Creep Parameter Inversion and Long‐Term Stability Analysis of Tunnel Based on GP‐DE Intelligent Algorithm

Zhang, Fengrui; Jiang, Annan; Guo, Xutao; Yang, Xiurong

doi:10.1155/2021/3769474

Cited by 2 publications

(1 citation statement)

References 25 publications

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“…The method was verified with three different types of cases, and the results showed that this method can accurately and quickly obtain hydrogeological parameters. Xu et al [21] and Zhang et al [22] used intelligent parameter inversion analysis by means of depth network optimization algorithm and numerical analysis to realize multi-means coupling inversion to solve complex engineering problems.…”

Section: Intelligent Phasementioning

confidence: 99%

Inversion Analysis Method for Tunnel and Underground Space Engineering: A Short Review

et al. 2023

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With the rise of the fourth industrial revolution, traditional methods of analyzing investment have been transformed into intelligent methods under big data and the Internet of Things. This has created a new approach to solving practical engineering problems. This paper examines the formation and evolution of the application of inversion theory in tunnel and underground engineering, summarizing research progress using traditional and intelligent inversion analysis methods to identify three types of target unknown quantities in tunnels and underground projects: initial ground stress, support structure load, and tunnel characteristic parameters. It also offers an outlook on how to optimize inversion analysis methods to solve more challenging and complex tunneling problems in the context of informatization, digitalization, and intelligence. In the current research process of tunnel and underground space engineering problems, the inversion theory system has been improved, but inversion analysis methods still face many challenges. These include the low reliability of initial ground stress inversion under complex geological conditions, the lack of indicators to objectively evaluate the accuracy of inversion analysis, and the high costs of intelligent inversion analysis means. Moving forward in the context of big data and the information era, the future development direction for inversion theory and inversion methods in tunnel and underground space engineering is to combine new monitoring technology, computer vision technology, and simulation analysis technology to establish multifaceted intelligent inversion analysis models.

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Section: Intelligent Phasementioning

confidence: 99%

Inversion Analysis Method for Tunnel and Underground Space Engineering: A Short Review

et al. 2023

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Nonlinear creep properties and time-to-failure prediction of sandstone under saturated and dry conditions

Xie

et al. 2022

Environ Earth Sci

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The moisture content of rock signi cantly in uences its time-dependent deformation behavior. This paper studied the different properties of the creep behavior of sandstone under saturated and dry conditions and their impact on the time-to-failure(TTF) through multistage creep tests. The results show that under an identical driving stress ratio (not identical creep stress), the dry specimens' creep strain and steadystate creep rate are relatively higher than those of the saturated ones. Nevertheless, the water-saturated specimen has a shorter creep strain path and TTF due to the softening effect of water. It is evident that in terms of creep deformation and creep rate, the impact of creep stress is much more signi cant than that of moisture content; however, in terms of creep TTF, the moisture content of sandstone plays a dominant role. The rationality of the generalized Kelvin, Burgers, and power-law creep models was evaluated based on the experimental data. The power-law model was found to be capable of tting the test data, and better predicting sandstone creep deformation than other two models. Finally, based on the assumption of a critical strain value ε cri , a method for predicting creep TTF from limited laboratory data was proposed, providing a foundation for incorporating TTF prediction into continuum numerical simulations.

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Creep Parameter Inversion and Long‐Term Stability Analysis of Tunnel Based on GP‐DE Intelligent Algorithm

Cited by 2 publications

References 25 publications

Inversion Analysis Method for Tunnel and Underground Space Engineering: A Short Review

Inversion Analysis Method for Tunnel and Underground Space Engineering: A Short Review

Nonlinear creep properties and time-to-failure prediction of sandstone under saturated and dry conditions

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