The authors acknowledge the great assistance from Dmitrii Klishch, Michel Delannoy, Tyler Musclow, Fraser Kirby, Joshua Ilse and Alex Naftel. Financial support by the National Research Council Canada (NRC) through the Security Materials Technology (SMT) Program is also appreciated.

1. Specimen preparation
<ol>
	<li>Prepare dog bone shaped tensile specimens according to ISO standard6 in advance. 
	NOTE: Similar specimens are also used4.</li>
	<li>Install strain gauges on the tab section (mandatory for load measurement) and on the gauge section (optional for strain measurement) of the tensile specimen.
	<ol>
		<li>Select the proper model of strain gauge based on the size, maximum extension, testing temperature, electrical resistance, etc.4.</li>
		<li>Clean the surface of the specimen with isopropanol to remove any contamination and install the strain gauge at the proper location. Install the tab section strain gauge at equal to or greater than the width of the tab section from the gripping section and the gauge section to ensure a uniform stress flow of the nominal value (i.e. no stress concentration), otherwise the numerical analysis is required to predict the stress value at the location of the strain gauge.</li>
		<li>Connect the strain gauge wires to the Wheatstone bridge box. Use a wire connection tab if required to mount the connections to the external wires.</li>
		<li>Verify the strain gauge reading with a simple loading and boundary conditions. Apply a known load to the specimen (e.g. hang a known mass from the specimen) and check the strain readouts.</li>
	</ol>
	</li>
	<li>Prepare the specimen for DIC as follows:
	<ol>
		<li>Prepare the surface of the specimen with high contrast features. For example, paint the specimen white and speckle it with fine black dots. Through trial and error match the speckle pattern to the camera image sensor size such that each speckle is composed of approximately 3 pixels or more. 
		NOTE: Avoid performing DIC on the side that the strain gauges are installed to prevent the undesirable surface features.</li>
		<li>Leave the paint to dry before the test. Test the specimen, preferably, in the same day it was painted. 
		NOTE: Depending on the type and consistency of the paint, this may take up to a few hours. Do not leave the speckled specimens for a prolonged period (e.g., several days) before testing as this will result in the paint becoming brittle and flaking off during the test.</li>
	</ol>
	</li>
</ol>
2. Start-up procedure
<ol>
	<li>Turn on the power to the Control Console using the button on the UPS (Uninterruptable Power Supply). Check that the isolation valve from the pump to the High Rate frame is open, and then turn on the computer.</li>
	<li>From the desktop start the Controller Application, selecting the High Rate Calculate Displacement.cfg configuration, then click Reset to clear interlock 1 (under Station Controls). 
	NOTE: The other two indicators (Program 1 and Gate 1) will be red because the high pressure hydraulic is not applied yet.</li>
	<li>Check Exclusive Control so the frame can only be controlled from the software (and not from the handset).</li>
	<li>Now, start up the hydraulic pump (HPU) and open the service manifold (HSM 1) one by one (3 total). For each case wait until the low indicator stops flashing before pressing the high indicator. If the pump has been off for a long time, wait for 30 s before selecting the high to give the feeder pump time to supply oil to the high-pressure pump.</li>
	<li>Again, from the desktop, start the Test Design software. From the toolbar make sure the HPU and HSM 1 are ON (green). From the top menu File&#62; New&#62; Test from Template select Custom Templates, and then select Tension test.</li>
</ol>
3. Setup of the strain gauges
<ol>
	<li>Go to the load frame crosshead control (next to the handset) and turn the switch to the low rate (turtle icon).</li>
	<li>Inside the test chamber connect the wires of the specimen strain gauge(s) to the strain gauge box using the color code (red, white and black). If there is only one strain gauge, use the SG 1 series. 
	NOTE: The red lead is the separate terminal (excitation + or -), and the white and black are the sense and signal leads.</li>
	<li>In the Controller Application and under Auxiliary Inputs go to Strain 1 (or 2) to select the maximum range of the strains (i.e. 2%, 5%, or 10%). For example, if 5% is chosen, the software maps this from 50,000 &#181;&#949; to 10 Volts output and cannot measure strains beyond 5%.</li>
	<li>Run the Conditioner Utility software to configure the strain gauges and balance the Wheatstone bridge according to the following steps:
	<ol>
		<li>Calculate the output voltage using the formula for the Wheatstone bridge: 
		<img alt="Equation 1" src="/files/ftp_upload/59168/59168eq1.jpg" /> 
		Here, VO is the output voltage, VE is the excitation voltage, GF is the gauge factor, &#949;1 is 50,000 (5%), whereas &#949;2, &#949;3, and &#949;4 are zero (completion bridge).</li>
	</ol>
	</li>
	<li>Calculate the gain using the following equation: 
	<img alt="Equation 2" src="/files/ftp_upload/59168/59168eq2.jpg" /></li>
	<li>In the conditioner utility software, there are options of 1, 8, 64, and 512 for the Preamp Gain, while the Post amp Gain value is limited to 9. 9976. Calculate the Post amp Gain based on different options of 1, 8, 64, and 512 for the Preamp Gain using the following equation: 
