Funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) EH 485/4-1.

1. Specimen preparation
CAUTION: The use of welding or machining equipment is potentially dangerous. The work should be executed by qualified personnel and according to the instructions provided by manufacturers.
<ol>
	<li>Prepare specimens with the desired weld geometry (e.g., butt weld, longitudinal stiffener, fillet weld). If the whole specimen width should be measured, specimen size might be limited by the area pictured by the employed camera system. In the tests presented here, specimens containing a multilayer K-butt weld between two plates of different thicknesses were used (Figure 1). The specimens were made of structural steel S355 using metal active gas welding. Further information on the specimen preparation can be found in Friedrich and Ehlers21.</li>
	<li>If necessary, mitigate competing crack locations by grinding. These might be the weld toe on the opposite side of the plate or the other end of a stiffener. Here, the surface should be ground until smooth and free of sharp notches to avoid cracks.</li>
	<li>Clean the specimen surface in the area around the weld using a cleaning cloth and a cleaner to degrease. Carefully remove all loose material from the weld surface and weld toe using a brass wire brush. The surface should be oil and grease-free.</li>
	<li>Apply the speckle pattern for DIC using alternating applications of black and white spray paint. Do not point the spray directly at the surface, but let the spray mist settle on the specimen. No continuous layer is needed. The speckle size should be as fine a possible, in the magnitude of 0.1 mm (see Figure 2). 
	NOTE: Matte paint is preferable in order to reduce reflections.</li>
</ol>
2. Test setup
CAUTION: The use of mechanical or servo-hydraulic testing equipment is potentially dangerous. Operate with caution and follow the instructions provided by the manufacturer.
<ol>
	<li>Position the DIC cameras to capture the area of interest on the specimen placed in the testing machine. The exact setup will depend on the employed equipment. In the tests presented here, the cameras were mounted on a scaffold reaching over the specimen arranged horizontally in the testing machine (Figure 3).</li>
	<li>Meticulously adjust the focus of the camera objectives to ensure that the measured area is in focus. On the employed cameras this is done by screwing the objectives in or out to change the distance between the lenses and the sensor of the camera.</li>
	<li>Adjust the position of the lights to maximize illumination (here, four 16 Watt LED lights were used; this allowed a uniform illumination of the measuring area, but other configurations are also possible). The use of polarization filters properly installed on the lights and objectives is recommended to reduce reflections on the metallic surface.</li>
	<li>Choose an adequate exposure time. It will depend on the testing frequency and should be a small enough fraction (~1/35) of the duration of one load cycle. In the test presented here, the exposure time was 0.8 ms for a testing frequency of 34 Hz.</li>
	<li>Calibrate the DIC system. The procedure will depend on the employed system and should be described in the specific user manual.</li>
	<li>Take some pictures with the selected exposure time. Compute strains using apposite DIC software. Verify that the image quality is good enough to calculate any strains, that the scatter in the results is not excessive (in the unloaded state strains it should be close to zero), and that the results cover the entire region of interest. If the images are too dark, adjust the lighting. It might be necessary to open the aperture on the objectives, although this will reduce the depth of focus. A brighter speckle pattern might help as well.</li>
	<li>Connect the force signal output from the testing machine to trigger the cameras. A commercial DIC system including hardware and software that allows setting off the trigger at specific intervals of load cycles was used. For this purpose, the load cycles are counted by the rising force signal crossing a certain value. When the specified number of load cycles is reached, the cameras are triggered, and counting starts over again. An exemplary triggerlist is supplied as a supplementary file.</li>
	<li>Perform a test run to determine the delay between the trigger signal and the camera exposure. Set the trigger before the peak of the load signal to compensate for the delay. If using the triggerlist (see step 2.7) adjust the parameter value to the required load signal in voltage. In the tests shown, the cameras were triggered at 91% and 96% of the maximum force, respectively. These values are only given as an example and are not always suitable. 
	NOTE: It is not necessary for the images to be taken exactly at the load peak. Cracks should become visible nonetheless.</li>
	<li>Set the trigger to an interval of load cycles so that the total number of images over the expected test duration is in the magnitude of 100&#8722;200 (e.g., every 10,000 cycles for a test with 106 load cycles). In the triggerlist (see step 2.7) adjust the value of loops to the desired number of load cycles.</li>
</ol>
3. Fatigue test
CAUTION: The use of mechanical or servo-hydraulic testing equipment is potentially dangerous. Operate with caution and follow the instructions provided by the manufacturer.
<ol>
	<li>Install the specimen in the testing machine.</li>
	<li>If required, take DIC images before loading. This is not necessary for crack detection, but it allows using DIC to measure the surface strain under loading.</li>
	<li>Apply the first load cycle statically. Stop at maximum load and take some images for DIC. One image should be sufficient, but because the quality of the DIC results may not always be optimal, it might be helpful to have a few more images to choose from for analysis. For these images, a longer exposure time can be used as appropriate. 
	NOTE: This static load cycle can be omitted, but the images acquired statically are probably of better quality than those acquired during the dynamic test, thus improving DIC results.</li>
	<li>Set the load range and start the cyclic test. Optionally, obtain beach marks by including intervals in which the upper load is maintained but the load range is reduced. For the examples shown here, one half of the load range was applied in 15,000 cycles for every 40,000 regular cycles. Beach marks are not necessary for the presented procedure but offer the possibility to validate the detected crack lengths.</li>
	<li>Specify the static and dynamic load and run the test until the specimen fails. In the presented tests a static load of 0 kN and dynamic amplitude of 22.5 kN were applied. Respectively 50 kN static and 50 kN dynamic load were used on the stress-relieved specimen.</li>
</ol>
4. Postprocessing
<ol>
	<li>Evaluate the DIC and calculate the strain in the specimen&#39;s axial (loading) direction using apposite software. Commercial software (see Table of Materials) that includes the automated computation of strains was employed. Information on the computation of strains can be found in Gr&#233;diac and Hild22 and an overview of current commercial and open source DIC software is given in Belloni et al.1. Use the image from the first, static load cycle acquired in step 3.3 as a reference image. Here, a facet size of 19 x 19 pixels (~0.32 x 0.32 mm) and a facet distance of 15 x 15 pixels was applied for the DIC assessment.</li>
	<li>Make a plot of the calculated strain and set the legend of the plot to relatively high values (0.5% to 1.0%) to suppress possible noise. Depending on the applied software, these plots will be available in the results section after displacements and strains have been computed (4.1).</li>
	<li>Run through the image sequence acquired over the duration of the test. A forming crack will become visible in terms of elevated strains. A macroscopic crack may occur when strains exceed 1%.</li>
	<li>To compare different test results, it might be of interest to determine when the crack reaches a specified length. Crack lengths of ~2 mm were considered technical or macroscopic cracks.</li>
</ol>

