The authors would like to thank Hong Kong Research Grants Council (no. GRF526913), Hong Kong Innovation and Technology Commission (no. ITS/334/15FP), and the US Office of Naval Research Global (no. N00014-16-1-2161) for financial support.

1. Wind Tunnel Setup
<ol>
	<li>Delta wing model
	<ol>
		<li>Construct a delta wing model from aluminum, with a sweep angle &#966; of 75&#176;, a chord length c of 280 mm, a root span b of 150 mm, and a thickness of 5 mm. Have both leading edges beveled at 35&#176; to fix the separation point17 (see Figure 1a).</li>
	</ol>
	</li>
	<li>Wind tunnel facility
	<ol>
		<li>Conduct experiments in a closed-loop low-speed wind tunnel, with a test section of 2.4 m (length) &#215; 0.6 m (width) &#215; 0.6 m (height) that is equipped with glass walls that allow optical access during the experiments. The turbulent intensity of such a facility should be less than 0.4%. 
		NOTE: In this study, we used a wind tunnel at The Hong Kong Polytechnic University with the above characteristics. Also, the freestream velocity U&#8734; ranged from 2.64 m/s to 10.56 m/s, corresponding to a Reynolds number, Re, from 5 &#215; 104 to 2 &#215; 105, based on the chord length of the delta wing, which is the typical flight range for an unmanned aerial vehicle (UAV).</li>
		<li>As needed, use three different arrangements (see Figure 1b-d) of the laser sheet and the cameras to observe the flow structures in the longitudinal cross section, the span-wise cross section, and the transverse cross section. Schematics of the setup are shown in Figure 1b. 
		NOTE: This protocol demonstrates the setup and measurement in the longitudinal cross section in detail.</li>
	</ol>
	</li>
	<li>Install the delta wing
	<ol>
		<li>Fix the delta wing trailing edge on the sting, which is on a circular motion guide used for adjusting the angle of attack (AoA), &#945;. The center of the circular guide is on the central line of the wind tunnel test section. Thus, the delta wing&#39;s center can always be at the center of the test section. Adjust the AoA to &#945; = 34&#176;.</li>
		<li>Carefully adjust the delta wing model to minimize any yaw angle and roll angle, by checking the readings of an angle meter and a three-axis laser level. In the current study, the uncertainty of these two angles is less than 0.1&#176;.</li>
	</ol>
	</li>
	<li>Set up the laser sheet
	<ol>
		<li>Use two lasers separately to illuminate the flow structures for PIV measurement and smoke flow visualization.
		<ol>
			<li>For PIV measurement, use a dual pulse laser, with a wavelength of 532 nm and a maximum energy of 600 mJ (adjustable) for each pulse. Control it with a synchronizer with transistor-transistor logic (TTL) signals (see Figure 1b).</li>
			<li>For smoke flow visualization, use a continuous laser with a wavelength of 532 nm and a power of 1 W. This continuous laser works independently. During the setup installation, use a neutral density filter with 10% transmittance to filter the laser beam for safety.</li>
		</ol>
		</li>
		<li>Wear appropriate laser goggles.</li>
		<li>Adjust the reflection mirror to introduce the laser beam into the wind tunnel. The angle between the laser light axis and the mirror is <img alt="Equation 1" src="/files/ftp_upload/57244/57244eq1.jpg" />, to make the laser beam normal to the delta wing surface. Ensure that the laser beam is around the position x/c &#8773; 0.25, which will later be the center of the field of view (FOV).</li>
		<li>Install laser optics (with the continuous laser, at first) to form the laser sheet, as shown in Figure 1b. The convex lens is used to control the laser beam size (also the sheet thickness). The cylindrical lens expands the laser beam to a laser sheet. 
		NOTE: In the current study, the focal length of the cylindrical lens is 700 mm, and the diameter of the cylindrical lens is 12 mm.</li>
		<li>Check the laser sheet thickness by measuring the laser line on the model. Adjust the location of the convex lens if the laser sheet thickness is not suitable (here, around 1 mm, with an effective width of the laser sheet in the test section of about 100 mm). Note that the thickness of the laser sheet is dependent on 1) the velocity component in the normal direction to the laser sheet and 2) the time interval between the pair of snapshots in PIV measurement.</li>
		<li>Put a calibration target plate on the delta wing, with its surface coincident to the laser sheet. This step is essential because the FOV in the current study is not orthogonal to the wind tunnel coordinate.</li>
	</ol>
	</li>
	<li>Camera setup
	<ol>
		<li>Turn off the lasers when setting up the camera. As with the lasers, use two cameras for each separate part of this experiment:
		<ol>
			<li>For PIV measurement, use a high-speed CCD camera with a resolution of 2048 &#215; 2048 pixels. This camera is controlled by the synchronizer and the dual pulse laser (see Figure 1b). Data in this camera will be transmitted directly to the computer.</li>
			<li>For smoke flow visualization, use a commercial digital camera with a snapshot resolution of 4,000 &#215; 6,000 pixels and a 50 Hz video recording resolution of 720 &#215; 1280 pixels during the smoke flow visualization. It will be operated manually.</li>
		</ol>
		</li>
		<li>Move the camera&#39;s position (commercial digital camera, at first) to obtain the desired FOV. Adjust the camera lens to focus on the calibration target plate. Make sure the entire field is focused. If not, the coordinates of the camera may not be orthogonal to the calibration target plate. Thus, adjust the camera&#39;s position carefully18.</li>
		<li>Take several frames after the camera is well set. Later, these frames of the calibration target plate will be used to calibrate the scale factor between the real size and the frame pixel, and to identify the reference position in the xyz coordinate. Then, remove the calibration target plate.</li>
	</ol>
	</li>
