New approaches of three-dimensional image processing applied to the study of lightweight mortars with EVA aggregates and piassava fibres

Abstract

Civil construction is an alternative for the reuse of industrial discarded materials. The ethylene-vinyl acetate's residue as an aggregate, generates light materials with interesting thermal and acoustic properties. However, adding EVA reduces the material strength. To soften this effect, natural fibres like piassava can be added. This work proposes a methodology of three dimensional tomographic image analysis for the characterisation of lightweight mortars reinforced with piassava fibres. For this, several image features were calculated using different algorithms approaches focusing on the memory efficiency, the main handicap of three-dimensional image analysis. The methodology identified the EVA grains, the fibres and the pores, being insufficient collected information for the cracks identification. Also, it was possible to verify the fibre action as reinforcement. Regarding the algorithm performance analysis, the two-passage approaches were better, being the memory focused approach, the only one that can work with very big 3D images.