This research was supported by the Basic Science Research Program of the National Research Foundation of Korea, which is funded by the Ministry of Education (NRF-2021R1I1A3040346 and NRF-2020R1A4A1019475). This study was also supported by 2018 Research Grant (PoINT) from Kangwon National University.

1. In vitro setup
<ol>
	<li>Prepare the experimental setup on an optic table, including a piston pump, data acquisition device (DAQ), and a computer with the required system engineering software and a motor controlling software (see Table of Materials) (Figure 1). 
	NOTE: The piston pump has been previously tested and calibrated and consists of a motor, motor driver, and linear actuator9.</li>
	<li>Import the spreadsheet file with the flow rate information to the system engineering software. 
	NOTE: For example, heart rate is 60 bpm, the maximum flow rate is 20 L/min, cardiac output is 4.8 L/min, and stroke volume is 70 mL.</li>
	<li>Set the parameter in systems engineering software, such as DAQ input and output channel; sample clock is 1,000 and feedback iteration is 10.</li>
	<li>Set the parameter in the motor controlling software; lead screw length is 10 mm, analog input and output are 14.5 mm/voltage.</li>
	<li>Install the check valve and resistance valve to the reservoir10. 
	NOTE: The check valve is connected to the piston pump as an inlet of the system, and the ball valve is connected to the acrylic sinus model as an outlet of the system.</li>
	<li>Fix the acrylic sinus model (Figure 2) with a square aluminum bar to the optic table. 
	NOTE: The dimensions of the acrylic sinus model are presented in Table 1.</li>
	<li>Install the pressure gauge (~0-15 psi) to the pressure tap of the acrylic sinus model for receiving a pressure signal from another computer. 
	NOTE: The pressure taps are located 140 mm from the sinotubular junction (STJ).</li>
	<li>Prepare a working fluid by mixing saline and glycerin (see Table of Materials) in a mass ratio of 60:40. 
	NOTE: A viscometer and a refractometer were used to measure the working fluid&#39;s viscosity and refractive index. The viscosity is ~4 cp, the refractive index is 1.45, and the density is 1,100 kg/m3.</li>
	<li>Connect the reservoir, piston pump, and the acrylic sinus model with a silicone hose (see Table of Materials).</li>
	<li>Tie the transcatheter aortic valve (TAV) (see Table of Materials) to the native leaflet made by a 3D printer with a thread11.</li>
	<li>Combine the fixed TAV on the native leaflet with the acrylic sinus model. 
	NOTE: The TAV used here (obtained commercially) has a diameter of 23 mm and 26 mm, and height is 18 mm and 20 mm, respectively12. For TAV (23 mm), the deployment depth and native leaflet length were 1.8 mm and 9 mm, and for TAV (26 mm), it is 2.0 mm and 10 mm, respectively. The inner diameter of the native leaflet was 21 mm, considering the patient&#39;s annulus size. 
	CAUTION: The TAV dries out if not preserved in saline solution. It is kept in the liquid even after being tied to the native leaflet.</li>
	<li>Fill the working fluid (step 1.8) in the in vitro system. 
	&#8203;CAUTION. Avoid making bubbles on the acrylic sinus model because it affects PIV results.</li>
</ol>
2. PIV setup
<ol>
	<li>Locate the laser on another optic table and one-axis rail. 
	NOTE: The laser is a continuous Nd: YAG laser that emits light with a wavelength of 532 nm and whose power can increase to 10 W (see Table of Materials). The laser sheet passed through optics has a 1 m distance from the acrylic sinus model.</li>
	<li>Locate the high-speed camera on a 2-axis traverse and move the traverse. 
	CAUTION: The high-speed camera is perpendicular to the laser sheet and acrylic sinus model.</li>
	<li>Equip the lens to the high-speed camera. 
	NOTE: The macro lens mounted on the high-speed camera has a focal length of 105 mm, and the aperture is f/2.8.</li>
	<li>Seed particle (see Table of Materials) in the reservoir. 
	NOTE: The particle is a hollow glass sphere with an average diameter of 10 &#181;m and a density of 1,090 kg/m3. The reservoir has a rectangular shape and, the width, length, and height inside are 23 cm, 23 cm, 35 cm, respectively. There is a hole for fastening in the upper part. The lid also had a hole for fastening and a bolt tap to install the bulb pump to apply pressure.</li>
	<li>Program an external trigger using an open-source electronic prototypic platform, Arduino (see Table of Materials). 
	NOTE: When the piston pump moves a predetermined distance, the output of Arduino becomes 1, which is transmitted to the high-speed camera as a trigger to be photographed.</li>
	<li>Run the camera controlling software (see Table of Materials), click on Current Session Reference (CSR), and remove the lens cap.</li>
	<li>Turn on the laser, set it to 7 W, and locate the laser sheet to the center of the TAV.</li>
	<li>Take a snapshot and check the particle density and diameter. 
	NOTE: To reduce errors, confirm that ~8-10 particles are in the interrogation window, with a particle diameter of 2-4 pixels13.</li>
	<li>Set the parameters, such as resolution (1280 x 720), random frame rate, exposure time to maximum according to random frame rate in the camera controlling software.</li>
	<li>Click on the Enable button in the motor controlling software at first and click on the Start button in the systems engineering software to operate the piston pump.</li>
	<li>Take a picture and check whether the maximum particle distance is less than 4-6 pixels. 
	NOTE: This study corresponds to 50% of the interrogation window, which set 16 pixels between velocity vectors. The maximum distance of particles in the interrogation window is limited to 8 pixels.</li>
	<li>Repeat step 2.11 to ensure the maximum particle distance within that range by adjusting the frames per second (fps) if it is more than 6 pixels and lowering the fps if it is less than 4 pixels.</li>
</ol>
3. Investigation of hemodynamics
<ol>
	<li>Check whether there is leakage from the connection part of the acrylic sinus model or the silicone hose becomes folded.</li>