	<li>Turn on the wind tunnel at a low speed (e.g., 3 m/s) and inject oil particles into the wind tunnel. Set the pressure of the aerosol generator at 2.5 bar and operate it for 30 s for the pre-seeded flow visualization method. After this, the whole wind tunnel will be uniformly seeded with oil particles at a normal diameter of about 1 &#181;m. 
	NOTE: In the current study, the estimated oil particle density concentration in the wind tunnel is approximately&#160;<img alt="Equation 2" src="/files/ftp_upload/57244/57244eq2.jpg" /> in the smoke flow visualization; thus, the overall flow density change in the wind tunnel is <img alt="Equation 3" src="/files/ftp_upload/57244/57244eq3.jpg" />.</li>
	<li>PIV software setup
	<ol>
		<li>Control the PIV system with the PIV software (see Table of Materials). This software can command the synchronizer to send TTL signals to the laser and the camera, as shown in Figure 1b.</li>
		<li>Set the sampling frequency at 5 Hz, with a total sampling number of 500. The time interval between PIV frames is 80 &#181;s. Note that the time interval is dependent on the size of the FOV and flow velocity. Make sure that the interrogation areas in two frames have about a 50 - 75% overlap.</li>
	</ol>
	</li>
</ol>
2. Running the Experiment
<ol>
	<li>Improved smoke flow visualization
	<ol>
		<li>Turn on the wind tunnel at the desired freestream velocity (U = 2.64 m/s). Run it for 10 min to stabilize the freestream velocity. At Re = 50,000, the freestream velocity is U = 2.64 m/s.</li>
		<li>Turn on the continuous laser. Use the digital camera to capture 5 - 10 snapshots of the flow structure.</li>
		<li>Check whether the laser sheet is at the longitudinal cross-section of the LEV core (see the typical structure shown in Figure 3). If so, mark this position on the delta wing model as a reference for the later PIV measurement; otherwise, change the position of the laser sheet by adjusting the optic lens and reset the calibration following steps 1.4.6 - 1.5.3.</li>
		<li>Review those images and check the focus and brightness. If the image quality is not satisfactory, adjust the aperture of the lens or the ISO setup.</li>
		<li>Take more snapshots (typically around 20) and videos (approximately 40 s) with the proper setup. Turn off the laser and transfer the data to the computer.</li>
	</ol>
	</li>
	<li>PIV measurement
	<ol>
		<li>Based on the reference position known from step 2.1.3 and the results of the snapshots from step 2.1.5, choose an interesting region (x/c&#8776; 0.3) as the FOV, where vortical substructures can be observed. Replace the continuous laser and digital camera with the dual pulse laser and CCD camera for PIV measurement.</li>
		<li>Repeat steps 1.4.6 - 1.5.3 to record the calibration for PIV measurement.</li>
		<li>Turn on the wind tunnel at the desired freestream velocity, U = 2.64 m/s. Run it for 10 minutes to ensure that the freestream velocity is stable.</li>
		<li>Adjust the dual pulse laser to the highest power level and stand by. Use the software to start the data acquisition for 100 s. Once the data recording has finished, turn off the laser head.</li>
		<li>Review the acquired images in the software and check the laser sheet distribution, the particle density (usually 6-10 particles in each desired interrogation area), the focus, and the particle displacement between the double frames (25-50% of the interrogation area).</li>
		<li>If the quality of the images is satisfactory, as described in step 2.2.5., save the data onto the hard disk of the PC and run the other cases by repeating the above steps. Otherwise, repeat steps 1.7 and 2.2 and carefully adjust the setup.</li>
	</ol>
	</li>
</ol>
3. Data Processing
<ol>
	<li>Improved smoke visualization 
	NOTE: The following steps, 3.1.1-3.1.4, are done via MATLAB code automatically (see the Supplemental Coding File).
	<ol>
		<li>Transform the video into a sequence of frames. Convert the frames from the RGB form into grayscale. Rotate the frame to make the delta wing surface horizontal. Choose the area of interest for later processing (Figure 2a).</li>
		<li>Adjust the brightness and the contrast to highlight the flow structure. Apply an adaptive threshold to transform the gray image to a binary image (Figure 2b).</li>
		<li>Add up the binary values in each column and find the position at which the sum suddenly changes. This position is the vortex breakdown location (Figure 2c).</li>
		<li>Record the vortex breakdown locations and their corresponding times. The time history of the breakdown oscillation thus can be obtained.</li>
		<li>Use the pixel-real size scale factor (measured from the images with the calibration target plate in step 1.5.3) to transform the time history from pixels to real size and to identify the reference position. Plot the time history of the breakdown oscillation.</li>
	</ol>
	</li>
	<li>PIV measurement
	<ol>
		<li>Run the PIV software. Use the images acquired in step 2.2.2 to set the scale factor and the reference position of the coordinates. Pre-process the acquired data through the image processing library to highlight the particles and reduce noise18.</li>
		<li>Use the adaptive interrogation area method with a minimum grid size of 32 &#215; 32 pixels and a minimum overlap of 50%. Choose the image area and set a 3 x 3 vector validation for the adaptive cross-correlations.</li>
		<li>The result is given as a velocity vector field, in which the blue vectors are the correct vectors, the green ones are the substituted vectors, and the red ones are bad vectors.</li>
		<li>Apply the 3 x 3 moving average validation method to estimate the local velocity by comparing the vectors in its neighborhood. Replace vectors that deviate too much from their neighbors with the average of their neighbors.</li>
		<li>Calculate vector statistics in the velocity maps to obtain the flow characteristics in the time history, e.g., the time-averaged velocity, the standard deviation, and the cross-correlation between velocity components. Compute the scalar derivatives from the vector map to demonstrate the internal features of the flow field, e.g., the vorticity, shear stresses, and swirling strength.</li>
	</ol>
	</li>
</ol>