<ol>
	<li>Belloni, V., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Digital+image+correlation+from+commercial+to+FOS+software:+a+mature+technique+for+full-field+displacement+measurements.">Digital image correlation from commercial to FOS software: a mature technique for full-field displacement measurements.</a> The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. XLII-2, 91-95 (2018).</li><li>Shrama, K., Clarke, A., Pullin, R., Evans, S. L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Detection+of+cracking+in+mild+steel+fatigue+specimens+using+acoustic+emission+and+digital+image+correlation.">Detection of cracking in mild steel fatigue specimens using acoustic emission and digital image correlation.</a> 31st Conference of the European Working Group on Acoustic Emission. , (2014).</li><li>Carroll, J. D., Abuzaid, W., Lambros, J., Sehitoglu, H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=High+resolution+digital+image+correlation+measurements+of+strain+accumulation+in+fatigue+crack+growth.">High resolution digital image correlation measurements of strain accumulation in fatigue crack growth.</a> International Journal of Fatigue. 57, 140-150 (2013).</li><li>Malitckii, E., Remes, H., Lehto, P., Bossuyt, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Full-field+strain+measurements+for+microstructurally+small+fatigue+crack+propagation+using+digital+image+correlation+method.">Full-field strain measurements for microstructurally small fatigue crack propagation using digital image correlation method.</a> Journal of Visualized Experiments. (143), e59134 (2019).</li><li>Rabbolini, S., Beretta, S., Foletti, S., Cristea, M. E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Crack+closure+effects+during+low+cycle+fatigue+propagation+in+line+pipe+steel:+An+analysis+with+digital+image+correlation.">Crack closure effects during low cycle fatigue propagation in line pipe steel: An analysis with digital image correlation.</a> Engineering Fracture Mechanics. 148, 441-456 (2015).</li><li>Carroll, J. D., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Multiscale+analysis+of+fatigue+crack+growth+using+digital+image+correlation.">Multiscale analysis of fatigue crack growth using digital image correlation.</a> Proceedings of the XIth International Congress and Exposition on Experimental and Applied Mechanics. , (2008).</li><li>Durif, E., Fregonese, M., Rethore, J., Combescure, A. <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+digital+image+correlation+controlled+fatigue+crack+propagation+experiment.">Development of a digital image correlation controlled fatigue crack propagation experiment.</a> EPJ Web of Conferences. 6, 31012 (2010).</li><li>Maletta, C., Bruno, L., Corigliano, P., Crupi, V., Guglielmino, E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Crack-tip+thermal+and+mechanical+hysteresis+in+Shape+Memory+Alloys+under+fatigue+loading.">Crack-tip thermal and mechanical hysteresis in Shape Memory Alloys under fatigue loading.</a> Materials Science &amp; Engineering A. 616, 281-287 (2014).</li><li>Rupil, J., Roux, S., Hild, F., Vincent, L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Fatigue+microcrack+detection+with+digital+image+correlation.">Fatigue microcrack detection with digital image correlation.</a> The Journal of Strain Analysis for Engineering Design. 46 (6), 492-509 (2011).</li><li>Risbet, M., Feissel, P., Roland, T., Brancherie, D., Roelandt, J. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Digital+image+correlation+technique:+application+to+early+fatigue+damage+detection+in+stainless+steel.">Digital image correlation technique: application to early fatigue damage detection in stainless steel.</a> Procedia Engineering. 2, 2219-2227 (2010).</li><li>Tavares, P. J., Ramos, T., Braga, D., Vaz, M. A. P., Moreira, P. M. G. P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=SIF+determination+with+digital+image+correlation.">SIF determination with digital image correlation.</a> International Journal of Structural Integrity. 6 (6), 668-676 (2015).</li><li>Hasheminejad, N., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Digital+image+correlation+to+investigate+crack+propagation+and+healing+of+asphalt+concrete.">Digital image correlation to investigate crack propagation and healing of asphalt concrete.</a> Proceedings of the 18th International Conference on Experimental Mechanics. , (2018).</li><li>Poncelet, M., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Biaxial+high+cycle+fatigue+of+a+type+304L+stainless+steel:+cyclic+strains+and+crack+initiation+detection+by+digital+image+correlation.">Biaxial high cycle fatigue of a type 304L stainless steel: cyclic strains and crack initiation detection by digital image correlation.</a> European Journal of Mechanics / A Solids. 29 (5), 810-825 (2010).</li><li>Corigliano, P., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Fatigue+assessment+of+Ti-6Al-4V+titanium+alloy+laser+welded+joints+in+absence+of+filler+material+by+means+of+full-field+techniques.">Fatigue assessment of Ti-6Al-4V titanium alloy laser welded joints in absence of filler material by means of full-field techniques.</a> Frattura ed Integrit&#224; Strutturale. 43, 171-181 (2018).</li><li>Corigliano, P., Crupi, V., Guglielmino, E., Sili, A. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Full-field+analysis+of+AL/FE+explosive+welded+joints+for+shipbuilding+applications.">Full-field analysis of AL/FE explosive welded joints for shipbuilding applications.</a> Marine Structures. 57, 207-218 (2018).</li><li>Koster, M., Kenel, C., Lee, W., Leinenbach, C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Digital+image+correlation+for+the+characterization+of+fatigue+damage+evolution+in+brazed+steel+joints.">Digital image correlation for the characterization of fatigue damage evolution in brazed steel joints.</a> Procedia Materials Science. 3, 1117-1122 (2014).</li><li>Vanlanduit, S., Vanherzeele, J., Longo, R., Guillaume, P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+digital+image+correlation+method+for+fatigue+test+experiments.">A digital image correlation method for fatigue test experiments.</a> Optics and Lasers in Engineering. 47, 371-378 (2009).</li><li>Lorenzino, P., Beretta, G., Navarro, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Application+of+Digital+Image+Correlation+(DIC)+in+resonance+machines+for+measuring+fatigue+crack+growth.">Application of Digital Image Correlation (DIC) in resonance machines for measuring fatigue crack growth.</a> Frattura ed Integrit&#224; Strutturale. 30, 369-374 (2014).</li><li>Kov&#225;r&#237;k, O., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Resonance+bending+fatigue+testing+with+simultaneous+damping+measurement+and+its+application+on+layered+coatings.">Resonance bending fatigue testing with simultaneous damping measurement and its application on layered coatings.</a> International Journal of Fatigue. 82, 300-309 (2016).</li><li>Kov&#225;r&#237;k, O., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Fatigue+crack+growth+in+bodies+with+thermally+sprayed+coating.">Fatigue crack growth in bodies with thermally sprayed coating.</a> Journal of Thermal Spray Technology. 25 (1-2), 311-320 (2016).</li><li>Friedrich, N., Ehlers, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+simplified+welding+simulation+approach+used+to+design+a+fatigue+test+specimen+containing+residual+stresses.">A simplified welding simulation approach used to design a fatigue test specimen containing residual stresses.</a> Ship Technology Research. 66 (1), 22-37 (2019).</li><li>Gr&#233;diac, M., Hild, F. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> Full-field measurements and identification in solid mechanics. , (2013).</li></ol>

