Concrete Corrosion and Durability
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Abstract
Abstract
External sulfate attack is a major durability threat to reinforced concrete structures. However, unlike carbonation- and chloride-induced deterioration, reliability-based service-life prediction methods for sulfate attack remain largely unavailable. To address this gap, this study proposes a probabilistic durability and structural reliability framework by extending a previously established deterministic failure-thickness model into a stochastic deterioration model. Experimental data together with approximately 14,000 chemo-diffusion-mechanical (CDM) simulation results are used to characterize the statistical properties of sulfate-induced failure thickness. A model uncertainty factor is introduced to quantify the discrepancy between the analytical model and CDM simulations, thereby establishing a stochastic prediction model for failure-thickness evolution. A sulfate-specific durability limit state is formulated by linking corrosion initiation to the evolution of failure thickness relative to the effective concrete cover depth. Analytical reliability analysis is subsequently employed to evaluate the time-dependent reliability evolution and service life under different sulfate concentrations and cover depths. The framework is further extended to structural performance assessment by incorporating reinforcement corrosion and time-dependent resistance degradation. The results show that increasing sulfate concentration significantly shortens the predicted service life, whereas increasing concrete cover thickness significantly extends the predicted service life. Sensitivity analyses indicate that the sulfate-attack residual depth has the greatest influence on service-life prediction, while the calibrated model uncertainty has only a limited effect, demonstrating the robustness of the proposed framework. The proposed framework provides a probabilistic basis for reliability-based durability design, service-life prediction, and life-cycle management of reinforced concrete structures exposed to sulfate environments.
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@article{Qin2026Probabilistic,
title = {Probabilistic modeling and reliability-based service life prediction of sulfate-attacked concrete},
author = {Shanshan Qin and M Zhang and Baojun Zhao and Tiejun Liu and Dujian Zou},
journal = {Construction and Building Materials},
year = {2026},
doi = {10.1016/j.conbuildmat.2026.147338},
url = {https://doi.org/10.1016/j.conbuildmat.2026.147338}
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