	<img alt="Equation 3" src="/files/ftp_upload/59168/59168eq3.jpg" /></li>
	<li>Select the lowest Preamp Gain that gives out a Post amp Gain that is lower than 9.9976 and input these values into the conditioner utility software.</li>
	<li>Run the High Rate Data Acquisition Configuration software. Under the strain channels (Channel 3 and 4), enter the full-scale range of the strain gauge (e.g. 50,000). 
	NOTE: Channel 1 and 2 are dedicated to Displacement and Force, respectively.</li>
	<li>Offset the strain gauges to zero according to the following steps:
	<ol>
		<li>First in the software, remove any offset values for the strain channels (bring offset values to zero). 
		NOTE: This process has to be done when the test specimen is resting (e.g. on the table) and is not under load.</li>
		<li>Then, adjust the Bridge balance parameter to bring the readout strain almost to zero. This is the coarse adjustment step.</li>
		<li>Then adjust the Feedback Zero parameter, to bring the strain value in the strain manager software completely to zero. This step is the fine adjustment.</li>
		<li>To assure the input parameters were correct, click on Shunt Enable option. 
		NOTE: The strain value in the Controller Application software should read 1640 &#181;&#949; (with either + or - sign). Remember to turn off the shunt to remove the shunt resistor out of the Wheatstone bridge. The Strain value will go back to zero.</li>
	</ol>
	</li>
	<li>If there are two strain gauges on the specimen, in the conditioner utility software, click on Strain 2 and repeat all the strain gauge setup steps.</li>
</ol>
4. Mounting the test specimen
<ol>
	<li>In the Controller Application activate the Manual Control and enter the position of the head to full extension at -125 mm.</li>
	<li>Then click to turn off the Enable Manual Command check box and uncheck the Exclusive Control box.</li>
	<li>Use the mounting fixture to align the coupon inside the grips. An elastic cord may be used to hold the slack adapter in a retracted position giving room to install the coupon. Tighten the coupon in the bottom grip first.</li>
	<li>On the handset push the key icon on the top right corner to activate the handset. Ensure that the Exclusive Control box on the software is unchecked. Make sure the top grip is loose to prevent the undesirable application of load to the specimen.
	<ol>
		<li>Remove the elastic cord and push the wheel icon below the thumbwheel on the controller to activate it. Slowly roll the wheel to bring the head down until the bottom arm of the slack adaptor is almost fully retracted and the crosshead is nearly at -125 mm. 
		NOTE: the position of the head can be read on the handset.</li>
	</ol>
	</li>
	<li>On the handset push the key icon once again to de-activate the handset. Return to the computer and on the Controller Application check the Exclusive Control box and use the Manual Control to bring the head to exactly -125 mm. The top grip is loose so there is no load applied to the coupon.</li>
	<li>Now, tighten the top grips with a wrench and a key by rotating the slack adapter. Do not twist the coupon while tightening the grip.</li>
	<li>Check the spiral washers&#160;between the slack adaptor and the intermediate crosshead and make sure they are tight and there is no axial clearance along the load train.</li>
	<li>Again, using the crosshead control box return the frame to the high rate (rabbit icon), and make sure the enclosure doors are tightly closed.</li>
	<li>Back on the computer, to clear the interlocks click Reset (on the right-hand side of the Controller Application). 
	NOTE: The interlocks include &#34;Interlock 1&#34; (an interlock chain running through all frames and the hydraulic pump), &#34;Program 1&#34; (computer software controlled, for example, high/low velocity), &#34;Gate 1&#34; (enclosure and Rate switch), and &#34;C-Stop 1&#34; (controlled stop).</li>
	<li>When there is no intention to move the head manually, uncheck the Enable Manual Command box in Manual Command menu to avoid accidentally entering a number into the software and moving the head.</li>
</ol>
5. DIC setup preparation
<ol>
	<li>Connect the high-speed camera to the computer using a Gigabit LAN Cable.</li>
	<li>Connect the Digital I/O box to the high-speed camera and MTC frame controller.</li>
	<li>Connect the computer to the MTS frame controller through the DAQ box. Force and displacement signals are transferred from the MTS controller to the computer through this box.</li>
	<li>Connect the high-speed camera to the DAQ box for the trigger signal and the synchronization signal.</li>
	<li>Mount the camera onto the base of the load frame to avoid relative movement between the camera and specimen during the test, as the frame shakes due to the impact.</li>
	<li>Position the camera carefully to ensure its image sensor is parallel to the specimen. Use a telecentric lens (e.g., Opto-engineering 23-64with a field of view of 64 &#215; 48 mm and a working distance of 182 mm) to reduce the possibility of perspective distortion from out-of-plane motion.</li>
	<li>During camera setup, consider the final deformation of the specimen and make sure the camera&#39;s field of view covers the specimen throughout the entire test.</li>
	<li>To set up the software connections in the computer, select Network and Sharing Centre from Windows Control Panel. Next click Local Area Connection.</li>