The authors have nothing to disclose.

The presented procedure consists of using DIC to detect and monitor fatigue cracks on welded specimens tested on a resonance testing machine without interrupting the test. The main challenge in the application is the high load frequency of the resonance testing machine. It requires relatively short exposure times and thus high illumination for the acquisition of the images for the DIC tests. Therefore, lighting has to be maximized. On the other hand, reflections on the metallic surface may require the use of polarization filters, which will reduce the amount of light entering the cameras. To make better use of the light available, the aperture of the objectives may be enlarged. This will reduce the depth of focus. It is therefore necessary to set the focus exactly at the distance of the specimen surface and the out of plane movement of the specimen should not exceed the focused range. The setup of the cameras and lighting requires particular care.
Nevertheless, the strains calculated by DIC might not be very accurate (Figure 6). The computed strains might show high noise. On some of the facets used for DIC, the speckle pattern might not be recognized and strains will not be calculated. But the proposed procedure has proven robust with respect to the quality of the DIC results. Even if the results are not good enough to determine the strains at the weld precisely, it should still be possible to detect cracks.
The butt weld presented here has a relatively smooth weld toe compared to other weld geometries. Cracks are likely to initiate at imperfections along the weld toe with a sharp notch and thus high stress concentration. Unfortunately, it may not be possible to evaluate strains by DIC at these exact locations because the facets used for the computation may not be recognized. For example, Figure 5 shows a crack initiating at the left side of the specimen, missing facets at +25 mm horizontal / -5 mm vertical. But as shown in the example, even if some facets are not evaluated it is still possible to determine when the crack initiates and starts to grow. For welds with a steeper angle and sharper notches (e.g., longitudinal stiffener, fillet weld) it may help to tilt the cameras ~15&#176; to increase the angle to the weld surface. The proposed procedure was applied on longitudinal stiffeners as well. Despite the relatively sharp notch at the weld toe it was possible to reliably detect crack initiation.
Macroscopic cracks are assumed when strains of 1% or more are reached. In a study by Kov&#225;r&#237;k et al.20, DIC was applied to detect cracks on thermal spray-coated, unnotched specimens. It was stated that the threshold value for crack detection could be set in the range of 0.5% and 1% without significantly affecting the results. These values are confirmed by the comparison with the beach marks (Figure 4 and Figure 5). A lower value will lead to an earlier crack detection but might be more prone to uncertainties and produce less comparable results. A higher value will lead to a later recognition of crack initiation, but the results will probably be more comparable and reproducible.
Applying the first load cycle statically (step 3.3) may result time consuming when many tests are performed. If no plastic strains occur at the weld toe (notch) it might also be omitted and the unloaded condition (step 3.2) used as a reference for strain calculations. Otherwise, one of the images acquired at the beginning of the dynamic test can be used if the image quality is adequate (see Figure 6).
If only a few specimens are tested, the setup time should not be underestimated. It may require some time and iterative loops to install and set up the cameras accurately and perform the calibration to get proper images for the DIC assessment.
Specimen preparation, on the other hand, is quick and inexpensive. Specimens need only be cleaned and sprayed with color to apply the speckle patter. This comes at little cost and makes the proposed DIC-based procedure practical, particularly if a large number of specimens will be tested.
A further benefit, especially for large sets of specimens or tests running overnight, is that the cameras are triggered automatically, and the tests do not need to be interrupted.
A restriction of the DIC procedure is that as an optical method it is limited to surface cracks. Furthermore, it requires that the area to be monitored be visible by the cameras while the specimen is mounted in the testing machine.
The presented procedure was used mainly to detect the start of technical cracks. But as demonstrated, it also allows for the assessment of crack growth (e.g., to determine crack propagation rates). The result will be the length visible on the surface. Crack front curvature cannot be detected, however.
The procedure proved its applicability on welded specimens presenting a relatively complicated surface topology. It should also be applicable to non-welded specimens, as the absence of geometrical notches should facilitate the DIC measurements. A similar procedure has been applied in Kov&#225;r&#237;k et al.20 on unnotched specimens.
Furthermore, the procedure could also be applied for fatigue tests on servo-hydraulic testing machines. Here, the testing frequency would be lower than on a resonance testing machine. The exposure time of the cameras could thus be longer, which should facilitate the camera setup.
In conclusion, the presented procedure offers a straightforward way to study the development of cracks in fatigue tests. It allows detection of technical cracks and monitoring of crack propagation (e.g., to determine crack propagation rates in fatigue tests). The illustrative nature of the results facilitates their interpretation and assessment. The technique is applicable to resonance testing machines with high loading frequencies without interrupting the tests. The measurements are fully automated, so no continuous supervision is needed. It is applicable on welded specimens presenting a relatively complicated geometry in the region of interest. On small-scale specimens, it allows coverage of the whole width of the specimen. Furthermore, the procedure is characterized by a simple setup and basic post processing, making it a practical alternative to existing methods.

