Investigation of a Light Boxplane Model Using Tuft Flow Visualization and CFD

Karpovich, E. A.; Gueraiche, Djahid; Natalya, Sergeeva; Alexander, Kuznetsov

doi:10.3390/fluids6120451

Cited by 5 publications

(2 citation statements)

References 16 publications

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“…The procedure outlined above was duplicated for the flow visualization experiments, except that the data acquisition system operator served as the camera operator rather than recording balance data. The tufts were placed at certain spanwise positions on the suction surface (SS) of the wing [35][36][37], using adhesives such as clear glue and tape, and firmly secured so as not to be blown off the model (Figure 12). It should be noted that the tape attained a balance between adhesive strength and thickness.…”

Section: Tuft Flow Visualizationmentioning

confidence: 99%

Low Observable Uncrewed Aerial Vehicle Wind Tunnel Model Design, Manufacturing, and Aerodynamic Characterization

Aleisa,

Kontis,

Nikbay

2024

Aerospace

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Developing wind tunnel models is time consuming, labor intensive, and expensive. Rapid prototyping for wind tunnel tests is an effective, faster, and cheaper method to obtain aerodynamic performance results while considerably reducing acquisition time and cost for the models. Generally, the rapid prototyping models suffer from insufficient stiffness or strength to withstand the loads generated during a wind tunnel test. In the present study, a rapid prototype model reinforced with metallic inserts was produced to experimentally investigate the aerodynamic characteristics of an uncrewed aerial vehicle with various wingtip deflections. The fused deposition modeling process was used to make the outer mold, whereas the metallic parts were produced using laser cutting and the computer numerical control machining process. Then, the model was evaluated both experimentally and numerically. The test campaign presented in this work was conducted in the de Havilland low-speed wind tunnel facility at the University of Glasgow. For better characterization of flow patterns dominated by leading edge vortices, numerical simulations were run using OpenFOAM 8.0 and validated with experimental data. The experimental data obtained from the hybrid rapid-prototyped model agreed well with the numerical results. This demonstrates the efficacy of hybrid rapid-prototyped models in providing reliable results for initial baseline aerodynamic database development within a short period and at a reduced cost for wind tunnel tests.

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Section: Tuft Flow Visualizationmentioning

confidence: 99%

Low Observable Uncrewed Aerial Vehicle Wind Tunnel Model Design, Manufacturing, and Aerodynamic Characterization

Aleisa,

Kontis,

Nikbay

2024

Aerospace

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“…Visually inspecting images of tufted models is still a common way to deduce the flow behavior in the different regions of the examined model, e.g. by identifying reversed or blurry tufts [29][30][31][32]. In [33], a quantitative analysis of tufts' behavior was performed, where statistics about each tuft's orientation were used to derive information about the local flow state.…”

Section: Flow Visualization With Tuftsmentioning

confidence: 99%

Deep learning based instance segmentation of particle streaks and tufts

Tsalicoglou

Roesgen

2022

Meas. Sci. Technol.

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3D Particle Streak Velocimetry (3D-PSV) and surface flow visualization using tufts both require the detection of curve segments, particle streaks or tufts, in images. We propose the use of deep learning based instance segmentation neural networks Mask R-CNN and Cascade Mask R-CNN, trained on fully synthetic data, to accurately identify, segment, and classify streaks and tufts. For 3D-PSV, we use the segmented masks and detected streak endpoints to volumetrically reconstruct flows even when the imaged streaks partly overlap or intersect. In addition, we use Mask R-CNN to segment images of tufts and classify the detected tufts according to their range of motion, thus automating the detection of regions of separated flow while at the same time providing accurate segmentation masks. Finally, we show a successful synthetic-to-real transfer by training only on synthetic data and successfully evaluating real data. The synthetic data generation is particularly suitable for the two presented applications, as the experimental images consist of simple geometric curves or a superposition of curves. Therefore, the proposed networks provide a general framework for instance detection, keypoint detection and classification that can be fine-tuned to the specific experimental application and imaging parameters using synthetic data.

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Research on airfoil surface flow structure testing based on Tuft velocity measurement method

Du,

Gui,

et al. 2024

Proceedings of the Institution of Mechanical Engineers, Part G:

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Fluorescent tuft visualization technology, as a practical and convenient technique, has attracted widespread attention. In this study, a novel fluorescent tuft velocity measurement method is developed based on existing technologies. This method involves the recognition of tuft deflection angles, image transformation, block processing, temporal averaging, and post-visualization processing. Additionally, quantitative measurement of flow field velocity is achieved through tuft calibration. The study begins by comparing tufts of different materials, examining both fluorescent and deflection characteristics to determine optimal tuft parameters. The impact of tuft length on deflection characteristics is also investigated. Finally, the cotton tuft with a length of 7 mm and a diameter of about 0.1 mm was obtained as the best tuft sought in this experiment. Subsequently, at Reynolds number Re = 1.7 × 105, airfoil surface flow field visualization and quantitative analysis are conducted, exploring the relationship between airfoil surface flow structure and aerodynamics at different angles of attack. Finally, a comparative study is conducted between tuft velocity results and oil flow visualization experiments, as well as particle image velocimetry experiments, confirming the feasibility of the fluorescent tuft velocity measurement method.

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Investigation of a Light Boxplane Model Using Tuft Flow Visualization and CFD

Cited by 5 publications

References 16 publications

Low Observable Uncrewed Aerial Vehicle Wind Tunnel Model Design, Manufacturing, and Aerodynamic Characterization

Low Observable Uncrewed Aerial Vehicle Wind Tunnel Model Design, Manufacturing, and Aerodynamic Characterization

Deep learning based instance segmentation of particle streaks and tufts

Research on airfoil surface flow structure testing based on Tuft velocity measurement method

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