Journal
TUNNELLING AND UNDERGROUND SPACE TECHNOLOGY
Volume 116, Issue -, Pages -Publisher
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.tust.2021.104111
Keywords
Soft rock tunnel; Data envelopment analysis; Efficiency analysis; Normal cloud model; Multi-inputs and multi-outputs system; Classification
Funding
- National Natural Science Foundations of China [41877239, 51379112, 51422904, 40902084, 41772298]
- Key Technology Research and Development Program of Shandong Province [2019GSF111028]
- Fundamental Research Funds of Shandong University [2018JC044]
- Natural Science Foundation of Shandong Province [JQ201513]
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This study establishes a deformation risk assessment system for soft rock tunnels based on twelve main influencing factors and utilizes data envelopment analysis to analyze the efficiency of these factors. A risk assessment model is developed using a normal cloud model and verified with actual deformation cases, confirming its consistency with real deformation risk degrees.
Deformation of the surrounding rock is an anticipated geological hazard when driving tunnels through soft rock. If deformation is not restricted, it can lead to serious engineering safety hazards. Therefore, studying the factors that affect the deformation of soft rock tunnels is highly significant. This study selected twelve main influencing factors involving subjective and objective factors and four actual indexes to establish a deformation risk assessment system for a soft rock tunnel. Data envelopment analysis (DEA) was innovatively utilized to analyze the efficiency of the twelve factors which affect the deformation of soft rock tunnels. The analytical results showed that the water content of the soft rock was the most efficient factor, followed by the tunnel depth, uniaxial compressive strength, excavation method, strength-stress ratio and groundwater seepage condition. A risk assessment model for the deformation of a soft rock tunnel was established using a normal cloud model and verified by the deformation occurred in typical soft rock tunnel cases. Risk assessment results confirmed that the proposed model was consistent with actual deformation risk degree. This model can guidie significance for the assessment of soft rock tunnel engineering.
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