Avaliação da confiabilidade de seções de vigas de concreto armado em situação de incêndio - Tulio Antunes Pinto Coelho (2018)
Current standards and specifications for the design of reinforced concrete (RC) structures are based on Limit State Methods, i.e. semi-probabilistic methods. In the last decades, much has been developed in terms of the reliability assessment of structural components in RC such as slabs, beams and columns aimed at the calibration of partial factors in semi-probabilistic methods. On the other hand, studies of the reliability of such structural components under fire are practically nonexistent. Due to the unpredictable nature of the fires and the various uncertainties related to the problem (mechanical properties of materials at high temperatures, dimensions, mathematical models employed, etc.), the reliability of the RC structural elements under fire should be investigated. This research aims to present the framework for the reliability analysis of RC structures, in the case of beams, in a fire situation, comprising the concepts, methods, probabilistic description of the relevant variables and definition of the corresponding performance function. As a practical example, the reliability of some beams sections of RC in a fire situation will be evaluated from probabilistic concepts and methods. The probability of failure of beams to a fully developed fire is obtained via Monte Carlo simulation. In these circumstances, the application of the reliability assessment seeks to highlight any deficiencies or shortcomings in the design and constitutes a good basis for the project review in order to satisfy the expected performance requirement. Based on the probabilities of failure found, the low influence of the aggregate type on the probability of failure is observed, the fact that the increase of the steel area, for the same cross section, increases the probability of failure and that the increase of the load ratio culminates in an increase of the probability of failure. Summarizing, it was possible to extract percentages of the influence of each evaluated parameter, serving as reference for later works.