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.

Single-Phase Heat Transfer and Fluid Flow in Micropipes

2003 ◽  
Author(s):  
Gian Piero Celata
Keyword(s):  
Heat Transfer ◽  
Experimental Data ◽  
Reynolds Number ◽  
Laminar Flow ◽  
Turbulent Flow ◽  
Transfer Rate ◽  
Single Phase ◽  
Flow Transition ◽  
Laminar And Turbulent Regimes ◽  
Good Agreement

The objective of the present paper is to provide a general overview of the research carried out so far in single-phase heat transfer and flow in capillary (micro) pipes. Laminar flow and laminar-to-turbulent flow transition are analyzed in detail in order to clarify the discrepancies among the results obtained by different researchers. Experiments performed in the ENEA laboratory indicate that in laminar flow regime the friction factor is in good agreement with the Hagen-Poiseuille theory for Reynolds number below 600–800. For higher values of Reynolds number, experimental data depart from the Hagen-Poiseuille law to the side of higher f values. The transition from laminar-to-turbulent flow occurs for Reynolds number in the range 1800–2500. Heat transfer experiments show that heat transfer correlations in laminar and turbulent regimes, developed for conventional (macro) tubes, are not properly adequate for heat transfer rate prediction in microtubes.

Computer Vision and robotics in postal automation

1999 ◽  
Vol 18 (3-4) ◽  
pp. 265-273
Author(s):  
Giovanni B. Garibotto
Keyword(s):  
Image Processing ◽  
Computer Vision ◽  
Pattern Recognition ◽  
Material Handling ◽  
State Of The Art ◽  
Short Description ◽  
The Other ◽  
Functional Requirements ◽  
Postal Automation ◽  
And Robotics

The paper is intended to provide an overview of advanced robotic technologies within the context of Postal Automation services. The main functional requirements of the application are briefly referred, as well as the state of the art and new emerging solutions. Image Processing and Pattern Recognition have always played a fundamental role in Address Interpretation and Mail sorting and the new challenging objective is now off-line handwritten cursive recognition, in order to be able to handle all kind of addresses in a uniform way. On the other hand, advanced electromechanical and robotic solutions are extremely important to solve the problems of mail storage, transportation and distribution, as well as for material handling and logistics. Finally a short description of new services of Postal Automation is referred, by considering new emerging services of hybrid mail and paper to electronic conversion.

scholarly journals InstantDL: an easy-to-use deep learning pipeline for image segmentation and classification

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Dominik Jens Elias Waibel ◽  
Sayedali Shetab Boushehri ◽  
Carsten Marr
Keyword(s):  
Image Processing ◽  
Deep Learning ◽  
Specific Problem ◽  
State Of The Art ◽  
Image Data ◽  
Semantic Segmentation ◽  
Parameter Tuning ◽  
Cellular Processes ◽  
Minimal Effort ◽  
Instance Segmentation

Abstract Background Deep learning contributes to uncovering molecular and cellular processes with highly performant algorithms. Convolutional neural networks have become the state-of-the-art tool to provide accurate and fast image data processing. However, published algorithms mostly solve only one specific problem and they typically require a considerable coding effort and machine learning background for their application. Results We have thus developed InstantDL, a deep learning pipeline for four common image processing tasks: semantic segmentation, instance segmentation, pixel-wise regression and classification. InstantDL enables researchers with a basic computational background to apply debugged and benchmarked state-of-the-art deep learning algorithms to their own data with minimal effort. To make the pipeline robust, we have automated and standardized workflows and extensively tested it in different scenarios. Moreover, it allows assessing the uncertainty of predictions. We have benchmarked InstantDL on seven publicly available datasets achieving competitive performance without any parameter tuning. For customization of the pipeline to specific tasks, all code is easily accessible and well documented. Conclusions With InstantDL, we hope to empower biomedical researchers to conduct reproducible image processing with a convenient and easy-to-use pipeline.