Welds are particularly prone to fatigue damages. Their fatigue properties are commonly determined on small-scale specimens that can be efficiently tested. During the tests, a cyclic load is applied. Eventually a crack will initiate and grow to macroscopic size. The crack will then grow and propagate through the specimen. The test is usually run until the specimen fails in full. The result of the test is the number of load cycles until failure for the applied load. This final failure is usually obvious. On the other hand, crack initiation is more complex to determine. However, it might be of interest in investigations on parameters that are not uniform over the specimen thickness or that affect the crack initiation specifically (e.g., residual stresses or post-weld treatments).
Different methods exist for the detection of cracks during fatigue tests. The simplest are visual inspection, dye penetration testing, or the application of strain gauges. More sophisticated methods include thermography, ultrasound, or eddy current testing. Crack propagation can be determined using apposite strain gauges, acoustic emission, or the potential drop method.
The proposed procedure uses digital image correlation (DIC) to visualize surface strains on the specimen. It allows detection of the formation of macroscopic cracks during fatigue tests. Furthermore, crack propagation can be monitored over the duration of the test. For DIC, an irregular pattern is applied to the specimen surface and monitored by cameras. From the distortion of the pattern under loading, surface strains are computed. Cracks will appear as elevated strains exceed a defined threshold value (&#62; 1%) and therefore become visible.
With the advance of computational technologies, DIC is becoming more and more popular for industrial and research applications. Several commercial measurement software systems as well as open-source software are available1. The proposed procedure offers another use of a technology already available in an increasing number of research facilities in mechanical and civil engineering.
Compared to visual inspections or dye penetration testing, the proposed procedure is not based on subjective perception, which depends on an operator&#39;s experience and the local geometry at the weld toe. Even with high magnification it may be challenging to detect cracks at an early stage (i.e., crack initiation), especially if the exact location is not known in advance. Furthermore, using DIC the results are saved and therefore reproducible and comparable, whereas visual inspection is possible only momentarily.
Using a full-field measurement the procedure allows monitoring the whole width of the specimen or length of the weld. Using strain gauges, it would be necessary to apply several gauges over the specimen width, because their measurement is localized. The changes in the strain gauge signal would depend on the distance and the position relative to the crack. The result would depend on whether the crack would initiate in between two gauges or by chance in front of one.
Another benefit of DIC is that it is visual, and it gives a descriptive image of the crack. Using strain gauges for crack detection or acoustic emission for crack growth, the crack length itself is not monitored but it is determined by changes in the measured strain or acoustic signals respectively. For example, in Shrama et al.2 DIC allowed for the understanding and interpretation of acoustic emission signals. Other influencing factors or interfering signals may affect the measured signal, leading to uncertainties and requiring careful interpretation of the results.
Various applications of DIC to monitor cracks in fatigue tests have been reported. In many cases DIC is used to assess the strain field at the crack tip3,4,5 and determine stress intensity factors6,7,8 or detect fatigue damages on a microscopic scale9,10. In these cases, microscopic images are used to investigate areas of interest in the range of a few millimeters. The tested specimens consist of machined base material with dimensions in the millimeter range. Larger measuring areas were recorded by Tavares et al.11 to determine stress intensity factors, by Shrama et al.2 to study acoustic emission signals, and by Hasheminejad et al.12 to investigate cracks in asphalt concrete. Poncelet et al.13 applied DIC to detect crack initiation based on the relative strain increment over a certain number of load cycles. The tests were performed on specimens with a machined surface. Welded14,15 or brazed specimens16 were studied using DIC to record the development of strains during fatigue tests. The specimens were observed from the side, showing the development of the crack in the depth direction, on the edge of the specimen.
All the aforementioned experiments were conducted on servo-hydraulic testing machines with load frequencies of a few hertz (&#60; 15 Hz). Usually the tests were interrupted to record the images for DIC. Vanlanduit et al.17 took images during the running test and applied algorithms to compensate for the different testing and image recording frequencies. Lorenzino et al.18 performed tests on a resonance testing machine and captured DIC images with microscopic cameras. Kov&#225;r&#237;k et al.19,20 performed tests on a resonance testing machine with a frequency of 100 Hz without interruptions, using a procedure very similar to the one presented here. The tests were conducted on flat, coated specimens under bending loads. A single camera and a triggered flash were used to capture images of an area of ~20 x 15 mm. Different crack assessments based on the strain field and on the displacement field were applied.
The procedure presented in this paper is applied to welded specimens presenting a notch, and thus a stress concentration. A 3D DIC-system with two cameras is employed, which allows to account for out of plane displacements of the specimen. The cameras are triggered while lighting is constant. Crack detection is based on the strain field measured on an area of 55 x 40 mm.
The procedure offers a robust and comparable way to detect cracks in fatigue tests. Furthermore, it provides a record of crack propagation. It is applicable on resonance testing machines with high loading frequencies.The tests do not have to be interrupted for measurements, and no operator needs to be present during the test. The procedure can therefore be efficiently applied to large numbers of tests to retrieve information on crack initiation and propagation.

