Using spatial reliability in the probabilistic study of concrete structures: The example of a reinforced concrete beam subjected to carbonatation inducing corrosion

Defaux, Gilles; Pendola, Maurice; Sudret, Bruno

doi:10.1051/jp4:2006136025

Cited by 5 publications

(2 citation statements)

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“…The probabilistic analysis for the civil structures and building has been the focus of a number of research efforts (Jones et al, 2002;Lee and Mosalam, 2006;Defaux et al, 2006). Several studies were also conducted concentrating on durability analysis of RC structures using computational approaches such as the Monte Carlo simulation.…”

Section: Overview Of Methodologymentioning

confidence: 99%

“…However, few research efforts considered the spatial variation of random variables of the RC structures, which requires the identification of the correlation characteristics of random variables which have effects on concrete. Because of the nature of RC construction and stochastic environmental nature, it is recognized that the spatial variation of material, geometrical properties, and environmental factors are needed to be considered for reliable estimates of the deterioration of the RC structures (Stewart and Mullard, 2006;Defaux et al, 2006;Capra et al, 2006).…”

Section: Overview Of Methodologymentioning

confidence: 99%

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Stochastic model for service life prediction of RC structures exposed to carbonation using random field simulation

Na¹,

Kwon

Chaudhuri

et al. 2011

KSCE J Civ Eng

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Deterioration of Reinforced Concrete (RC) structures is related to the corrosion of reinforcement since it propagates to structural degradation. In urban or underground conditions, carbonation-initiated corrosion in reinforcement is reported. In this paper, a stochastic model for predicting service life of RC structure subjected to carbonation is proposed through Monte Carlo simulation method with the spatial variation of material, geometric properties of RC structures, and environmental factors. This model can take into account the spatial variation of uncertain parameters by generating non-Gaussian and multi-dimensional random fields using spectral representation method. To estimate the temporal variation of the probability to exceed a pre-defined serviceability, timedependent reliability analyses are performed. Spatial reliability indicators such as the mean and standard deviation of the area are calculated through 20-sample with 4-variable full-factorial realization. It is evaluated that there exists large variation in predicted service life and quality control for concrete is required during construction for the service life. Based on these results, design and construction considerations are provided.

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Section: Overview Of Methodologymentioning

confidence: 99%

Section: Overview Of Methodologymentioning

confidence: 99%