Title:	Caracterização morfológica-geotécnica utilizando imagens de microtomografia computadorizada de raio-x
Authors:	Moura, Thaís Kogui de
Orientador(es)::	Casagrande, Michéle Dal Toé
Coorientador(es)::	Ozelim, Luan Carlos de Sena Monteiro
Assunto::	Microtomografia Processamento de imagens Caracterização morfológica (Geotecnia) Python
Issue Date:	13-Nov-2024
Data de defesa::	13-Jun-2024
Citation:	MOURA, Thais Kogui de.Caracterização morfológica-geotécnica utilizando imagens de microtomografia computadorizada de raio-x. 2024. 130 f., il. Dissertação (Mestrado em Geotecnia) — Universidade de Brasília, Brasília, 2024.
Abstract:	Geotechnical engineering has been leveraging technological advances and numerical analyses to minimize errors in the measurement of soil properties and to achieve more precise results. Methods from material science have contributed to the analysis of soil properties at the grain scale, enabling morphological characterizations, such as X-ray computed microtomography (µCT). In this context, this dissertation aims to implement algorithms and develop Python scripts to process two-dimensional images generated by X-ray computed microtomography. The samples analyzed included sand, iron ore tailings, and a composite of iron ore tailings with polymer, aiming to analyze meso-scale morphological parameters such as sphericity, granulometry, porosity, and void ratio. The research highlighted that the configuration of the images in the microtomograph and the image pre-processing can significantly influence the results. Python libraries such as OpenCV, NumPy, Matplotlib, PIL, Scikit-image, SciPy, and Pandas were used for the morphological parameter analysis of geotechnical samples, demonstrating a relatively viable alternative, provided the specificities of the microtomographed images of the studied samples are considered. The results of the analyses using Python code for the geotechnical parameters through image processing for the sand sample showed that the obtained sphericity matched the value found using Mathematica software, the granulometry exhibited a distribution similar to the experimental curve, maintaining its classification as medium sand, and the void ratio and porosity found were significantly close; for the iron ore tailings sample, the sphericity had variability in values depending on the chosen methods, the granulometry showed a tendency for larger particles compared to the experimental curve, and the void ratio and porosity found by the Python code exactly matched the values obtained by DragonFly software; however, for the composite of iron ore tailings stabilized with polymer, the results obtained by the Python code did not closely correlate with the values found by DragonFly software.
metadata.dc.description.unidade:	Faculdade de Tecnologia (FT) Departamento de Engenharia Civil e Ambiental (FT ENC)
Description:	Dissertação (mestrado) — Universidade de Brasília, Faculdade de Tecnologia, Departamento de Engenharia Civil e Ambiental, 2024.
metadata.dc.description.ppg:	Programa de Pós-Graduação em Geotecnia
Licença::	A concessão da licença deste item refere-se ao termo de autorização impresso assinado pelo autor com as seguintes condições: Na qualidade de titular dos direitos de autor da publicação, autorizo a Universidade de Brasília e o IBICT a disponibilizar por meio dos sites www.unb.br, www.ibict.br, www.ndltd.org sem ressarcimento dos direitos autorais, de acordo com a Lei nº 9610/98, o texto integral da obra supracitada, conforme permissões assinaladas, para fins de leitura, impressão e/ou download, a título de divulgação da produção científica brasileira, a partir desta data.
Appears in Collections:	Teses, dissertações e produtos pós-doutorado

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.