<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>ARAMIS 5M</td>
			<td>gom</td>
			<td></td>
			<td>DIC system including two 5 megapixel cameras and control unit</td>
		</tr>
		<tr>
			<td>ARAMIS</td>
			<td>gom</td>
			<td>v6.3.1-2</td>
			<td>DIC software</td>
		</tr>
		<tr>
			<td>Calibration object</td>
			<td>gom</td>
			<td>CP 20</td>
			<td>MV 30 x 24 mm2</td>
		</tr>
		<tr>
			<td>Camera objectives, 50 mm</td>
			<td></td>
			<td></td>
			<td>Titanar 2.8 / 50</td>
		</tr>
		<tr>
			<td>Hydraulic Wedge Grip</td>
			<td>MTS</td>
			<td>647.25A02</td>
			<td></td>
		</tr>
		<tr>
			<td>Hydraulic Grip Supply</td>
			<td>MTS</td>
			<td>685.10</td>
			<td>10,000 Psi</td>
		</tr>
		<tr>
			<td>LED lights</td>
			<td>Diana LEDscale</td>
			<td>KSP0495-0001A</td>
			<td>4 x 16 W LED lights</td>
		</tr>
		<tr>
			<td>Polarization filters</td>
			<td>Schneider-Kreuznach</td>
			<td></td>
			<td>52,0 AUF (2 x for cameras)</td>
		</tr>
		<tr>
			<td>Polarization filters</td>
			<td>Schneider-Kreuznach</td>
			<td></td>
			<td>67,0 AUF (4 x for lights)</td>
		</tr>
		<tr>
			<td>Resonance testing machine</td>
			<td>Schenck</td>
			<td></td>
			<td>200 kN resonance testing machine</td>
		</tr>
		<tr>
			<td>Resonance testing machine control unit</td>
			<td>Rumul</td>
			<td>v 2.5.3</td>
			<td>Resonance testing machine control unit and software</td>
		</tr>
		<tr>
			<td>Spray paint</td>
			<td></td>
			<td></td>
			<td>Black and white spray paint, matt</td>
		</tr>
	</tbody>
</table>

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.