	<li>Select Internet Protocol Version 4 (TCP/IPv6) in the Local Area Connection properties and set the IP address.</li>
	<li>Open the High-Speed Imaging viewer software and click detect and then save the setup.</li>
	<li>Click on the Camera Option button and select the I/O tab to set the external signals.</li>
	<li>To set the frame rate and frame resolution, click on the variable button. Set the camera frequency and the data acquisition (DAQ) box acquisition rate to the same number as the high-speed data acquisition system in the load frame to make the data analysis step easier</li>
	<li>Open the high speed DAQ in the High-Speed Imaging viewer and select the required channels and the samples per frame.</li>
	<li>After camera setup, capture several static images and calculate the strain field using the image correlation routine. 
	NOTE: The maximum strain and displacements measured from this noise floor are noted and provide a qualitative measure of the image quality.</li>
</ol>
6. Running the test
<ol>
	<li>In the test design software, from the top menu follow File&#62; New&#62; Test&#62; Test from Template. Then under Custom Templates open Tension Test.</li>
	<li>Select New Test Run and enter a valid file name (usually the name of the coupon without spaces). Modify the fields as needed; then click OK.
	<ol>
		<li>If strain gauges are included, remember to input Channel Count as 4.</li>
		<li>The starting point is usually -125 mm. This is important because if this is not correct the head will move to this value before the test starts possibly damaging the coupon.</li>
		<li>The default values for High Speed Acquisition Rate and Buffer Size are 50,000 and 20,000, respectively. Depending on the duration of the test and required time resolution (time interval between data points), modify these numbers if necessary. 
		NOTE: The default parameters result in saving data for the duration of 0.4 s.</li>
		<li>For Ramp Rate select the nominal desired head velocity (for example, 8,000 mm/s), then click OK.</li>
	</ol>
	</li>
	<li>A series of prompts will appear, reminding to check key hardware times, after which the test will be initiated by clicking on the Run icon.</li>
	<li>On the Control Console switch the Mode Select to High Rate. This activates the large valve for high rate load application. The default Valve 1 is selected (the light is on).</li>
	<li>On the computer screen, a series of steps are shown. Follow the steps.</li>
	<li>On the Control Console, depress and hold Arm/Charge Accumulator switch. The system is now ready.</li>
	<li>Press Fire to complete the test.</li>
	<li>Switch the Mode Select back to Standard and press the return to start (Green button) on the console to return the head back from the endcap (125 mm).</li>
	<li>Go to the crosshead control and switch back to the low rate (turtle icon).</li>
	<li>Open the enclosure and take out the specimen. Find the data files stored on the computer at 
	C:\Datafiles\High Rate Data (for high rate data) and at C:\Datafiles\Low Rate Data (for low rate data).</li>
</ol>
7. Shutdown procedure
<ol>
	<li>On the Controller Application software turn the HSM 1 to Low (yellow) and then to Off (red). This will close the manifold and shut down the pump.</li>
	<li>In the test design software, save the test run, if required, by following from the top menu File&#62; Save as and then choose the test. Close the test design software.</li>
	<li>Close the Controller Application. Save the parameters before closing the software, if required. Shut down the computer.</li>
	<li>Close the hydraulic valve (large lever) and turn off power to the Control Console again using the power button on the UPS.</li>
</ol>
8. Data analysis
<ol>
	<li>Export the raw data from the load frame computer into the post-processing software of choice.</li>
	<li>Calculate the actual load from the strain gauge readouts mounted on the gauge section and compare it with the raw load data from the high speed DAQ. If the ringing in the high speed DAQ data is severe, use the calculated load from the strain gauge in the next steps4.</li>
	<li>Calculate the stress in the gauge section, &#963;gauge, based on the calculated load, P, and the specimen cross-section at the gauge section, Ax - section: 
	<img alt="Equation 4" src="/files/ftp_upload/59168/59168eq4.jpg" /></li>
	<li>Obtain the strain on the gauge section from one of the following methods:
	<ol>
		<li>Average strain in the gauge section:
		<ol>
			<li>Calculate the tab section elongation by knowing the load, tab section length, specimen&#39;s elastic modulus, and cross-sectional area. 
			NOTE: If the elastic modulus is a function of strain rate, an iterative procedure (details are explained in reference7) is required.</li>
			<li>Subtract the tab section elongation from the entire specimen elongation (i.e. load frame head displacement) to obtain the gauge section elongation.</li>
			<li>Calculate the average strain in the gauge section based on the gauge section elongation and the initial length.</li>
		</ol>
		</li>
		<li>Local strain from DIC:
		<ol>
			<li>Determine the location on the gauge section where the specimen failed (i.e. split in two) and restrict the strain field to a local area at the vicinity of the failure section.</li>
			<li>Measure and record the strain in the local area using the DIC post-processing software of the choice.</li>
		</ol>
		</li>
	</ol>
	</li>
	<li>Draw the stress-strain curve obtained from the previous steps.</li>
</ol>