	<li>Import the excel file having stored flow rate and bpm information in the system engineering software. 
	NOTE: For example, heart rate is 60 bpm, the maximum flow rate is 20 L/min, cardiac output is 4.8 L/min, stroke volume is 70 mL (Figure 3A).</li>
	<li>Confirm the system engineering software parameter, such as DAQ device input and output channel. The sample clock is 1,000, and the feedback iteration is 10.</li>
	<li>Confirm the motor controlling software parameter, e.g., lead screw length is 10 mm, analog input and output are 14.5 mm/voltage.</li>
	<li>Turn on the high-speed camera and run the camera controlling software.</li>
	<li>Click on CSR and remove a lens cap.</li>
	<li>Set the camera controlling software parameters, e.g., the resolution of 1280 x 720, a frame rate of 300 fps, burst period of 200 &#181;s and 150 &#181;s, burst count of 3, and exposure (forced by the burst period).</li>
	<li>Turn on the laser, set it to 7 W, and locate the laser sheet on the center of TAV. Focus on the laser sheet by controlling the lens.</li>
	<li>Adjust the pressure to the reservoir. 
	NOTE: The mean post-valvular pressure is 100 mmHg while operating the piston pump (Figure 3B,C).</li>
	<li>Click on the Enable button in the motor controlling software at first and click on the Start button in the system engineering software to operate the piston pump.</li>
	<li>Wait until the flow rate stabilizes. 
	NOTE: The flow rate calculates the difference based on the signal from the piston pump and executes negative feedback, so it takes time to wait until it stabilizes.</li>
	<li>Check a trigger that works in the Arduino serial plotter.</li>
	<li>Capture particle images for continuous 14 cycles and repeat a total of seven times. 
	&#8203;NOTE: The storage capacity of a high-speed camera is related to the resolution and the number of particle images. According to the parameter set in step 3.7, it is possible to take a picture only for 14 cycles at a time.</li>
</ol>
4. Data processing
<ol>
	<li>Convert from .cine file to .tiff files using the camera controlling software.</li>
	<li>Calculate the average image for all the particle images over time. Remove the area corresponding to the reflection of the laser at the wall or the TAV by subtracting the average image14.</li>
	<li>Make the mask by separating the areas to be analyzed from those to discard. 
	NOTE: In this study, two masks were used: one to analyze the sinus region alone and the other to analyze the entire region, which contains the region after STJ.</li>
	<li>Perform PIV using the PIVlab, an open-source tool based on MATLAB15 (see Table of Materials).
	<ol>
		<li>Import particle images saved by the time-resolved method or pairwise method.</li>
		<li>Execute contrast limited adaptive histogram equalization (CLAHE)16. 
		NOTE: CLAHE is a method for image pre-processing. The contrast of the particle image is redistributed so that the laser reflects the increase and decrease in the particle intensity. The particle image is divided by a window with 20 pixels.</li>
		<li>Import the mask and apply it to all the particle images.</li>
		<li>Set the multi-pass interrogation window. 
		NOTE: The interrogation window is decreased from 64 x 64 to 32 x 32 with a 50% overlap. The distance between the two vectors corresponds to 16 pixels.</li>
		<li>Execute the cross-correlation13 about the particle image pair converted into the frequency domain using fast Fourier transform (FFT)13.</li>
		<li>Find a peak value using a 2 x 3 Gaussian fit in correlation result. 
		NOTE: The peak value selected in the Gaussian fitting determined the particle distance.</li>
	</ol>
	</li>
	<li>Run the smoothing process, which involves the following processes.
	<ol>
		<li>Remove the outliers into a &#34;NaN&#34; using the &#34;isoutlier&#34; built-in function in MATLAB.</li>
		<li>Interpolate a nan to value using the &#34;inpaint_nans&#34; function in MATLAB15.</li>
		<li>Convert from &#34;pixel/frame&#34; to &#34;m/s&#34; according to the frame rate and burst period. 
		NOTE: The conversion is related to the time interval, determined by the frame rate and burst period. Specifically, the coefficient of the time-resolved method is derived by the frame rate, and that of a pairwise method is derived by the burst period.</li>
		<li>Merge the pairwise method and time-resolved method using the weighting factor. 
		NOTE: The weighting factor depends on the velocity magnitude and has a total value of 1 in each section. If the velocity magnitude exceeds a certain threshold, the factor for the pairwise method is higher than that for the time-resolved method.</li>
		<li>Run the &#34;smoothn&#34; function of DCT-PLS using a smoothing factor of 0.5915,17. 
		&#8203;NOTE: The &#34;smoothn&#34; and &#34;inpaint_nans&#34; functions are present in the PIVlab.</li>
	</ol>
	</li>
</ol>
5. Data analysis
<ol>
	<li>Load PIV data into MATLAB.</li>
	<li>Extract &#34;u&#34; and &#34;v&#34; components from the PIV data.</li>
	<li>Calculate the velocity field18 (Equation 1, Supplementary File 1).</li>
	<li>Derive hemodynamics parameters using the in-house code and built-in function19.
	<ol>
		<li>Derive the vorticity with MATLAB built-in function &#34;curl&#34;18 (Equation 2, Supplementary File 1).</li>
		<li>Derive the stasis with the in-house code20 (Equation 3, Supplementary File 1).</li>
		<li>Derive the &#915;1 with the in-house code21 (Equation 4, Supplementary File 1).</li>
		<li>Derive the particle residence with an in-house code19 (Equation 5, Supplementary File 1).</li>
	</ol>
	</li>
	<li>Calculate the average and standard deviation of hemodynamics parameters (Table 2). 
	NOTE: Peak velocity, vorticity, &#915;1, and stasis were calculated for a total of 98 cycles. The decay was obtained through exponential fitting to the percentage of particle residence. The decay set 14 cycles as one dataset and calculated the average and standard deviation for seven times.</li>
</ol>