<ol>
	<li>Smits, A. 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> Flow visualization: Techniques and examples. , (2012).</li><li>Barlow, J. B., Rae, W. H., Pope, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> Low-speed wind tunnel testing. , (1999).</li><li>Merzkirch, W. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> Flow visualization. , (1987).</li><li>Raffel, M., Willert, C. E., Wereley, S., 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>Westerweel, J., Elsinga, G. E., 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+Image+Velocimetry+for+Complex+and+Turbulent+Flows.">Particle Image Velocimetry for Complex and Turbulent Flows.</a> Annu Rev Fluid Mech. 45 (1), 409-436 (2013).</li><li>Meinhart, C. D., Wereley, S. T., Santiago, J. G. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=PIV+measurements+of+a+microchannel+flow.">PIV measurements of a microchannel flow.</a> Exp Fluids. 27 (5), 414-419 (1999).</li><li>Gursul, I. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Review+of+unsteady+vortex+flows+over+slender+delta+wings.">Review of unsteady vortex flows over slender delta wings.</a> J Aircraft. 42 (2), 299-319 (2005).</li><li>Gursul, I., Gordnier, R., Visbal, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Unsteady+aerodynamics+of+nonslender+delta+wings.">Unsteady aerodynamics of nonslender delta wings.</a> Prog Aerosp Sci. 41 (7), 515-557 (2005).</li><li>Lowson, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Some+experiments+with+vortex+breakdown.">Some experiments with vortex breakdown.</a> JRoy Aeronaut Soc. 68, 343-346 (1964).</li><li>Payne, F. M., Ng, T., Nelson, R. C., Schiff, L. B. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Visualization+and+wake+surveys+of+vortical+flow+over+a+delta+wing.">Visualization and wake surveys of vortical flow over a delta wing.</a> AIAA J. 26 (2), 137-143 (1988).</li><li>Lowson, M. V. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+three+dimensional+vortex+sheet+structure+on+delta+wings.">The three dimensional vortex sheet structure on delta wings.</a> Fluid Dynamics of Three-Dimensional Turbulent Shear Flows and Transition. , 11.11-11.16 (1989).</li><li>Riley, A. J., Lowson, M. V. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Development+of+a+three-dimensional+free+shear+layer.">Development of a three-dimensional free shear layer.</a> J Fluid Mech. 369, 49-89 (1998).</li><li>Menke, M., Gursul, I. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Unsteady+nature+of+leading+edge+vortices.">Unsteady nature of leading edge vortices.</a> Phys Fluids. 9 (10), 2960 (1997).</li><li>Yayla, S., Canpolat, C., Sahin, B., Akilli, H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Yaw+angle+effect+on+flow+structure+over+the+nonslender+diamond+wing.">Yaw angle effect on flow structure over the nonslender diamond wing.</a> AIAA J. 48 (10), 2457-2461 (2010).</li><li>Menke, M., Gursul, I. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Nonlinear+response+of+vortex+breakdown+over+a+pitching+delta+Wing.">Nonlinear response of vortex breakdown over a pitching delta Wing.</a> J Aircraft. 36 (3), 496-500 (1999).</li><li>Sahin, B., Yayla, S., Canpolat, C., Akilli, H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Flow+structure+over+the+yawed+nonslender+diamond+wing.">Flow structure over the yawed nonslender diamond wing.</a> Aerosp Sci Technol. 23 (1), 108-119 (2012).</li><li>Kohlman, D. L., Wentz, J. W. H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Vortex+breakdown+on+slender+sharp-edged+wings.">Vortex breakdown on slender sharp-edged wings.</a> J Aircraft. 8 (3), 156-161 (1971).</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> J Vis Exp. (76), e50559 (2013).</li><li>Mitchell, A. M., Barberis, D., Molton, P., D&#233;lery, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Oscillation+of+Vortex+Breakdown+Location+and+Blowing+Control+of+Time-Averaged+Location.">Oscillation of Vortex Breakdown Location and Blowing Control of Time-Averaged Location.</a> AIAA J. 38 (5), 793-803 (2000).</li><li>Shen, L., Wen, C. -. y., Chen, H. -. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Asymmetric+Flow+Control+on+a+Delta+Wing+with+Dielectric+Barrier+Discharge+Actuators.">Asymmetric Flow Control on a Delta Wing with Dielectric Barrier Discharge Actuators.</a> AIAA J. 54 (2), 652-658 (2016).</li><li>Leibovich, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+Structure+of+Vortex+Breakdown.">The Structure of Vortex Breakdown.</a> Annu Rev Fluid Mech. 10 (1), 221-246 (1978).</li><li>Mitchell, A. M., Molton, P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Vortical+Substructures+in+the+Shear+Layers+Forming+Leading-Edge+Vortices.">Vortical Substructures in the Shear Layers Forming Leading-Edge Vortices.</a> AIAA J. 40 (8), 1689-1692 (2002).</li><li>Gad-El-Hak, M., Blackwelder, R. F. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+discrete+vortices+from+a+delta+wing.">The discrete vortices from a delta wing.</a> AIAA J. 23 (6), 961-962 (1985).</li><li>Zhou, J., Adrian, R. J., Balachandar, S., Kendall, T. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Mechanisms+for+generating+coherent+packets+of+hairpin+vortices+in+channel+flow.">Mechanisms for generating coherent packets of hairpin vortices in channel flow.</a> J. Fluid Mech. 387, 353-396 (1999).</li><li>Adrian, R. J., Christensen, K. T., Liu, Z. C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Analysis+and+interpretation+of+instantaneous+turbulent+velocity+fields.">Analysis and interpretation of instantaneous turbulent velocity fields.</a> Exp Fluids. 29 (3), 275-290 (2000).</li><li>Yoda, M., Hesselink, L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+three-dimensional+visualization+technique+applied+to+flow+around+a+delta+wing.">A three-dimensional visualization technique applied to flow around a delta wing.</a> Exp. Fluids. 10 (2-3), (1990).</li><li>Greenwell, D. I. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> RTO AVT Symposium. , (2001).</li><li>Furman, A., Breitsamter, C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Turbulent+and+unsteady+flow+characteristics+of+delta+wing+vortex+systems.">Turbulent and unsteady flow characteristics of delta wing vortex systems.</a> Aerosp Sci Technol. 24 (1), 32-44 (2013).</li><li>Wang, C., Gao, Q., Wei, R., Li, T., Wang, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=3D+flow+visualization+and+tomographic+particle+image+velocimetry+for+vortex+breakdown+over+a+non-slender+delta+wing.">3D flow visualization and tomographic particle image velocimetry for vortex breakdown over a non-slender delta wing.</a> Exp Fluids. 57 (6), (2016).</li></ol>