To detect cracks and monitor crack propagation the strain in the loading direction of the specimen was plotted. Cracks became visible in terms of elevated strains (&#62; 1%).
The results obtained from two fatigue tests are presented. The tests were performed at different loads and load ratios. The results are not intended for direct comparison between the two tests but represent typical outcomes of these tests and demonstrate the capabilities of the presented procedure.
The development of a crack in a specimen in as-welded conditions is shown in Figure 4. The specimen contained residual stresses caused by the shrinkage of the weld during cooling. They were measured by X-ray diffraction and hole-drilling and calculated by welding simulations21. Because of tensile residual stresses in the middle of the specimen, the crack initiates at the center line. First, the strain began to increase at the location of the forming crack. A technical crack was assumed when strains exceeded 1% over a length of 2 mm (N = 755,000). The crack then propagated symmetrically to both sides. The detected crack length was compared to beach marks generated during the test and showed good agreement. The video of the DIC results shows how crack propagation slowed down during the formation of the beach marks.
The development of a crack on a stress-relieved specimen is shown in Figure 5. Crack initiation was not influenced by residual stresses. Several cracks formed at different locations along the weld. A crack of 2 mm was detected after 574,000 cycles. The single cracks then grew and eventually unified. The detected crack length was compared to the beach marks again.
The generation of beach marks offers a good possibility to validate the crack lengths detected using the DIC technique. Furthermore, it offers the possibility to correlate the depth of the crack with the length measured on the specimen surface. At an early stage of the crack, close to the surface, it might be challenging to obtain beach marks that are clearly visible. Here, the results showed the advantage of the DIC approach.
As presented in Figure 4 and Figure 5 the outcome of the procedure is a series of images (or a video) showing the development of cracks at the weld. From these images, it is possible to determine the origin and the number of cracks. Furthermore, they can be used to determine when a crack has reached a specific length. Cracks 2 mm in length were considered macroscopic or technical. This crack length could reliably be retrieved from the images and in this study was used to compare the outcome of a series of tests. Furthermore, from an engineering point of view, this crack length would be detectable in service using available inspection techniques. By measuring the crack length from the resulting images and correlating it to the number of load cycles, it is also possible to plot a crack growth curve or determine crack growth rates. These may be of interest in fracture mechanical calculations of crack propagation.
<img alt="Figure 1" class="xfigimg" src="/files/ftp_upload/60390/60390fig1.jpg" /> 
Figure 1: Multilayer K-butt weld specimens used for the fatigue tests. Dimensions in millimeters. <a href="https://www.jove.com/files/ftp_upload/60390/60390fig1large.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/60390/60390fig2.jpg" /> 
Figure 2: Speckle pattern for digital image correlation at the weld. <a href="https://www.jove.com/files/ftp_upload/60390/60390fig2large.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/60390/60390fig3.jpg" /> 
Figure 3: Test setup with DIC cameras and lights supported by a scaffold structure installed above the specimen. <a href="https://www.jove.com/files/ftp_upload/60390/60390fig3large.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/60390/60390fig4.jpg" /> 
Figure 4: Percent strain in the loading direction (vertical) showing the development of a crack and comparison with beach marks on a specimen in as-welded conditions. N = number of load cycles. <a href="https://www.jove.com/files/ftp_upload/60390/60390fig4large.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/60390/60390fig5.jpg" /> 
Figure 5: Percent strain in the loading direction (vertical) showing the development of cracks and comparison with beach marks on a stress-relieved specimen. N = number of load cycles. <a href="https://www.jove.com/files/ftp_upload/60390/60390fig5large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 6" class="xfigimg" src="/files/ftp_upload/60390/60390fig6.jpg" /> 
Figure 6: Percent strain in the loading direction at maximum load on the first, static load cycle (N = 1) and at the beginning of the fatigue test at different numbers of load cycles. <a href="https://www.jove.com/files/ftp_upload/60390/60390fig6large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
Supplemental File 1: Trigger List. <a href="https://www.jove.com/files/ftp_upload/60390/triggerlist.txt" target="_blank">Please click here to view this file (Right click to download).</a>

Watch this Scientific Journal Video about Crack Monitoring in Resonance Fatigue Testing of Welded Specimens Using Digital Image Correlation at JoVE.com

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

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 ...

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8.1K Views.  Hamburg University of Technology (TUHH). 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.

Video: Crack Monitoring in Resonance Fatigue Testing of Welded Specimens Using 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 ...

Micro 3D Printing Using a Digital Projector and its Application in the Study of Soft Materials Mechanics

Buckling is a classical topic in mechanics. While buckling has long been studied as one of the major structural failure modes1, it has recently drawn new attention as a unique mechanism for pattern transformation. Nature is full of such examples where a wealth of exotic patterns are formed through mechanical instability2-5. Inspired by this elegant mechanism, many studies have demonstrated creation and transformation of patterns using soft materials such as elastomers and hydrogels6-11. Swelling gels are of particular interest because they can spontaneously trigger mechanical instability to create various patterns without the need of external force6-10. Recently, we have reported demonstration of full control over buckling pattern of micro-scaled tubular gels using projection micro-stereolithography (P&mu;SL), a three-dimensional (3D) manufacturing technology capable of rapidly converting computer generated 3D models into physical objects at high resolution12,13. Here we present a simple method to build up a simplified P&mu;SL system using a commercially available digital data projector to study swelling-induced buckling instability for controlled pattern transformation.
A simple desktop 3D printer is built using an off-the-shelf digital data projector and simple optical components such as a convex lens and a mirror14. Cross-sectional images extracted from a 3D solid model is projected on the photosensitive resin surface in sequence, polymerizing liquid resin into a desired 3D solid structure in a layer-by-layer fashion. Even with this simple configuration and easy process, arbitrary 3D objects can be readily fabricated with sub-100 &mu;m resolution.
This desktop 3D printer holds potential in the study of soft material mechanics by offering a great opportunity to explore various 3D geometries. We use this system to fabricate tubular shaped hydrogel structure with different dimensions. Fixed on the bottom to the substrate, the tubular gel develops inhomogeneous stress during swelling, which gives rise to buckling instability. Various wavy patterns appear along the circumference of the tube when the gel structures undergo buckling. Experiment shows that circumferential buckling of desired mode can be created in a controlled manner. Pattern transformation of three-dimensionally structured tubular gels has significant implication not only in mechanics and material science, but also in many other emerging fields such as tunable matamaterials.

