Abstract
Degradation of performance and deterioration of different components of reinforced concrete (RC) structures increase with the age of structure. This deterioration of reinforced component depends on several parameters. However, modeling service life of RC structure by considering all the parameters is a difficult job, as most of the parameters are uncertain in nature. Probabilistic models account well for the uncertainties in the parameters responsible for deterioration of RC structures. This paper presents a review of several recent service life models developed using probability based concepts.
Highlights
Performance and service life of a reinforced concrete (RC) structure are governed by several parameters such as strength, quality of concrete, concrete cover, age, and most significantly by exposure conditions
Present paper reviewed several probability based service life models developed by researchers for evaluating the probability of failure and estimating the residual life of RC structures
In most of the above models, service life of RC structures is divided in different phases
Summary
Performance and service life of a RC structure are governed by several parameters such as strength, quality of concrete, concrete cover, age, and most significantly by exposure conditions. Because of random nature of the parameters governing the performance of RC structures, probabilistic approach is better to develop reliable service life prediction model. Probabilistic models calibrated with monitored field data can provide more reliable models to predict the probabilities of corrosion. This category includes models based on probability or statistical concepts such as probability function, reliability based models, Monte Carlo simulation, Markov chain methods, and fuzzy logic. Present paper reviewed several probability based service life models developed by researchers for evaluating the probability of failure and estimating the residual life of RC structures
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