The authors have nothing to disclose.

This article presents the two flow visualization methods, improved smoke flow visualization and PIV measurement, to investigate flow structure over the delta wing qualitatively and quantitatively. The general procedures of the experiment are described step by step. The setups of these two methods are almost the same, while the devices involved are different. The basic principle of these two flow visualization methods is to illuminate the particles in the flow via the laser sheet. The improved smoke flow visualization can obtain the global flow structure and small local structures at the same time, which is helpful for obtaining an overview of an unknown flow structure. The quantitative PIV analysis provides a detailed vector map of the interesting flow field. Thus, combining these flow visualization methods can significantly improve research efficiency.
Compared with normal smoke wire flow visualization, the smoke flow visualization method demonstrated here is rather efficiently conducted. Because the particles are uniformly distributed, small flow structures are easily identified. In a complex three-dimensional flow, this method allows the laser sheet to be set up at any spatial position to observe the flow fields in different cross-sections, whereas in the traditional smoke wire method, the laser sheet must always be aligned with the smoke direction and the observation window is accordingly limited26. Additionally, this improved method should not miss any flow details caused by the absence of the smoke in some regions during a smoke wire experiment. However, this method would not be suitable for open-loop wind tunnel facilities due to how seeding is conducted. Flow visualization data should be carefully analyzed to avoid the pitfalls of imaginary illuminations3,27.
Because the flow field over the delta wing is highly three-dimensional and sensitive to any disturbance, non-intrusive investigations are recommended21. For measurements in planes, it is essential to consider the orthogonal velocity component on the observation plane during PIV measurement28,29. In this case, the time interval between two frames and the laser sheet thickness should be a compromise with the orthogonal velocity to ensure that most of the particles do not move out the laser sheet. For similar measurements, it is suggested to run several cases with different setup parameters in advance to identify the most suitable ones.
The flow visualization methods described in this paper are convenient, efficient, and low-cost. In the future, these techniques will be applied to complex flow fields with active flow control, such as bluff body drag reduction and vortex-structure interaction, to evaluate control effects quickly, understand control mechanisms, and accelerate the optimization of control parameters.

Flow field measurement via visualization techniques is a basic methodology in fluid engineering. Among the different visualization techniques, smoke wire flow visualization in wind tunnel experiments and dye visualization in water tunnel experiments are the most widely used to illustrate flow structures qualitatively. PIV and laser Doppler anemometry (LDA) are two typical quantitative techniques1.
In smoke wire flow visualization, smoke streaklines are generated from oil droplets on a heating wire or injected from the outer smoke generator/container during the experiments. High-power lights or laser sheets are used to illuminate the smoke streaklines. Images are then recorded for further analysis. This is a simple but very useful flow visualization method2. However, the effectiveness of this method may be limited by various factors, such as the short duration of smoke wires, the complex three-dimensional flow field, the relatively high velocity of the flow, and the efficiency of smoke generation3.
In PIV measurements, a cross-section of a flow field with entrained particles is illuminated by a laser sheet, and instant positions of the particles in this cross-section are captured by a high-speed camera. Within an extremely small time interval, a pair of images is recorded. By dividing the images into a grid of interrogation areas and calculating the average motion of particles in interrogation areas through cross-correlation functions, the instantaneous velocity vector map in this observed cross-section can be obtained. However, it is also known that compromises must be reached for factors including the size of the observation window, the resolution of the velocity map, the velocity magnitude in the plane, the time interval between the pair of images, the orthogonal velocity magnitude, and the particle density4. Therefore, many exploratory experiments may be needed to optimize the experimental settings. It would be expensive and time-consuming to investigate an unknown and complex flow field with PIV measurement alone5,6. Considering the above concerns, a strategy to combine smoke flow visualization and PIV measurement is proposed and demonstrated here to study the complex flow over a slender delta wing.
Numerous studies of LEV flows over delta wings have been conducted7,8, with flow visualization techniques used as the primary tools. Many interesting flow phenomena have been observed: spiral type and bubble type vortex breakdowns9,10, an unsteady shear layer substructure11,12, oscillations of LEV breakdown locations13, and effects of pitching and yaw angles14,15,16 on the flow structures. However, the underlying mechanisms of some unsteady phenomena in the delta wing flows remain unclear7. In this work, the smoke flow visualization is improved using the same seeding particles used in PIV measurement, instead of a smoke wire. This improvement greatly simplifies the operation of the visualization and increases the quality of the images. Based on the results from the improved smoke flow visualization, PIV measurement focuses on those flow fields of interest to acquire the quantitative information.
Here, a detailed description is provided to explain how to conduct a flow visualization experiment in a wind tunnel and to investigate unsteady flow phenomena over a delta wing. Two visualization methods, the improved smoke flow visualization and PIV measurement, are used together in this experiment. The procedure includes step-by-step guidance for device setup and parameter adjustment. Typical results are demonstrated to show the advantage of combining these two methods for measuring the complex flow field spatially and temporally.

