Wenbin Xu, Wenbin Xu, Yao Li, Wei Yang, Wenqiang Xu, Wenqiang Xu, Zhenyu Xu, Danni Luo, Juan Wang, Hailong Wang
Roller-compacted concrete (RCC) dam construction occurs under complex and variable environmental conditions, where temperature, humidity, and wind speed markedly influence interlayer bonding quality. Conventional quality control methods mainly rely on casting interval time, neglecting environmental effects on the moisture state of the underlying layer. This can cause discrepancies between actual bonding performance and predicted strength, posing risks to structural safety. To address this issue, this study proposes a moisture-based interlayer strength prediction method grounded in the hydration mechanism and strength development characteristics of concrete. The reliability of the model was validated through systematic measurements of parameters such as evaporated moisture, residual moisture content, and interlayer splitting tensile strength. A practical interlayer strength prediction method was proposed, incorporating standard-condition residual moisture and measured evaporated moisture. The linear fitting accuracy of the practical moisture-strength model reached 0.934, while the quadratic fitting accuracy was as high as 0.982. The study identified the 10–20 mm depth as the critical reaction zone for interlayer strength. By monitoring moisture variations in this zone, the prediction model achieved over 95 % accuracy across different environmental conditions. This method effectively overcomes the limitations of traditional time-based criteria that often lead to inaccurate or large deviations, providing an efficient and practical tool for interlayer quality control and safety assurance of RCC dams constructed under complex climatic conditions. • Proposed a moisture-strength model for RCC interlayer performance with high accuracy. • Identified 10–20 mm depth as the critical zone affecting interlayer strength. • Developed a practical method using residual and evaporated moisture for real-time strength prediction. • Quantified environmental impacts on moisture loss and interlayer bonding quality. • Validated the model in field applications, improving RCC construction control.