scholarly journals Towards Accurate Boundary Conditions for CFD Models of Synthetic Jets in Quiescent Flow

Energies ◽  
2020 ◽  
Vol 13 (24) ◽  
pp. 6514
Author(s):  
Andrea Matiz-Chicacausa ◽  
Omar D. Lopez Mejia
Keyword(s):  
Experimental Data ◽  
Boundary Condition ◽  
Computational Modeling ◽  
Flow Control ◽  
Computational Models ◽  
Active Flow Control ◽  
Synthetic Jets ◽  
Complex Flow ◽  
Main Technique ◽  
Lumped Element Model

In this paper, an accurate model to simulate the dynamics of the flow of synthetic jets (SJ) in quiescent flow is proposed. Computational modeling is an effective approach to understand the physics involved in these devices, commonly used in active flow control for several reasons. For example, SJ actuators are small; hence, it is difficult to experimentally measure pressure changes within the cavity. Although computational modeling is an advantageous approach, experiments are still the main technique employed in the study of SJs due to the lack of accurate computational models. The same aspect that represents an advantage over other techniques also represents a challenge for the computational simulations, such as capturing the unsteady phenomena, localized compressible effects, and boundary layer formation characteristic of this complex flow. One of the main challenges in the simulation of SJs is related to the fact that the spatial and temporal scales of the actuator and the corresponding flow control application differed in several orders of magnitude. Hence, in this study we focus on the use of Computational Fluid Dynamics (CFD) and Reduced Order Models (ROM) to develop an accurate yet low-cost model to capture the complexities of the flow of a SJ in quiescent flow. Numerical results show two possible paths for SJ modeling; (1) to obtain a boundary condition to predict velocity profile and jet formation from experimental data of diaphragm’s deformation; and, (2) to predict peak velocity at the jet’s outlet with a ROM approach and to use the physical details of the actuator to develop an accurate boundary condition for CFD. Both approaches are validated through experimental data available in the literature; good agreement between results from CFD, Lumped Element Model (LEM), and experimental data are achieved. Finally, it was concluded that the coupling between LEM and CFD is a novel and accurate approach, which improves CFD due to the advantages of LEM closing the gap between LEM’s lack of flow detail and CFD’s lack of geometrical/physical information of the actuator.

Active flow control, for fixed wings, using synthetic jets

2022 ◽  
Author(s):  
Marcel Ilie ◽  
Jackson Asiatico ◽  
Matthew Chan
Keyword(s):  
Flow Control ◽  
Active Flow Control ◽  
Synthetic Jets ◽  
Active Flow

Accuracy Investigation of Active Flow Control Using Synthetic Jets

2015 ◽  
Vol 741 ◽  
pp. 475-480
Author(s):  
Na Gao ◽  
Chen Pu ◽  
Bao Chen
Keyword(s):  
Flow Control ◽  
Velocity Distribution ◽  
Active Flow Control ◽  
Flow Fields ◽  
Synthetic Jet ◽  
Synthetic Jets ◽  
Experimental Results ◽  
Center Line ◽  
Mean Velocity ◽  
The Mean

2nd order implicit format is implemented in the Navier-Stokes code to deal with instantaneous item unsteady flows. Three simulations are made to testify the method on flow control. First, the external flow fields of synthetic jets are simulated, the mean velocity on the center line, the jet width and velocity distribution are compared well with experimental results. Secondly, the flow fields of synthetic jet in a crossflow are simulated, orifice slot, the mean velocity on the center line and velocity distribution are compared well with experimental results. Finally, the flow control experiments on separation of airfoil are simulated, control methods include steady suction and synthetic jets. Both methods show their ability to favorably effect the flow separation, shortening the length of separation bubble and improving the pressure levels in separation areas in different degrees.

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.

Computational Modeling to Predict Mechanical Function of Joints: Application to the Lower Leg With Simulation of Two Cadaver Studies

2007 ◽  
Vol 129 (6) ◽  
pp. 811-817 ◽  
Author(s):  
Peter C. Liacouras ◽  
Jennifer S. Wayne
Keyword(s):  
Experimental Data ◽  
Computational Modeling ◽  
Computational Models ◽  
Three Dimensional ◽  
Lower Leg ◽  
Joint Kinematics ◽  
Syndesmotic Injury ◽  
Joint Function ◽  
Calcaneofibular Ligament ◽  
Cadaver Studies

Computational models of musculoskeletal joints and limbs can provide useful information about joint mechanics. Validated models can be used as predictive devices for understanding joint function and serve as clinical tools for predicting the outcome of surgical procedures. A new computational modeling approach was developed for simulating joint kinematics that are dictated by bone/joint anatomy, ligamentous constraints, and applied loading. Three-dimensional computational models of the lower leg were created to illustrate the application of this new approach. Model development began with generating three-dimensional surfaces of each bone from CT images and then importing into the three-dimensional solid modeling software SOLIDWORKS and motion simulation package COSMOSMOTION. Through SOLIDWORKS and COSMOSMOTION, each bone surface file was filled to create a solid object and positioned necessary components added, and simulations executed. Three-dimensional contacts were added to inhibit intersection of the bones during motion. Ligaments were represented as linear springs. Model predictions were then validated by comparison to two different cadaver studies, syndesmotic injury and repair and ankle inversion following ligament transection. The syndesmotic injury model was able to predict tibial rotation, fibular rotation, and anterior/posterior displacement. In the inversion simulation, calcaneofibular ligament extension and angles of inversion compared well. Some experimental data proved harder to simulate accurately, due to certain software limitations and lack of complete experimental data. Other parameters that could not be easily obtained experimentally can be predicted and analyzed by the computational simulations. In the syndesmotic injury study, the force generated in the tibionavicular and calcaneofibular ligaments reduced with the insertion of the staple, indicating how this repair technique changes joint function. After transection of the calcaneofibular ligament in the inversion stability study, a major increase in force was seen in several of the ligaments on the lateral aspect of the foot and ankle, indicating the recruitment of other structures to permit function after injury. Overall, the computational models were able to predict joint kinematics of the lower leg with particular focus on the ankle complex. This same approach can be taken to create models of other limb segments such as the elbow and wrist. Additional parameters can be calculated in the models that are not easily obtained experimentally such as ligament forces, force transmission across joints, and three-dimensional movement of all bones. Muscle activation can be incorporated in the model through the action of applied forces within the software for future studies.

Closed-loop Active Flow Control of Stall Separation using Synthetic Jets

2013 ◽  
Author(s):  
Byunghyun Lee ◽  
Minhee Kim ◽  
Byounghun Choi ◽  
Chongam Kim ◽  
H Jin Kim ◽  
...  
Keyword(s):  
Flow Control ◽  
Closed Loop ◽  
Active Flow Control ◽  
Synthetic Jets ◽  
Active Flow

scholarly journals Active Flow Control on a UCAV Planform Using Synthetic Jets

2016 ◽  
Vol 17 (3) ◽  
pp. 315-323 ◽  
Author(s):  
Junhee Lee ◽  
Byunghyun Lee ◽  
Minhee Kim ◽  
Chongam Kim
Keyword(s):  
Flow Control ◽  
Active Flow Control ◽  
Synthetic Jets ◽  
Active Flow
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