Numerical Modeling of Tunnel Excavation in Rock Mass

Numerical modelling of tunnel excavation in rock mass encompasses a suite of computational techniques designed to predict the mechanical and hydro‐mechanical response of geological media under excavation. By discretising rock masses into finite elements, discrete particles or hybrid meshes, engineers simulate stress redistribution, deformation patterns and failure mechanisms around underground openings. Constitutive models capture rock anisotropy, nonlinearity and jointed fabric, while coupled flow–mechanics formulations reproduce pore‐pressure evolution and rock‐support interaction. High‐performance computing now enables three‐dimensional, time‐dependent simulations of complex sequences such as sequential tunnel faces, cross passages and shaft connections. Integration with monitoring data—from convergence measurements to microseismicity—permits real‐time model calibration and risk assessment. Practical applications range from metro tunnelling in weak urban grounds to deep mining shafts in high‐stress regimes. Recent advances include machine learning–assisted parameter inversion, multi‐physics coupling and digital twin frameworks that promise more reliable support design, optimised excavation strategies and enhanced safety for critical underground infrastructure worldwide.

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Numerical Modeling of Tunnel Excavation in Rock Mass publication trend

The graph below shows the total number of articles in numerical modeling of tunnel excavation in rock mass across all publications each year (not limited to Nature Index journals).

Technical terms

Finite element method (FEM): A numerical technique that divides a continuum into discrete elements to solve boundary value problems in mechanics.

True‐triaxial stress path: A stress‐control history in which all three principal stresses vary independently to replicate in situ loading during excavation.

Plastic zone: The region around an excavation where rock has yielded and undergone irreversible deformation beyond its elastic limit.

Numerical simulation: Computational replication of physical processes through discretised mathematical models to predict system behaviour.

Long short‐term memory (LSTM) network: A recurrent neural network architecture capable of learning long‐range dependencies in sequential data for prediction tasks.

Acoustic emission (AE): Elastic waves generated by sudden micro‐crack growth or stress redistributions within a material under load.

References

1. Using true-triaxial stress path to simulate excavation-induced rock damage: a case study. International Journal of Coal Science & Technology (2022).
2. Construction Method Optimization for Transfer Section Between Cross Passage and Main Tunnel of Metro Station. Frontiers in Earth Science (2022).
3. Deep Learning Method on Deformation Prediction for Large-Section Tunnels. Symmetry (2022).