We demonstrate controlled pattern transformation of swelling gel tubes by elastic instability. A simple projection micro stereo-lithography setup is built using an off-the-shelf digital data projector to fabricate three-dimensional polymeric structures in a layer-by-layer fashion. Swelling hydrogel tubes under mechanical constraint display various circumferential buckling modes depending on dimension.

Buckling is a classical topic in mechanics. While buckling has long been studied as one of the major structural failure modes1, it has recently drawn new ...

Ultrasonic Welding of Thermoplastic Composite Coupons for Mechanical Characterization of Welded Joints through Single Lap Shear Testing

This paper presents a novel straightforward method for ultrasonic welding of thermoplastic-composite coupons in optimum processing conditions. The ultrasonic welding process described in this paper is based on three main pillars. Firstly, flat energy directors are used for preferential heat generation at the joining interface during the welding process. A flat energy director is a neat thermoplastic resin film that is placed between the parts to be joined prior to the welding process and heats up preferentially owing to its lower compressive stiffness relative to the composite substrates. Consequently, flat energy directors provide a simple solution that does not require molding of resin protrusions on the surfaces of the composite substrates, as opposed to ultrasonic welding of unreinforced plastics. Secondly, the process data provided by the ultrasonic welder is used to rapidly define the optimum welding parameters for any thermoplastic composite material combination. Thirdly, displacement control is used in the welding process to ensure consistent quality of the welded joints. According to this method, thermoplastic-composite flat coupons are individually welded in a single lap configuration. Mechanical testing of the welded coupons allows determining the apparent lap shear strength of the joints, which is one of the properties most commonly used to quantify the strength of thermoplastic composite welded joints.

A straightforward procedure for ultrasonic welding of thermoplastic composite coupons for basic mechanical testing is described. Key characteristics of this ultrasonic welding process are the use of flat energy directors for simplified process preparation and the use of process data for the fast definition of optimum processing conditions.

This paper presents a novel straightforward method for ultrasonic welding of thermoplastic-composite coupons in optimum processing conditions. The ...

Subsurface Defect Localization by Structured Heating Using Laser Projected Photothermal Thermography

The presented method is used to locate subsurface defects oriented perpendicularly to the surface. To achieve this, we create destructively interfering thermal wave fields that are disturbed by the defect. This effect is measured and used to locate the defect. We form the destructively interfering wave fields by using a modified projector. The original light engine of the projector is replaced with a fiber-coupled high-power diode laser. Its beam is shaped and aligned to the projector&#39;s spatial light modulator and optimized for optimal optical throughput and homogeneous projection by first characterizing the beam profile, and, second, correcting it mechanically and numerically. A high-performance infrared (IR) camera is set up according to the tight geometrical situation (including corrections of the geometrical image distortions) and the requirement to detect weak temperature oscillations at the sample surface. Data acquisition can be performed once a synchronization between the individual thermal wave field sources, the scanning stage, and the IR camera is established by using a dedicated experimental setup which needs to be tuned to the specific material being investigated. During data post-processing, the relevant information on the presence of a defect below the surface of the sample is extracted. It is retrieved from the oscillating part of the acquired thermal radiation coming from the so-called depletion line of the sample surface. The exact location of the defect is deduced from the analysis of the spatial-temporal shape of these oscillations in a final step. The method is reference-free and very sensitive to changes within the thermal wave field. So far, the method has been tested with steel samples but is applicable to different materials as well, in particular to temperature sensitive materials.

This method aims at locating vertical subsurface defects. Here, we couple a laser with a spatial light modulator and trigger its video input to heat a sample surface deterministically with two anti-phased modulated lines while acquiring highly resolved thermal images. The defect position is retrieved from evaluating thermal wave interference minima.

The presented method is used to locate subsurface defects oriented perpendicularly to the surface. To achieve this, we create destructively interfering ...

A Novel Method for In Situ Electromechanical Characterization of Nanoscale Specimens

Electrically assisted deformation (EAD) is increasingly being used to improve the formability of metals during processes such as sheet metal rolling and forging. Adoption of this technique is proceeding despite disagreement concerning the underlying mechanism responsible for EAD. The experimental procedure described herein enables a more explicit study compared to previous EAD research by removing thermal effects, which are responsible for disagreement in interpreting previous EAD results. Furthermore, as the procedure described here enables EAD observation in situ and in real time in a transmission electron microscope (TEM), it is superior to existing post-mortem methods that observe EAD effects post-test. Test samples consist of a single crystal copper (SCC) foil having a free-standing tensile test section of nanoscale thickness, fabricated using a combination of laser and ion beam milling. The SCC is mounted to an etched silicon base that provides mechanical support and electrical isolation while serving as a heat sink. Using this geometry, even at high current density (~3,500 A/mm2), the test section experiences a negligible temperature increase (&#60;0.02 &#176;C), thus eliminating Joule heating effects. Monitoring material deformation and identifying the corresponding changes to microstructures, e.g. dislocations, are accomplished by acquiring and analyzing a series of TEM images. Our sample preparation and in situ experiment procedures are robust and versatile as they can be readily utilized to test materials with different microstructures, e.g., single and polycrystalline copper.

