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Total loads modeling and geological adaptability analysis for mixed soil-rock tunnel boring machines

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摘要 Rock-soil interface mixed ground(RSI)is often encountered in tunnel construction.The excavation loads of tunnel boring machines(TBMs)are controlled by the interaction characteristics between TBM and rock/soil layers.The different properties of rock and soil cause the varying interaction range and stress distribution.Currently,there have been several studies available to estimate excavation loads under RSI,and the conclusion is that the total loads increase with increasing the rock layer proportion in the excavation face.However,the previous studies cannot take the difference of rock/soil properties into account,except for the calculation of cutters loads.Therefore,the interaction characteristics between RSI and TBM is unclear.This paper analyzes the interaction characteristics between TBM’s main components and complex geological conditions(e.g.,layered soil,layered rock,and RSI condition).A model is proposed to calculate the total thrust and total torque assuming quasi-static equilibrium of the tunneling equipment.The rationality and applicability of the model are discussed and verified by two typical projects.Furthermore,the geological adaptability is discussed in terms of the excavation difficulty and the matching relationship between total torque and total thrust.The results indicate that when the rock layer proportion in the excavation face increases,the reduction of overall extrusion and friction loads is 1.5 times higher than the increase of disc cutters breaking load.The total loads and the ratio of the total torque to total thrust decrease approximately linearly.There is a power function relationship between the excavation difficulty index and the penetration depth.The results of this study provide an important reference for the total loads design of equipment propulsion systems and the parameter adjustment during tunnel construction.
出处 《Underground Space》 SCIE EI 2022年第3期337-351,共15页 地下空间(英文)
基金 funded by National Key R&D Program of China[No.2018YFB1702505] National Natural Science Foundation of China[Grant Nos.12022205 and 11872269].
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