1998 Fiscal Year Final Research Report Summary
Improvement on efficiency and reliability of Full-Face Tunneling Boring Machine
| Project/Area Number |
09555319
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| Research Category |
Grant-in-Aid for Scientific Research (B)
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| Allocation Type | Single-year Grants |
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| Section | 展開研究 |
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| Research Field |
資源開発工学
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| Research Institution | The University of Tokyo |
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Principal Investigator |
OKUBO Seisuke The University of Tokyo, Graduate School of Engineering, Professor, 大学院・工学系研究科, 教授 (90092155)
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| Co-Investigator(Kenkyū-buntansha) |
AKIYAMA Masao The University of Tokyo, Graduate School of Engineering, Assistant, 大学院・工学系研究科, 助手 (00011172)
FUKUI Katsunori The University of Tokyo, Graduate School of Engineering, Associate Professor, 大学院・工学系研究科, 助教授 (70251361)
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| Project Period (FY) |
1997 – 1998
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| Keywords | TBM / Rock Mass / Strength / bedrock survey / Schmidt-hammer rebound hardness / Thrust / Torque / Reliability |
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| Research Abstract |
At present, various types of tunneling boring machines (TBMs) are widely used as a substitute for conventional tunneling methods. The performance of TBM is potentially far better than that of conventional methods. However, TBM performance is very poor when applied under conditions that are adverse to TBM.Therefore, measuring geological characteristics forward of the face is essential in order to improve the efficiency of TBM.
In the present study, a method for estimating the rock strength of face using TBM cutting force, such as thrust, torque and cutting depth, is proposed. Rock strength along the tunnels is estimated from actual excavation data for sections a few hundred meters in length. The estimated strengths were then compared with those obtained using the bedrock survey and Schmidt-hammer rebound hardness. Estimated rock strengths were found to agree well with those found using these surveys. Moreover, the relationships between rock mass classification and estimated rock strength are discussed. The estimated rock strength was found to be in good agreement with the rock mass classification. Therefore, the proposed method provides a useful method for properly selecting a supporting pattern for rapidly changing rock mass characteristics, thereby preventing accidents and reducing construction time and expense.
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