This work was supported by the Young Scientists Fund of the National Natural Science Foundation of China (51709082) and the Fundamental Research Funds for the Central Universities (2018B13014).

1. Laboratory safety check
<ol>
	<li>Review the safety rules relating to the use of the laser and flume system.</li>
	<li>Ensure that the safety training requirements of the laboratory have been met. 
	NOTE: In this experiment, a set of 5W air-cooling continuous wave laser with a wavelength of 532 nm and a glass-sided straight flume (Figure 1) with dimensions of 11 m length, 0.6 m width, and 0.6 m depth are used. The basic safety recommendations for these two apparatuses are as follows:
	<ol>
		<li>Check the potential reflection surfaces in the laser line-of-sight prior to testing; wear safety goggles when operating the laser device.</li>
		<li>Avoid having eyes at the level of the laser beam during the experiments and be careful of reflected laser lights when handling the optical elements or reflective tools.</li>
		<li>Ensure that the water hose does not fall off and that there is always no water overflowing from the flume.</li>
	</ol>
	</li>
</ol>
2. Flume and seabed model setup
<ol>
	<li>Prepare the erodible seabed model located in the middle of the flume. 
	NOTE: The sediment material used in this study was a uniformly distributed medium sand with a median grain size d50 = 0.45 mm, relative submerged particle density &#916; = 1.65 and geometric standard deviation &#963;g = 1.30.</li>
	<li>Compact and level the seabed using a sand leveler.</li>
	<li>Slowly fill the flume with a water hose and make sure that a flat seabed surface is intact during the filling process; stop filling when the water level has reached a depth of 0.4 m above the seabed.</li>
	<li>Clear the flume top platform and glass for setting up the pipeline model and PIV system.</li>
</ol>

3. Pipeline model and vibration system setup

<ol>
	<li>Use a prefabricated pipeline model in the form of an acrylic cylinder with a diameter of 35 mm and a length of 0.56 m.</li>
	<li>Mount the pipeline model on an aluminum supporting frame, which, in turn, is connected by two springs to a moveable pole on another fixed frame that is locked on the top rails of the flume, as illustrated in Figure 2. Fix the supporting frame inside the fixed frame by using four bearings to ensure that the supporting frame could freely vibrate only along the vertical direction (Figure 2).</li>
	<li>Use a connecting rod to tie the moveable pole to a servo motor mounted on the top of the fixed frame. In this study, the weight of the assembled vibrating system, including the pipeline model and the aluminum frames, is 1.445 kg, which has an equivalent mass ratio (m*) of 2.682; a natural frequency (fN) of 0.82 Hz; and damping ratio (&#950;) of 0.124.</li>
	<li>Adjust the moveable pole and the supporting frame to obtain a certain gap ratio between the pipeline and seabed. &#160;In this study, G/D =1, where G is the vertical distance between the bottom of the pipeline and initial seabed surface; and D is the pipeline diameter.</li>
	<li>Turn on the servo motor to induce a forced vibration on the pipeline; adjust the supporting frames and four bearings to ensure that the pipeline vibration is along the vertical direction. Turn off the servo motor when adjustments of the supporting frames have completed.</li>
	<li>Compact and level the seabed again before running the experiment if the seabed model is disturbed in 3.5.</li>
</ol>

4. PIV setup

<ol>
	<li>Place the laser device on the top of the flume and install the laser sheet forming optics.</li>
	<li>Turn on the laser device and adjust the laser sheet forming optics so that an illuminated flat sheet inside the field-of-interest is formed. 
	NOTE: In this study, the illuminated green laser sheet is 1.5 mm thick, parallel to the flume glass walls and is cast downward into the water along the centerline of the flume. The field-of-interest of this study refers to the interaction region of the pipeline-fluid-seabed and is confined to the right half side of the pipeline. The shadow of the pipeline will be seen on the left half side of the pipeline.</li>
	<li>Set up the high-speed camera. 
	NOTE: For this study, a high-speed camera with 12-gigabyte-memory storage and a maximum resolution of 2.3 Mpx (1920&#215;1200) is used (e.g., Phantom Miro LAB 320). The detailed operation procedures are as follows:
	<ol>
		<li>Mount the lens with appropriate focal length on the high-speed camera. Screw the high-speed camera onto a height-adjustable tripod; adjust the camera to the level of the observation region with its axis perpendicular to the illuminated laser sheet. 
		NOTE: This study uses a 60 mm prime lens at its maximum aperture of f/2.8.</li>
		<li>Connect the camera to the computer by using an Ethernet cable and turn on the camera control software (e.g., Phantom PCC 2.6); turn on the camera and connect it to the computer in the camera control software interface.</li>
		<li>Adjust the tripod to ensure that the field-of-view of the camera covers the pipeline-fluid-seabed interaction region; level the camera using the built-in bubble level on the tripod; tune the focus ring on the lens to ensure that the laser sheet is clear on the focal plane.</li>
	</ol>
	</li>
</ol>

5. Experimental setup optimization and calibration

<ol>
	<li>Add PIV seeding particles to the test section of the flume. 
	NOTE: The seeding particles used in this study were aluminum powders with a diameter of 10 &#956;m and a specific density of 2.7.</li>
	<li>Enhance the light intensity of the laser sheet if necessary.</li>
	<li>Verify the focus of the camera by observing the illuminated seeding particles on the laser sheet through a live camera view on the computer; fine-tune the focus ring, if necessary, to ensure that the seeding particles are sharp and in focus.</li>
	<li>Place a calibration ruler inside the field-of-view on the plane of the laser sheet and capture one calibration image. 
	NOTE: The adopted resolution of the image in this study was 1600 &#215; 1200 pixels.</li>
	<li>Select a proper sampling rate for data collection. 
	NOTE: The chosen sampling rate should ensure that the seeding particle displacement within a pair of images is less than 50% of the maximum interrogation window length. In this study, the maximum interrogation window size is 32 &#215; 32 pixels and the adopted sampling rate is 200 frames per second.</li>
	<li>Turn off the laser and camera when steps 5.1-5.5 are completed.</li>
</ol>

6. Running the experiment and data collection

<ol>
	<li>Place a transparent acrylic plate (20 mm thick) below the laser source and on the water surface, to suppress water surface fluctuations, and ensure tranquil optical access for the laser light.</li>
	<li>Turn on the servo motor to induce forced vibrations on the pipeline model. 
	NOTE: In this study, the induced frequency of the servo motor is f0 = 0.3 Hz.</li>
	<li>Keep the vibration system running for (t =)1440 min to obtain a quasi-equilibrium scour hole beneath the vibrating pipeline.</li>
	<li>Turn on the laser and adjust the output power to the optimized intensity. Turn on the camera and camera control software and apply the calibrated settings to the camera. Turn off the background lights in the laboratory.</li>
	<li>Start recording the seeding particle-laden flow field image with the sampling rate selected in 5.6 by clicking the Capture Bottom in the camera software control software. 
	NOTE: For every single recording in this study, the camera storage allows 1,000 images to be captured.</li>
	<li>Once the data collection is completed, review the recorded image quality and check if the seeding particle density per interrogation window (32&#215;32 pixels) is greater than 8. Save the recorded file if satisfied, otherwise, the seeding density is increased by slowly injecting seeding solutions in the observation region, and repeat steps 6.3-6.5.</li>
	<li>Repeat steps 6.3-6.5 to collect more data sets. 
	NOTE: For this study, more than 20,000 images were taken to ensure that enough raw data are obtained for calculating the flow velocities, vorticities, turbulence, and near-boundary stresses.</li>
	<li>Turn off the laser device, camera, and server motor when all the data collections are completed; turn on the background lights in the laboratory.</li>
</ol>

