Numerical investigation of the low-frequency flow oscillation over a NACA-0012 aerofoil at the inception of stall

ElAwad, Yasir A; ElJack, Eltayeb

doi:10.1177/1756829319833687

Cited by 9 publications

(9 citation statements)

References 31 publications

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“…This was identified in the lift forces from load cell measurements and via the POD of the PIV in both the velocity and pressure fields. These frequencies are in excellent agreement with previous experimental and numerical studies for symmetric and cambered airfoils [14,26,29,31].…”

Section: Discussionsupporting

confidence: 91%

“…At angles near peak lift, where the airfoil transitions into a stalled state, energetic low-frequency phenomena are observed [26] at a non-dimensional frequency 𝑓 ★ 𝛼 = 𝑓 𝑐 𝑈 ∞ sin 𝛼 (where 𝑓 is the frequency in Hz and 𝛼 the angle of attack) of 𝑂 (10 −2 ) . This frequency is known to be associated with non-linear separation and reattachment and has been observed numerically [29,30], experimentally [26], and has been predicted via linear instability analysis [14]. Beyond the critical stall angle a dominant frequency at 𝑓 ★ 𝛼 of 𝑂 (10 −1 ) emerges related to flapping shear layers at the leading and trailing edges [31,32].…”

Section: Introductionmentioning

confidence: 75%

“…Further, the growth of the separated region appears to originate at the trailing edge (𝑡/𝑇 ★ = 0.91), possibly indicative of trailing edge stall [8]. The sinusoidal variation of the separated region appears to oscillate along the chord, similar to the laminar separation bubble elongating and bursting as identified numerically by ElAwad and ElJack [29] at similar 𝑓 ★ 𝛼 . The high-energy low-frequency expansion and contraction of the separated region explains the comparatively wide region of TKE (figures 3 and 4) in the TS cases compared to the thin region of TKE concentrated at the incipient shear layer for the DS cases.…”

Section: B Model Dynamics Using Three Modesmentioning

confidence: 88%

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Low-Order Modeling and Sensor-Based Prediction of Stalled Airfoils at Moderate Reynolds Number

Carter

Ganapathisubramani

2023

AIAA Journal

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We present analysis from planar time-resolved particle image velocimetry fields in the streamwise surface-normal plane of turbulent flow surrounding NACA 0012 and NACA 65-410 airfoils at [Formula: see text] focusing on stall phenomena at intermediate to high angles of attack [Formula: see text]. Dominant flow frequencies, identified from the lift spectra obtained from a load cell mounted to the foils, highlight the presence of bluff-body shedding [[Formula: see text] of [Formula: see text], where [Formula: see text] is the frequency, [Formula: see text] the airfoil chord, and [Formula: see text] the freestream velocity] for all cases and prominent low frequencies [[Formula: see text] of [Formula: see text]] for cases in transient stall (TS). A data-driven modeling framework via the proper orthogonal decomposition (POD) reveals that the low frequencies are associated to flow separation and reattachment driven by underlying expansion and contraction normal to the suction surface. Further, the ability to predict the low-order features from (pseudo) pressure probes at the leading, midchord, and trailing edges for both TS and deep stall (DS) cases is quantified using linear stochastic estimation (LSE). The framework pinpoints the centroid of the region of reverse flow with error on the order of 5 and 20% for DS and TS regimes, respectively. Notably, it is found that LSE coefficients governing the low-order POD correlations do not strongly depend on the airfoil geometry. This is demonstrated by the comparative performance of training the LSE using the probes of the NACA 0012 cases to predict the NACA 65-410 velocity fields and vice versa. This work demonstrates the insight afforded by the POD on the low-order features of turbulent stalled airfoils as well as the similarity of such features across geometries toward predicting flow features for potentially any airfoil geometry without the need to retrain an LSE library.