<table>
	<tbody>
		<tr>
			<td>532 nm Nd:YAG laser</td>
			<td>Quantel Laser</td>
			<td>Evergreen 600mJ</td>
			<td></td>
		</tr>
		<tr>
			<td>High speed camera</td>
			<td>Dantec Dynamic</td>
			<td>HiSense 4M</td>
			<td></td>
		</tr>
		<tr>
			<td>camera lens</td>
			<td>Tamron</td>
			<td>SP AF180mm F/3.5 Di</td>
			<td></td>
		</tr>
		<tr>
			<td>PIV recording and processing software</td>
			<td>Dantec Dynamic</td>
			<td>DynamicStudio</td>
			<td></td>
		</tr>
		<tr>
			<td>cylindrical lens</td>
			<td>Newport</td>
			<td></td>
			<td>&#934;=12 mm</td>
		</tr>
		<tr>
			<td>convex lens</td>
			<td>Newport</td>
			<td></td>
			<td>f=700 mm</td>
		</tr>
		<tr>
			<td>neutral density filter</td>
			<td>Newport</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Calibration target</td>
			<td></td>
			<td></td>
			<td>custom made</td>
		</tr>
		<tr>
			<td>aerosol generator</td>
			<td>TSI</td>
			<td>TSI 9307-6</td>
			<td></td>
		</tr>
		<tr>
			<td>PULSE GENERATOR</td>
			<td>Berkeley Nucleonics Corp</td>
			<td>BNC 575</td>
			<td></td>
		</tr>
		<tr>
			<td>continuous laser</td>
			<td></td>
			<td>APGL-FN-532-1W</td>
			<td></td>
		</tr>
		<tr>
			<td>Digital camera</td>
			<td>Nikon</td>
			<td>Nikon D5200</td>
			<td></td>
		</tr>
		<tr>
			<td>Image processing</td>
			<td>Matlab</td>
			<td></td>
			<td>custom code</td>
		</tr>
		<tr>
			<td>wind tunnel support</td>
			<td></td>
			<td></td>
			<td>custom made</td>
		</tr>
		<tr>
			<td>laser level</td>
			<td>BOSCH</td>
			<td>GLL3-15X</td>
			<td></td>
		</tr>
		<tr>
			<td>angle meter</td>
			<td>BOSCH</td>
			<td>GAM220</td>
			<td></td>
		</tr>
	</tbody>
</table>

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.

Figure 2d shows the time histories of the LEV breakdown locations. The black curve indicates the portside LEV and the red curve indicates the starboard LEV. The time scale is nondimensionalized by the free stream velocity and chord length. The correlation coefficient between these two time histories is r = &#8722;0.53, indicating a strong anti-symmetric interaction of the LEV breakdown location oscillations. This result agrees well with the work of others13,19,20.
Figure 3 shows the LEV flow structure in the longitudinal cross section at &#945; = 34&#176; and Re = 75,000. The original image was captured by the digital camera in RGB form, with an exposure duration of 1/500 seconds. In this figure, the coordinate is normalized by the delta wing chord length. A 10 mm scale is plotted at the upper right corner for reference. The result clearly demonstrates the primary LEV core, which develops from the tip of the delta wing to the downstream in a straight line. Near the position at x = 0.19 c, the vortex core suddenly expands. This is known as the leading edge vortex breakdown9,21. After the breakdown location, the wake becomes turbulent. Around the primary LEV core are small vortical structures. These substructures originate from the leading edges and swirl around the primary vortex core within the rolling up shear layer12,22,23. As the substructures move into the inner layer of the LEV, their shape is stretched due to the relatively high velocity component in the longitudinal direction near the vortex core. During the experiment, it is noted that the flow structure of the LEV is quite stationary, except at the LEV breakdown location. This result shows that this smoke flow visualization method can achieve a good balance between the local small flow structure and the global flow structure evolution.
Figure 4 shows the typical particle images in a 64 x 64 pixel region, captured from PIV measurement. In the 32 x 32 pixel interrogation area in Frame A, there are 10 identified particles, marked by yellow circles. After the time interval between two frames, these particles displace to new locations, as shown in Frame B. The displacements are about one-quarter of the interrogation area, resulting in an almost 70% overlap between these interrogation areas. Additionally, almost all of the particles remain in the laser sheet plane, indicating that the setup parameters were appropriately chosen for this case.
Figure 5 shows the time-averaged PIV results in the streamwise and spanwise cross sections. Before these measurements are carried out, the improved smoke flow visualization is conducted to identify the primary vortex core position, following steps 2.1.1 - 2.1.3. The coordinates in Figure 5 are normalized by the delta wing chord length c and the local semispan length SL. The vorticity <img alt="Equation 4" src="/files/ftp_upload/57244/57244eq4.jpg" /> is normalized as &#969;* = &#969;U&#8734;/c. According to this result, the primary vortex core can be easily identified by the inflection line of the positive and negative vorticities, and it is marked by the black dotted line. In the upper and bottom regions, the rolling shear layers show large vorticities. The &#955;ci criterion24,25 is used to identify the vortices from PIV measurement. In Figure 5, the solid lines illustrate the region with a local swirling strength lower than zero, indicating the existence of vortices. Near the core, the substructures are stretched and do not appear in the swirling strength contour. However, the concentrated vorticity contour still suggests the substructures here, marked by the white dotted line. In Figure 5b, the velocity vector map clearly illustrates that on each side, the flow separates at the leading edge and forms a strong shear layer, which later rolls into the LEV core. Complementary to the flow structure in the streamwise cross section, the spanwise flow structure clearly shows the evolution of the outer vortical substructures.
<img alt="Figure 1" class="xfigimg" src="/files/ftp_upload/57244/57244fig1.jpg" /> 
Figure 1: Schematics of setups. (a) The delta wing model; (b-d) setups for PIV measurement in the longitudinal cross-section, the spanwise cross-section, and the transverse cross-section, respectively. <a href="https://cloudflare-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/57244/57244fig1large.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/57244/57244fig2.jpg" /> 
Figure 2: Measurement of the LEV breakdown location. (a) A smoke flow visualization result showing the leading-edge vortex structure in the transverse cross section: &#945; = 34&#176; and Re = 50,000; the marked area is rotated and further processed. (b) The binary image of the marked area in (a), clearly showing the LEV core and breakdown. (c) The summation of each column in the binary image (b) and the identified LEV breakdown location in the streamwise direction (x-direction), normalized by the chord length c. (d) The time histories of the LEV breakdown locations. <img alt="Equation 5" src="/files/ftp_upload/57244/57244eq5.jpg" /> is the time-averaged position and <img alt="Equation 6" src="/files/ftp_upload/57244/57244eq6.jpg" /> is the instant distance to the time-averaged position. <a href="https://cloudflare-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/57244/57244fig2large.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/57244/57244fig3.jpg" /> 
Figure 3: The leading-edge vortex structure in the longitudinal cross section at &#945; = 34&#176; and Re = 75,000, obtained from the smoke flow visualization. <a href="https://cloudflare-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/57244/57244fig3large.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/57244/57244fig4.jpg" /> 
Figure 4: Particle images in a 64 x 64 pixel region. The corresponding interrogation area is 32 x 32 pixels. The time interval between Frames A and B is 80 microseconds. The identified particles in the original interrogation area are marked by yellow circles. <a href="https://cloudflare-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/57244/57244fig4large.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/57244/57244fig5.jpg" /> 
Figure 5: Time-averaged PIV results. (a) Dimensionless vorticity &#969;* contour with solid lines marking the regions with local swirling strength lower than zero in the longitudinal cross section. (b) Dimensionless vorticity &#969;* contour with velocity vectors in the spanwise cross section at x = 0.4c; coordinates are normalized by the local semispan length SL (&#945; = 34&#176; and Re = 50,000). <a href="https://cloudflare-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/57244/57244fig5large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>