7. Data processing

<ol>
	<li>Open the software; click the File folder button on the toolbar and load the calibration image taken in step 5.4. 
	NOTE: Use the data processing program for pipeline displacement tracking and flow field calculations software (e.g., PISIOU).</li>
	<li>Click the Scale setup button on the toolbar; measure a known distance on the calibration image to calculate the scale of the image. 
	NOTE: The calculated image scale was 0.1694 mm/pixel.</li>
	<li>Click the Origin button on the toolbar; set the origin of the coordinates on each image.</li>
	<li>Extract the displacement time-series of the vibrating pipeline from the recorded images.
	<ol>
		<li>Load the raw images taken in step 6. Then click on the Parameter panel, enter the number of data files and the sample rate.</li>
		<li>Apply the Low pass filter in the Image filter menu. 
		NOTE: This operation will allow the edge of the pipeline (target to be tracked) to be readily recognized on the processed images (see Figure 3a).</li>
		<li>In the toolbar, click the PTV module. Then click Tracing point button, select the center point of the pipeline. Go to PTV tools, adjust Gamma, Light Gate and Median Filter to single out the pipeline outline in the image. Click the Object tracking button on the toolbar; select the target region (i.e. the pipeline) on the processed image and track the displacement of the vibrating pipeline from consecutive processed images; record the displacement time-series, &#951;(t), of the vibrating pipeline for subsequent flow field data processes (see Figure 4).</li>
		<li>Export and save the pipeline displacement time-series data for further calculations.</li>
	</ol>
	</li>
	<li>Determine instantaneous velocity fields from the recorded images.
	<ol>
		<li>Go to PTV tools, click Default button to resume the raw image for subsequent PIV analysis. Deactivate the PTV module by clicking the PTV module. Open the Parameter panel on the toolbar; specify the velocity vector calculation parameter. 
		NOTE: In this study, a multi-pass iteration process is adopted as the interrogation windows, which started from 32 &#215; 32 pixels, then passed with 16 &#215; 16 pixels, and ended with 8 &#215; 8 pixels; all passes use a 50% overlap between adjacent sub-windows.</li>
		<li>Apply the Laplacian filter function in the Image filter menu to the raw images to highlight the seeding particles and filter out undesirable scattering light (see Figure 3c).</li>
		<li>Click the Boundary button on the toolbar, set the geometric mask on the images to exclude the seabed region for further calculation.&#160;Click Boundary Save button to save the boundary data.</li>
		<li>Click the Run button on the toolbar to calculate the instantaneous velocity fields for different vibrating phases using the cross-correlation method. 
		NOTE: In this study, a multi-time interval algorithm is adopted to reduce the bias error due to high velocity gradient in the flow field (see Figure 5). The adopted multiple-time intervals for cross-correlation calculations are &#916;t, 3&#916;t, 9&#916;t and 21&#916;t (&#916;t = 5 ms). The satisfactory correlation criterion is greater than 70%.</li>
		<li>Export and save the instantaneous velocity fields data for further analysis.</li>
	</ol>
	</li>
	<li>Determine the phase-averaged velocity fields from the calculated instantaneous velocity fields with the algorithm as described in Newland 199429,30&#160; and Hsieh 200828. 
	NOTE: The calculation procedures for this step is described as follows:
	<ol>
		<li>Apply the wavelet transform function to the displacement time-series, &#951;(t), of the vibrating pipeline to obtain the instantaneous phase for each instantaneous velocity field. The wavelet transform function is defined as: 
		<img alt="Equation 1" src="/files/ftp_upload/59745/59745eq1.jpg" />&#160; &#160; &#160; &#160; &#160; &#160; &#160; &#160; &#160; &#160;(1) 
		where W&#936; is wavelet coefficient; &#945; and &#946; are the scale and translation parameters, respectively; the function &#936; is the Morlet function and is calculated as <img alt="Equation 2" src="/files/ftp_upload/59745/59745eq2.jpg" />; the superscript &#8220;*&#8221; denotes the complex conjugate. The instantaneous phases, &#934;, of the vibrating pipeline that correspond to the different pipeline displacements can be calculated from: 
		<img alt="Equation 3" src="/files/ftp_upload/59745/59745eq3.jpg" />&#160;&#160; &#160; &#160; &#160; &#160; &#160; &#160; &#160; (2)</li>
		<li>Average the instantaneous velocity fields with the same phase to obtain the phase-averaged velocity fields.</li>
		<li>Determine the flow vorticity, &#969;2, in the calculated phase-averaged velocity fields from: 
		<img alt="Equation 4" src="/files/ftp_upload/59745/59745eq4.jpg" />&#160; &#160;&#160; &#160; &#160; &#160; &#160;(3) 
		where <img alt="Equation 5" src="/files/ftp_upload/59745/59745eq5.jpg" /> and <img alt="Equation v" src="/files/ftp_upload/59745/59745eqv.jpg" /> are phase-averaged velocities along x and y directions.</li>
	</ol>
	</li>
	<li>Load the calculated phase-averaged velocity and vorticity data in Tecplot software for visualization.</li>
	<li>Determine the near-boundary shear and normal stresses from the calculated instantaneous velocity fields with the algorithm as described in Hsieh et al. 2016 9. The calculation procedures for this step is described as follows:
	<ol>
		<li>Extract the near-boundary velocity data (0-5 mm above the seabed) from the calculated phase-averaged velocity flow fields.</li>
		<li>Compute the near-boundary shear stresses, ts and normal stresses, tn, along the scour profile (approximately 2 mm above the scour hole boundary) for different phases within one vibrating cycle. Note: The calculation equations are as follows: 
		<img alt="Equation 7" src="/files/ftp_upload/59745/59745eq7.jpg" />, <img alt="Equation 8" src="/files/ftp_upload/59745/59745eq8.jpg" />&#160; &#160; &#160; &#160; &#160; &#160; &#160; (4) 
		where, &#956; = dynamic viscosity of the fluid (herein taken as 1&#215;10-3 Pa&#8729;s); up = near-boundary velocity parallel to the bed; un = near-boundary velocity perpendicular to the bed; n = normal distance from the bed.</li>
	</ol>
	</li>
	<li>Load the calculated near-boundary shear and normal stresses data in a software (e.g., Tecplot) for visualization.</li>
</ol>