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The authors have nothing to disclose.

The sinus flow changed due to different sinus geometry after TAVI. The vortex was formed by the aortic valve opening and the interaction with the forward jet of systole22. In the study of the artificial surgical valve without native leaflets, vortex observed in the sinus region at systole was normal23. This study forms the vortex presented at diastole by reducing the forward jet and coming into the sinus. The sinus flow encountered the native leaflet; as a result, it splits...

Aortic stenosis is a common disease in older adults, and it is when the aortic valve doesn&#39;t open, reducing blood flow. The problem is caused by the thickening or calcification of the aortic valve1. Therefore, it is a necessary treatment to enhance the blood flow and decrease the load on the heart. It is treated by remodeling the aortic valve or replacing it with an artificial valve. This study focuses on transcatheter aortic valve implantation (TAVI), replacing the malfunctioning aortic valve with an artificial one using a catheter.
TAVI has been recommended for patients challenged in surgery, and the mortality has also been low2. Recently, it has been reported that thrombus in patients after TAVI caused valve dysfunction and stroke3,4. Thrombus in the aortic sinus and neo-sinus is suspected, with its cause probably being the changes in the hemodynamics caused by TAVI. It is performed without removing the native leaflets; these leaflets can disturb the sinus flow and elevate the risk of thrombosis5.
It is difficult to determine how blood flow is affected by TAVI and how thrombosis is induced in patients. It is desirable to elucidate the relationship between blood flow and thrombus formation in vivo. However, a lack of practical techniques for measuring blood flow makes this problematic. On the other hand, in vitro techniques have the advantage of allowing one to monitor the changes in the blood flow by limiting the parameters that must be investigated. In vitro setup and particle image velocimetry (PIV) have been used to identify velocity in medical fields6,7,8. Therefore, in vitro and PIV are sufficient for determining the parameters to be reported by mimicking the patient&#39;s condition: the heart rate and pressure, viscosity, and sinus geometry, and allowing one to control these parameters.
In this study, in vitro setup and PIV are used to investigate the flow in the aortic sinus after TAVI. The aortic phantom and TAVI for the PIV and the data acquisition process and post-processing flow analysis are described in this protocol. Various hemodynamic parameters are derived, including the velocity, stasis, vortex, vorticity, and particle residence. The results demonstrate that in vitro setup and PIV help investigate the hemodynamic features in the aortic sinus.

<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>3D Printer</td>
			<td>Prusa Research</td>
			<td></td>
			<td>Original Prusa i3 MK2; FDM printer</td>
		</tr>
		<tr>
			<td>Aluminum bar (square)</td>
			<td>APSPRO</td>
			<td>KHP-3030, KHP-6060</td>
			<td>Dimension: 30 mm x 30 mm, 60 mm x 60 mm</td>
		</tr>
		<tr>
			<td>Bulb pump</td>
			<td>Skyhope</td>
			<td></td>
			<td>MHL-1</td>
		</tr>
		<tr>