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The authors have nothing to disclose.

The raw data obtained from the experiment is influenced by the specimen geometry and strain gauges location on the specimen. The load data in low strain rate dynamic tests acquired by a piezo-electric load washer incorporated into the load frame at higher strain rates (Bruce et al.3 suggested &#62; 10/s, while for Wang et al.9 reported this limit to be 100/s) typically suffer from large amplitude oscillations due to dynamic waves associated with the loadin...

Most materials demonstrate some degree of strain rate dependency in their mechanical behavior1 and, therefore, mechanical testing conducted only at quasistatic strain rates is not suitable to determine the material properties for dynamic applications. The strain rate dependency of materials is typically investigated using five types of mechanical testing systems: conventional screw drive load frames, servo-hydraulic systems, high-rate servo-hydraulic systems, impact testers, and Hopkinson bar systems1. Split Hopkinson bars have been a common facility for the dynamic characterization of materials for the past 50 years2. There have also been efforts to modify Hopkinson bars to test at intermediate and lower strain rates. However, these facilities are typically more suitable for the high strain rate characterizations of the material (i.e., usually greater than 200/s). There is a gap in the literature on the strain rate characterization of material properties at intermediate strain rates in the range of 10&#8722;200/s (i.e., between quasistatic and high strain rate results obtained from split Hopkinson bars3), which is due to the limited access to facilities and a lack of reliable procedures of intermediate strain rate material testing.
A high-speed servo-hydraulic load frame applies load to the specimen at a constant and predefined velocity. These load frames benefit from a slack adaptor, which, in tensile tests, allows the crosshead to reach the desired velocity before the loading starts. The slack adaptor allows the head to travel a certain distance (e.g., 0.1 m) to reach the target velocity and then starts applying the load to the specimen. High-speed servo-hydraulic load frames typically perform tests under displacement control mode and maintain a constant actuator velocity to produce constant engineering strain rates3.
Techniques for measuring specimen elongation are generally classified as either contact or noncontact techniques4. Contact techniques include the use of instruments such as clip-on extensometers, while laser extensometers are employed for noncontact measurements. Since contact extensometers are prone to inertia influences, they are not suitable for dynamic tests; noncontact extensometers do not suffer from this problem.
Digital image correlation (DIC) is an optical, non-contact, full-field strain measurement technique, which is an alternative approach to strain gauging to measure strain/load and overcome some of the challenges (e.g., the ringing phenomenon) associated with dynamic material characterization5. Resistance strain gauges can suffer from limitations such as a limited area of measurement, a limited range of elongation, and limited mounting methods, whereas DIC is always capable of providing a full-field strain measurement from the specimen surface during the experiment.
The presented procedure describes the use of a high-speed servo-hydraulic load frame along with DIC and can be used as a complementary document to the recently developed standard guidelines6 to clarify the details of the experimental procedure. The section on the servo-hydraulic load frame can be followed for a variety of test setups (e.g., tensile, compressive, and shear) and even with common quasistatic load frames as well, and, therefore, covers a vast range of facilities. Furthermore, the DIC section may be applied separately to any type of mechanical or thermal tests, with minor modifications.