<ol>
	<li>Freds&#248;e, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Pipeline-seabed+interaction.">Pipeline-seabed interaction.</a> Journal of Waterway, Port, Coastal, and Ocean Engineering. 142 (6), 03116002 (2016).</li><li>Larsen, B. E., Fuhrman, D. R., Sumer, B. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Simulation+of+wave-plus-current+scour+beneath+submarine+pipelines.">Simulation of wave-plus-current scour beneath submarine pipelines.</a> Journal of Waterway, Port, Coastal, and Ocean Engineering. 142 (5), 04016003 (2016).</li><li>Chiew, Y. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Mechanics+of+local+scour+around+submarine+pipelines.">Mechanics of local scour around submarine pipelines.</a> Journal of Hydraulic Engineering. 116 (4), 515-529 (1990).</li><li>Chiew, Y. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Prediction+of+maximum+scour+depth+at+submarine+pipelines.">Prediction of maximum scour depth at submarine pipelines.</a> Journal of Hydraulic Engineering. 117 (4), 452-466 (1991).</li><li>Gao, F. -. P., Yang, B., Wu, Y. -. X., Yan, S. -. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Steady+current+induced+seabed+scour+around+a+vibrating+pipeline.">Steady current induced seabed scour around a vibrating pipeline.</a> Applied Ocean Research. 28 (5), 291-298 (2006).</li><li>Wu, Y., Chiew, Y. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Mechanics+of+three-dimensional+pipeline+scour+in+unidirectional+steady+current.">Mechanics of three-dimensional pipeline scour in unidirectional steady current.</a> Journal of Pipeline Systems Engineering and Practice. 4 (1), 3-10 (2013).</li><li>Zhu, Y., Xie, L., Su, T. -. C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Visualization+tests+on+scour+rates+below+pipelines+in+steady+currents.">Visualization tests on scour rates below pipelines in steady currents.</a> Journal of Hydraulic Engineering. 145 (4), 04019005 (2019).</li><li>Guan, D., Hsieh, S. -. C., Chiew, Y. -. M., Low, Y. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Experimental+study+of+scour+around+a+forced+vibrating+pipeline+in+quiescent+water.">Experimental study of scour around a forced vibrating pipeline in quiescent water.</a> Coastal Engineering. 143, 1-11 (2019).</li><li>Hsieh, S. -. C., Low, Y. M., Chiew, Y. -. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Flow+characteristics+around+a+circular+cylinder+subjected+to+vortex-induced+vibration+near+a+plane+boundary.">Flow characteristics around a circular cylinder subjected to vortex-induced vibration near a plane boundary.</a> Journal of Fluids and Structures. 65, 257-277 (2016).</li><li>Sumer, B., Freds&#248;e, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Scour+below+pipelines+in+waves.">Scour below pipelines in waves.</a> Journal of Waterway, Port, Coastal, and Ocean Engineering. 116 (3), 307-323 (1990).</li><li>Sumer, B. M., Freds&#248;e, J., Gravesen, H., Bruschi, R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Response+of+marine+pipelines+in+scour+trenches.">Response of marine pipelines in scour trenches.</a> Journal of Waterway, Port, Coastal, and Ocean Engineering. 115 (4), 477-496 (1989).</li><li>&#199;evik, E., Y&#252;ksel, Y. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Scour+under+submarine+pipelines+in+waves+in+shoaling+conditions.">Scour under submarine pipelines in waves in shoaling conditions.</a> Journal of Waterway, Port, Coastal, and Ocean Engineering. 125 (1), 9-19 (1999).</li><li>Sumer, B. M., Truelsen, C., Sichmann, T., Freds&#248;e, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Onset+of+scour+below+pipelines+and+self-burial.">Onset of scour below pipelines and self-burial.</a> Coastal Engineering. 42 (4), 313-335 (2001).</li><li>Li, F., Cheng, L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Prediction+of+lee-wake+scouring+of+pipelines+in+currents.">Prediction of lee-wake scouring of pipelines in currents.</a> Journal of Waterway, Port, Coastal, and Ocean Engineering. 127 (2), 106-112 (2001).</li><li>Yang, B., Gao, F. -. P., Jeng, D. -. S., Wu, Y. -. X. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Experimental+study+of+vortex-induced+vibrations+of+a+pipeline+near+an+erodible+sandy+seabed.">Experimental study of vortex-induced vibrations of a pipeline near an erodible sandy seabed.</a> Ocean Engineering. 35 (3), 301-309 (2008).</li><li>Zhao, M., Cheng, L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Numerical+investigation+of+local+scour+below+a+vibrating+pipeline+under+steady+currents.">Numerical investigation of local scour below a vibrating pipeline under steady currents.</a> Coastal Engineering. 57 (4), 397-406 (2010).</li><li>Fu, S., Xu, Y., Chen, Y. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Seabed+effects+on+the+hydrodynamics+of+a+circular+cylinder+undergoing+vortex-induced+vibration+at+high+reynolds+number.">Seabed effects on the hydrodynamics of a circular cylinder undergoing vortex-induced vibration at high reynolds number.</a> Journal of Waterway, Port, Coastal, and Ocean Engineering. 140 (3), 04014008 (2014).</li><li>Guo, Z., Jeng, D. -. S., Zhao, H., Guo, W., Wang, L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Effect+of+seepage+flow+on+sediment+incipient+motion+around+a+free+spanning+pipeline.">Effect of seepage flow on sediment incipient motion around a free spanning pipeline.</a> Coastal Engineering. 143, 50-62 (2019).</li><li>Adrian, R. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Particle-imaging+techniques+for+experimental+fluid+mechanics.">Particle-imaging techniques for experimental fluid mechanics.</a> Annual Review of Fluid Mechanics. 23 (1), 261-304 (1991).</li><li>Raffel, M., Willert, C. E., Wereley, S. T., Kompenhans, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> Particle image velocimetry: A practical guide. , (2007).</li><li>Piirto, M., Saarenrinne, P., Eloranta, H., Karvinen, R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Measuring+turbulence+energy+with+piv+in+a+backward-facing+step+flow.">Measuring turbulence energy with piv in a backward-facing step flow.</a> Experiments in Fluids. 35 (3), 219-236 (2003).</li><li>Guan, D., Chiew, Y. -. M., Wei, M., Hsieh, S. -. C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Characterization+of+horseshoe+vortex+in+a+developing+scour+hole+at+a+cylindrical+bridge+pier.">Characterization of horseshoe vortex in a developing scour hole at a cylindrical bridge pier.</a> International Journal of Sediment Research. , (2018).</li><li>Guan, D., Agarwal, P., Chiew, Y. -. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Quadrant+analysis+of+turbulence+in+a+rectangular+cavity+with+large+aspect+ratios.">Quadrant analysis of turbulence in a rectangular cavity with large aspect ratios.</a> Journal of Hydraulic Engineering. 144 (7), 04018035 (2018).</li><li>Kim, J. -. T., Kim, D., Liberzon, A., Chamorro, L. P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Three-dimensional+particle+tracking+velocimetry+for+turbulence+applications:+Case+of+a+jet+flow.">Three-dimensional particle tracking velocimetry for turbulence applications: Case of a jet flow.</a> Journal of Visualized Experiments. (108), e53745 (2016).</li><li>Lu, L., Sick, V. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=High-speed+particle+image+velocimetry+near+surfaces.">High-speed particle image velocimetry near surfaces.</a> Journal of Visualized Experiments. (76), e50559 (2013).</li><li>Lin, W. -. J., Lin, C., Hsieh, S. -. C., Dey, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Flow+characteristics+around+a+circular+cylinder+placed+horizontally+above+a+plane+boundary.">Flow characteristics around a circular cylinder placed horizontally above a plane boundary.</a> Journal of Engineering Mechanics. 135 (7), 697-716 (2009).</li><li>Hsieh, S. -. C., Low, Y. M., Chiew, Y. -. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Flow+characteristics+around+a+circular+cylinder+undergoing+vortex-induced+vibration+in+the+initial+branch.">Flow characteristics around a circular cylinder undergoing vortex-induced vibration in the initial branch.</a> Ocean Engineering. 129, 265-278 (2017).</li><li>Hsieh, S. -. C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Establishment+of+high+time-resolved+piv+system+with+application+to+the+characteristics+of+a+near+wake+flow+behind+a+circular+cylinder.">Establishment of high time-resolved piv system with application to the characteristics of a near wake flow behind a circular cylinder.</a> National Chung Hsing University. , (2008).</li><li>Newland, D. E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Wavelet+analysis+of+vibration:+Part+1-theory.">Wavelet analysis of vibration: Part 1-theory.</a> Journal of Vibration and Acoustics. 116 (4), 409-416 (1994).</li><li>Newland, D. E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Wavelet+analysis+of+vibration:+Part+2-wavelet+maps.">Wavelet analysis of vibration: Part 2-wavelet maps.</a> Journal of Vibration and Acoustics. 116 (4), 417-425 (1994).</li><li>Lin, C., Hsieh, S. -. C., Lin, W. -. J., Raikar, R. V. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Characteristics+of+recirculation+zone+structure+behind+an+impulsively+started+circular+cylinder.">Characteristics of recirculation zone structure behind an impulsively started circular cylinder.</a> Journal of Engineering Mechanics. 138 (2), 184-198 (2012).</li><li>Sarpkaya, T. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+critical+review+of+the+intrinsic+nature+of+vortex-induced+vibrations.">A critical review of the intrinsic nature of vortex-induced vibrations.</a> Journal of Fluids and Structures. 19 (4), 389-447 (2004).</li></ol>

