Logo PUC-Rio Logo Maxwell
ETDs @PUC-Rio
Estatística
Título: PORE NETWORK MODELING OF IRON ORE AGGLOMERATES: DEVELOPMENT OF A METHODOLOGY BASED ON X-RAY MICROTOMOGRAPHY
Autor: IGOR NOGUEIRA LIMA
Colaborador(es): SIDNEI PACIORNIK - Orientador
KAREN SOARES AUGUSTO - Coorientador
Catalogação: 19/OUT/2023 Língua(s): PORTUGUESE - BRAZIL
Tipo: TEXT Subtipo: THESIS
Notas: [pt] Todos os dados constantes dos documentos são de inteira responsabilidade de seus autores. Os dados utilizados nas descrições dos documentos estão em conformidade com os sistemas da administração da PUC-Rio.
[en] All data contained in the documents are the sole responsibility of the authors. The data used in the descriptions of the documents are in conformity with the systems of the administration of PUC-Rio.
Referência(s): [pt] https://www.maxwell.vrac.puc-rio.br/projetosEspeciais/ETDs/consultas/conteudo.php?strSecao=resultado&nrSeq=64365&idi=1
[en] https://www.maxwell.vrac.puc-rio.br/projetosEspeciais/ETDs/consultas/conteudo.php?strSecao=resultado&nrSeq=64365&idi=2
DOI: https://doi.org/10.17771/PUCRio.acad.64365
Resumo:
One of the most relevant features of iron ore agglomerates is their porosity, which strongly impacts the performance of these materials in steelmaking processes. Performance is directly dependent on the existence of a porous network that allows gas flow through the interior of these agglomerates without compromising their physical integrity. This study characterized samples of different iron ore agglomerates using X-ray microcomputed tomography (microCT), digital image processing, and pore network modeling (PNM). The influence of the microstructure of these agglomerates on the variation of their porosity and permeability was evaluated. MicroCT enabled a 3D visualization of the agglomerate structure, allowing for an analysis of the internal structure of the samples to discriminate the porous space. The ideal pixel size was determined through various captures at different resolutions. PNM was used to simulate the absolute permeability of the samples, correlating it with porosity, pore connectivity, and pore and connection diameter. A variation of more or less 5 gray tones in the segmentation thresholds was performed to determine the sensitivity of this parameter s impact on the modeling results. The two agglomerates had similar porosity of around 20 percent. The results for lower resolutions showed inconsistency, with many cases lacking permeability altogether. Images acquired with a pixel size of 2 micrometers resulted in consistent permeability calculations, ranging from 0.4 to 2.4 mD for briquettes and 0.03 to 1.6 mD for pellets, indicating that briquettes are slightly more permeable. The variation of pore segmentation threshold had a strong impact on the modeling results, directly influencing the value of the absolute permeability calculation.
Descrição: Arquivo:   
COMPLETE PDF