现代隧道技术
現代隧道技術
현대수도기술
MODERN TUNNELLING TECHNOLOGY
2014年
6期
58-65
,共8页
硬岩掘进机%样本数据%模糊聚类理论%围岩分级
硬巖掘進機%樣本數據%模糊聚類理論%圍巖分級
경암굴진궤%양본수거%모호취류이론%위암분급
TBM%Sample data%Fuzzy clustering theory%Classification of surrounding rock cuttability
文章针对硬岩掘进机(TBM)在复杂地质条件下的可掘进性,进行了系统及定量的研究;基于模糊聚类理论和施工样本数据分析,建立了以掘进速率为分级指标,包括岩石单轴抗压强度、岩石完整性系数、围岩结构面与隧道轴线夹角和渗水量四项性质指标的可掘进性分级预测模型,将TBM施工围岩可掘进性分为好、一般和差三个性能等级;并在此基础上进一步细化模型粒度,以提高模型的精度和地质适用性。将所建模型应用于西秦岭隧道和大伙房水库输水隧洞工程实际工程效果表明,TBM掘进速率与由模型预测的掘进速率基本相吻合,验证了掘进性分级预测模型的可行性、科学性和有效性,进而对TBM的选型、设计和施工提供了重要的理论依据。
文章針對硬巖掘進機(TBM)在複雜地質條件下的可掘進性,進行瞭繫統及定量的研究;基于模糊聚類理論和施工樣本數據分析,建立瞭以掘進速率為分級指標,包括巖石單軸抗壓彊度、巖石完整性繫數、圍巖結構麵與隧道軸線夾角和滲水量四項性質指標的可掘進性分級預測模型,將TBM施工圍巖可掘進性分為好、一般和差三箇性能等級;併在此基礎上進一步細化模型粒度,以提高模型的精度和地質適用性。將所建模型應用于西秦嶺隧道和大夥房水庫輸水隧洞工程實際工程效果錶明,TBM掘進速率與由模型預測的掘進速率基本相吻閤,驗證瞭掘進性分級預測模型的可行性、科學性和有效性,進而對TBM的選型、設計和施工提供瞭重要的理論依據。
문장침대경암굴진궤(TBM)재복잡지질조건하적가굴진성,진행료계통급정량적연구;기우모호취류이론화시공양본수거분석,건립료이굴진속솔위분급지표,포괄암석단축항압강도、암석완정성계수、위암결구면여수도축선협각화삼수량사항성질지표적가굴진성분급예측모형,장TBM시공위암가굴진성분위호、일반화차삼개성능등급;병재차기출상진일보세화모형립도,이제고모형적정도화지질괄용성。장소건모형응용우서진령수도화대화방수고수수수동공정실제공정효과표명,TBM굴진속솔여유모형예측적굴진속솔기본상문합,험증료굴진성분급예측모형적가행성、과학성화유효성,진이대TBM적선형、설계화시공제공료중요적이론의거。
In this paper, systematic and quantitative studies are carried out regarding rock cuttability by a TBM under complex geological conditions. Based on the fuzzy clustering theory and construction sample analysis, a rock cuttability classification prediction model is established by using the rate of penetration (ROP) as a basic index. The ROP is related to four property indexes: rock uniaxial compressive strength, rock integrity coefficient, the angle between the rock structural plane and the tunnel axis, and water seepage. In the prediction model, the rock mass cuttability is classified into three levels: good, moderate, and poor. Furthermore the prediction model is refined to improve model precision and geological applicability. According to the prediction results for the West Qinling tunnel and the Dahuofang water conveyance tunnel projects, the ROP of the TBM basically agrees with that of the prediction model, proving the feasibility, scientific soundness, and availability of the rock cuttability classification prediction model and providing a basis for the selection, design, and construction of the TBM.