The authors have nothing to disclose.

The protocol presented in this paper describes a method for visualization of the two-dimensional flow fields and determination of the near-boundary flow stress fields around a forced vibrating pipeline in an equilibrium scour hole by using the PIV techniques. Since the designed pipeline motion is one-dimensional along the y direction, preparing and adjusting the pipeline model and vibration system to fulfill this objective are critical prerequisites for a successful outcome. Any undesirable motions of the pipeline along the x direction may induce asymmetrical flow fields and scour hole formation around the vibrating pipeline. Besides the apparatus effects, the selection of vibration frequency and amplitude of the pipeline for the experiments is also important for inducing a symmetrical flow field around the pipeline. In fact, in a quiescent water condition, Lin et al.31 showed that the structure of flow recirculation behind an impulsively started circular cylinder can maintain its symmetry when the non-dimensional time TD = tDUD/D &#60; 5, where tD = cylinder moving time; and UD = cylinder speed. For the condition when TD &#62; 5, the oblique vortex shedding may occur around the cylinder. In this study, the maximum pipeline speed can be estimated as 2&#960; &#402; &#8226; A0, and the cylinder moving time can be taken as 1/2 &#402;, thus the maximum non-dimensional time TD = &#960; A0/D = 4.48.
During the PIV setup stage, the laser sheet and camera adjustments and the seeding particle selection are the critical protocol steps for obtaining high quality flow field data. The camera shooting direction must be perpendicular to the laser sheet, otherwise, perspective distortions will be shown in the captured images. As this method aims to obtain the near-boundary flow stresses in an unsteady flow field, the intensity of the laser and the position of the field-of-view should be properly set to avoid strong light reflection of the boundary. The chosen seeding particles need to effectively scatter the illuminating laser sheet and be able to follow the flow streamlines without excessive settlement20. Based on this consideration, the seeding particles used in this study were aluminum powders, whose settling velocity was estimated to be 92.6 &#956;m/s using Stoke&#39;s law. This settling velocity is negligible compared to the flow velocities (0.1-0.2 m/s) near the vibrating pipeline. To optimize the experimental setup, verifying the focus of the camera and determining the camera sampling rate are also crucial steps for reliable measurements.
For the data process stage, there are two challenges for obtaining high quality phase-averaged flow fields and near-boundary flow stresses: (1) accurately calculate the instantaneous flow fields and avoid the displacement bias error in the flow regions with a large velocity gradient; and (2) accurately catalogue the captured images that have the same vibrating phase. For calculating the instantaneous flow fields, the traditional PIV cross-correlation method 19 determines the velocity vector between two consecutive images with a fixed time interval &#916;t (See Figure 5a). This traditional method may not be suitable for this study because the calculated flow field may have significant displacement bias errors near the vibrating pipeline and seabed boundaries. To overcome this problem, a multi-time-interval algorithm is adopted in this study (See Figure 5b).&#160; By using this method, image interrogations are executed reiteratively on different image pairs for different selected intervals. The velocity vector at each grid point is determined based on the estimations of suitable time interval9,27,28. It should be noted that when using this method, the raw image datasets should be acquired by a time resolved PIV with a high sampling rate camera and continuous wave laser. To overcome the second challenge, this paper provides a wavelet transform technique. By applying the wavelet transform function to the displacement time-series of the pipeline, the instantaneous phase of each captured image can be accurately calculated. This method can also be applied to investigate vortex induced vibration processes, such as pipeline vibration induced by asymmetry vortex shedding15,27,32.
The key advantages of the flow measurement technique described in this paper are high temporal and spatial resolution and the capacity to simultaneously obtain the pipeline dynamics, flow fields, and near-boundary flow stresses. By using this technique, more in-depth studies on pipeline scour in complex environments can be carried out and the complex mechanism of scour around the vibrating pipeline could be better understood.

Subsea pipelines are widely used in offshore environments for the purpose of fluid or hydro-carbon products conveyance. When a pipeline is placed on an erodible seabed, a scour hole around the pipeline is likely to form because of the waves, currents or dynamic motions of the pipeline itself (forced-vibration or vortex-induced-vibration)1,2. To improve the understanding of the scour mechanism around a subsea pipeline, measurements of the turbulent flow fields and estimations of the bed shear and normal stresses within the pipeline-fluid-seabed interaction region are essential in addition to measurements of the scour hole dimension1,2,3,4,5,6,7. In an environment where the bed shear and normal stresses are extremely difficult to be determined because the flow field is unsteady and the bottom boundary is rough, measured instantaneous near-boundary stresses (at approximately 2 mm above the boundary) could be used as their surrogate8,9. In the past few decades, scour around a vibrating pipeline has been studied and published without quantitatively presenting the values of the sophisticated flow fields around the pipeline within the scour hole3,4,5,10,11,12,13,14,15,16,17,18. Therefore, the goal of this method paper is to provide a novel experimental protocol for visualizing the detailed flow fields and to determine the near-boundary shear and normal stresses within an equilibrium scour hole induced by a forced vibrating pipeline. It should be noted that the pipeline-fluid-seabed interaction process in this study is in a quiescent water environment rather than those with unidirectional currents and waves.
This experimental method consists of two important components, namely, (1) simulation of pipeline (forced) vibrations; and (2) measurements of the flow fields around the pipeline. In the first component, the vibrating pipeline was simulated in an experimental flume by using a vibrating system, which has a servo motor, two connecting springs, and pipeline supporting frames. Different vibration frequencies and amplitudes can be simulated by adjusting the motor speed and location of the connecting springs. In the second component, the time-resolved particle image velocimetry (PIV) and wavelet transform techniques were adopted to obtain high temporal and spatial resolution flow field data at different pipeline vibration phases. The time-resolved PIV system consists of a continuous wave laser, a high-speed camera, seeding particles, and cross-correlation algorithms. Although PIV techniques have been widely used in obtaining steady turbulent flow fields19,20,21,22,23,24,25, applications in complex unsteady flow field conditions, such as cases of pipeline-fluids-seabed interaction, are relatively limited8,9,26,27. The reason probably is because traditional single-time-interval cross-correlation algorithm of PIV techniques is unable to accurately capture the flow features in unsteady flow fields where a relatively high velocity gradient is present9,20. The method described in this paper can solve this problem by using the multiple-time-interval cross-correlation algorithm9,28.