			<td>Camera controlling software</td>
			<td>Phantom</td>
			<td>PCC 3.4 software</td>
			<td>The software controll the high speed camera</td>
		</tr>
		<tr>
			<td>Check valve</td>
			<td>HANJU STEEL PIPE</td>
			<td></td>
			<td>Check valve; 1/2 inch (15A)</td>
		</tr>
		<tr>
			<td>Digital Aqusition device</td>
			<td>National Instruments</td>
			<td></td>
			<td>USB-6001</td>
		</tr>
		<tr>
			<td>Glycerin</td>
			<td>ANU Korea</td>
			<td></td>
			<td>It used for making a working fluid</td>
		</tr>
		<tr>
			<td>High-speed camera</td>
			<td>Phantom</td>
			<td></td>
			<td>Phantom VEO 710E-L</td>
		</tr>
		<tr>
			<td>Laser</td>
			<td>Changchun New Industries Optoelectronics Technology</td>
			<td></td>
			<td>MGL-W-532; CW Nd:YAG Laser</td>
		</tr>
		<tr>
			<td>Linear actuator</td>
			<td>THOMSON</td>
			<td></td>
			<td>PC-40; it converts the rotational motion to lenear motion</td>
		</tr>
		<tr>
			<td>Macro lens</td>
			<td>Nikon</td>
			<td></td>
			<td>VR Micro-NIKKOR 105mm, f/1.4</td>
		</tr>
		<tr>
			<td>Motor</td>
			<td>KOLLMORGEN</td>
			<td></td>
			<td>AKM33H-ANCNR-00; DC servo motor</td>
		</tr>
		<tr>
			<td>Motor controlling software</td>
			<td>KOLLMORGEN</td>
			<td></td>
			<td>Kollmorgen software; the software controll the motor driver</td>
		</tr>
		<tr>
			<td>Motor driver</td>
			<td>KOLLMORGEN</td>
			<td></td>
			<td>AKD-B00606-NBAN-0000</td>
		</tr>
		<tr>
			<td>Open-source electronic prototypic platform</td>
			<td>Arduino</td>
			<td>A000066</td>
			<td>Arduino Uno R3. It used for making a external trigger</td>
		</tr>
		<tr>
			<td>Optic table</td>
			<td>SMTECH</td>
			<td></td>
			<td>1800 (W) x 900 (B) x 800 (H)</td>
		</tr>
		<tr>
			<td>Particle</td>
			<td>Dantec Dynamics</td>
			<td>80A6011</td>
			<td>Hollow Glass Sphere. Mean diameter:10 &#181;m, Density: 1090 kg/m3</td>
		</tr>
		<tr>
			<td>PIVlab</td>
			<td>PIVlab</td>
			<td></td>
			<td>Open source algorithm based on MATLAB 
			https://kr.mathworks.com/matlabcentral/fileexchange/27659-pivlab-particle-image-velocimetry-piv-tool-with-gui</td>
		</tr>
		<tr>
			<td>Pressure gauge</td>
			<td>OMEGA</td>
			<td></td>
			<td>PX309-015A5V. Measurement range: 0~15psi</td>
		</tr>
		<tr>
			<td>Refractometer</td>
			<td>ATAGO</td>
			<td>2350</td>
			<td>R-5000. Hand held refractometer; measurement range: 1.333-1.520</td>
		</tr>
		<tr>
			<td>Resistance valve</td>
			<td>HANJU STEEL PIPE</td>
			<td></td>
			<td>Ball valve; 1/2 inch (15A)</td>
		</tr>
		<tr>
			<td>Saline</td>
			<td>DAI HAN PHARM</td>
			<td></td>
			<td>It is used for making a working fluid and for preserving the TAV</td>
		</tr>
		<tr>
			<td>Silicone hose</td>
			<td>HSW</td>
			<td></td>
			<td>Inner diameter 26mm, Outter diameter 30mm; Inlet length 5m, Outlet length 1.5m</td>
		</tr>
		<tr>
			<td>System enginnering software</td>
			<td>National Instruments</td>
			<td></td>
			<td>LabVIEW software. The software controlls the DAQ.</td>
		</tr>
		<tr>
			<td>Transcatheter Aortic Valve, TAV (23 mm) and TAV (26 mm)</td>
			<td>Edwards Lifesciences</td>
			<td></td>
			<td>SAPIEN3 23mm, SAPIEN3 26mm. It is supported by Seoul Asan Medical</td>
		</tr>
		<tr>
			<td>Viscosmeter</td>
			<td>Brookfiled</td>
			<td></td>
			<td>DVELV; Measurement range: 1-2x109 cp</td>
		</tr>
	</tbody>
</table>

