scholarly journals Explorative gradient method for active drag reduction of the fluidic pinball and slanted Ahmed body

2021 ◽  
Vol 932 ◽  
Author(s):  
Yiqing Li ◽  
Wenshi Cui ◽  
Qing Jia ◽  
Qiliang Li ◽  
Zhigang Yang ◽  
...  
Keyword(s):  
Reynolds Number ◽  
Drag Reduction ◽  
Flow Control ◽  
Gradient Method ◽  
Active Flow Control ◽  
Latin Hypercube Sampling ◽  
Latin Hypercube ◽  
Downhill Simplex ◽  
Active Flow ◽  
Ahmed Body

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.

Comparison of Two Active Flow Control Mechanisms of Pure Blowing and Pure Suction on a Pitching NACA0012 Airfoil at Reynolds Number of 1 × 106

2018 ◽  
Author(s):  
Ehsan Asgari ◽  
Mehran Tadjfar
Keyword(s):  
Reynolds Number ◽  
Flow Control ◽  
Active Flow Control ◽  
Hysteresis Loops ◽  
Leading Edge ◽  
Control Mechanisms ◽  
Airfoil Surface ◽  
Naca0012 Airfoil ◽  
Maximum Angle ◽  
Active Flow

In this study, we have applied and compared two active flow control (AFC) mechanisms on a pitching NACA0012 airfoil at Reynolds number of 1 × 106 using 2-D computational fluid dynamics (CFD). These mechanisms are continuous blowing and suction which are applied separately on the airfoil which pitches around its quarter-chord in a sinusoidal motion. The location for suction and blowing was determined in our previous study based on the formation of a counter clock-wise vortex near the leading-edge. In our current study, we have compared the effectiveness of pure blowing and pure suction in suppressing the dynamic stall vortex (DSV) which is the main contributor to the drag increase, particularly near the maximum angle of attack (AOA) and in early downstroke motion. The blowing/suction slot is considered as a dent on the airfoil surface which enables the AFC to perform in a tangential manner. This configuration would allow blowing jet to penetrate further downstream and was shown to be more effective compared to a cross-flow orientation. We have compared the two aforementioned mechanisms in terms of hysteresis loops of lift and drag coefficients and have demonstrated the dynamics of flow in controlled and uncontrolled situations.

Active Flow Control of Dynamic Stall by Means of Continuous Jet Flow at Reynolds Number of 1 × 106

2017 ◽  
Vol 140 (1) ◽  
Author(s):  
Mehran Tadjfar ◽  
Ehsan Asgari
Keyword(s):  
Reynolds Number ◽  
Flow Control ◽  
Pressure Difference ◽  
Active Flow Control ◽  
Velocity Ratio ◽  
Dynamic Stall ◽  
Hysteresis Curve ◽  
Small Range ◽  
Active Flow ◽  
The Impact

We have studied the influence of a tangential blowing jet in dynamic stall of a NACA0012 airfoil at Reynolds number of 1 × 106, for active flow control (AFC) purposes. The airfoil was oscillating between angles of attack (AOA) of 5 and 25 deg about its quarter-chord with a sinusoidal motion. We have utilized computational fluid dynamics to investigate the impact of jet location and jet velocity ratio on the aerodynamic coefficients. We have placed the jet location upstream of the counter-clockwise (CCW) vortex which was formed during the upstroke motion near the leading-edge; we have also considered several other locations nearby to perform sensitivity analysis. Our results showed that placing the jet slot within a very small range upstream of the CCW vortex had tremendous effects on both lift and drag, such that maximum drag was reduced by 80%. There was another unique observation: placing the jet at separation point led to an inverse behavior of drag hysteresis curve in upstroke and downstroke motions. Drag in downstroke motion was significantly lower than upstroke motion, whereas in uncontrolled case the converse was true. Lift was significantly enhanced during both upstroke and downstroke motions. By investigating the pressure coefficients, it was found that flow control had altered the distribution of pressure over the airfoil upper surface. It caused a reduction in pressure difference between upper and lower surfaces in the rear part, while substantially increased pressure difference in the front part of the airfoil.

scholarly journals Reinforcement learning for bluff body active flow control in experiments and simulations

2020 ◽  
Vol 117 (42) ◽  
pp. 26091-26098
Author(s):  
Dixia Fan ◽  
Liu Yang ◽  
Zhicheng Wang ◽  
Michael S. Triantafyllou ◽  
George Em Karniadakis
Keyword(s):  
Reinforcement Learning ◽  
Fluid Mechanics ◽  
Drag Reduction ◽  
Flow Control ◽  
Bluff Body ◽  
Control Strategies ◽  
Active Flow Control ◽  
Reduction Process ◽  
Automatic Sequence ◽  
Active Flow