<table><tbody><tr><td>Camera control software</td><td>Vision Research</td><td>Phantom PCC 2.6</td><td>Camera control, image data acquisition and processing</td></tr><tr><td>Camera lens</td><td>Nikon Chiyoda</td><td></td><td>Nikor&amp;nbsp; 60mm, f=2.8 prime lens</td></tr><tr><td>Continuous wave laser&amp;nbsp;</td><td>Beijing Laserwave optoelectronics technology co. ltd.</td><td></td><td>PIV Laser source; Nd:YAG laser, 532 nm; air-cooling</td></tr><tr><td>High-speed camera</td><td>Vision Research</td><td>Phantom Miro LAB 320</td><td>Image data recording</td></tr><tr><td>Laser sheet forming optics&amp;nbsp;</td><td>Thorlabs Inc</td><td></td><td>Transform the point laser to a thin laser sheet</td></tr><tr><td>Pipeline model</td><td>ZONCEPZ SOLUTIONS</td><td></td><td>Acrylic cylinder with a diameter of 35 mm</td></tr><tr><td>Pipeline vibration system</td><td>ZONCEPZ SOLUTIONS</td><td></td><td>Consists of a sever motor, two connecting springs and pipeline supporting frames.</td></tr><tr><td>PIV calcuation software</td><td>AXESEA Engineering Technology Limited Co.</td><td>PISIOU</td><td>Image data processing for obtaining flow fields and pipeline displacements</td></tr><tr><td>PIV seeding materials</td><td>Shimakyu</td><td></td><td>Aluminum powder with a diameter of 10um</td></tr><tr><td>Recirculating flume&amp;nbsp;</td><td>SZU ENGINEERING PTE LTD</td><td></td><td>Glass-sided, 11 m long, 0.6 m wide, and 0.6 m deep</td></tr><tr><td>Tri-pod</td><td>MANFROTTO</td><td>SKU MT190GOC4US 410</td><td>Camara supporting</td></tr></tbody></table>

visualization of flow field around a vibrating pipeline within an equilibrium scour hole

An experimental method is presented in this paper to facilitate visualization of the detailed flow fields and determination of the near-boundary shear and normal stresses within an equilibrium scour hole induced by a vibrating pipeline. This method involves the implementation of a pipeline vibration system in a straight flume, a time-resolved particle image velocimetry (PIV) system for pipeline displacement tracking and flow fields measurements. The displacement time-series of the vibrating pipeline are obtained by using the cross-correlation algorithms. The steps for processing raw particle laden images obtained by using the time-resolved PIV are described. The detailed instantaneous flow fields around the vibrating pipeline at different vibrating phases are calculated by using a multiple-time-interval cross-correlation algorithm to avoid displacement bias error in the flow regions with a large velocity gradient. By applying the wavelet transform technique, the captured images that have the same vibrating phase are accurately cataloged before the phase-averaged velocity fields are obtained. The key advantages of the flow measurement technique described in this paper are that it has a very high temporal and spatial resolution and can be simultaneously used to obtain the pipeline dynamics, flow fields, and near-boundary flow stresses. By using this technique, more in-depth studies of the 2-dimensional flow field in a complex environment, such as that around a vibrating pipeline, can be conducted to better understand the associated sophisticated scour mechanism.

An example of the comparison between the raw image and processed image of the pipeline displacements tracking and instantaneous velocity calculation is shown in Figure 3. As shown in Figure 3b, the seeding particles and noise in the raw image are filtered out and the shining pipeline edge is retained to obtain the displacement time series. As shown in Figures 3c, light scatters/reflections around the seeding particles, pipeline edge and seabed surface are filtered out by the Laplacian filter. An example of the displacement time-series of the vibrating pipeline is shown in Figure 4. The vibration of the pipeline is almost sinusoidal, and the vibrating frequency and amplitude are 0.3 Hz and ~50 mm, respectively.
Figure 6 shows an example of the image of the quasi-equilibrium scour profile and vibrating pipeline at t = 1440 min, in which the origin of the coordinate (x-O-y) of this study is set at the intersection point of the original seabed surface and the pipeline vertical centerline. As shown in Figure 6, in addition to the seeding particles, very few suspended sediment particles can be observed in the flow; therefore, the raw image quality was not compromised. This also indicates that a quasi-equilibrium stage was reached for the pipeline scour process.
Examples of the visualized phase-averaged velocity field and vorticity dynamics are shown in Figure 7. It should be noted that because of the shadow of the pipeline during the PIV measurements, the region on the left side of the pipeline has no data (see subplots in Figure 7). As seen in Figure 7, nine discrete phases of the flow field within one cycle of vibration are presented. During the pipeline falling phases (0 &#8804; t0/T &#60; 0.5, where T is the vibration period and t0 is the time varies from 0 to T), a pair of vortices with symmetrical patterns is generated from the shear layers on both sides of the vibrating pipeline. Immediately after the pipeline has reached the scour trench bottom (t0/T = 4/8), the counter-clockwise vortex is distorted and sucked into the scour trench as the pipeline rises from the seabed. For the period of the pipeline ascending phases (0.5 &#8804; t0/T &#60; 1), another pair of vortices with opposite rotating directions to those in the descending phase is symmetrically generated around the top edge of the pipeline. For a better observation of the flow dynamics in Figure 7, a corresponding video (Video 1) made of 72 phases (frames) of flow fields for one cycle of pipeline vibration is provided.
An example of the near-boundary shear stresses, Ts and normal stresses, Tn evolution along the scour profile within one vibrating cycle is presented in Figure 8. Since the flow field is symmetrical about the y axis, the near-boundary shear stresses and normal stresses presented in this study are confined to the right half of the scour profile (0 &#60; x &#60; 5). As shown in Figure 8, these two stresses are normalized by the value of the critical bed shear stress, Tc (obtained from Shields&#39;&#160;curve as 0.243 Pa) of the sand particles on a plane bed condition. The absolute values of Ts and Tn within the scour trench and beneath the vibrating pipeline increase significantly when the pipeline is falling to the bed or ascending from the bed. The regions where Ts and Tn exhibit the maximum and minimum values are consistent with the evolution of flow fields between the vibrating pipeline and scour boundary as shown in Figure 7.
<img alt="Figure 1" class="xfigimg" src="/files/ftp_upload/59745/59745fig1.jpg" /> 
Figure 1: Schematic of the experimental flume. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/59745/59745fig1large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 2" class="xfigimg" src="/files/ftp_upload/59745/59745fig2.jpg" /> 
Figure 2: Schematic of the pipeline model and vibration system set-up. (a) Section view, (b) Side view. This figure has been modified from8. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/59745/59745fig2large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 3" class="xfigimg" src="/files/ftp_upload/59745/59745fig3.jpg" /> 
Figure 3: Example of the comparison between raw and processed images. (a) the raw image, (b) the processed image for pipeline displacements tracking, and (c) the processed image for instantaneous velocity calculation. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/59745/59745fig3large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 4" class="xfigimg" src="/files/ftp_upload/59745/59745fig4.jpg" /> 
Figure 4: Example of the displacement time-series of vibrating pipeline at t = 1440 min. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/59745/59745fig4large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 5" class="xfigimg" src="/files/ftp_upload/59745/59745fig5.jpg" /> 
Figure 5: Comparison between single-time and multi-time interval cross-correlation algorithm. This figure is reproduced from9. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/59745/59745fig5large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 6" class="xfigimg" src="/files/ftp_upload/59745/59745fig6.jpg" /> 
Figure 6: Example image of the quasi-equilibrium scour profile at t = 1440 min. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/59745/59745fig6large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 7" class="xfigimg" src="/files/ftp_upload/59745/59745fig7.jpg" /> 
Figure 7: Examples of visualized phase-averaged velocity field and vorticity dynamics. This figure is reproduced from8. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/59745/59745fig7large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 8" class="xfigimg" src="/files/ftp_upload/59745/59745fig8.jpg" /> 
Figure 8: Example of evolutions of ts&#160;and tn&#160;along the scour profile within one vibrating cycle. The touchdown and liftoff times refer to the times when the bottom of the pipeline just touches and rises from the scour hole boundary, respectively. This figure is reproduced from8. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/59745/59745fig8large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Video 1" src="/files/ftp_upload/59745/59745video1.jpg" /> 
Video 1: Flow field evolution around the vibrating pipeline within the equilibrium scour hole. The video is made from 72 phases (frames) of flow fields for one cycle of pipeline vibration. This video is reproduced from8. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/59745/Video1.mp4" target="_blank">Please click here to view this video. (Right-click to download.)</a>

