Avaliação probabilística da vida útil de estruturas de concreto armado sujeitas à carbonatação

• Ano de defesa: 2017
• Autor(a) principal: Rafael Arêdes Couto
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal de Minas Gerais; UFMG
• Palavras-chave em Português: Concreto armado; Normalização; Avaliação probabilística; Carbonatação; Durabilidade; Vida útil; Simulação de Monte Carlo; Incertezas; Método de Monte Carlo; Engenharia de estruturas; Incerteza; Durabilidade (Engenharia)
• Link de acesso: http://hdl.handle.net/1843/BUOS-AUWK3J

Current sustainability requirements for the built environment, have posed a great emphasis on the service life prediction of reinforced concrete (RC) structures. Among the degradation mechanisms affecting RC structures, carbonation is one of the main causes of deterioration ofthe steel reinforcement. Considering that the concentration of CO2 in the atmosphere in urban and industrial environments has increased over the last decades, the deterioration of RC structures due to carbonation is a major issue. Additionally, due to the uncertainties in the variables related to the deterioration process, a probabilistic treatment of these uncertainties must be adopted in the service-life prediction of RC structures. In spite of the relevance of this issue, durability of RC structures is treated via prescriptive procedures in most design codes(e.g. ACI 318-14, NBR 6118:2014), i.e. specifying water/cementitious ratio, concrete strength, cover thickness, as a function of the environmental exposure. On the other hand, fib Model Code 2010 has paved the way for more advanced code formats which includesprobabilistic assessment of the service-life of RC structures. While a framework for such probabilistic assessment can be easily envisioned at present, the main difficulties in the implementation of such format arise from the selection of the models to be used in the calculation of the carbonation depht and the statistical description of the attendant variables. In this study, Monte Carlo simulation (MCS) is used for the probabilistic service-life prediction of RC structures, for the limit state of depassivation. Service-life predictions are obtained using three different models for the prediction of the carbonation depth. Different scenarios are assumed for the materials, construction practices and level of CO2 concentration in the atmosphere.