本文關(guān)鍵詞：淺埋隧道開挖巖體移動分析的模糊測度方法　出處：《河北大學》2014年碩士論文　論文類型：學位論文

  更多相關(guān)文章： 山區(qū)淺埋隧道 巖體移動變形 模糊測度 人工神經(jīng)網(wǎng)絡 Ansys

【摘要】：本文針對山區(qū)淺埋隧道開挖引起的巖體移動問題，采用模糊測度模型進行預測分析，并以MATLAB為平臺進行數(shù)值計算。本研究以韓家莊隧道工程為例，確定不同的地質(zhì)剖面進行巖體移動變形預測分析。計算中對理論模型中所涉及的參數(shù)，采用人工神經(jīng)網(wǎng)絡方法進行確定。 利用模糊神經(jīng)網(wǎng)絡方法分析結(jié)果表明：（1）山區(qū)淺埋隧道開挖后地表位移變形呈現(xiàn)出明顯的非對稱性；（2）隧道埋深與地表最大沉降成反比，且埋深越大，，對地表最大沉降值的影響越不敏感；（3）地表坡度的變化對最大沉降值影響較小；（4）隧道跨度的大小與地表最大沉降成正比，且跨度越大，對最大沉降值的影響越敏感。 針對韓家莊隧道工程，在利用模糊測度模型進行了具體分析的同時，采用有限單元法對隧道開挖巖體移動進行了數(shù)值模擬分析，并將所得數(shù)值模擬結(jié)果與模糊測度模型計算結(jié)果及實測數(shù)據(jù)進行了對比，使不同方法所獲結(jié)果能夠相互驗證。 對比結(jié)果表明，模糊測度模型計算結(jié)果與韓家莊隧道實測結(jié)果基本一致，從而為山區(qū)淺埋隧道開挖引起的地表下沉預測提供了一種新的方法—模糊神經(jīng)網(wǎng)絡方法。理論分析結(jié)果表明，ANSYS軟件預測所獲的最大下沉值與實測最大下沉值二者基本一致，但整體下沉分布與實測值相差較大，主要是邊界效應不符合工程實際，而模糊測度模型則可以解決這一問題。
[Abstract]:In this paper, fuzzy measure model is used to predict and analyze rock mass movement caused by shallow tunnel excavation in mountainous area, and numerical calculation is carried out on the platform of MATLAB. In this study, Hanjiazhuang tunnel project is taken as an example. The parameters involved in the theoretical model are determined by artificial neural network method. The results of fuzzy neural network analysis show that the surface displacement and deformation of shallow buried tunnel in mountainous area show obvious asymmetry after excavation. (2) the depth of the tunnel is inversely proportional to the maximum settlement of the earth's surface, and the greater the depth, the less sensitive it is to the maximum settlement of the surface; (3) the change of surface slope has little effect on the maximum settlement value; (4) the size of tunnel span is proportional to the maximum surface settlement, and the larger the span is, the more sensitive it is to the maximum settlement value. In view of Hanjiazhuang tunnel project, the fuzzy measure model is used to carry out the concrete analysis, and the finite element method is used to simulate the rock mass movement of the tunnel excavation. The numerical simulation results are compared with the calculated results of fuzzy measure model and the measured data, so that the results obtained by different methods can be verified mutually. The comparison results show that the calculation results of fuzzy measure model are basically consistent with the measured results of Hanjiazhuang tunnel. It provides a new method for prediction of surface subsidence caused by shallow tunnel excavation in mountainous area, which is called fuzzy neural network method. The theoretical analysis results show that this method can be used to predict the surface subsidence of shallow buried tunnels. The maximum subsidence value predicted by ANSYS software is basically consistent with the measured maximum subsidence value, but the difference between the overall subsidence distribution and the measured value is quite large, mainly because the boundary effect is not in line with the engineering practice. Fuzzy measure model can solve this problem.
【學位授予單位】：河北大學
【學位級別】：碩士
【學位授予年份】：2014
【分類號】：U456.3

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