摘要
Salt cavern energy storage technology contributes to energy reserves and renewable energy scale-up.This study focuses on salt cavern gas storage in Jintan to assess the long-term stability of its surrounding rock under frequent operation.The fatigue test results indicate that stress holding significantly reduces fatigue life,with the magnitude of stress level outweighing the duration of holding time in determining peak strain.Employing a machine learning approach,the impact of various factors on fatigue life and peak strain was quantified,revealing that higher stress limits and stress holding adversely impact the fatigue index,whereas lower stress limits and rate exhibit a positive effect.A novel fatigue-creep composite damage constitutive model is constructed,which is able to consider stress magnitude,rate,and stress holding.The model,validated through multi-path tests,accurately captures the elasto-viscous behavior of salt rock during loading,unloading,and stress holding.Sensitivity analysis further reveals the time-and stress-dependent behavior of model parameters,clarifying that strain changes stem not only from stress variations but are also influenced by alterations in elasto-viscous parameters.This study provides a new method for the mechanical assessment of salt cavern gas storage surrounding rocks.
基金
supported by the National Natural Science Foundation of China(Nos.52374078,U24A20616 and 52074043)
the Sichuan-Chongqing Science and Technology Innovation Cooperation Program Project(No.2024TIAD-CYKJCXX0011)
the Fundamental Research Funds for the Central Universities(No.2023CDJKYJH021)。
