Stochastic mesoscale modeling of chloride ingress in coastal concrete structures under climate change

Climate change is intensifying chloride-induced corrosion in marine reinforced concrete (RC) structures, yet conventional durability assessment fails to capture the coupled effects of material heterogeneity, environmental variability, and thermo-hygro-ionic transport. This paper presents a probabilistic framework for service-life durability assessment of marine atmospheric RC structures under climate-change-adjusted boundary conditions, integrating spatially resolved mesoscale chloride transport with stochastic uncertainty quantification through the probability density function-informed method (PDFM). The coupled thermo-hygro-ionic transport equations are solved on a stochastic mesoscale finite element domain that explicitly resolves aggregates, interfacial transition zones, and a stochastic porosity field; PDFM with representative-point sampling replaces crude Monte Carlo simulation at 50–95 times the computational efficiency. Model predictions are validated against a 34-month marine atmospheric exposure test. The coefficient of variation of the local chloride to mean content ratio is 5.7 times higher in the mesoscale model than in a homogenized random-field benchmark, confirming that aggregate topology, rather than parametric randomness, generates the heavy-tailed distribution of local extremes. The homogenized bias in the 50-year corrosion probability exhibits a cover-dependent crossover: macroscale homogenization underestimates risk by 37% at 30 mm cover and overestimates it by a factor of 5.6 at 50 mm cover. Each 10 mm cover increment attenuates the 50-year corrosion probability by approximately one order of magnitude, and the high-warming scenario raises the cover-averaged 50-year corrosion probability by 8.6% relative to the low-emission baseline. The framework provides a computationally tractable route for quantifying chloride ingress and corrosion risk under future warming scenarios.