Coarse aggregate in concrete is basically free from sulfate corrosion. If the influence of the coarse aggregate in the concrete is not eliminated, the change amount of the concrete ultrasonic pulse velocity value is directly used to evaluate the damage degree of sulfate corrosion in the concrete, and the results are often inaccurate. This paper presents an evaluation method of corrosion damage for the sulfate-attacked concrete by CT, ultrasonic velocity testing and AHP methods. CT was used to extract the coarse aggregate information in the specimen, and the proportion of coarse aggregate on the ultrasonic test line was calculated based on CT image analysis. Then, the correction value of ultrasonic pulse velocity (UPV) of the concrete structure was calculated, and the sulfate corrosion degree of concrete structure was evaluated using the analytic hierarchy process (AHP). The results show that the evaluation method proposed in this paper could more accurately evaluate the corrosion damage in the sulfate-attacked concrete structures, and the evaluation results were more in line with reality.

Sulfate erosion is a major cause of concrete durability deteriorations, especially for the service tunnels that suffer sulfate erosion for a long time. Accurately predicting the concrete damage failure under sulfate erosion has been a challenging problem in the evaluation and maintenance of concrete structures. Here we design the dry–wet cycle test of service tunnel concrete under sulfate erosion and analyze the Elastic relative dynamic modulus (Erd) and mass under 35 times cycle periods. Then we develop an autoregressive integrated moving average (ARIMA) prediction model linking damage failure to Erd and mass. The results show that the deterioration of concrete first increased and then decreased with an extension of the dry–wet cycle period. Moreover, based on a finite set of training data, the proposed prediction approach shows high accuracy for the changes of concrete damage failure parameters in or out of the training dataset. The ARIMA method is proven to be feasible and efficient for predicting the concrete damage failure of service tunnels under sulfate erosion for a long time.

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In order to study the protection performance of silane coating on in-service concrete structures in a sulfate environment, we collect concrete samples in the field to simulate the concrete erosion process by accelerated erosion with wetting–drying cycles. We place the samples into protected, exposed and control groups corresponding to a corrosive environment with silane protection, corrosive environment without protection and general environment for three different service conditions. A combination of ultrasonic velocimetry, CT (Computed Tomography) scan imaging, NMR (Nuclear Magnetic Resonance) pore structure analysis, strength testing and other methods are used to analyze the strength, ultrasonic wave velocity, pore structure and other characteristics of the specimens during sulfate erosion. Based on the test results, the protective effect of silane coating on concrete structures under sulfate attack is quantitatively analyzed, and an index for judging the damage rate of specimens is proposed to quantitatively analyze the protective effect of silane coating. The research results show that the damage of the concrete structure under silane protection in a sulfate-attack environment can be reduced by more than 50%; its integrity damage index and strength damage index are easily affected by the location of local defects, which leads to a decrease in the protection efficiency of the surface silane coating.

Sulfate erosion is a major cause of concrete durability deteriorations, especially for the service tunnels which are in sulfate erosion for a long time. Accurately predicting the concrete damage failure under sulfate erosion has been a challenging problem in the evaluation and maintenance of concrete structures. Here we design the dry-wet cycle test of service tunnel concrete under sulfate erosion, and analyze the Elastic relative dynamic modulus(Erd) and mass under 35 times cycle periods. Then we develop an autoregressive integrated moving average (ARIMA) prediction model linking damage failure to Erd and mass. The results show that the deterioration of concrete first increased and then decreased with an extension of the dry–wet cycle period. Moreover, based on a finite set of training data, the proposed prediction approach shows high accuracy for the changes of concrete damage failure parameters in or out of the training dataset. The ARIMA method is proven to be feasible and efficient for predicting the concrete damage failure of service tunnel under sulfate erosion for a long time.