Full-field identification of mixed-mode adhesion properties in a flexible, multi-layer microelectronic material system

Ruybalid, AP Andre; Sluis, O. van der; Geers, M.G.D.; Hoefnagels, Jpm Johan

doi:10.1016/j.engfracmech.2020.106879

Cited by 2 publications

(1 citation statement)

References 47 publications

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“…Specifically note-worthy is the fine tuning done in [26][27][28], where time-Integrated Digital Image Correlation algorithms are proposed exploiting the periodicity of the deformation to simultaneously correlate all images at once to stabilize the correlation and identify material parameters with high sensitivity, by further increasing the ratio of measurement points to DOFs. Where in [27] this algorithm was only validated on synthetically generated images, the strength of this method was later demonstrated on experimental images, for instance for the challenging test case of identifying insensitive mixed-mode interface adhesion properties [29,30]. In [28], this concept was again proven to be valuable for vibrational analysis, while in an earlier more specific paper a time-integrated algorithm tuned to periodic motion has been validated for fatigue testing [26].…”

Section: Introductionmentioning

confidence: 99%

Accurate Strain Field Measurement During Strip Rolling by Exploiting Recurring Material Motion with Time-Integrated Digital Image Correlation

et al. 2021

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Background 95% Of all metals and alloys are processed using strip rolling, explaining the great number of existing strip rolling optimization models. Yet, an accurate in-situ full-field experimental measurement method of the deformation, velocity and strain fields of the strip in the deformation zone is lacking. Objective Here, a novel time-Integrated Digital Image Correlation (t-IDIC) framework is proposed and validated that fully exploits the notion of continuous, recurring material motion during strip rolling. Methods High strain accuracy and robustness against unavoidable light reflections and missing speckles is achieved by simultaneously correlating many (e.g. 200) image pairs in a single optimization step, i.e. each image pair is correlated with the same average global displacement field but is multiplied by a unique velocity corrector to account for differences in material velocity between image pairs. Results Demonstration on two different strip rolling experiments revealed previously inaccessible subtle changes in the deformation and strain fields due to minor variations in pre-deformation, elastic recovery, and geometrical irregularities. The influence of the work roll force and entry/exit strip tension has been investigated for strip rolling with an industrial pilot mill, which revealed unexpected non-horizontal material feed. This asymmetry was reduced by increasing the entry strip tension and rolling force, resulting in a more symmetric strain distribution, while increased distance between the neutral and entry point was found for a larger rolling force. Conclusions The proposed t-IDIC method allows for robust and accurate characterization of the strip’s full-field behavior of the deformation zone during rolling, revealing novel insights in the material behavior.

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