Abstract：Deep rock masses are situated in a complex environment characterized by high ground stress and elevated water pressure. Under repeated blasting disturbances, these rock masses are prone to inducing water inrush disasters. However, research on the effects of water pressure on the strength degradation characteristics of rock remains limited, resulting in a lag of relevant theoretical studies behind engineering practices. In this context, a self-developed dynamic test system has been employed to conduct cyclic impact tests on red sandstone under hydro-mechanical coupling conditions. Based on the test results, the evolution of dynamic peak stress, dynamic degradation coefficient, dynamic intensity factor (DIF), and damage variable with cyclic impacts has been analyzed. Additionally, dynamic damage accumulation and fatigue life models for rocks subjected to hydro-mechanical coupling conditions have been established to explore the mechanisms by which hydro-mechanical coupling affects strength degradation. This research aims to elucidate the mechanisms behind water inrush disasters in deep rock mass engineering and to enhance the safety resilience of such projects. Key findings are as follows: both the dynamic peak stress and DIF of rock under hydro-mechanical coupling conditions exhibit accelerated decreasing trends, while the dynamic degradation coefficient and damage variable increase rapidly, demonstrating distinct strength degradation characteristics. When the number of cyclic impacts approaches 50% of its fatigue life, the growth rate of the dynamic degradation coefficient spikes, resulting in an “accelerated deterioration phenomenon”. Water pressure mitigates the rate of change of dynamic peak stress, DIF, dynamic degradation coefficient, and damage variable in rock, thereby attenuating the “accelerated deterioration phenomenon” and prolonging fatigue life. Conversely, axial static stress increases the rate of change of these parameters, intensifying the accelerated deterioration phenomenon and shortening the fatigue life of the rock. The developed fatigue life model for rocks demonstrates an error rate below 16%, accurately predicting the fatigue life of deep rock masses.
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2026, Vol. 45 