Watch this Scientific Journal Video about Visualization of Flow Field Around a Vibrating Pipeline Within an Equilibrium Scour Hole at JoVE.com

Visualization of Flow Field Around a Vibrating Pipeline Within an Equilibrium Scour Hole

The goal of the protocol is to enable visualization of the detailed flow fields and determination of the near-boundary shear and normal stresses within an equilibrium scour hole induced by a vibrating pipeline.

An experimental method is presented in this paper to facilitate visualization of the detailed flow fields and determination of the near-boundary shear and ...

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Flow in Pipes

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5.5K Views.  Hohai University. The goal of the protocol is to enable visualization of the detailed flow fields and determination of the near-boundary shear and normal stresses within an equilibrium scour hole induced by a vibrating pipeline.

Video: Visualization of Flow Field Around a Vibrating Pipeline Within an Equilibrium Scour Hole

Echo Particle Image Velocimetry

The transport of mass, momentum, and energy in fluid flows is ultimately determined by spatiotemporal distributions of the fluid velocity field.1 Consequently, a prerequisite for understanding, predicting, and controlling fluid flows is the capability to measure the velocity field with adequate spatial and temporal resolution.2 For velocity measurements in optically opaque fluids or through optically opaque geometries, echo particle image velocimetry (EPIV) is an attractive diagnostic technique to generate "instantaneous" two-dimensional fields of velocity.3,4,5,6 In this paper, the operating protocol for an EPIV system built by integrating a commercial medical ultrasound machine7 with a PC running commercial particle image velocimetry (PIV) software8 is described, and validation measurements in Hagen-Poiseuille (i.e., laminar pipe) flow are reported.
For the EPIV measurements, a phased array probe connected to the medical ultrasound machine is used to generate a two-dimensional ultrasound image by pulsing the piezoelectric probe elements at different times. Each probe element transmits an ultrasound pulse into the fluid, and tracer particles in the fluid (either naturally occurring or seeded) reflect ultrasound echoes back to the probe where they are recorded. The amplitude of the reflected ultrasound waves and their time delay relative to transmission are used to create what is known as B-mode (brightness mode) two-dimensional ultrasound images. Specifically, the time delay is used to determine the position of the scatterer in the fluid and the amplitude is used to assign intensity to the scatterer. The time required to obtain a single B-mode image, t, is determined by the time it take to pulse all the elements of the phased array probe. For acquiring multiple B-mode images, the frame rate of the system in frames per second (fps) = 1/&delta;t. (See 9 for a review of ultrasound imaging.)
For a typical EPIV experiment, the frame rate is between 20-60 fps, depending on flow conditions, and 100-1000 B-mode images of the spatial distribution of the tracer particles in the flow are acquired. Once acquired, the B-mode ultrasound images are transmitted via an ethernet connection to the PC running the PIV commercial software. Using the PIV software, tracer particle displacement fields, D(x,y)[pixels], (where x and y denote horizontal and vertical spatial position in the ultrasound image, respectively) are acquired by applying cross correlation algorithms to successive ultrasound B-mode images.10 The velocity fields, u(x,y)[m/s], are determined from the displacements fields, knowing the time step between image pairs, &Delta;T[s], and the image magnification, M[meter/pixel], i.e., u(x,y) = MD(x,y)/&Delta;T. The time step between images &Delta;T = 1/fps + D(x,y)/B, where B[pixels/s] is the time it takes for the ultrasound probe to sweep across the image width. In the present study, M = 77[&mu;m/pixel], fps = 49.5[1/s], and B = 25,047[pixels/s]. Once acquired, the velocity fields can be analyzed to compute flow quantities of interest.

An echo particle image velocimetry (EPIV) system capable of acquiring two-dimensional fields of velocity in optically opaque fluids or through optically opaque geometries is described, and validation measurements in pipe flow are reported.

The transport of mass, momentum, and energy in fluid flows is ultimately determined by spatiotemporal distributions of the fluid velocity field.1 ...

Engineering

Determining 3D Flow Fields via Multi-camera Light Field Imaging

In the field of fluid mechanics, the resolution of computational schemes has outpaced experimental methods and widened the gap between predicted and observed phenomena in fluid flows. Thus, a need exists for an accessible method capable of resolving three-dimensional (3D) data sets for a range of problems. We present a novel technique for performing quantitative 3D imaging of many types of flow fields. The 3D technique enables investigation of complicated velocity fields and bubbly flows. Measurements of these types present a variety of challenges to the instrument. For instance, optically dense bubbly multiphase flows cannot be readily imaged by traditional, non-invasive flow measurement techniques due to the bubbles occluding optical access to the interior regions of the volume of interest. By using Light Field Imaging we are able to reparameterize images captured by an array of cameras to reconstruct a 3D volumetric map for every time instance, despite partial occlusions in the volume. The technique makes use of an algorithm known as synthetic aperture (SA) refocusing, whereby a 3D focal stack is generated by combining images from several cameras post-capture 1. Light Field Imaging allows for the capture of angular as well as spatial information about the light rays, and hence enables 3D scene reconstruction. Quantitative information can then be extracted from the 3D reconstructions using a variety of processing algorithms. In particular, we have developed measurement methods based on Light Field Imaging for performing 3D particle image velocimetry (PIV), extracting bubbles in a 3D field and tracking the boundary of a flickering flame. We present the fundamentals of the Light Field Imaging methodology in the context of our setup for performing 3DPIV of the airflow passing over a set of synthetic vocal folds, and show representative results from application of the technique to a bubble-entraining plunging jet.

