Digital Image Correlation (DIC) is probably one of the most used optical methods for displacements and strains measurement and has been used both in its standard form and in its integrated variant to extract the fracture mechanics parameters from a set of images of the crack. However, differently from photoelasticity, where stress data is directly available because the imaged fringes are proportional to sigma_1 - sigma_2, in the DIC case the fracture mechanics parameters result from a reverse calibration procedure involving the least-squares fit of a theoretical displacement model to the experimental data. Thus, the accuracy of the computed parameters critically depends on the exact identification of the crack location and orientation. This problem is well known, and a partial solution has been provided by Réthoré et al. (2008), who proposed an approach for computing the distance from the estimated and the true location of the crack tip in the longitudinal direction using the first hypersingular functions (i.e., the 1st negative term of William’s series). However, no hint is provided to estimate the crack orientation. This work wants to fill the gap, describing an automatic algorithm for the complete identification of the crack tip location.

Kinematic estimation of fracture mechanics parameter with automatic crack-tip identification

Antonio Baldi
Primo
Writing – Original Draft Preparation
;
Pietro Maria Santucci
Secondo
Data Curation
2022-01-01

Abstract

Digital Image Correlation (DIC) is probably one of the most used optical methods for displacements and strains measurement and has been used both in its standard form and in its integrated variant to extract the fracture mechanics parameters from a set of images of the crack. However, differently from photoelasticity, where stress data is directly available because the imaged fringes are proportional to sigma_1 - sigma_2, in the DIC case the fracture mechanics parameters result from a reverse calibration procedure involving the least-squares fit of a theoretical displacement model to the experimental data. Thus, the accuracy of the computed parameters critically depends on the exact identification of the crack location and orientation. This problem is well known, and a partial solution has been provided by Réthoré et al. (2008), who proposed an approach for computing the distance from the estimated and the true location of the crack tip in the longitudinal direction using the first hypersingular functions (i.e., the 1st negative term of William’s series). However, no hint is provided to estimate the crack orientation. This work wants to fill the gap, describing an automatic algorithm for the complete identification of the crack tip location.
2022
Digital Image Correlation; Crack tip opening angle; Stress intensity factor; Fatigue crack growth
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11584/325107
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