Study on the multi-source response characteristics and damage evolution mechanisms of graphene-modified concrete

In deep underground engineering, lining concrete structures in underground gas storage facilities are exposed to prolonged high in-situ stress and intense disturbances, which increase their susceptibility to progressive damage and sudden instability-induced failures. The mechanisms of damage evolution and the associated precursor responses prior to failure require systematic investigation. Rock mechanics experiments were conducted to comprehensively analyze the mechanical response, resistivity variation, acoustic emission parameters, strain field evolution, and underlying microscopic mechanisms of graphene-modified concrete. The results show that, under specific aggregate proportions and graphene dosages of 0.05% and 0.1% by cement mass, the compressive strength of concrete after 28 days of curing increased by 18.27-60.27%. The resistivity response exhibited a three-stage evolution ("rapid decrease-stable variation-abrupt increase"), with a total reduction exceeding 90%. A rebound of 20-30% occurred in the elastic-plastic transition zone, consistent with the stress-strain relationship. The b-value exhibits a continuous decreasing trend at approximately 90% of σ_max, indicating the transition from stable crack propagation to unstable crack coalescence. RA/AF and DIC analyses demonstrate that graphene promotes crack evolution from tension-dominated to tension-shear coupled modes, leading to a transition in failure behavior from brittle to progressive. Microscopic analysis reveals that graphene nanosheets fill micro and nanopores and reinforce the interfacial transition zone, thereby inhibiting crack propagation and enhancing failure stability. Based on multi-source information synergy, a comprehensive method was developed to characterize load-induced damage evolution and failure precursors in graphene-modified concrete. The study demonstrates that graphene-modified concrete exhibits integrated "load-bearing-sensing" properties, providing theoretical and data support for identifying damage precursors and predicting instability in deep underground lining structures.