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Classification of Rock Hardness at Tunnel Faces Based on a Drilling Parameter Cloud Map and Convolutional Neural Network
Publisher: American Society of Civil Engineers
Abstract: Accurately measuring rock hardness at a tunnel face is crucial for evaluating rock mass quality and ensuring construction safety. This study developed a fast and accurate classification method for rock hardness. Firstly, ...
Fusion of Convolution Neural Network and Visual Transformer for Lithology Identification Using Tunnel Face Images
Publisher: American Society of Civil Engineers
Abstract: This study proposes an intelligent method for recognizing the lithology of a tunnel working face by combining a convolutional neural network and visual transformer. First, an efficient method for collecting high-resolution ...
Influence of Pea-Gravel Layer on Segment Ring Support Performance in Shield TBM Tunnels: A Discrete-Continuous Coupling Simulation and Model Test
Publisher: ASCE
Abstract: In shield tunnel boring machine (TBM) tunnel construction, grouted pea gravel is used to fill gaps between the surrounding rock and segment rings, acting as a connecting layer that significantly impacts the support performance ...
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