Ricerc@Sapienza

With a view to gaining an in-depth assessment of the response of particleboards (PBs) to different in-service loading conditions,
samples of high-density homogeneous PBs of sugarcane bagasse and castor oil polyurethane resin were manufactured and
subjected to low velocity impacts using an instrumented drop weight impact tower and four different energy levels, namely
5, 10, 20 and 30 J. The prediction of the damage modes was assessed using Comsol Multiphysics. In particular, the random
distribution of the fibres and their lengths were reproduced through a robust model. The experimentally obtained dent depths
due to the impactor were compared with the ones numerically simulated showing good agreement. The post-impact damage
was evaluated by a simultaneous system of image acquisitions coming from two different sensors. In particular, thermograms
were recorded during the heating up and cooling down phases, while the specklegrams were gathered one at room temperature
(as reference) and the remaining during the cooling down phase. On one hand, the specklegrams were processed via a new
software package named Ncorr v.1.2, which is an open-source subset-based 2D digital image correlation (DIC) package
that combines modern DIC algorithms proposed in the literature with additional enhancements. On the other hand, the
thermographic results linked to a square pulse were compared with those coming from the laser line thermography technique
that heats a line-region on the surface of the sample instead of a spot. Surprisingly, both the vibrothermography and the line
scanning thermography methods coupled with a robotized system show substantial advantages in the defect detection around
the impacted zone.