Watch this Scientific Journal Video about Experimental Investigation of the Flow Structure over a Delta Wing Via Flow Visualization Methods at JoVE.com

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

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 ...

experimental-investigation-flow-structure-over-delta-wing-via-flow

Nanyang Technological University

Research

Education

JoVE Journal

JoVE Core

Civil Engineering

Mechanical Engineering

Engineering

Unit 1

Flow over Immersed Bodies

Force Vectors

SCIENTISTS IN ACTION

10.5K Views.  Hong Kong Polytechnic University. 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.

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

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 ...

Measuring Material Microstructure Under Flow Using 1-2 Plane Flow-Small Angle Neutron Scattering

A new small-angle neutron scattering (SANS) sample environment optimized for studying the microstructure of complex fluids under simple shear flow is presented. The SANS shear cell consists of a concentric cylinder Couette geometry that is sealed and rotating about a horizontal axis so that the vorticity direction of the flow field is aligned with the neutron beam enabling scattering from the 1-2 plane of shear (velocity-velocity gradient, respectively). This approach is an advance over previous shear cell sample environments as there is a strong coupling between the bulk rheology and microstructural features in the 1-2 plane of shear. Flow-instabilities, such as shear banding, can also be studied by spatially resolved measurements. This is accomplished in this sample environment by using a narrow aperture for the neutron beam and scanning along the velocity gradient direction. Time resolved experiments, such as flow start-ups and large amplitude oscillatory shear flow are also possible by synchronization of the shear motion and time-resolved detection of scattered neutrons. Representative results using the methods outlined here demonstrate the useful nature of spatial resolution for measuring the microstructure of a wormlike micelle solution that exhibits shear banding, a phenomenon that can only be investigated by resolving the structure along the velocity gradient direction. Finally, potential improvements to the current design are discussed along with suggestions for supplementary experiments as motivation for future experiments on a broad range of complex fluids in a variety of shear motions.

A shear cell is developed for small-angle neutron scattering measurements in the velocity-velocity gradient plane of shear and is used to characterize complex fluids. Spatially resolved measurements in the velocity gradient direction are possible for studying shear-banding materials. Applications include investigations of colloidal dispersions, polymer solutions, and self-assembled structures.

A new small-angle neutron scattering (SANS) sample environment optimized for studying the microstructure of complex fluids under simple shear flow is ...

Advanced Experimental Methods for Low-temperature Magnetotransport Measurement of Novel Materials

Novel electronic materials are often produced for the first time by synthesis processes that yield bulk crystals (in contrast to single crystal thin film synthesis) for the purpose of exploratory materials research. Certain materials pose a challenge wherein the traditional bulk Hall bar device fabrication method is insufficient to produce a measureable device for sample transport measurement, principally because the single crystal size is too small to attach wire leads to the sample in a Hall bar configuration. This can be, for example, because the first batch of a new material synthesized yields very small single crystals or because flakes of samples of one to very few monolayers are desired. In order to enable rapid characterization of materials that may be carried out in parallel with improvements to their growth methodology, a method of device fabrication for very small samples has been devised to permit the characterization of novel materials as soon as a preliminary batch has been produced. A slight variation of this methodology is applicable to producing devices using exfoliated samples of two-dimensional materials such as graphene, hexagonal boron nitride (hBN), and transition metal dichalcogenides (TMDs), as well as multilayer heterostructures of such materials. Here we present detailed protocols for the experimental device fabrication of fragments and flakes of novel materials with micron-sized dimensions onto substrate and subsequent measurement in a commercial superconducting magnet, dry helium close-cycle cryostat magnetotransport system at temperatures down to 0.300 K and magnetic fields up to 12 T.

