The quality of strain measurements by digital image correlation (DIC) strongly depends on the quality of the pattern on the specimen’s surface. An ideal pattern should be highly contrasted, stochastic, and isotropic. In addition, the speckle pattern should have an average size that exceeds the image pixel size by a factor of 3–5. (Smaller speckles cause poor contrast, and larger speckles cause poor spatial resolution.) Finally, the ideal pattern should have a limited scatter in terms of speckle sizes.
The aims of this study were: (i) to define the ideal speckle size in relation to the specimen size and acquisition system; (ii) provide practical guidelines to identify the optimal settings of an airbrush gun, in order to produce a pattern that is as close as possible to the desired one while minimizing the scatter of speckle sizes.
Patterns of different sizes were produced using two different airbrush guns with different settings of the four most influential factors (dilution, airflow setting, spraying distance, and air pressure). A full-factorial DOE strategy was implemented to explore the four factors at two levels each: 36 specimens were analyzed for each of the 16 combinations.
The images were acquired using the digital cameras of a DIC system. The distribution of speckle sizes was analyzed to calculate the average speckle size and the standard deviation of the corresponding truncated Gaussian distribution. A mathematical model was built to enable prediction of the average speckle size in relation to the airbrush gun settings.
We showed that it is possible to obtain a pattern with a highly controlled average and a limited scatter of speckle sizes, so as to match the ideal distribution of speckle sizes for DIC. Although the settings identified here apply only to the specific equipment being used, this method can be adapted to any airbrush to produce a desired speckle pattern.
Calcium phosphate cements (CPCs) should ideally have mechanical properties similar to those of the bone tissue the material is used to replace or repair. Usually, the compressive strength of the CPCs is reported and, more rarely, the elastic modulus. Conversely, scarce or no data are available on Poisson's ratio and strain-to-crack-initiation. This is unfortunate, as data on the elastic response is key to, e.g., numerical model accuracy. In this study, the compressive behaviour of brushite, monetite and apatite cements was fully characterised. Measurement of the surface strains was done using a digital image correlation (DIC) technique, and compared to results obtained with the commonly used built-in displacement measurement of the materials testers. The collected data showed that the use of fixed compression platens, as opposed to spherically seated ones, may in some cases underestimate the compressive strength by up to 40%. Also, the built-in measurements may underestimate the elastic modulus by up to 62% as compared to DIC measurements. Using DIC, the brushite cement was found to be much stiffer (24.3 ± 2.3GPa) than the apatite (13.5 ± 1.6GPa) and monetite (7.1 ± 1.0GPa) cements, and elastic moduli were inversely related to the porosity of the materials. Poisson's ratio was determined to be 0.26 ± 0.02 for brushite, 0.21 ± 0.02 for apatite and 0.20 ± 0.03 for monetite. All investigated CPCs showed low strain-to-crack-initiation (0.17-0.19%). In summary, the elastic modulus of CPCs is substantially higher than previously reported and it is concluded that an accurate procedure is a prerequisite in order to properly compare the mechanical properties of different CPC formulations. It is recommended to use spherically seated platens and measuring the strain at a relevant resolution and on the specimen surface.
Measuring small-magnitude strain fields using a digital image correlation (DIC) technique is challenging, due to the noise-signal ratio in strain maps. Here, we determined the level of accuracy achievable in measuring small-magnitude (<0.1%) homogeneous strain fields. We investigated different sets of parameters for image processing and imaging pre-selection, based on single-image noise level. The trueness of DIC was assessed by comparison of Young’s modulus (E) and Poisson’s ratio (ν) with values obtained from strain gauge measurements. Repeatability was improved, on average, by 20–25% with experimentally-determined optimal parameters and image pre-selection. Despite this, the intra- and inter-specimen repeatability of strain gauge measurements was 5 and 2.5 times better than DIC, respectively. Moreover, although trueness was also improved, on average, by 30–45%, DIC consistently overestimated the two material parameters by 1.8% and 3.2% for E and ν, respectively. DIC is a suitable option to measure small-magnitude homogeneous strain fields, bearing in mind the limitations in achievable accuracy.
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