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Section: Discussionsupporting

confidence: 91%

Section: Introductionmentioning

confidence: 75%

Section: B Model Dynamics Using Three Modesmentioning

confidence: 88%

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Low-Order Modeling and Sensor-Based Prediction of Stalled Airfoils at Moderate Reynolds Number

Carter

Ganapathisubramani

2023

AIAA Journal

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“…Such correlations are known to exist from previous CFD simulations and TR-PIV measurement on a NACA0012 aerofoil undergoing stall. It has been shown [7] how, at moderate to high pre-stall angles of attack, breathing modes of the laminar separation bubble existing on the suction side of a NACA0012 can trigger shear layer separation resulting in quasi-periodic oscillations in lift and drag. This is further validated with LES simulations in which they have shown the presence of this separation bubble and how the frequency of oscillation changes at angles of incidence approaching stall.…”

Section: Introductionmentioning

confidence: 99%

Detecting aerofoil separation pre-cursors using on-board optical tracking of flexible pillar sensors

Selim

Brücker

2022

Preprint

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A novel approach for detecting characteristic flow signatures precursory to stall along aerofoils is introduced. It uses arrays of flexible wind-hair like sensors distributed around the aerofoil which are tracked remotely using high-speed imaging and processing. The sensors act as “digital tufts" providing real-time readings of local velocity information with a high temporal resolution. Such sensors are integrated into a NACA0012 aerofoil and tested in a wind-tunnel for varying angles of attack in static tests and dynamically in a ramp-up test. For the static tests, the mean values of the sensor signals provide information on local free-stream velocity and angle of incidence. The fluctuating part of the signals show that at angles approaching separation prominent low frequency oscillations are detected, the magnitudes of which scale with the angle of incidence. These are hypothesised to be linked to breathing modes of the Laminar Separation Bubble causing a shear-layer flapping observed on the sensors. Such low-frequency oscillations were also detected short before separation in the ramp-up studies. As the high-speed cameras are mounted in a simulated “on-board" position, the sensing method could be used for early stall warnings in small-scale UAVs with integrated on-board object tracking cameras.

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“…Bionic micro aerial vehicles (BMAVs), a kind of MAVs, are widely concerned because of their high thrust efficiency and deceptive appearances. In recent years, more and more studies are focused on BMAVs, making great progress in various aspects, such as low Reynolds number aerodynamic mechanism, 1–4 mechanical driving system and prototype, 5,6 and control law design. 7,8 As military and commercial demands grow, flight capabilities of BMAVs such as maneuverability, taking off, and landing manners need to be improved.…”

Section: Introductionmentioning

confidence: 99%

Numerical simulation of flapping airfoil with alula

Bao

Yang

et al. 2020

International Journal of Micro Air Vehicles

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Bionic micro aerial vehicles have become popular because of their high thrust efficiency and deceptive appearances. Leading edge or trailing edge devices (such as slots or flaps) are often used to improve the flight performance. Birds in nature also have leading-edge devices, known as the alula that can improve their flight performance at large angles of attack. In the present study, the aerodynamic performance of a flapping airfoil with alula is numerically simulated to illustrate the effects of different alula geometric parameters. Different alula relative angles of attack β (the angle between the chord line of the alula and that of the main airfoil) and vertical distances h between the alula and the main airfoil are simulated at pre-stall and post-stall conditions. Results show that at pre-stall condition, the lift increases with the relative angle of attack and the vertical distance, but the aerodynamic performance is degraded in the presence of alula compared with no alula, whereas at post-stall condition, the alula greatly enhances the lift. However, there seems to be an optimal relative angle of attack for the maximum lift enhancement at a fixed vertical distance considering the unsteady effect, which may indicate birds can adjust the alula twisting at different spanwise positions to achieve the best flight performance. Different alula geometric parameters may affect the aerodynamic force by modifying the pressure distribution along the airfoil. The results are instructive for design of flapping-wing bionic unmanned air vehicles.

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Numerical investigation of the low-frequency flow oscillation over a NACA-0012 aerofoil at the inception of stall

Cited by 9 publications

References 31 publications

Low-Order Modeling and Sensor-Based Prediction of Stalled Airfoils at Moderate Reynolds Number

Low-Order Modeling and Sensor-Based Prediction of Stalled Airfoils at Moderate Reynolds Number

Detecting aerofoil separation pre-cursors using on-board optical tracking of flexible pillar sensors

Numerical simulation of flapping airfoil with alula

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