Exploring the short-term water damage characteristics of asphalt mixtures: The combined effect of salt erosion and dynamic water scouring

Abstract

In icy or snowy conditions, improper application and uneven dispersion of deicing salts on roadways can lead to saltwater accumulation, subsequently causing roadway scouring when vehicles transit. This study aims to assess the combined influence of salt erosion and dynamic water scouring on short-term water damage of asphalt mixtures. A custom-designed dynamic water scouring simulation apparatus is used, employing three diverse deicing salt solutions as agents for dynamic water scouring. Numerous iterations of dynamic water scouring tests are conducted on two types of graded asphalt mixtures. Post-scouring, alterations in air void content and water stability are evaluated through void content tests, Marshall water immersion tests, and freeze-thaw splitting tests. Additionally, the GM (1,N) damage prediction model from gray theory is applied for data modeling and prediction. The results reveal a significant impact of the combined effects of salt erosion and dynamic water scouring on the short-term performance of asphalt mixtures. In the early phase, dynamic water scouring primarily influences the asphalt composite, augmenting micro-cracks and causing aggregate disintegration. The intermediate phase sees the disintegration of the asphalt membrane by deicing salts, disrupting adhesion between asphalt and aggregate, and progressively leading to the emergence of new micro-cracks. During later stages, dynamic water scouring continues to deteriorate the asphalt composite, building on the erosion instigated by deicing salts, resulting in the expansion of newly formed micro-cracks and further aggregate disintegration. Among the three deicing salts, CH4N2O exhibits the most pronounced impact on short-term water damage, followed by NaCl, while CH2CH3OH has the least effect. Increasing the fine aggregate proportion in the asphalt mixture enhances water damage resistance. The GM (1,N) damage prediction model effectively anticipates air void content and water stability of asphalt mixtures. The research outcomes offer theoretical and technical support for understanding the durability and service lifespan of asphalt pavements in cold regions.