We have demonstrated the effectiveness of reinforcement learning (RL) in bluff body flow control problems both in experiments and simulations by automatically discovering active control strategies for drag reduction in turbulent flow. Specifically, we aimed to maximize the power gain efficiency by properly selecting the rotational speed of two small cylinders, located parallel to and downstream of the main cylinder. By properly defining rewards and designing noise reduction techniques, and after an automatic sequence of tens of towing experiments, the RL agent was shown to discover a control strategy that is comparable to the optimal strategy found through lengthy systematically planned control experiments. Subsequently, these results were verified by simulations that enabled us to gain insight into the physical mechanisms of the drag reduction process. While RL has been used effectively previously in idealized computer flow simulation studies, this study demonstrates its effectiveness in experimental fluid mechanics and verifies it by simulations, potentially paving the way for efficient exploration of additional active flow control strategies in other complex fluid mechanics applications.

Low Reynolds Number Laminar Airfoil with Active Flow Control

2010 ◽  
Author(s):  
Michael Thake ◽  
Nathan Packard ◽  
Carlos Bonilla ◽  
Jeffrey Bons
Keyword(s):  
Reynolds Number ◽  
Flow Control ◽  
Low Reynolds Number ◽  
Active Flow Control ◽  
Low Reynolds ◽  
Active Flow

Active Flow Control of Separated Turbulent Flow Over a Hump Using RANS, DES, and LES

2008 ◽  
Author(s):  
Subhadeep Gan ◽  
Urmila Ghia ◽  
Karman Ghia
Keyword(s):  
Reynolds Number ◽  
Flow Control ◽  
Flow Separation ◽  
Turbulence Modeling ◽  
Active Flow Control ◽  
Separated Flow ◽  
Experimental Results ◽  
Complex Flow ◽  
Active Flow ◽  
Turbulent Separated Flow

Most practical flows in engineering applications are turbulent, and exhibit separation. Losses due to separation are undesirable because they generally have adverse effects on performance and efficiency. Therefore, control of turbulent separated flows has been a topic of significant interest as it can reduce separation losses. It is of utmost importance to understand the complex flow dynamics that leads to flow separation and come up with methods of flow control. In the past, passive flow-control was mostly implemented that does not require any additional energy source to reduce separation losses but it leads to increasing viscous losses at higher Reynolds number. More recent work has been focused primarily on active flow-control techniques that can be turned on and off depending on the requirement of flow-control. The present work is focused on implementing flow control using steady suction in the region of flow separation. The present work is Case 3 of the 2004 CFD Validation on Synthetic Jets and Turbulent Separation Control Workshop, http://cfdval2004.larc.nasa.gov/case3.html, conducted by NASA for the flow over a wall-mounted hump. The flow over a hump is an example of a turbulent separated flow. This flow is characterized by a simple geometry, but, nevertheless, is rich in many complex flow phenomena such as shear layer instability, separation, reattachment, and vortex interactions. The baseline case has been successfully simulated by Gan et al., 2007. The flow is simulated at a Reynolds number of 371,600, based on the hump chord length, C, and Mach number of 0.04. The flow control is being achieved via a slot at approximately 65% C by using steady suction. Solutions are presented for the three-dimensional RANS SST, steady and unsteady, turbulence model and DES and LES turbulence modeling approaches. Multiple turbulence modeling approaches help to ascertain what techniques are most appropriate for capturing the physics of this complex separated flow. Second-order accurate time derivatives are used for all implicit unsteady simulation cases. Mean-velocity contours and turbulent kinetic energy contours are examined at different streamwise locations. Detailed comparisons are made of mean and turbulence statistics such as the pressure coefficient, skinfriction coefficient, and Reynolds stress profiles, with experimental results. The location of the reattachment behind the hump is compared with experimental results. The successful control of this turbulent separated flow causes a reduction in the reattachment length, compared with the uncontrolled case. The effects of steady suction on flow separation and reattachment are discussed.

Large Eddy Simulation of Active Flow Control Over SD7003 at Reynolds Number of 60,000

2020 ◽  
Author(s):  
Djavad Kamari ◽  
Mehran Tadjfar ◽  
Ali Tarokh
Keyword(s):  
Reynolds Number ◽  
Large Eddy Simulation ◽  
Flow Control ◽  
Turbulent Viscosity ◽  
Active Flow Control ◽  
Smagorinsky Model ◽  
Eddy Simulation ◽  
Large Eddy ◽  
Active Flow

Abstract Large Eddy Simulation for active flow control (AFC) by employing synthetic and continuous blowing is done to investigate their effects on resizing separation. The flow around an SD7003 airfoil at Reynolds number of 60,000 and angles of attack of 13° is considered where a widespread separation occurs at post stall. In this work, the Dynamic Smagorinsky model is used as to calculate the turbulent viscosity.

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