particle image velocimetry investigation of hemodynamics via aortic phantom

Aortic valve dysfunction and stroke have recently been reported in transcatheter aortic valve implantation (TAVI) patients. Thrombus in the aortic sinus and neo-sinus due to hemodynamic changes has been suspected. In vitro experiments help investigate the hemodynamic characteristics in the cases where an in vivo assessment proves to be limited. In vitro experiments are also more robust, and the variable parameters are controlled readily. Particle image velocimetry (PIV) is a popular velocimetry method for in vitro studies. It provides a high-resolution velocity field such that even small-scale flow features are observed. The purpose of this study is to show how PIV is used to investigate the flow field in the aortic sinus after TAVI. The in vitro setup of the aortic phantom, TAVI for PIV, and the data acquisition process and post-processing flow analysis are described. The hemodynamic parameters are derived, including the velocity, flow stasis, vortex, vorticity, and particle residence. The results confirm that in vitro experiments and PIV help investigate the hemodynamic features in the aortic sinus.

The velocity fields showed a different sinus flow structure depending on the valve diameter in Figure 4. For TAV (23 mm), the velocity was higher than 0.05 m/s between TAV and STJ from early systole to peak systole that TAV was opened using the forwarding jet. High velocity was then distributed in a narrow range near the stent at late systole. The velocity at diastole was lower than 0.025 m/s, and two vortexes with low velocity appeared. For TAV (26 mm), when the valve opened, high velocity ...

Watch this Scientific Journal Video about Particle Image Velocimetry Investigation of Hemodynamics via Aortic Phantom at JoVE.com

Particle Image Velocimetry Investigation of Hemodynamics via Aortic Phantom

The present protocol describes particle image velocimetry (PIV) measurements performed to investigate the sinus flow through the in vitro setup of the transcatheter aortic valve (TAV). The hemodynamic parameters based on velocity are also determined.