<table><tbody><tr><td>Camera Lens</td><td>Opto Engineering</td><td></td><td>Telecentric lens 23-64</td></tr><tr><td>High Speed Camera&amp;nbsp;</td><td>SAX Photron Fastcam&amp;nbsp;</td><td></td><td></td></tr><tr><td>High Speed DAQ&amp;nbsp;</td><td>National Instruments</td><td>USB-6259</td><td></td></tr><tr><td>High Speed Servo-Hydraulic Load Frame</td><td>MTS Systems Corporation</td><td>Custom Built</td><td></td></tr><tr><td>Jab Bullet Light with diffuser&amp;nbsp;</td><td>AADyn JAB BULLET&amp;nbsp;</td><td></td><td>&amp;nbsp;15&amp;deg; diffusers&amp;nbsp;</td></tr><tr><td>Strain gauge</td><td>Micro-Measurements</td><td>Model EA-13-062AQ-350</td><td></td></tr></tbody></table>

intermediate strain rate material characterization with digital image correlation

The mechanical response of a material under dynamic load is typically different than its behavior under static conditions; therefore, the common quasistatic equipment and procedures used for material characterization are not applicable for materials under dynamic loads. The dynamic response of a material depends on its deformation rate and is broadly categorized into high (i.e., greater than 200/s), intermediate (i.e., 10&#8722;200/s) and low strain rate regimes (i.e., below 10/s). Each of these regimes calls for specific facilities and testing protocols to ensure the reliability of the acquired data. Due to the limited access to high-speed servo-hydraulic facilities and validated testing protocols, there is a noticeable gap in the results at the intermediate strain rate. The current manuscript presents a validated protocol for the characterization of different materials at these intermediate strain rates. Strain gauge instrumentation and digital image correlation protocols are also included as complimentary modules to extract the utmost level of detailed data from every single test. Examples of raw data, obtained from a variety of materials and test setups (e.g., tensile and shear) is presented and the analysis procedure used to process the output data is described. Finally, the challenges of dynamic characterization using the current protocol, along with the limitations of the facility and methods of overcoming potential problems are discussed.

The duration of a dynamic test is typically comparable to the time required for the stress waves to travel a round trip over the length of the load train (i.e. grips, specimen, and loading) system1. A dynamic test is valid if the number and amplitude of stress waves during a dynamic test is controlled so that a dynamic equilibrium is achieved, and the specimen experiences a homogeneous deformation at an almost constant strain rate. The Society of Automotive Enginee...

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Intermediate Strain Rate Material Characterization with Digital Image Correlation

Here we present a methodology for the dynamic characterization of tensile specimens at intermediate strain rates using a high-speed servo-hydraulic load frame. Procedures for strain gauge instrumentation and analysis, as well as for digital image correlation strain measurements on the specimens, are also defined.

The mechanical response of a material under dynamic load is typically different than its behavior under static conditions; therefore, the common ...

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7.1K Views.  National Research Council Canada. Here we present a methodology for the dynamic characterization of tensile specimens at intermediate strain rates using a high-speed servo-hydraulic load frame. Procedures for strain gauge instrumentation and analysis, as well as for digital image correlation strain measurements on the specimens, are also defined.

Video: Intermediate Strain Rate Material Characterization with Digital Image Correlation

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-resolution, High-speed, Three-dimensional Video Imaging with Digital Fringe Projection Techniques

Digital fringe projection (DFP) techniques provide dense 3D measurements of dynamically changing surfaces.&#160;Like the human eyes and brain, DFP uses triangulation between matching points in two views of the same scene at different angles to compute depth.&#160;However, unlike a stereo-based method, DFP uses a digital video projector to replace one of the cameras1. The projector rapidly projects a known sinusoidal pattern onto the subject, and the surface of the subject distorts these patterns in the camera&#8217;s field of view. Three distorted patterns (fringe images) from the camera can be used to compute the depth using triangulation.
Unlike other 3D measurement methods, DFP techniques lead to systems that tend to be faster, lower in equipment cost, more flexible, and easier to develop.&#160;DFP systems can also achieve the same measurement resolution as the camera.&#160;For this reason, DFP and other digital structured light techniques have recently been the focus of intense research (as summarized in1-5). Taking advantage of DFP, the graphics processing unit, and optimized algorithms, we have developed a system capable of 30&#160;Hz 3D video data acquisition, reconstruction, and display for over 300,000 measurement points per frame6,7.&#160;Binary defocusing DFP methods can achieve even greater speeds8.
Diverse applications can benefit from DFP techniques. Our collaborators have used our systems for facial function analysis9, facial animation10, cardiac mechanics studies11, and fluid surface measurements, but many other potential applications exist.&#160;This video will teach the fundamentals of DFP techniques and illustrate the design and operation of a binary defocusing DFP system.

