Caracterização do rejeito de minério de ferro (IOT) e avaliação da sua influência no comportamento físico-químico e mecânico de pastas de cimento

• Ano de defesa: 2017
• Autor(a) principal: Bezerra, Carolina Goulart
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal do Rio de Janeiro; Brasil; Instituto Alberto Luiz Coimbra de Pós-Graduação e Pesquisa de Engenharia; Programa de Pós-Graduação em Engenharia Civil; UFRJ
• Palavras-chave em Português: Engenharia civil; Rejeito de minério de ferro; Pastas de cimento; CNPQ::ENGENHARIAS::ENGENHARIA CIVIL
• Link de acesso: http://hdl.handle.net/11422/9756

The use of mining wastes in another productive chain is a sustainable way of minimizing the environmental damages caused by the mining activity. Civil construction, by consuming large quantities of natural materials, emerges as a potential alternative for the use of these wastes. The present work aims to characterize the iron ore tailings (IOT) sludge from the Conceição/ MG dam, and to evaluate the physicochemical and mechanical behavior of cement pastes were produced with water: solid ratio of 0.45 and 0.65 and cement substitution (by mass) for IOT sludge of 0, 5, 10 and 15% (solids content). In addition, the influence of the drying of the IOT before its addition the mixture was evaluated. The IOT was characterized by granulometry, density, moisture / solids content, chemical and mineralogical composition, micrographs and thermoanalysis. In the pastes, the hydration kinetics, rheology, and physical and mechanical behavior were evaluated. The results indicated that the increase in IOT content accelerated the hydration reactions and reduced the workability of the pastes. The mechanical behavior at a few ages (3 and 7 days) was not altered by the presence of up to 10% IOT in the mixtures. For the ages of 28 and 90 days there was a small reduction of strength with the increase of IOT content used. The segregation, density and voids index were little affected by the IOT contents used (differences below 5%).