A technique for performing quantitative three-dimensional (3D) imaging for a range of fluid flows is presented. Using concepts from the area of Light Field Imaging, we reconstruct 3D volumes from arrays of images. Our 3D results span a broad range including velocity fields and multi-phase bubble size distributions.

In the field of fluid mechanics, the resolution of computational schemes has outpaced experimental methods and widened the gap between predicted and ...

Fabrication, Operation and Flow Visualization in Surface-acoustic-wave-driven Acoustic-counterflow Microfluidics

Surface acoustic waves (SAWs) can be used to drive liquids in portable microfluidic chips via the acoustic counterflow phenomenon. In this video we present the fabrication protocol for a multilayered SAW acoustic counterflow device. The device is fabricated starting from a lithium niobate (LN) substrate onto which two interdigital transducers (IDTs) and appropriate markers are patterned. A polydimethylsiloxane (PDMS) channel cast on an SU8 master mold is finally bonded on the patterned substrate. Following the fabrication procedure, we show the techniques that allow the characterization and operation of the acoustic counterflow device in order to pump fluids through the PDMS channel grid. We finally present the procedure to visualize liquid flow in the channels. The protocol is used to show on-chip fluid pumping under different flow regimes such as laminar flow and more complicated dynamics characterized by vortices and particle accumulation domains.

In this video we first describe fabrication and operation procedures of a surface acoustic wave (SAW) acoustic counterflow device. We then demonstrate an experimental setup that allows for both qualitative flow visualization and quantitative analysis of complex flows within the SAW pumping device.

Surface acoustic waves (SAWs) can be used to drive liquids in portable microfluidic chips via the acoustic counterflow phenomenon. In this video we ...

Visualizing Hyporheic Flow Through Bedforms Using Dye Experiments and Simulation

Advective exchange between the pore space of sediments and the overlying water column, called hyporheic exchange in fluvial environments, drives solute transport in rivers and many important biogeochemical processes. To improve understanding of these processes through visual demonstration, we created a hyporheic flow simulation in the multi-agent computer modeling platform NetLogo. The simulation shows virtual tracer flowing through a streambed covered with two-dimensional bedforms. Sediment, flow, and bedform characteristics are used as input variables for the model. We illustrate how these simulations match experimental observations from laboratory flume experiments based on measured input parameters. Dye is injected into the flume sediments to visualize the porewater flow. For comparison virtual tracer particles are placed at the same locations in the simulation. This coupled simulation and lab experiment has been used successfully in undergraduate and graduate laboratories to directly visualize river-porewater interactions and show how physically-based flow simulations can reproduce environmental phenomena. Students took photographs of the bed through the transparent flume walls and compared them to shapes of the dye at the same times in the simulation. This resulted in very similar trends, which allowed the students to better understand both the flow patterns and the mathematical model. The simulations also allow the user to quickly visualize the impact of each input parameter by running multiple simulations. This process can also be used in research applications to illustrate basic processes, relate interfacial fluxes and porewater transport, and support quantitative process-based modeling.

This manuscript describes how to create regular bedforms in a flume, visualize flow through the bedforms, and use computer simulations to simulate the hyporheic flow. The computer simulations compare well with the experimental observations. This coupled simulation and experiment is well-suited for both research and educational purposes.

Advective exchange between the pore space of sediments and the overlying water column, called hyporheic exchange in fluvial environments, drives solute ...

Investigating the Three-dimensional Flow Separation Induced by a Model Vocal Fold Polyp

The fluid-structure energy exchange process for normal speech has been studied extensively, but it is not well understood for pathological conditions. Polyps and nodules, which are geometric abnormalities that form on the medial surface of the vocal folds, can disrupt vocal fold dynamics and thus can have devastating consequences on a patient&#39;s ability to communicate. Our laboratory has reported particle image velocimetry (PIV) measurements, within an investigation of a model polyp located on the medial surface of an in&#160;vitro driven vocal fold model, which show that such a geometric abnormality considerably disrupts the glottal jet behavior. This flow field adjustment is a likely reason for the severe degradation of the vocal quality in patients with polyps. A more complete understanding of the formation and propagation of vortical structures from a geometric protuberance, such as a vocal fold polyp, and the resulting influence on the aerodynamic loadings that drive the vocal fold dynamics, is necessary for advancing the treatment of this pathological condition. The present investigation concerns the three-dimensional flow separation induced by a wall-mounted prolate hemispheroid with a 2:1 aspect ratio in cross flow, i.e. a model vocal fold polyp, using an oil-film visualization technique. Unsteady, three-dimensional flow separation and its impact of the wall pressure loading are examined using skin friction line visualization and wall pressure measurements.

Vocal fold polyps can disrupt vocal fold dynamics and thus can have devastating consequences on a patient&#39;s ability to communicate. Three-dimensional flow separation induced by a wall-mounted model polyp and its impact on the wall pressure loading are examined using particle image velocimetry, skin friction line visualization, and wall pressure measurements.

The fluid-structure energy exchange process for normal speech has been studied extensively, but it is not well understood for pathological conditions. ...

Bioengineering

Experimental Investigation of Secondary Flow Structures Downstream of a Model Type IV Stent Failure in a 180&#176; Curved Artery Test Section

The arterial network in the human vasculature comprises of ubiquitously present blood vessels with complex geometries (branches, curvatures and tortuosity). Secondary flow structures are vortical flow patterns that occur in curved arteries due to the combined action of centrifugal forces, adverse pressure gradients and inflow characteristics. Such flow morphologies are greatly affected by pulsatility and multiple harmonics of physiological inflow conditions and vary greatly in size-strength-shape characteristics compared to non-physiological (steady and oscillatory) flows 1 - 7.
Secondary flow structures may ultimately influence the wall shear stress and exposure time of blood-borne particles toward progression of atherosclerosis, restenosis, sensitization of platelets and thrombosis 4 - 6, 8 - 13. Therefore, the ability to detect and characterize these structures under laboratory-controlled conditions is precursor to further clinical investigations.
A common surgical treatment to atherosclerosis is stent implantation, to open up stenosed arteries for unobstructed blood flow. But the concomitant flow perturbations due to stent installations result in multi-scale secondary flow morphologies 4 - 6. Progressively higher order complexities such as asymmetry and loss in coherence can be induced by ensuing stent failures vis-&#224;-vis those under unperturbed flows 5. These stent failures have been classified as &#34;Types I-to-IV&#34; based on failure considerations and clinical severity 14.
This study presents a protocol for the experimental investigation of the complex secondary flow structures due to complete transverse stent fracture and linear displacement of fractured parts (&#34;Type IV&#34;) in a curved artery model. The experimental method involves the implementation of particle image velocimetry (2C-2D PIV) techniques with an archetypal carotid artery inflow waveform, a refractive index matched blood-analog working fluid for phase-averaged measurements 15 - 18. Quantitative identification of secondary flow structures was achieved using concepts of flow physics, critical point theory and a novel wavelet transform algorithm applied to experimental PIV data 5, 6, 19 - 26.