This video describes the fundamentals of digital fringe projection techniques, which provide dense 3D measurements of dynamically changing surfaces.&#160;It also demonstrates the design and operation of a high-speed binary defocusing system based on these techniques.

Digital fringe projection (DFP) techniques provide dense 3D measurements of dynamically changing surfaces.&#160;Like the human eyes and brain, DFP uses ...

Characterization of Full Set Material Constants and Their Temperature Dependence for Piezoelectric Materials Using Resonant Ultrasound Spectroscopy

During the operation of high power electromechanical devices, a temperature rise is unavoidable due to mechanical and electrical losses, causing the degradation of device performance. In order to evaluate such degradations using computer simulations, full matrix material properties at elevated temperatures are needed as inputs. It is extremely difficult to measure such data for ferroelectric materials due to their strong anisotropic nature and property variation among samples of different geometries. Because the degree of depolarization is boundary condition dependent, data obtained by the IEEE (Institute of Electrical and Electronics Engineers) impedance resonance technique, which requires several samples with drastically different geometries, usually lack self-consistency. The resonant ultrasound spectroscopy (RUS) technique allows the full set material constants to be measured using only one sample, which can eliminate errors caused by sample to sample variation. A detailed RUS procedure is demonstrated here using a lead zirconate titanate (PZT-4) piezoceramic sample. In the example, the complete set of material constants was measured from room temperature to 120 &#176;C. Measured free dielectric constants <img alt="Equation 1" src="/files/ftp_upload/53461/image001.jpg" /> and&#160;<img alt="Equation 2" src="/files/ftp_upload/53461/image002.jpg" /> were compared with calculated ones based on the measured full set data, and piezoelectric constants d15 and d33 were also calculated using different formulas. Excellent agreement was found in the entire range of temperatures, which confirmed the self-consistency of the data set obtained by the RUS.

This protocol describes the procedure of measuring the temperature dependence of the full set material constants of piezoelectric materials using resonant ultrasound spectroscopy (RUS).

During the operation of high power electromechanical devices, a temperature rise is unavoidable due to mechanical and electrical losses, causing the ...

Shrinkage of Dental Composite in Simulated Cavity Measured with Digital Image Correlation

Polymerization shrinkage of dental resin composites can lead to restoration debonding or cracked tooth tissues in composite-restored teeth. In order to understand where and how shrinkage strain and stress develop in such restored teeth, Digital Image Correlation (DIC) was used to provide a comprehensive view of the displacement and strain distributions within model restorations that had undergone polymerization shrinkage.
Specimens with model cavities were made of cylindrical glass rods with both diameter and length being 10 mm. The dimensions of the mesial-occlusal-distal (MOD) cavity prepared in each specimen measured 3 mm and 2 mm in width and depth, respectively. After filling the cavity with resin composite, the surface under observation was sprayed with first a thin layer of white paint and then fine black charcoal powder to create high-contrast speckles. Pictures of that surface were then taken before curing and 5 min after. Finally, the two pictures were correlated using DIC software to calculate the displacement and strain distributions.
The resin composite shrunk vertically towards the bottom of the cavity, with the top center portion of the restoration having the largest downward displacement. At the same time, it shrunk horizontally towards its vertical midline. Shrinkage of the composite stretched the material in the vicinity of the &#8220;tooth-restoration&#8221; interface, resulting in cuspal deflections and high tensile strains around the restoration. Material close to the cavity walls or floor had direct strains mostly in the directions perpendicular to the interfaces. Summation of the two direct strain components showed a relatively uniform distribution around the restoration and its magnitude equaled approximately to the volumetric shrinkage strain of the material.

In order to understand the spatial development of polymerization shrinkage stress in dental resin-composite restorations, Digital Image Correlation was used to provide full-field displacement/strain measurement of restored model glass cavities by correlating images of the restoration taken before and after polymerization.

Polymerization shrinkage of dental resin composites can lead to restoration debonding or cracked tooth tissues in composite-restored teeth. In order to ...

Medicine

Full-field Strain Measurements for Microstructurally Small Fatigue Crack Propagation Using Digital Image Correlation Method

A novel measurement approach is used to reveal the cumulative deformation field at a sub-grain level and to study the influence of microstructure on the growth of microstructurally small fatigue cracks. The proposed strain field analysis methodology is based on the use of a unique pattering technique with a characteristic speckle size of approximately 10 &#181;m. The developed methodology is applied to study the small fatigue crack behavior in body centered cubic (bcc) Fe-Cr ferritic stainless steel with a relatively large grain size allowing a high spatial measurement accuracy at the sub-grain level. This methodology allows the measurement of small fatigue crack growth retardation events and associated intermittent shear strain localization zones ahead of the crack tip. In addition, this can be correlated with the grain orientation and size. Thus, the developed methodology can provide a deeper fundamental understanding of the small fatigue crack growth behavior, required for the development of robust theoretical models for the small fatigue crack&#160;propagation in polycrystalline materials.