Keel Design for Low Viscous Drag

1987 ◽  
Author(s):  
Clifford J. Obara ◽  
C. P. van Dam
Keyword(s):  
Boundary Layer ◽  
Laminar Flow ◽  
Laminar Boundary Layer ◽  
Leading Edge ◽  
Boundary Layer Transition ◽  
Viscous Drag ◽  
Hydrodynamic Characteristics ◽  
Sweep Angle ◽  
Layer Transition ◽  
Layer Flow

In this paper, foil and planform parameters which govern the level of viscous drag produced by the keel of a sailing yacht are discussed. It is shown that the application of laminar boundary-Layer flow offers great potential for increased boat speed resulting from the reduction in viscous drag. Three foil shapes have been designed and it is shown that their hydro­dynamic characteristics are very much dependent on location and mode of boundary-Layer transition. The planform parameter which strongly affects the capabilities of the keel to achieve laminar flow is lea ding-edge sweep angle. The two significant phenomena related to keel sweep angle which can cause premature transition of the laminar boundary layer are crossflow instability and turbulent contamination of the leading-edge attachment line. These flow phenomena and methods to control them are discussed in detail. The remaining factors that affect the maintainability of laminar flow include surface roughness, surface waviness, and freestream turbulence. Recommended limits for these factors are given to insure achievability of laminar flow on the keel. In addition, the application of a simple trailing-edge flap to improve the hydrodynamic characteristics of a foil at moderate-to-high leeway angles is studied.

The Growth of a Vortex in Turbulent Flow

1965 ◽  
Vol 16 (3) ◽  
pp. 302-306 ◽  
Author(s):  
H. B. Squire
Keyword(s):  
Laminar Flow ◽  
Turbulent Flow ◽  
Eddy Viscosity ◽  
Line Vortex ◽  
Trailing Vortices

SummaryThe growth of a line vortex with time and the spread of a trailing vortex behind a wing due to turbulence are considered. It is shown that the eddy viscosity for this type of motion may be taken to be proportional to the circulation round the vortex and the solution is then similar to the solution for the growth of a vortex in laminar flow. The method is applied to calculate the distance behind a wing for which the trailing vortices will touch one another.

scholarly journals Automatic Microaneurysms Detection Based on Multifeature Fusion Dictionary Learning

2017 ◽  
Vol 2017 ◽  
pp. 1-11 ◽  
Author(s):  
Wei Zhou ◽  
Chengdong Wu ◽  
Dali Chen ◽  
Zhenzhu Wang ◽  
Yugen Yi ◽  
...  
Keyword(s):  
Image Processing ◽  
Diabetic Retinopathy ◽  
Dictionary Learning ◽  
Medical Image ◽  
State Of The Art ◽  
Critical Role ◽  
Medical Image Processing ◽  
Unified Framework ◽  
Semantic Relationships ◽  
Detection Approach

Recently, microaneurysm (MA) detection has attracted a lot of attention in the medical image processing community. Since MAs can be seen as the earliest lesions in diabetic retinopathy, their detection plays a critical role in diabetic retinopathy diagnosis. In this paper, we propose a novel MA detection approach named multifeature fusion dictionary learning (MFFDL). The proposed method consists of four steps: preprocessing, candidate extraction, multifeature dictionary learning, and classification. The novelty of our proposed approach lies in incorporating the semantic relationships among multifeatures and dictionary learning into a unified framework for automatic detection of MAs. We evaluate the proposed algorithm by comparing it with the state-of-the-art approaches and the experimental results validate the effectiveness of our algorithm.

scholarly journals Unravelling turbulence near walls

2009 ◽  
Vol 630 ◽  
pp. 1-4 ◽  
Author(s):  
IVAN MARUSIC
Keyword(s):  
Laminar Flow ◽  
Turbulent Flow ◽  
Numerical Simulations ◽  
Turbulent Flows ◽  
Direct Numerical Simulations ◽  
Aircraft Wing ◽  
Physical Mechanisms ◽  
Drag And Lift

Turbulent flows near walls have been the focus of intense study since their first description by Ludwig Prandtl over 100 years ago. They are critical in determining the drag and lift of an aircraft wing for example. Key challenges are to understand the physical mechanisms causing the transition from smooth, laminar flow to turbulent flow and how the turbulence is then maintained. Recent direct numerical simulations have contributed significantly towards this understanding.

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