Laminar-to-turbulent flow transition under the action of acoustic oscillations

1983 ◽  
Vol 45 (4) ◽  
pp. 1106-1108 ◽  
Author(s):  
A. N. Shel'pyakov ◽  
A. M. Kasimov ◽  
G. P. Isupov
Keyword(s):  
Turbulent Flow ◽  
Flow Transition ◽  
Acoustic Oscillations

scholarly journals Contactless Localization of Premature Laminar–Turbulent Flow Transitions on Wind Turbine Rotor Blades in Operation

2020 ◽  
Vol 10 (18) ◽  
pp. 6552
Author(s):  
Daniel Gleichauf ◽  
Michael Sorg ◽  
Andreas Fischer
Keyword(s):  
Image Processing ◽  
Laminar Flow ◽  
Turbulent Flow ◽  
State Of The Art ◽  
Flow Transition ◽  
Transition Line ◽  
Systematic Deviation ◽  
Transition Position ◽  
Layer Flow ◽  
Flow Transitions

Thermographic flow visualization enables a noninvasive detection of the laminar–turbulent flow transition and allows a measurement of the impact of surface erosion and contamination due to insects, rain, dust, or hail by quantifying the amount of laminar flow reduction. The state-of-the-art image processing is designed to localize the natural flow transition as occurring on an undisturbed blade surface by use of a one-dimensional gradient evaluation. However, the occurrence of premature flow transitions leads to a high measurement uncertainty of the localized transition line or to a completely missed flow transition detection. For this reason, regions with turbulent flow are incorrectly assigned to the laminar flow region, which leads to a systematic deviation in the subsequent quantification of the spatial distribution of the boundary layer flow regimes. Therefore, a novel image processing method for the localization of the laminar–turbulent flow transition is introduced, which provides a reduced measurement uncertainty for sections with premature flow transitions. By the use of a two-dimensional image evaluation, local maximal temperature gradients are identified in order to locate the flow transition with a reduced uncertainty compared to the state-of-the-art method. The transition position can be used to quantify the reduction of the laminar flow regime surface area due to occurrences of premature flow transitions in order to measure the influence of surface contamination on the boundary layer flow. The image processing is applied to the thermographic measurement on a wind turbine of the type GE 1.5 sl in operation. In 11 blade segments with occurring premature flow transitions and a high enough contrast of the developed turbulence wedge, the introduced evaluation was able to locate the flow transition line correctly. The laminar flow reduction based on the evaluated flow transition position located with a significantly reduced systematic deviation amounts to 22% for the given measurement and can be used to estimate the reduction of the aerodynamic lift. Therefore, the image processing method introduced allows a more accurate estimation of the effects of real environmental conditions on the efficiency of wind turbines in operation.

Experimental Research on Transition and Flow Separation of Laminar Airfoil

2011 ◽  
Vol 301-303 ◽  
pp. 937-942
Author(s):  
Yu Qin Jiao ◽  
Yan Lu ◽  
Chun Sheng Xiao
Keyword(s):  
Laminar Flow ◽  
Turbulent Flow ◽  
Experimental Research ◽  
Flow Separation ◽  
Flow Speed ◽  
Attack Angle ◽  
Experimental Results ◽  
Experimental Device ◽  
Flow Transition

Experimental research on transition and flow separation of laminar airfoil and the influence of transition and flow separation on the performance of laminar airfoil are carried through. The experimental device and instruments used in the research are introduced. It is shown from the experimental results that at certain scope of attack angle, flow transition shifts from 50%c to 30%c on the upper surface of airfoil model along with 1 degree increase of airfoil attack angle; For flow speed of 35m/s and 50m/s with attack angle from 4 degree to 8 degree, flow separation position don’t vary but only separation scope increase; For flow speed of 15m/s laminar flow separation on the upper surface of airfoil take place at attack angle of 4 degree, flow become attaching at attack angle of 6 degree and turbulent flow separation take place at attack angle of 8 degree.

scholarly journals Laminar-Turbulent Transition Localization in Thermographic Flow Visualization by Means of Principal Component Analysis

2021 ◽  
Vol 11 (12) ◽  
pp. 5471
Author(s):  
Daniel Gleichauf ◽  
Felix Oehme ◽  
Michael Sorg ◽  
Andreas Fischer
Keyword(s):  
Image Processing ◽  
Principal Component Analysis ◽  
Turbulent Flow ◽  
Flow Regime ◽  
Principal Component ◽  
Flow Regimes ◽  
Component Analysis ◽  
Flow Transition ◽  
Turbulent Flow Regime ◽  
Laminar And Turbulent Flow

Thermographic flow visualization is a contactless, non-invasive technique to visualize the boundary layer flow on wind turbine rotor blades, to assess the aerodynamic condition and consequently the efficiency of the entire wind turbine. In applications on wind turbines in operation, the distinguishability between the laminar and turbulent flow regime cannot be easily increased artificially and solely depends on the energy input from the sun. State-of-the-art image processing methods are able to increase the contrast slightly but are not able to reduce systematic gradients in the image or need excessive a priori knowledge. In order to cope with a low-contrast measurement condition and to increase the distinguishability between the flow regimes, an enhanced image processing by means of the feature extraction method, principal component analysis, is introduced. The image processing is applied to an image series of thermographic flow visualizations of a steady flow situation in a wind tunnel experiment on a cylinder and DU96W180 airfoil measurement object without artificially increasing the thermal contrast between the flow regimes. The resulting feature images, based on the temporal temperature fluctuations in the images, are evaluated with regard to the global distinguishability between the laminar and turbulent flow regime as well as the achievable measurement error of an automatic localization of the local flow transition between the flow regimes. By applying the principal component analysis, systematic temperature gradients within the flow regimes as well as image artefacts such as reflections are reduced, leading to an increased contrast-to-noise ratio by a factor of 7.5. Additionally, the gradient between the laminar and turbulent flow regime is increased, leading to a minimal measurement error of the laminar-turbulent transition localization. The systematic error was reduced by 4% and the random error by 5.3% of the chord length. As a result, the principal component analysis is proven to be a valuable complementary tool to the classical image processing method in flow visualizations. After noise-reducing methods such as the temporal averaging and subsequent assessment of the spatial expansion of the boundary layer flow surface, the PCA is able to increase the laminar-turbulent flow regime distinguishability and reduce the systematic and random error of the flow transition localization in applications where no artificial increase in the contrast is possible. The enhancement of contrast increases the independence from the amount of solar energy input required for a flow evaluation, and the reduced errors of the flow transition localization enables a more precise assessment of the aerodynamic condition of the rotor blade.

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