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Soda residue soil (SRS) is a man-made engineering foundation soil formed by soda residue; it is mainly distributed in coastal areas in China. SRS is rich in a variety of corrosive salts, among which the concentrations of chloride ions are about 2–3 times that of seawater. These highly concentrated chloride ions migrate and diffuse in reinforced concrete (RC) structures built on coastal SRS through multiple transport mechanisms. However, current research on the durability of RC structures exposed to the coastal SRS environment has not led to the publication of any reports in the literature. SRS may be classified by analyzing the quantitative relationships among the corrosive ions it contains. In this paper, the deterioration of RC structures due to the corrosive saline-soil environment in China is discussed, and advances in RC structure durability under such circumstances are reviewed. Our findings show that a corrosive environment, especially when this is a result of coastal SRS, has a significant influence on the deterioration of RC structures, greatly threatening such buildings. A series of effective measures for enhancing the durability of RC structures in saline soil, including improvements in concrete strength, reductions in the water–binder ratio, the addition of mineral admixtures and fiber-reinforcing agents, etc., could provide a vital foundation for enhancing the durability of RC structures which are at risk due to coastal SRS. Vital issues that must be investigated regarding the durability of RC structures are proposed, including the transport mechanism and a prediction model of corrosive ions, dominated by chloride ions (Cl−), in SRS and RC structures, the deterioration mechanism of RC materials, a long-term performance deduction process of RC components, durability design theory, and effective performance enhancement measures. The findings of this paper provide some clear exploration directions for the development of basic theories regarding RC structure durability in coastal SRS environments and go some way to making up for the research gap regarding RC structure durability under corrosive soil environments.

The corrosion of reinforcement induced by chloride ions is one of the most significant causes of durability deterioration for reinforced concrete (RC) buildings. The concrete material factors, including the water-to-cement ratio (w/c) of concrete, as well as the content, shape, particle grading, and random distribution of coarse aggregate embedded in mortar, have a marked effect on chloride transport performance within concrete. However, comprehensive consideration for the effects of both w/c and coarse aggregate performances on chloride diffusion characteristics in concrete is scarce, especially regarding the chloride diffusion model of concrete. In this paper, an indoor exposure experiment exploring chloride ions intruding into mortar and concrete specimens with w/c = 0.4, 0.5 and 0.6 was carried out, in order to acquire the chloride diffusion parameters for concrete three-phases composites. Based on the numerical algorithm of random generation and placement of two-dimensional random convex polygon coarse aggregate, mesoscopic numerical models for concrete, considering various coarse aggregate contents as well as grading, were established. Using the numerical simulation method of finite element analysis for chloride transport in cement-based materials, which can replace some of the exposure tests, the influences of w/c, coarse aggregate content and grading on chloride diffusion performance in concrete mesoscopic models were systematically probed. According to the Fick’s second law, a chloride diffusion model by the consideration of w/c, volume fraction of coarse aggregate (VFCA), and maximum size of coarse aggregate (MSCA) was developed to assess the chloride concentration profiles in concrete under arbitrary w/c, coarse aggregate content, and coarse aggregate grading conditions. Certainly, the precision accuracy for this proposed chloride diffusion model was validated. The research results can provide theoretical support for chloride erosion behavior and structural durability assessment of concrete with different mix proportions.

Chloride ions are generally considered one of the most significant factors in the corrosion of steel bars in reinforced concrete (RC) structures exposed to alternate drying-wetting marine environments. When RC structures are exposed to cyclic drying-wetting conditions, such as in the marine tidal zone, the chloride concentration distributions in RC structures along the elevation direction changes due to the influence of various drying-wetting ratios. In the study presented here, an indoor exposure experiment for chloride transport in concrete specimens under different conditions of drying-wetting ratios is employed to explore the chloride concentration distributions along the elevation of an RC structure. The elevation related to the peak value of the chloride concentration, which corresponds to the most unfavourable drying-wetting ratio for the RC structure, is determined. On the basis of the tested chloride concentration results, the variation of the time-dependent models of surface chloride concentration and apparent chloride diffusion coefficient with elevation are established for an RC structure. Furthermore, an empirical model of chloride diffusion based on Fick’s second law is developed and adopted to predict the chloride concentrations in concrete at an arbitrary elevation and exposure time. The accuracy of this prediction model of chloride diffusion is validated in terms of the experimental chloride measurements.

Chloride ingression into reinforced concrete (RC) is currently considered an important reason behind the deterioration of RC structures exposed to aggressive environments. Previous studies have been mostly devoted to investigations on the one-dimensional transport characteristics of chloride in concrete; however, for the RC structures exposed to marine environment, the corners and edges of various components are often subjected to two-dimensional chloride penetration. Moreover, concrete is generally considered a typical heterogeneous material because of its coarse aggregate being randomly distributed in a cement paste. Both the two-dimensional chloride diffusion behaviour and the heterogeneity of concrete materials have large influences on the chloride concentration distribution in concrete. For the investigations in this paper, using the coarse aggregate volume fraction (CAVF) to quantify the heterogeneity of concrete materials, an indoor experiment for exploring the two-dimensional chloride diffusion behavior of concrete under real-time tidal cycles in a marine environment was carried out. The two-dimensional chloride diffusion concentrations within concrete specimens cast using different CAVFs of Vca = 0, 0.2, 0.3, 0.4, and 0.5 were tested at various exposure periods of t = 30, 70, 100, 140, and 180 days. The decreased percentages for the tested two-dimensional chloride diffusion concentrations increased with increasing CAVF, and the percentage values decreased from −4.95%, −5.22%, −6.29%, and −7.46% to −65.52%, −73.68%, −91.56%, and −97.22% for Vca = 0.2, 0.3, 0.4, and 0.5 in relation to Vca = 0 in the diagonal sample holes of the concrete specimens, respectively. The quantitative influence of Vca = 0.5 on the two-dimensional chloride diffusivity showed an average reduction of approximately 50.79% for each exposure period in relation to the specimen values for Vca = 0. On the basis of the two impact factors related to the exposure period (If (t)) and the CAVF (If (Vca)), a time-dependent model for predicting the two-dimensional chloride diffusion concentration in concrete by accounting for the heterogeneity of concrete materials was developed and compared with those determined by the meso-scopic numerical simulation method and physical experiment. The comparisons exhibited that the two-dimensional chloride concentrations assessed by the model and numerical simulation were almost within a ±20% error margin, validating the accuracy, correctness and reasonability of the prediction model developed in this paper.