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Comprehensive Prediction of Rockburst in High-Speed Railway Tunnel

Applied Mechanics and Materials, 2013
Dayanwan tunnel in Shanghai-Kunming high-speed railway is deeply buried and its rock lithology is brittle and hard. The typical tunnel cross section was selected to do hydraulic fracturing field geostress test. The stress in the measured depth was obtained. In order to forecast the rock burst in the whole tunnel, the finite element inversion method has
Bo Li   +4 more
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A finite element perturbation method for the prediction of rockburst

Computers & Structures, 2007
A finite element model is proposed to predict the potential occurrence of rockburst in underground openings. It is assumed that rockburst results due to instability of rock mass and the analysis is based on a perturbation technique. The rock mass is considered to be elastic-brittle-plastic.
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Rockburst Prediction Using Gaussian Process Machine Learning

2009 International Conference on Computational Intelligence and Software Engineering, 2009
Rockburst is a geological disaster occurred usually in deep mines. Because of poor understanding of the mechanism and influence factors of rockbust, it is very difficult to give accurate prediction using conventional methods. A new model based on Gaussian process (GP), which is a probabilistic kernel machine leaning and has become a power tool for ...
Guo-Shao Su, Ke-Shi Zhang, Zhi Chen
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The study of barrier fracture in relation to earthquake and rockburst prediction

pure and applied geophysics, 1986
One of the simplest models of earthquakes and rockbursts was studied in laboratory conditions in which the fracture was initiated in a barrier between two preexisting faults. The treated models were built of concrete; during the construction of the models, the stress concentrators were inserted inside the models.
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Rockburst prediction

International Journal of Rock Mechanics and Mining Sciences & Geomechanics Abstracts, 1987
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Rockbursts: prediction and control

International Journal of Rock Mechanics and Mining Sciences & Geomechanics Abstracts, 1984
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Combining machine learning and numerical modelling for rockburst prediction

Geomechanics and Geoengineering, 2023
Dimitrios Papadopoulos, Andreas Benardos
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