Analysis of Mechanical Behavior through Digital Image Correlation and Reliability of Pinus halepensis Mill.

Abstract

The mechanical behavior of test pieces extracted from two specimens of Pinus halepensis Mill., from the same geographical area and close to each other, was examined in this study. Using a methodology based on Digital Image Correlation (DIC) and implemented during compression strength testing, the modulus of elasticity in compression parallel to the grain (MOEc) was obtained. In addition, the value of compressive strength (MORc) was obtained for this type of wood. The research was complemented with a reliability study, determined using the Weibull modulus, from the MORc values. A microstructural and behavioral study of the most representative pieces after failure was also conducted to correlate breakage with the behavior of the pieces during the tests monitored by DIC, to link both studies. DIC was shown to be an ideal and low-cost technique for the determination of the studied properties, and obtained average values of MOEc of 50.72 MPa and MORc of 9693 MPa. These values represent fundamental data for design and calculations of wooden structures. A reliability value of between 11 and 12 was obtained using the Weibull modulus for this type of wood.

A Comparative Study of 2D and 3D Digital Image Correlation Approaches for the Characterization and Numerical Analysis of Composite Materials

“…Among the main techniques available to determinate the global mechanical characteristics are Moiré Interferometry [22]; Particle Image Velocimetry (PIV) [23]; photoelasticity [24]; multi-camera tracking and the Digital Image Correlation (DIC) [25][26][27]. In this context, DIC supposes a good technique for the characterisation of heterogeneous materials such as wood [28], concrete [29] or composites [25,[30][31][32]. There are two types of DIC strategies: the first one consists of a two-dimensional approach (2D DIC), while the second consists of a threedimensional approach (3D DIC) [6,31].…”

Compression and Strain Predictive Models in Non-Structural Recycled Concretes Made from Construction and Demolition Wastes

“…This method allows us to obtain a full field of displacements and strains through the use of correspondence procedures based on correlations and numerical differentiation algorithms [29]. Thanks to this, DIC has been widely used for the analysis and characterization of various heterogeneous materials, such as wood [30], composites [31] and concrete [32]. In this last field, there are studies that cover both the measurement of strains [33] and the analysis of cracks [34,35], and even the characterization of the influence of aggregate size on drying contractions [36].…”