Abstract Predicting surrounding rock deformation in fault zones has been much debated in observation-based tunnel construction and management, but so far a scientific and rational method for this sort of prediction is lacking. For NATM tunnelling, surrounding rock deformation is often used as an important indicator to judge the stability of a tunnel and the economic rationality of the supporting structure. As surrounding rock deformation is a kind of series varying with time, a prediction model is established to trace and predict deformation in real time. Considering the large deformation rate of the surrounding rock around the Daxiangling Tunnel on the Ya'an-Xichang expressway, a BP artificial neural network based genetic algorithm is introduced, improving prediction accuracy by modifying the basic genetic algorithm. Using GA-BP neural network techniques, a comprehensive model to predict rock deformation in a fractured fault zone is established and applied to the Daxiangling tunnel, and the predicted results are verified to be accurate and reliable.
Abstract：
Predicting surrounding rock deformation in fault zones has been much debated in observation-based tunnel construction and management, but so far a scientific and rational method for this sort of prediction is lacking. For NATM tunnelling, surrounding rock deformation is often used as an important indicator to judge the stability of a tunnel and the economic rationality of the supporting structure. As surrounding rock deformation is a kind of series varying with time, a prediction model is established to trace and predict deformation in real time. Considering the large deformation rate of the surrounding rock around the Daxiangling Tunnel on the Ya'an-Xichang expressway, a BP artificial neural network based genetic algorithm is introduced, improving prediction accuracy by modifying the basic genetic algorithm. Using GA-BP neural network techniques, a comprehensive model to predict rock deformation in a fractured fault zone is established and applied to the Daxiangling tunnel, and the predicted results are verified to be accurate and reliable.
ZHANG Zhi-Qiang,
LI Hua-Yun,
HAN etc
.Prediction of Surrounding Rock Deformation of the Daxiangling Tunnel
in Fault Zones Using the GA-BP Nerve Network Technique
[J] MODERN TUNNELLING TECHNOLOGY, 2014,V51(2): 83-89
2014, Vol. 51 