Microstructurally small fatigue crack growth behavior is investigated using a novel methodological approach combining crack growth rate measurement and strain-field analysis to reveal the cumulative deformation field at sub-grain level.

A novel measurement approach is used to reveal the cumulative deformation field at a sub-grain level and to study the influence of microstructure on the ...

Production of a Strain-Measuring Device with an Improved 3D Printer

A traditional strain measurement sensor needs to be electrified and is susceptible to electromagnetic interference. In order to solve the fluctuations in the analog electrical signal in a traditional strain gauge operation, a new strain measurement method is presented here. It uses a photographic technique to display the strain change by amplifying the change of the pointer displacement of the mechanism. A visual polydimethylsiloxane (PDMS) lens with a focal length of 7.16 mm was added to a smartphone camera to generate a lens group acting as a microscope to capture images. It had an equivalent focal length of 5.74 mm. Acrylonitrile butadiene styrene (ABS) and nylon amplifiers were used to test the influence of different materials on the sensor performance. The production of the amplifiers and PDMS lens is based on improved 3D printing technology. The data obtained were compared with the results from finite element analysis (FEA) to verify their validity. The sensitivity of the ABS amplifier was 36.03 &plusmn; 1.34 &#181;&epsilon;/&#181;m, and the sensitivity of the nylon amplifier was 36.55 &plusmn; 0.53 &#181;&epsilon;/&#181;m.

This work presents a strain measurement sensor consisting of an amplification mechanism and a polydimethylsiloxane microscope manufactured using an improved 3D printer.

A traditional strain measurement sensor needs to be electrified and is susceptible to electromagnetic interference. In order to solve the fluctuations in ...

Crack Monitoring in Resonance Fatigue Testing of Welded Specimens Using Digital Image Correlation

A procedure using digital image correlation (DIC) to detect cracks on welded specimens during fatigue tests on resonance testing machines is presented. It is intended as a practical and reproducible procedure to identify macroscopic cracks at an early stage and monitor crack propagation during fatigue tests. It consists of strain field measurements at the weld using DIC. Images are taken at fixed load cycle intervals. Cracks become visible in the computed strain field as elevated strains. This way, the whole width of a small-scale specimen can be monitored to detect where and when a crack initiates. Subsequently, it is possible to monitor the development of the crack length. Because the resulting images are saved, the results are verifiable and comparable. The procedure is limited to cracks initiating at the surface and is intended for fatigue tests under laboratory conditions. By visualizing the crack, the presented procedure allows direct observation of macrocracks from their formation until rupture of the specimen.

Digital image correlation is used in fatigue tests on a resonance testing machine to detect macroscopic cracks and monitor crack propagation in welded specimens. Cracks on the specimen surface become visible as increased strains.

A procedure using digital image correlation (DIC) to detect cracks on welded specimens during fatigue tests on resonance testing machines is presented. It ...

A Method to Estimate Cadaveric Femur Cortical Strains During Fracture Testing Using Digital Image Correlation

This protocol describes the method using digital image correlation to estimate cortical strain from high speed video images of the cadaveric femoral surface obtained from mechanical testing. This optical method requires a texture of many contrasting fiduciary marks on a solid white background for accurate tracking of surface deformation as loading is applied to the specimen. Immediately prior to testing, the surface of interest in the camera view is painted with a water-based white primer and allowed to dry for several minutes. Then, a black paint is speckled carefully over the white background with special consideration for the even size and shape of the droplets. Illumination is carefully designed and set such that there is optimal contrast of these marks while minimizing reflections through the use of filters. Images were obtained through high speed video capture at up to 12,000 frames/s. The key images prior to and including the fracture event are extracted and deformations are estimated between successive frames in carefully sized interrogation windows over a specified region of interest. These deformations are then used to compute surface strain temporally during the fracture test. The strain data is very useful for identifying fracture initiation within the femur, and for eventual validation of proximal femur fracture strength models derived from Quantitative Computed Tomography-based Finite Element Analysis (QCT/FEA).

In this protocol, the femur surface strains are estimated during fracture testing using the digital image correlation technique. The novelty of the method involves application of a high-contrast stochastic speckle pattern on the femur surface, carefully specified illumination, high speed video capture, and digital image correlation analysis for strain calculations.