Particle Image Velocimetry Investigation of Hemodynamics via Aortic Phantom

Aortic valve dysfunction and stroke have recently been reported in transcatheter aortic valve implantation (TAVI) patients. Thrombus in the aortic sinus ...

particle-image-velocimetry-investigation-hemodynamics-via-aortic

Research

JoVE Journal

Engineering

3.1K Views.  Kangwon National University. The present protocol describes particle image velocimetry (PIV) measurements performed to investigate the sinus flow through the in vitro setup of the transcatheter aortic valve (TAV). The hemodynamic parameters based on velocity are also determined.

Video: Particle Image Velocimetry Investigation of Hemodynamics via Aortic Phantom

Investigation of Early Plasma Evolution Induced by Ultrashort Laser Pulses

Early plasma is generated owing to high intensity laser irradiation of target and the subsequent target material ionization. Its dynamics plays a significant role in laser-material interaction, especially in the air environment1-11.
Early plasma evolution has been captured through pump-probe shadowgraphy1-3 and interferometry1,4-7. However, the studied time frames and applied laser parameter ranges are limited. For example, direct examinations of plasma front locations and electron number densities within a delay time of 100 picosecond (ps) with respect to the laser pulse peak are still very few, especially for the ultrashort pulse of a duration around 100 femtosecond (fs) and a low power density around 1014 W/cm2. Early plasma generated under these conditions has only been captured recently with high temporal and spatial resolutions12. The detailed setup strategy and procedures of this high precision measurement will be illustrated in this paper. The rationale of the measurement is optical pump-probe shadowgraphy: one ultrashort laser pulse is split to a pump pulse and a probe pulse, while the delay time between them can be adjusted by changing their beam path lengths. The pump pulse ablates the target and generates the early plasma, and the probe pulse propagates through the plasma region and detects the non-uniformity of electron number density. In addition, animations are generated using the calculated results from the simulation model of Ref. 12 to illustrate the plasma formation and evolution with a very high resolution (0.04 ~ 1 ps).
Both the experimental method and the simulation method can be applied to a broad range of time frames and laser parameters. These methods can be used to examine the early plasma generated not only from metals, but also from semiconductors and insulators.

An experimental method to examine the early plasma evolution induced by ultrashort laser pulses is described. Using this method, high quality images of early plasma are obtained with high temporal and spatial resolutions. A novel integrated atomistic model is used to simulate and explain the mechanisms of early plasma.

Early plasma is generated owing to high intensity laser irradiation of target and the subsequent target material ionization. Its dynamics plays a ...

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 ...

High-speed Particle Image Velocimetry Near Surfaces

Multi-dimensional and transient flows play a key role in many areas of science, engineering, and health sciences but are often not well understood. The complex nature of these flows may be studied using particle image velocimetry (PIV), a laser-based imaging technique for optically accessible flows. Though many forms of PIV exist that extend the technique beyond the original planar two-component velocity measurement capabilities, the basic PIV system consists of a light source (laser), a camera, tracer particles, and analysis algorithms. The imaging and recording parameters, the light source, and the algorithms are adjusted to optimize the recording for the flow of interest and obtain valid velocity data. 
Common PIV investigations measure two-component velocities in a plane at a few frames per second. However, recent developments in instrumentation have facilitated high-frame rate (&gt; 1 kHz) measurements capable of resolving transient flows with high temporal resolution. Therefore, high-frame rate measurements have enabled investigations on the evolution of the structure and dynamics of highly transient flows. These investigations play a critical role in understanding the fundamental physics of complex flows.
A detailed description for performing high-resolution, high-speed planar PIV to study a transient flow near the surface of a flat plate is presented here. Details for adjusting the parameter constraints such as image and recording properties, the laser sheet properties, and processing algorithms to adapt PIV for any flow of interest are included.

A procedure for studying transient flows near boundaries using high-resolution, high-speed particle image velocimetry (PIV) is described here. PIV is a non-intrusive measurement technique applicable to any optically accessible flow by optimizing several parameter constraints such as the image and recording properties, the laser sheet properties, and analysis algorithms.

Multi-dimensional and transient flows play a key role in many areas of science, engineering, and health sciences but are often not well understood. The ...

