期刊
JOURNAL OF BIOMECHANICAL ENGINEERING-TRANSACTIONS OF THE ASME
卷 124, 期 5, 页码 557-567出版社
ASME
DOI: 10.1115/1.1503795
关键词
optimized digital image correlation; thin-plate; spline smoothing generalized cross-validation unconfined compression; inhomogeneity; anisotropy
资金
- NIAMS NIH HHS [R01 AR046532-03, R01 AR046532, R01 AR043628, AR 43628, AR 46532, R01 AR043628-08, AR 46568] Funding Source: Medline
An automated approach for measuring in situ two-dimensional strain fields was developed and validated for its application to cartilage mechanics. This approach combines video microscopy, optimized digital image correlation (DIC), thin-plate spline smoothing (TPSS) and generalized cross-validation (GCV) techniques to achieve the desired efficiency and accuracy. Results demonstrate that sub-pixel accuracies can be achieved for measuring tissue displacements with this methodology with a measurement uncertainty ranging from 0.25 to 0.30 pixels. The deformational gradients (from which the strains are determined) can be evaluated directly using the optimized DIC, with a measurement uncertainty of 0.017similar to0.032. In actual measurements of strain in cartilage, TPSS and differentiation can be used to achieve a more accurate measurement of the gradients from the displacement data. Using this automated approach, the two-dimensional strain fields inside immature bovine carpometacarpal joint cartilage specimens under unconfined compression were characterized (n =21). The depth-dependent apparent elastic modulus and Poissons ratio were also determined and found to be smallest at the articular surface and increasing with depth. The apparent Poisson's ratio is found to decrease with increasing compressive strain, with values as low as 0.01 observed near the articular surface at 25% compression. The variation of the apparent Poisson's ratio with depth is found to be consistent with a theoretical model of cartilage which accounts for the disparity in its tensile and compressive moduli.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据