Stochastic Modeling of Service Life of Concrete Structures in Chloride-Laden Environments
by Yajun Liu, Ph.D., (Research Scientist, Corrosion & Sustainable Infrastructure Laboratory, Western Transportation Institute, Montana State Univ., P.O. Box 174250, Bozeman, MT 59717-4250.) and Xianming Shi, Ph.D., P.E., (corresponding author), (Associate Research Professor, Civil Engineering Dept., Montana State Univ., 205 Cobleigh Hall, MT State Univ., Bozeman, MT 59717-3900; Program Manager, Corrosion & Sustainable Infrastructure Laboratory, Western Transportation Institute, Montana State Univ., P.O. Box 174250, Bozeman, MT 59717-4250. E-mail: xianming_s@coe.montana.edu)
Journal of Materials in Civil Engineering, Vol. 24, No. 4, April 2012, pp. 381-390, (doi: http://dx.doi.org/10.1061/(ASCE)MT.1943-5533.0000399)
Access full text
Purchase Subscription
Permissions for Reuse 
| Document type: |
Journal Paper |
| Abstract: |
Chloride-induced rebar corrosion is a common degradation process for concrete infrastructure, which is a practical concern for cold-climate states and coastal areas. In this work, numeric models based on the FEM are utilized to study service life of concrete structures subject to chloride ingress, where two models are utilized. The first one deals with multiple ionic species in the concrete pore solution, while the second one only accounts for the presence of chloride ions. The stochastic nature of model inputs is taken into consideration because each factor of interest is subject to random variabilities and inherent uncertainties. Specifically, the surface chloride concentrations and concrete cover depth follow the normal distribution; the diffusion coefficients obey the gamma distribution; the actual chloride threshold features the triangular distribution. The nonlinear partial differential equations (PDEs) to characterize the spatial and temporal evolution of ionic species are numerically solved, the results of which were utilized to elucidate the influence of various factors on concrete service life, such as mix design, surface chloride concentrations, cracking level, and coarse aggregate and concrete cover depth. |
| Author Keywords: | 
| Finite-element method |
| Service life prediction |
| Stochastic modeling |
| Chloride diffusion |
| Mineral admixtures |
| Reinforced concrete |
|