A Novel Method for In Situ Electromechanical Characterization of Nanoscale Specimens

Isolating electrical and thermal effects on electrically assisted deformation (EAD) is very difficult using macroscopic samples. Metallic sample micro- and nanostructures together with a custom test procedure have been developed to evaluate the impact of applied current on the formation without joule heating and evolution of dislocations on these samples.

Electrically assisted deformation (EAD) is increasingly being used to improve the formability of metals during processes such as sheet metal rolling and ...

Ultrasonic Fatigue Testing in the Tension-Compression Mode

Ultrasonic fatigue testing is one of a few methods which allow investigating fatigue properties in the ultra-high cycle region. The method is based on exposing the specimen to longitudinal vibrations on its resonance frequency close to 20 kHz. With use of this method, it is possible to significantly decrease the time required for the test, when compared to conventional testing devices usually working at frequencies under 200 Hz. It is also used to simulate loading of material during operation in high speed conditions, such as those experienced by components of jet engines or car turbo pumps. It is necessary to operate only in the high and ultra-high cycle region, due to the possibility of extremely high deformation rates, which can have a significant influence on the test results. Specimen shape and dimensions have to be carefully selected and calculated to fulfill the resonance condition of the ultrasonic system; thus, it is not possible to test the full components or specimens of arbitrary shape. Before each test, it is necessary to harmonize the specimen with the frequency of the ultrasonic system to compensate for deviations of the real shape from the ideal one. It is not possible to run a test until a total fracture of the specimen, since the test is automatically terminated after initiation and propagation of the crack to a certain length, when the stiffness of the system changes enough to shift the system out of the resonance frequency. This manuscript describes the process of evaluation of materials' fatigue properties at high-frequency ultrasonic fatigue loading with use of mechanical resonance at a frequency close to 20 kHz. The protocol includes a detailed description of all steps required for a correct test, including specimen design, stress calculation, harmonizing with the resonance frequency, performing the test, and final static fracture.

A protocol for ultrasonic fatigue testing in the high and ultra-high cycle region in axial tension-compression loading mode.

Ultrasonic fatigue testing is one of a few methods which allow investigating fatigue properties in the ultra-high cycle region. The method is based on ...

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 ...

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.

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 ...

Micromechanical Tension Testing of Additively Manufactured 17-4 PH Stainless Steel Specimens

This study presents a methodology for the rapid fabrication and micro-tensile testing of additively manufactured (AM) 17-4PH stainless steels by combining photolithography, wet-etching, focused ion beam (FIB) milling, and modified nanoindentation. Detailed procedures for proper sample surface preparation, photo-resist placement, etchant preparation, and FIB sequencing are described herein to allow for high throughput (rapid) specimen fabrication from bulk AM 17-4PH stainless steel volumes. Additionally, procedures for the nano-indenter tip modification to allow tensile testing are presented and a representative micro specimen is fabricated and tested to failure in tension. Tensile-grip-to-specimen alignment and sample engagement were the main challenges of the micro-tensile testing; however, by reducing the indenter tip dimensions, alignment and engagement between the tensile grip and specimen were improved. Results from the representative micro-scale in situ SEM tensile test indicate a single slip plane specimen fracture (typical of a ductile single crystal failure), differing from macro-scale AM 17-4PH post-yield tensile behavior.

Presented here is a procedure for measuring fundamental material properties through micromechanical tension testing. Described are the methods for micro-tensile specimen fabrication (allowing rapid micro-specimen fabrication from bulk material volumes by combining photolithography, chemical etching, and focused ion beam milling), indenter tip modification, and micromechanical tension testing (including an example).

This study presents a methodology for the rapid fabrication and micro-tensile testing of additively manufactured (AM) 17-4PH stainless steels by combining ...

In vitro Assessment of Aortic Regurgitation Using Four-Dimensional Flow Magnetic Resonance Imaging

Aortic regurgitation (AR) refers to backward blood flow from the aorta into the left ventricle (LV) during ventricular diastole. The regurgitant jet arising from the complex shape is characterized by the three-dimensional flow and high-velocity gradient, sometimes limiting an accurate measurement of the regurgitant volume using 2D echocardiography. Recently developed four-dimensional flow magnetic resonance imaging (4D flow MRI) enables three-dimensional volumetric flow measurements, which can be used to accurately quantify the amount of the regurgitation. This study focuses on (i) magnetic resonance compatible AR model fabrication (dilatation, perforation, and prolapse) and (ii) systematic analysis of the performance of 4D flow MRI in AR quantification. The results indicated that the formation of the forward and backward jets over time was highly dependent on the types of AR origin. The amount of regurgitation volume bias for the model types were -7.04%, -33.21%, 6.75%, and 37.04% compared to the ground truth (48 mL) volume measured from the pump stroke volume. The largest error of the regurgitation fraction was around 12%. These results indicate that careful selection of imaging parameters is required when absolute regurgitation volume is important. The suggested in vitro flow phantom can easily be modified to simulate other valvular diseases such as aortic stenosis or bicuspid aortic valve (BAV) and can be used as a standard platform to test different MRI sequences in the future.

In vitro Assessment of Aortic Regurgitation Using Four-Dimensional Flow Magnetic Resonance Imaging

Aortic regurgitation is an aortic valve heart disease. This manuscript demonstrates how four-dimensional flow magnetic resonance imaging can evaluate aortic regurgitation using in vitro heart valves mimicking aortic regurgitation.

Aortic regurgitation (AR) refers to backward blood flow from the aorta into the left ventricle (LV) during ventricular diastole. The regurgitant jet ...