AI Article Synopsis

  • The study introduces a method for identifying stiffness in materials by analyzing 3-D deformation fields obtained from silicone rubber models using digital volume correlation with optical coherence tomography.
  • The researchers tested how noise and uncertainties in reconstruction affect the correlation algorithm's ability to measure strain reliably, determining the minimum strain that could be accurately detected.
  • They then used the 3-D deformation data to calculate elastic properties under tension, finding that their results for different strain conditions matched well with analytic calculations based on constant stress assumptions.

Article Abstract

This paper presents a methodology for stiffness identification from depth-resolved three-dimensional (3-D) full-field deformation fields. These were obtained by performing digital volume correlation on optical coherence tomography volume reconstructions of silicone rubber phantoms. The effect of noise and reconstruction uncertainties on the performance of the correlation algorithm was first evaluated through stationary and rigid body translation tests to give an indication of the minimum strain that can be reliably measured. The phantoms were then tested under tension, and the 3-D deformation fields were used to identify the elastic constitutive parameters using a 3-D manually defined virtual fields method. The identification results for the cases of uniform and heterogeneous strain fields were compared with those calculated analytically through the constant uniaxial stress assumption, showing good agreement.

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Source
http://dx.doi.org/10.1117/1.JBO.18.12.121512DOI Listing

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