Development of an Experimental Setup for the Measurement of the Coefficient of Restitution under Vacuum Conditions

The Discrete Element Method is used for the simulation of particulate systems to describe and analyze them, to predict and afterwards optimize their behavior for single stages of a process or even an entire process. For the simulation with occurring particle-particle and particle-wall contacts, the value of the coefficient of restitution is required. It can be determined experimentally. The coefficient of restitution depends on several parameters like the impact velocity. Especially for fine particles the impact velocity depends on the air pressure and under atmospheric pressure high impact velocities cannot be reached. For this, a new experimental setup for free-fall tests under vacuum conditions is developed. The coefficient of restitution is determined with the impact and rebound velocity which are detected by a high-speed camera. To not hinder the view, the vacuum chamber is made of glass. Also a new release mechanism to drop one single particle under vacuum conditions is constructed. Due to that, all properties of the particle can be characterized beforehand.

The coefficient of restitution is a parameter that describes the loss of kinetic energy during collision. Here, a free-fall setup under vacuum conditions is developed to be able to determine the coefficient of restitution parameter for particles in micrometer range with high impact velocities.

The Discrete Element Method is used for the simulation of particulate systems to describe and analyze them, to predict and afterwards optimize their ...

Use of a Multi-compartment Dynamic Single Enzyme Phantom for Studies of Hyperpolarized Magnetic Resonance Agents

Imaging of hyperpolarized substrates by magnetic resonance shows great clinical promise for assessment of critical biochemical processes in real time. Due to fundamental constraints imposed by the hyperpolarized state, exotic imaging and reconstruction techniques are commonly used. A practical system for characterization of dynamic, multi-spectral imaging methods is critically needed. Such a system must reproducibly recapitulate the relevant chemical dynamics of normal and pathological tissues. The most widely utilized substrate to date is hyperpolarized [1-13C]-pyruvate for assessment of cancer metabolism. We describe an enzyme-based phantom system that mediates the conversion of pyruvate to lactate. The reaction is initiated by injection of the hyperpolarized agent into multiple chambers within the phantom, each of which contains varying concentrations of reagents that control the reaction rate. Multiple compartments are necessary to ensure that imaging sequences faithfully capture the spatial and metabolic heterogeneity of tissue. This system will aid the development and validation of advanced imaging strategies by providing chemical dynamics that are not available from conventional phantoms, as well as control and reproducibility that is not possible in vivo.

A multi-compartment dynamic phantom is used to simulate some biology of interest for metabolic studies using hyperpolarized magnet resonance agents.

Imaging of hyperpolarized substrates by magnetic resonance shows great clinical promise for assessment of critical biochemical processes in real time. Due ...

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 ...

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 ...

Fabrication of Flexible Image Sensor Based on Lateral NIPIN Phototransistors

Flexible photodetectors have been intensely studied for the use of curved image sensors, which are a crucial component in bio-inspired imaging systems, but several challenging points remain, such as a low absorption efficiency due to a thin active layer and low flexibility. We present an advanced method to fabricate a flexible phototransistor array with an improved electrical performance. The outstanding electrical performance is driven by a low dark current owing to deep impurity doping. Stretchable and flexible metal interconnectors simultaneously offer electrical and mechanical stabilities in a highly deformed state. The protocol explicitly describes the fabrication process of the phototransistor using a thin silicon membrane. By measuring I-V characteristics of the completed device in deformed states, we demonstrate that this approach improves the mechanical and electrical stabilities of the phototransistor array. We expect that this approach to a flexible phototransistor can be widely used for the applications of not only next-generation imaging systems/optoelectronics but also wearable devices such as tactile/pressure/temperature sensors and health monitors.

We present a detailed method to fabricate a deformable lateral NIPIN phototransistor array for curved image sensors. The phototransistor array with an open mesh form, which is composed of thin silicon islands and stretchable metal interconnectors, provides flexibility and stretchability. The parameter analyzer characterizes the electrical property of the fabricated phototransistor.

Flexible photodetectors have been intensely studied for the use of curved image sensors, which are a crucial component in bio-inspired imaging systems, ...