This protocol describes the method using digital image correlation to estimate cortical strain from high speed video images of the cadaveric femoral ...

Bioengineering

Measuring Local Tissue Strains in Tendons via Open-Source Digital Image Correlation

There is considerable scientific interest in understanding the strains that tendon cells experience in situ and how these strains influence tissue remodeling. Based on this interest, several analytical techniques have been developed to measure local tissue strains within tendon explants during loading. However, in several cases, the accuracy and sensitivity of these techniques have not been reported, and none of the algorithms are publicly available. This has made it difficult for the more widespread measurement of local tissue strains in tendon explants. Therefore, the objective of this paper was to create a validated analysis tool for measuring local tissue strains in tendon explants that is readily available and easy to use. Specifically, a publicly available augmented-Lagrangian digital image correlation (ALDIC) algorithm was adapted for measuring 2D strains by tracking the displacements of cell nuclei within mouse Achilles tendons under uniaxial tension. Additionally, the accuracy of the calculated strains was validated by analyzing digitally transformed images, as well as by comparing the strains with values determined from an independent technique (i.e., photobleached lines). Finally, a technique was incorporated into the algorithm to reconstruct the reference image using the calculated displacement field, which can be used to assess the accuracy of the algorithm in the absence of known strain values or a secondary measurement technique. The algorithm is capable of measuring strains up to 0.1 with an accuracy of 0.00015. The technique for comparing a reconstructed reference image with the actual reference image successfully identified samples that had erroneous data and indicated that, in samples with good data, approximately 85% of the displacement field was accurate. Finally, the strains measured in mouse Achilles tendons were consistent with the prior literature. Therefore, this algorithm is a highly useful and adaptable tool for accurately measuring local tissue strains in tendons.

Measuring Local Tissue Strains in Tendons via Open-Source Digital Image Correlation

This paper describes an open-source digital image correlation algorithm for measuring local 2D tissue strains within tendon explants. The accuracy of the technique has been validated using multiple techniques, and it is available for public use.

There is considerable scientific interest in understanding the strains that tendon cells experience in situ and how these strains influence tissue ...

Using Digital Image Correlation to Characterize Local Strains on Vascular Tissue Specimens

Characterization of the mechanical behavior of biological and engineered soft tissues is a central component of fundamental biomedical research and product development. Stress-strain relationships are typically obtained from mechanical testing data to enable comparative assessment among samples and in some cases identification of constitutive mechanical properties. However, errors may be introduced through the use of average strain measures, as significant heterogeneity in the strain field may result from geometrical non-uniformity of the sample and stress concentrations induced by mounting/gripping of soft tissues within the test system. When strain field heterogeneity is significant, accurate assessment of the sample mechanical response requires measurement of local strains. This study demonstrates a novel biomechanical testing protocol for calculating local surface strains using a mechanical testing device coupled with a high resolution camera and a digital image correlation technique. A series of sample surface images are acquired and then analyzed to quantify the local surface strain of a vascular tissue specimen subjected to ramped uniaxial loading. This approach can improve accuracy in experimental vascular biomechanics and has potential for broader use among other native soft tissues, engineered soft tissues, and soft hydrogel/polymeric materials. In the video, we demonstrate how to set up the system components and perform a complete experiment on native vascular tissue.

We describe the use of digital image correlation to characterize the local surface strain field on vascular tissue samples subjected to uniaxial tensile testing. These measurements facilitate precise quantification of the sample mechanical response and the generation of constitutive stress-strain relations.

Characterization of the mechanical behavior of biological and engineered soft tissues is a central component of fundamental biomedical research and ...

Intermediate Strain Rate Material Characterization with Digital Image Correlation

Podsumowanie

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Characterization of Full Set Material Constants and Their Temperature Dependence for Piezoelectric Materials Using Resonant Ultrasound Spectroscopy

Shrinkage of Dental Composite in Simulated Cavity Measured with Digital Image Correlation

Full-field Strain Measurements for Microstructurally Small Fatigue Crack Propagation Using Digital Image Correlation Method

Production of a Strain-Measuring Device with an Improved 3D Printer

Crack Monitoring in Resonance Fatigue Testing of Welded Specimens Using Digital Image Correlation

A Method to Estimate Cadaveric Femur Cortical Strains During Fracture Testing Using Digital Image Correlation

Measuring Local Tissue Strains in Tendons via Open-Source Digital Image Correlation

Using Digital Image Correlation to Characterize Local Strains on Vascular Tissue Specimens