We describe the methodology of mechanical exfoliation and deposition of flakes of novel materials with micron-sized dimensions onto substrate, fabrication of experimental device structures for transport experimentation, and the magnetotransport measurement in a dry helium close-cycle cryostat at temperatures down to 0.300 K and magnetic fields up to 12 T.

Novel electronic materials are often produced for the first time by synthesis processes that yield bulk crystals (in contrast to single crystal thin film ...

Experimental Methods for Investigation of Shape Memory Based Elastocaloric Cooling Processes and Model Validation

Shape Memory Alloys (SMA) using elastocaloric cooling processes have the potential to be an environmentally friendly alternative to the conventional vapor compression based cooling process. Nickel-Titanium (Ni-Ti) based alloy systems, especially, show large elastocaloric effects. Furthermore, exhibit large latent heats which is a necessary material property for the development of an efficient solid-state based cooling process. A scientific test rig has been designed to investigate these processes and the elastocaloric effects in SMAs. The realized test rig enables independent control of an SMA&#39;s mechanical loading and unloading cycles, as well as conductive heat transfer between SMA cooling elements and a heat source/sink. The test rig is equipped with a comprehensive monitoring system capable of synchronized measurements of mechanical and thermal parameters. In addition to determining the process-dependent mechanical work, the system also enables measurement of thermal caloric aspects of the elastocaloric cooling effect through use of a high-performance infrared camera. This combination is of particular interest, because it allows illustrations of localization and rate effects &#8212; both important for efficient heat transfer from the medium to be cooled.
The work presented describes an experimental method to identify elastocaloric material properties in different materials and sample geometries. Furthermore, the test rig is used to investigate different cooling process variations. The introduced analysis methods enable a differentiated consideration of material, process and related boundary condition influences on the process efficiency. The comparison of the experimental data with the simulation results (of a thermomechanically coupled finite element model) allows for better understanding of the underlying physics of the elastocaloric effect. In addition, the experimental results, as well as the findings based on the simulation results, are used to improve the material properties.

Experimental methods for investigation of solid state cooling processes and characterization of elastocaloric material properties of Shape Memory Alloys (SMA) are presented. A custom-built test rig has been designed for controlling and comprehensive monitoring of elastocaloric cooling processes. Furthermore, it provides a validation platform for thermomechanically coupled modeling approaches.

Shape Memory Alloys (SMA) using elastocaloric cooling processes have the potential to be an environmentally friendly alternative to the conventional vapor ...

Three-dimensional Particle Tracking Velocimetry for Turbulence Applications: Case of a Jet Flow

3D-PTV is a quantitative flow measurement technique that aims to track the Lagrangian paths of a set of particles in three dimensions using stereoscopic recording of image sequences. The basic components, features, constraints and optimization tips of a 3D-PTV topology consisting of a high-speed camera with a four-view splitter are described and discussed in this article. The technique is applied to the intermediate flow field (5 &#60;x/d &#60;25) of a circular jet at Re &#8776; 7,000. Lagrangian flow features and turbulence quantities in an Eulerian frame are estimated around ten diameters downstream of the jet origin and at various radial distances from the jet core. Lagrangian properties include trajectory, velocity and acceleration of selected particles as well as curvature of the flow path, which are obtained from the Frenet-Serret equation. Estimation of the 3D velocity and turbulence fields around the jet core axis at a cross-plane located at ten diameters downstream of the jet is compared with literature, and the power spectrum of the large-scale streamwise velocity motions is obtained at various radial distances from the jet core.

A three-dimensional particle tracking velocimetry (3D-PTV) system based on a high-speed camera with a four-view splitter is described here. The technique is applied to a jet flow from a circular pipe in the vicinity of ten diameters downstream at Reynolds number Re &#8776; 7,000.

3D-PTV is a quantitative flow measurement technique that aims to track the Lagrangian paths of a set of particles in three dimensions using stereoscopic ...

Design and Use of a Full Flow Sampling System (FFS) for the Quantification of Methane Emissions

The use of natural gas continues to grow with increased discovery and production of unconventional shale resources. At the same time, the natural gas industry faces continued scrutiny for methane emissions from across the supply chain, due to methane&#39;s relatively high global warming potential (25-84x that of carbon dioxide, according to the Energy Information Administration). Currently, a variety of techniques of varied uncertainties exists to measure or estimate methane emissions from components or facilities. Currently, only one commercial system is available for quantification of component level emissions and recent reports have highlighted its weaknesses.
In order to improve accuracy and increase measurement flexibility, we have designed, developed, and implemented a novel full flow sampling system (FFS) for quantification of methane emissions and greenhouse gases based on transportation emissions measurement principles. The FFS is a modular system that consists of an explosive-proof blower(s), mass airflow sensor(s) (MAF), thermocouple, sample probe, constant volume sampling pump, laser based greenhouse gas sensor, data acquisition device, and analysis software. Dependent upon the blower and hose configuration employed, the current FFS is able to achieve a flow rate ranging from 40 to 1,500 standard cubic feet per minute (SCFM). Utilization of laser-based sensors mitigates interference from higher hydrocarbons (C2+). Co-measurement of water vapor allows for humidity correction. The system is portable, with multiple configurations for a variety of applications ranging from being carried by a person to being mounted in a hand drawn cart, on-road vehicle bed, or from the bed of utility terrain vehicles (UTVs). The FFS is able to quantify methane emission rates with a relative uncertainty of &#177; 4.4%. The FFS has proven, real world operation for the quantification of methane emissions occurring in conventional and remote facilities.