Simultaneous Measurement of Turbulence and Particle Kinematics Using Flow Imaging Techniques

Numerous problems in scientific and engineering fields involve understanding the kinematics of particles in turbulent flows, such as contaminants, marine micro-organisms, and/or sediments in the ocean, or fluidized bed reactors and combustion processes in engineered systems. In order to study the effect of turbulence on the kinematics of particles in such flows, simultaneous measurements of both the flow and particle kinematics are required. Non-intrusive, optical flow measurement techniques for measuring turbulence, or for tracking particles, exist but measuring both simultaneously can be challenging due to interference between the techniques. The method presented herein provides a low cost and relatively simple method to make simultaneous measurements of the flow and particle kinematics. A cross section of the flow is measured using a particle image velocimetry (PIV) technique, which provides two components of velocity in the measurement plane. This technique utilizes a pulsed-laser for illumination of the seeded flow field that is imaged by a digital camera. The particle kinematics are simultaneously imaged using a light emitting diode (LED) line light that illuminates a planar cross section of the flow that overlaps with the PIV field-of-view (FOV). The line light is of low enough power that it does not affect the PIV measurements, but powerful enough to illuminate the larger particles of interest imaged using the high-speed camera. High-speed images that contain the laser pulses from the PIV technique are easily filtered by examining the summed intensity level of each high-speed image. By making the frame rate of the high-speed camera incommensurate with that of the PIV camera frame rate, the number of contaminated frames in the high-speed time series can be minimized. The technique is suitable for mean flows that are predominantly two-dimensional, contain particles that are at least 5 times the mean diameter of the PIV seeding tracers, and are low in concentration.

The technique described herein offers a low cost and relatively simple method to simultaneously measure particle kinematics and turbulence in flows with low particle concentrations. The turbulence is measured using particle image velocimetry (PIV), and particle kinematics are calculated from images obtained with a high-speed camera in an overlapping field-of-view.

Numerous problems in scientific and engineering fields involve understanding the kinematics of particles in turbulent flows, such as contaminants, marine ...

3D Printing - Evaluating Particle Emissions of a 3D Printing Pen

Three-dimensional (3D) printing as a type of additive manufacturing shows continuing increase in application and consumer popularity. The fused filament fabrication (FFF) is an inexpensive method used most frequently by consumers. Studies with 3D printers have shown that during the printing process particulate and volatile substances are released. Handheld 3D printing pens also use the FFF method but the consumer&#8217;s proximity to the 3D pens gives reason to higher exposure compared to a 3D printer. At the same time, 3D printing pens are often marketed for children who could be more sensitive to the printing emission. The aim of this study was to implement a low cost method to analyze the emissions of 3D printing pens. Polylactide (PLA) and acrylonitrile butadiene styrene (ABS) filaments of different colors were tested. In addition, filaments containing metal and carbon nanotubes (CNTs) were analyzed. An 18.5 L chamber and sampling close to the emission source was used to characterize emissions and concentrations near the breathing zone of the user.
Particle emissions and particle size distributions were measured and the potential release of metal particles and CNTs investigated. Particle number concentrations were found in a range of 105 - 106 particles/cm3, which is comparable to previous reports from 3D printers. Transmission electron microscopy (TEM) analysis showed nanoparticles of the different thermoplastic materials as well as of metal particles and CNTs. High contents of metal were observed by inductively coupled plasma mass spectrometry (ICP-MS).
These results call for a cautious use of 3D pens due to potential risk to the consumers.

This protocol presents a method to analyze the emission of 3D printing pens. Particle concentration and particle size distribution of the released particle is measured. Released particles are further analyzed with transmission electron microscopy (TEM). Metal content in filaments is quantified by inductively coupled plasma mass spectrometry (ICP-MS).

Three-dimensional (3D) printing as a type of additive manufacturing shows continuing increase in application and consumer popularity. The fused filament ...

Particle Image Velocimetry Investigation of Hemodynamics via Aortic Phantom

Summary

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Chapters in this video

Investigation of Early Plasma Evolution Induced by Ultrashort Laser Pulses

Echo Particle Image Velocimetry

High-speed Particle Image Velocimetry Near Surfaces

Development of an Experimental Setup for the Measurement of the Coefficient of Restitution under Vacuum Conditions

Use of a Multi-compartment Dynamic Single Enzyme Phantom for Studies of Hyperpolarized Magnetic Resonance Agents

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

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

Fabrication of Flexible Image Sensor Based on Lateral NIPIN Phototransistors

Simultaneous Measurement of Turbulence and Particle Kinematics Using Flow Imaging Techniques

3D Printing - Evaluating Particle Emissions of a 3D Printing Pen