GEOTECHNICAL MORPHOLOGICAL CHARACTERIZATION USING X-RAY COMPUTED MICROTOMOGRAPHY IMAGES
Microtomography, Image Processing, Morphological Characterization, Python
Geotechnical engineering has utilized technological advancements and numerical analyses to minimize errors in soil property measurements and achieve more accurate results. Methods from materials science have contributed to the analysis of soil properties at the grain scale, enabling morphological characterizations such as X-ray micro-computed tomography (µCT). In this context, this dissertation aims to implement algorithms and develop scripts in Python to process two-dimensional images generated by X-ray micro-computed tomography. The samples analyzed included sand, iron ore tailings, and a composite of iron ore tailings with polymer, aiming to analyze mesoscale morphological parameters such as sphericity, granulometry, porosity, and void ratio. The research highlighted that the configuration of the images in the micro-CT scanner and the pre-processing of the images can significantly influence the results. The use of Python for analyzing the morphological parameters of geotechnical samples proved to be relatively feasible, provided that the specificities of the micro-CT images of the studied sample are considered.