Stent implants in stenosed arterial curvatures are prone to "Type IV" failures involving the complete transverse fracture of stents and linear displacement of the fractured parts. We present a protocol for detection of secondary flow (vortical) structures in a curved artery model, downstream of clinically relevant "Type IV" stent failures.

The arterial network in the human vasculature comprises of ubiquitously present blood vessels with complex geometries (branches, curvatures and ...

Experimental Investigation of the Flow Structure over a Delta Wing Via Flow Visualization Methods

It is well known that the flow field over a delta wing is dominated by a pair of counter rotating leading edge vortices (LEV). However, their mechanism is not well understood. The flow visualization technique is a promising non-intrusive method to illustrate the complex flow field spatially and temporally. A basic flow visualization setup consists of a high-powered laser and optic lenses to generate the laser sheet, a camera, a tracer particle generator, and a data processor. The wind tunnel setup, the specifications of devices involved, and the corresponding parameter settings are dependent on the flow features to be obtained.
Normal smoke wire flow visualization uses a smoke wire to demonstrate the flow streaklines. However, the performance of this method is limited by poor spatial resolution when it is conducted in a complex flow field. Therefore, an improved smoke flow visualization technique has been developed. This technique illustrates the large-scale global LEV flow field and the small-scale shear layer flow structure at the same time, providing a valuable reference for later detailed particle image velocimetry (PIV) measurement.
In this paper, the application of the improved smoke flow visualization and PIV measurement to study the unsteady flow phenomena over a delta wing is demonstrated. The procedure and cautions for conducting the experiment are listed, including wind tunnel setup, data acquisition, and data processing. The representative results show that these two flow visualization methods are effective techniques for investigating the three-dimensional flow field qualitatively and quantitatively.

Here, we present a protocol to observe unsteady vortical flows over a delta wing using a modified smoke flow visualization technique and investigate the mechanism responsible for the oscillations of the leading-edge vortex breakdown locations.

It is well known that the flow field over a delta wing is dominated by a pair of counter rotating leading edge vortices (LEV). However, their mechanism is ...

Flow Visualization in a Water Tunnel: Observing the Leading-edge Vortex Over a Delta Wing

Source: Jose Roberto Moreto, Gustaaf Jacobs and Xiaofeng Liu, Department of Aerospace Engineering, San Diego State University, San Diego, California
The delta wing, shown in Figure 1D, is a popular design in high-speed airplanes due to its superb performance in transonic and supersonic flight regimes. This type of wing has a small aspect ratio and high sweep angle, which reduces drag at high subsonic, transonic and supersonic flight regimes. The aspect ratio is defined as the wing span divided by the average chord <img align="middle" src="/files/ftp_upload/10459/10459eq1a.jpg" />.
An important advantage of the delta wing is its high stall angle. The stall of a delta wing is delayed compared to the stall of a high aspect ratio wing. This is because the lift of a delta wing is enhanced by the leading-edge vortex over the wing.
An effective way to observe this vortex flow phenomenon and study the vortex breakdown in a delta wing is by visualizing the flow in a water tunnel. By injecting dye in the flow surrounding a model from dye ports on the leading-edge, the vortex development and breakdown can be observed and its position measured. The data can also be used to estimate the stall angle.
<img src="/files/ftp_upload/10459/10459fig1.jpg" />
Figure 1. Typical wing planform shapes: A) Rectangular, with constant chord along span, B) elliptical, C) tapered, with variable chord along the span, and D) delta wing, an aft-swept wing with zero taper ratio.

Flow in a Water Tunnel: Leading-edge Vortex over a Delta Wing

Source: Jose Roberto Moreto, Gustaaf Jacobs and Xiaofeng Liu, Department of Aerospace Engineering, San Diego State University, San Diego, California
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Aeronautical Engineering

Surface Dye Flow Visualization: A Qualitative Method to Observe Streakline Patterns in Supersonic Flow

Flow visualization around or on a body is an important tool in aerodynamics research. It provides a method to qualitatively and quantitatively study flow structure, and it also helps researchers theorize and verify fluid flow behavior. Flow visualization can be divided into two categories: off-the-surface visualization and surface flow visualization. Off-the-surface flow visualization techniques involve determining the flow characteristics around the body of interest. They include but are not restricted to particle image velocimetry (PIV), Schlieren imaging, and smoke flow visualization. These techniques can provide qualitative as well as quantitative data on the flow around a body. However, these techniques are generally expensive and difficult to set-up. Surface flow visualization techniques, on the other hand, involve coating the body of interest with a dye to study flow on the surface. These techniques, which are more invasive in practice, include dye flow visualization and, more recently, use pressure-sensitive paint, which gives a detailed image of the flow on the body&#39;s surface. This allows researchers to visualize different flow features, including laminar bubbles, boundary layer transitions, and flow separation. Dye flow visualization, the technique of interest in the current experiment, provides a qualitative picture of the surface flow and is one of the simplest and most cost-effective surface flow visualization methods, specifically for visualizing gaseous flows on a body.
In this experiment, the surface flow behavior on six bodies are studied in supersonic flow. The streakline patterns are obtained using the dye flow visualization technique, and the flow paths, degree of flow attachment and separation, and location and type of shocks are identified and studied from the flow images.

Surface Dye Flow: Streakline Patterns in Supersonic Flow

Flow visualization around or on a body is an important tool in aerodynamics research. It provides a method to qualitatively and quantitatively study flow ...

Visualization of Flow Past a Bluff Body

Source: Ricardo Mejia-Alvarez, Hussam Hikmat Jabbar and Mahmoud N. Abdullatif, Department of Mechanical Engineering, Michigan State University, East Lansing, MI
Owing to the non-linear nature of its governing laws, fluid motion induces complicated flow patterns. Understanding the nature of these patterns has been the subject of intense scrutiny for centuries. Although personal computers and supercomputers are extensively used to deduce fluid flow patterns, their capabilities are still insufficient to determine the exact flow behavior for complex geometries or highly inertial flows (e.g. when momentum dominates over viscous resistance). With this in mind, a multitude of experimental techniques to make flow patterns evident have been developed that can reach flow regimes and geometries inaccessible to theoretical and computational tools.
This demonstration will investigate fluid flow around a bluff body. A bluff body is an object that, due to its shape, causes separated flow over most of its surface. This is in contrast to a streamlined body, like an airfoil, which is aligned in the stream and causes less flow separation. The purpose of this study is to use hydrogen bubbles as a method of visualizing flow patterns. The hydrogen bubbles are produced via electrolysis using a DC power source by submerging its electrodes in the water. Hydrogen bubbles are formed in the negative electrode, which needs to be a very fine wire to ensure that the bubbles remain small and track fluid motion more effectively. This method is suitable for steady and unsteady laminar flows, and is based on the basic flow lines that describe the nature of the flow around objects. [1-3]
This paper focuses on describing the implementation of the technique, including details about the equipment and its installation. Then, the technique is used to demonstrate the use of two of the basics flow lines to characterize the flow around a circular cylinder. These flow lines are used to estimate some important flow parameters like flow velocity and the Reynolds number, and to determine flow patterns.

Flow Around a Bluff Body, Bubbles and Von Karman Vortex Street

Source: Ricardo Mejia-Alvarez, Hussam Hikmat Jabbar and Mahmoud N. Abdullatif, Department of Mechanical Engineering, Michigan State University, East ...