Design and Use of a Full Flow Sampling System FFS for the Quantification of Methane Emissions

We have designed, developed, and implemented a novel full flow sampling system (FFS) for quantification of methane emissions and greenhouse gases from across the natural gas supply chain.

The use of natural gas continues to grow with increased discovery and production of unconventional shale resources. At the same time, the natural gas ...

Microfluidic Imaging Flow Cytometry by Asymmetric-detection Time-stretch Optical Microscopy (ATOM)

Scaling the number of measurable parameters, which allows for multidimensional data analysis and thus higher-confidence statistical results, has been the main trend in the advanced development of flow cytometry. Notably, adding high-resolution imaging capabilities allows for the complex morphological analysis of cellular/sub-cellular structures. This is not possible with standard flow cytometers. However, it is valuable for advancing our knowledge of cellular functions and can benefit life science research, clinical diagnostics, and environmental monitoring. Incorporating imaging capabilities into flow cytometry compromises the assay throughput, primarily due to the limitations on speed and sensitivity in the camera technologies. To overcome this speed or throughput challenge facing imaging flow cytometry while preserving the image quality, asymmetric-detection time-stretch optical microscopy (ATOM) has been demonstrated to enable high-contrast, single-cell imaging with sub-cellular resolution, at an imaging throughput as high as 100,000 cells/s. Based on the imaging concept of conventional time-stretch imaging, which relies on all-optical image encoding and retrieval through the use of ultrafast broadband laser pulses, ATOM further advances imaging performance by enhancing the image contrast of unlabeled/unstained cells. This is achieved by accessing the phase-gradient information of the cells, which is spectrally encoded into single-shot broadband pulses. Hence, ATOM is particularly advantageous in high-throughput measurements of single-cell morphology and texture &#8211; information indicative of cell types, states, and even functions. Ultimately, this could become a powerful imaging flow cytometry platform for the biophysical phenotyping of cells, complementing the current state-of-the-art biochemical-marker-based cellular assay. This work describes a protocol to establish the key modules of an ATOM system (from optical frontend to data processing and visualization backend), as well as the workflow of imaging flow cytometry based on ATOM, using human cells and micro-algae as the examples.

Microfluidic Imaging Flow Cytometry by Asymmetric-detection Time-stretch Optical Microscopy ATOM

This protocol describes the implementation of an asymmetric-detection time-stretch optical microscopy system for single-cell imaging in ultrafast microfluidic flow and its applications in imaging flow cytometry.

Scaling the number of measurable parameters, which allows for multidimensional data analysis and thus higher-confidence statistical results, has been the ...

Experimental Methods for Trapping Ions Using Microfabricated Surface Ion Traps

Ions trapped in a quadrupole Paul trap have been considered one of the strong physical candidates to implement quantum information processing. This is due to their long coherence time and their capability to manipulate and detect individual quantum bits (qubits). In more recent years, microfabricated surface ion traps have received more attention for large-scale integrated qubit platforms. This paper presents a microfabrication methodology for ion traps using micro-electro-mechanical system (MEMS) technology, including the fabrication method for a 14 &#181;m-thick dielectric layer and metal overhang structures atop the dielectric layer. In addition, an experimental procedure for trapping ytterbium (Yb) ions of isotope 174 (174Yb+) using 369.5 nm, 399 nm, and 935 nm diode lasers is described. These methodologies and procedures involve many scientific and engineering disciplines, and this paper first presents the detailed experimental procedures. The methods discussed in this paper can easily be extended to the trapping of Yb ions of isotope 171 (171Yb+) and to the manipulation of qubits.

This paper presents a microfabrication methodology for surface ion traps, as well as a detailed experimental procedure for trapping ytterbium ions in a room-temperature environment.

Ions trapped in a quadrupole Paul trap have been considered one of the strong physical candidates to implement quantum information processing. This is due ...

Flow-assisted Dielectrophoresis: A Low Cost Method for the Fabrication of High Performance Solution-processable Nanowire Devices

Flow-assisted dielectrophoresis (DEP) is an efficient self-assembly method for the controllable and reproducible positioning, alignment, and selection of nanowires. DEP is used for nanowire analysis, characterization, and for solution-based fabrication of semiconducting devices. The method works by applying an alternating electric field between metallic electrodes. The nanowire formulation is then dropped onto the electrodes which are on an inclined surface to create a flow of the formulation using gravity. The nanowires then align along the gradient of the electric field and in the direction of the liquid flow. The frequency of the field can be adjusted to select nanowires with superior conductivity and lower trap density. 
In this work, flow-assisted DEP is used to create nanowire field effect transistors. Flow-assisted DEP has several advantages: it allows selection of nanowire electrical properties; control of nanowire length; placement of nanowires in specific areas; control of orientation of nanowires; and control of nanowire density in the device. 
The technique can be expanded to many other applications such as gas sensors and microwave switches. The technique is efficient, quick, reproducible, and it uses a minimal amount of dilute solution making it ideal for the testing of novel nanomaterials. Wafer scale assembly of nanowire devices can also be achieved using this technique, allowing large numbers of samples for testing and large-area electronic applications.

In this paper, flow assisted dielectrophoresis is demonstrated for the self-assembly of nanowire devices. The fabrication of a silicon nanowire field effect transistor is shown as an example.

Flow-assisted dielectrophoresis (DEP) is an efficient self-assembly method for the controllable and reproducible positioning, alignment, and selection of ...