Active Flow Control Virtual Maneuvering System Applied to Conventional Airfoil

Dolgopyat, Danny; Seifert, Avi

doi:10.2514/1.j056258

Cited by 22 publications

(14 citation statements)

References 11 publications

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“…The increase of the lift was observed with the AFC active. The comparison of our CFD results with the experimental data [21] shows that the effect of the SaOB actuator was replicated in the simulation.…”

Section: Introductionmentioning

confidence: 65%

“…The SaOB actuator is very effective, especially in the low range of the blowing momentum coefficient, C µ (see Equation 3), in comparison with other types of fluidic actuators (steady, pulsed blowing, sweeping jets, and so on). It can be used for many applications, from flow separation control to maneuvering [21,24].…”

Section: Characterization Of the Saob Actuatormentioning

confidence: 99%

“…The CFD simulations were focused on the internal flow-field and on the flow at the nozzle exit of the single SaOB actuator. These simulations corresponded to the bench-top test of the SaOB in the laboratory, in still-air ambient conditions [21]. The geometrical setup of the detailed actuator interior layout is shown in Figure 2.…”

Section: Cfd Simulation Of the Isolated Saob Actuatormentioning

confidence: 99%

“…Flow direction was set as perpendicular to the geometry of the boundary conditions. The total pressure at the pressure supply boundary was varied, to obtain a wide range of working points for the comparison between CFD computations and the experimental data (available from [21]). The ambient atmospheric conditions were prescribed at the suction ports.…”

Section: Cfd Simulation Of the Isolated Saob Actuatormentioning

confidence: 99%

“…This is done by the CFD simulation using an Unsteady Reynolds Average Navier-Stokes (URANS) solver with a k-ω type turbulence model [19], and using hybrid Reynolds Average Navier-Stokes (RANS)-Large Eddy Simulation (LES) turbulence modeling [20]. The use of two approaches with different levels of complexity, validated using the experimental data [21], allows better insight and confidence in the computational methods. This approach, although still quite heavy on resources, is an alternative to the even more demanding LES simulations [22], which require a computational force that is out of reach, in most cases.…”

Section: Introductionmentioning

confidence: 99%

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Verification of Boundary Conditions Applied to Active Flow Circulation Control

2019

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Inclusion of Active Flow Control (AFC) into Computational Fluid Dynamics (CFD) simulations is usually highly time-consuming and requires extensive computational resources and effort. In principle, the flow inside of the fluidic AFC actuators should be incorporated into the problem under consideration. However, for many applications, the internal actuator flow is not crucial, and only its effect on the outer flow needs to be resolved. In this study, the unsteady periodic flow inside the Suction and Oscillatory Blowing (SaOB) actuator is analyzed, using two CFD methods of ranging complexity (URANS and hybrid RANS-LES). The results are used for the definition and development of the simplified surface boundary condition for simulating the SaOB flow at the actuator’s exit. The developed boundary condition is verified and validated, in the case of a low-speed airfoil with suction applied on the upper (suction) side of the airfoil and oscillatory blowing applied on the lower (pressure) side, close to the trailing edge—a fluidic Gurney flap. Its effect on the circulation is analyzed and compared to the experimental data.

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Section: Introductionmentioning

confidence: 65%

Section: Characterization Of the Saob Actuatormentioning

confidence: 99%

Section: Cfd Simulation Of the Isolated Saob Actuatormentioning

confidence: 99%

Section: Cfd Simulation Of the Isolated Saob Actuatormentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Verification of Boundary Conditions Applied to Active Flow Circulation Control

2019

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Sliding mode estimation and closed‐loop active flow control under actuator uncertainty

Kidambi

MacKunis

Drakunov

et al. 2020

Intl J Robust & Nonlinear

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This article presents a nonlinear closed-loop active flow control (AFC) method, which achieves asymptotic regulation of a fluid flow velocity field in the presence of actuator uncertainty and sensor measurement limitations. To achieve the result, a reduced-order model of the flow dynamics is derived, which utilizes proper orthogonal decomposition (POD) to express the Navier-Stokes equations as a set of nonlinear ordinary differential equations. The reduced-order model formally incorporates the actuation effects of synthetic jet actuators (SJA). Challenges inherent in the resulting POD-based reduced-order model include (1) the states are not directly measurable, (2) the measurement equation is in a nonstandard mathematical form, and (3) the SJA model contains parametric uncertainty. To address these challenges, a sliding mode observer (SMO) is designed to estimate the unmeasurable states in the reduced-order model of the actuated flow field dynamics. A salient feature of the proposed SMO is that it formally compensates for the parametric uncertainty inherent in the SJA model. The SMO is rigorously proven to achieve local finite-time estimation of the unmeasurable state in the presence of the parametric uncertainty in the SJA. The state estimates are then utilized in a nonlinear control law, which regulates the flow field velocity to a desired state. A Lyapunov-based stability analysis is provided to prove local asymptotic regulation of the flow field velocity. To illustrate the performance of the proposed estimation and AFC method, comparative numerical simulation results are provided, which demonstrate the improved performance that is achieved by incorporating the uncertainty compensator. K E Y W O R D S robust control, sliding mode estimation, uncertainty List of Symbols , flow field velocity p , flow field pressure (s) , POD mode (s) , actuation mode x(t) , time-varying Galerkin coefficient

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