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Non-Steady Cvisc Creep Model for Rock and Its Parameter Inversion Method
(1. Key Laboratory of Transportation Tunnel Engineering of Ministry of Education，Southwest Jiaotong University，Chengdu 610031；2. National Engineering Research Center of Geological Disaster Prevention Technology in Land Transportation，Southwest Jiaotong University，Chengdu 610031；3. Pipe China Engineering Technology Innovation Co.,Ltd.，Tianjin 300450)
Abstract Rock creep under long-term stress may exhibit three stages: decay creep,steady-state creep, and accelerated creep. The Cvisc model in FLAC 3D software can effectively simulate the decay and steady-state creep stages of rocks but shows significant limitations in describing the accelerated creep stage. To address this, the viscosity coefficient of the Cvisc model was modified to create a non-steady version capable of capturing the characteristics of accelerated creep. A corresponding three-dimensional creep equation was derived.To obtain the creep parameters of the non-steady Cvisc model for surrounding rock, a BP-PSO algorithm-based neural network inversion model was established. This algorithm was validated using monitored vault settlement data from field tunnels. A comparative analysis of the vault settlement prediction performance of the non-steady Cvisc model and the original Cvisc model was conducted.The results demonstrate that the non-steady Cvisc model significantly outperforms the original model in fitting the accelerated creep stage, enabling a more accurate description of the entire creep process, including the accelerated stage.
Abstract：
Rock creep under long-term stress may exhibit three stages: decay creep,steady-state creep, and accelerated creep. The Cvisc model in FLAC 3D software can effectively simulate the decay and steady-state creep stages of rocks but shows significant limitations in describing the accelerated creep stage. To address this, the viscosity coefficient of the Cvisc model was modified to create a non-steady version capable of capturing the characteristics of accelerated creep. A corresponding three-dimensional creep equation was derived.To obtain the creep parameters of the non-steady Cvisc model for surrounding rock, a BP-PSO algorithm-based neural network inversion model was established. This algorithm was validated using monitored vault settlement data from field tunnels. A comparative analysis of the vault settlement prediction performance of the non-steady Cvisc model and the original Cvisc model was conducted.The results demonstrate that the non-steady Cvisc model significantly outperforms the original model in fitting the accelerated creep stage, enabling a more accurate description of the entire creep process, including the accelerated stage.
WANG Yanyan1,
2 SHEN Yusheng1,
2 CHANG Mingyu1 etc
.Non-Steady Cvisc Creep Model for Rock and Its Parameter Inversion Method[J] MODERN TUNNELLING TECHNOLOGY, 2024,V61(6): 9-20
2024, Vol. 61 