of the two-dimensional fluidic pinball benchmark with three cylinder rotations as actuation parameters. The net drag power is reduced by 29 % employing direct numerical simulations at a Reynolds number of $100$ based on the cylinder diameter. This optimal actuation leads to 52 % drag reduction employing Coanda forcing for boat tailing and partial stabilization of vortex shedding. The price is an actuation energy corresponding to 23 % of the unforced parasitic drag power. EGM is also used to minimize drag of the $35^\circ$ slanted Ahmed body employing distributed steady blowing with 10 inputs. 17 % drag reduction are achieved using Reynolds-averaged Navier–Stokes simulations at the Reynolds number $Re_H=1.9 \times 10^5$ based on the height of the Ahmed body. The wake is controlled with seven local jet-slot actuators at all trailing edges. Symmetric operation corresponds to five independent actuator groups at top, middle, bottom, top sides and bottom sides. Each slot actuator produces a uniform jet with the velocity and angle as free parameters, yielding 10 actuation parameters as free inputs. The optimal actuation emulates boat tailing by inward-directed blowing with velocities which are comparable to the oncoming velocity. We expect that EGM will be employed as efficient optimizer in many future active flow control plants as alternative or augmentation to pure gradient search or explorative methods.

Shock-induced vortex breakdown, which occurs on the delta wings at transonic speed, causes a sudden and significant change in the aerodynamic coefficients at a moderate angle-of-attack. Wind-tunnel tests show a sudden jump in the aerodynamic coefficients such as lift force, pitching moment and centre of pressure which affect the longitudinal stability and controllability of the vehicle. A pneumatic jet operated at sonic condition blown spanwise and along the vortex core over a 60° swept delta-wing-body configuration is found to be effective in postponing this phenomenon by energising the vortical structure, pushing the vortex breakdown location downstream. The study reports that a modest level of spanwise blowing enhances the lift by about 6 to 9% and lift-to-drag ratio by about 4 to 9%, depending on the free-stream transonic Mach number, and extends the usable angle-of-attack range by 2°. The blowing is found to reduce the magnitude of unsteady pressure fluctuations by 8% to 20% in the aft portion of the wing, depending upon the method of blowing. Detailed investigations carried out on the location of blowing reveal that the blowing close to the apex of the wing maximises the benefits.

A formal framework to characterize and control/optimize the flow past permeable membranes by means of a homogenization approach is proposed and applied to the wake flow past a permeable cylindrical shell. From a macroscopic viewpoint, a Navier-like effective stress jump condition is employed to model the presence of the membrane, in which the normal and tangential velocities at the membrane are respectively proportional to the so-called filtrability and slip numbers multiplied by the stresses. Regarding the particular geometry considered here, a characterization of the steady flow for several combinations of constant filtrability and slip numbers shows that the flow morphology is dominantly influenced by the filtrability and exhibits a recirculation region that moves downstream of the body and eventually disappears as this number increases. A linear stability analysis further shows the suppression of vortex shedding as long as large values of the filtrability number are employed. In the control/optimization phase, specific objectives for the macroscopic flow are formulated by adjoint methods. A homogenization-based inverse procedure is proposed to obtain the optimal constrained microscopic geometry from macroscopic objectives, which accounts for fast variations of the filtrability and slip profiles along the membrane. As a test case for the proposed design methodology, a cylindrical membrane is designed to maximize the resulting drag coefficient.

We use resolvent analysis to develop a physics-based, open-loop, unsteady control strategy to attenuate pressure fluctuations in turbulent flow over a rectangular cavity with a length-to-depth ratio of $6$ at a Mach number of $1.4$ and a Reynolds number based on cavity depth of $10\,000$. Large-eddy simulations (LES) of the baseline uncontrolled flow reveal the dominance of Rossiter modes II and IV that generate high-amplitude unsteadiness via trailing-edge impingement and oblique shock waves that obstruct the free stream. To suppress the oscillations, we introduce three-dimensional unsteady blowing along the cavity leading edge. We leverage resolvent analysis as a linear model with respect to the baseline flow to guide the selections of the optimal spanwise wavenumber and frequency of the unsteady actuation input for a fixed momentum coefficient of 0.02. Instead of choosing the most amplified resolvent forcing modes, we seek a disturbance that yields sustained amplification of the primary response mode-based kinetic energy distribution over the entire cavity length. This necessary but not sufficient guideline for effective mean flow modification is evaluated using LES of the controlled cavity flows. The most effective control case reduces the pressure root mean square level up to $52\,\%$ along cavity walls relative to the baseline and is approximately twice that achievable by comparable steady blowing. Dynamic mode decomposition on the controlled flows confirms that the optimal actuation input indeed suppresses the formation of the large-scale Rossiter modes. It is expected that the present flow control guideline derived from resolvent analysis will also be applicable at higher Reynolds numbers with the aid of physical insights and further validation.