本文選題：隧道 + 軟弱圍巖��； 參考：《遼寧工程技術(shù)大學》2015年博士論文

【摘要】：軟弱巖體的存在給大斷面隧道支護結(jié)構(gòu)設(shè)計及圍巖穩(wěn)定性計算等帶來一系列棘手的問題。由于軟弱巖體中節(jié)理、裂隙的存在,其力學行為受巖石強度、結(jié)構(gòu)面狀況及應(yīng)力狀態(tài)等多方面影響,存在節(jié)理的硬巖在高應(yīng)力作用下仍會表現(xiàn)出明顯的大變形特性及應(yīng)變軟化特性,巖體的擴容現(xiàn)象突出,巖體變形具有不連續(xù)性。所以,對于軟弱巖體強度特性及峰后力學行為等問題值得深入研究與討論。論文針對以上問題,從隧道軟弱圍巖的變形破壞機制出發(fā),通過室內(nèi)巖石三軸試驗及現(xiàn)場超前地質(zhì)探測技術(shù)相結(jié)合的方法,探討軟弱圍巖的強度特征,確定圍巖結(jié)構(gòu)特性,分析深埋隧道軟弱圍巖在卸載過程中的應(yīng)變軟化行為及強度損傷演化規(guī)律,研究圍巖在二次應(yīng)力作用下的應(yīng)力場、位移場分布規(guī)律；采用收斂-約束法確定圍巖及支護結(jié)構(gòu)安全系數(shù),并對支護結(jié)構(gòu)及隧道開挖方法進行優(yōu)化設(shè)計,通過現(xiàn)場監(jiān)測及數(shù)值計算驗證優(yōu)化結(jié)構(gòu)的安全穩(wěn)定性。論文得出具體結(jié)論如下：(1)基于量化GSI圍巖評級系統(tǒng),確定隧道軟弱圍巖在峰值及峰后殘余狀態(tài)的強度參數(shù),結(jié)合Hoek-Brown準則及巖體連續(xù)介質(zhì)應(yīng)變軟化理論,構(gòu)建深埋軟弱圍巖峰值及峰后殘余強度參數(shù)的函數(shù)關(guān)系式。(2)通過巖石室內(nèi)三軸試驗,確定峰后軟化模量與圍壓關(guān)系,構(gòu)建完整巖石峰后應(yīng)變軟化模型,結(jié)合超前地質(zhì)預(yù)報方法,確定深埋隧道軟弱圍巖力學參數(shù),指導隧道開挖方案優(yōu)化及支護結(jié)構(gòu)設(shè)計。(3)通過數(shù)值計算與現(xiàn)場監(jiān)測數(shù)據(jù)可知,收斂-約束法適用于大斷面軟弱隧道圍巖支護結(jié)構(gòu)設(shè)計,通過FLAC3D有限差分軟件構(gòu)建隧道三維數(shù)值模型,得出不同開挖方法的圍巖-支護結(jié)構(gòu)相互作用關(guān)系,提出各開挖方案的圍巖安全系數(shù),并對現(xiàn)有支護方案及開挖方法進行優(yōu)化設(shè)計,通過現(xiàn)場監(jiān)測數(shù)據(jù)驗證優(yōu)化設(shè)計的可靠性。(4)提出進化神經(jīng)元算法與BP神經(jīng)網(wǎng)絡(luò)算法耦合的GA-BP神經(jīng)元算法,應(yīng)用于鋪子山隧道施工圍巖大變形預(yù)測,對隧道圍巖變形監(jiān)測數(shù)據(jù)進行多步滾動預(yù)測,通過實測數(shù)據(jù)與預(yù)測結(jié)果相比較,表明該算法具有極高的預(yù)測精度,可對類似工程提供借鑒。
[Abstract]:The existence of weak rock mass brings a series of thorny problems to the design of large section tunnel support structure and the calculation of surrounding rock stability. Because of the existence of joints and fissures in weak rock mass, its mechanical behavior is affected by rock strength, structural plane condition and stress state, etc. The jointed hard rock will still exhibit large deformation and strain softening characteristics under the action of high stress. The expansion of rock mass is prominent and the deformation of rock mass is discontinuous. Therefore, the strength characteristics and post-peak mechanical behavior of weak rock mass are worthy of further study and discussion. Aiming at the above problems, starting from the mechanism of deformation and failure of soft surrounding rock in tunnel, this paper discusses the strength characteristics of soft surrounding rock and determines the structural characteristics of surrounding rock through the combination of indoor triaxial test of rock and advance geological exploration technology. The strain softening behavior and strength damage evolution law of soft surrounding rock in deep buried tunnel during unloading are analyzed, and the stress field and displacement field distribution law of surrounding rock under secondary stress are studied. The safety factor of surrounding rock and supporting structure is determined by convergence-constraint method, and the optimum design of supporting structure and tunnel excavation method is carried out. The safety and stability of the optimized structure are verified by field monitoring and numerical calculation. The concrete conclusions are as follows: (1) based on the quantitative GSI surrounding rock rating system, the strength parameters of the peak and post-peak residual state of the soft surrounding rock in tunnel are determined, combined with the Hoek-Brown criterion and the strain softening theory of rock mass continuum. The relationship between post-peak softening modulus and confining pressure is determined through laboratory triaxial tests of rock, and a complete post-peak strain softening model is constructed, combined with advanced geological prediction method. To determine the mechanical parameters of soft surrounding rock of deep buried tunnel, to guide the optimization of excavation scheme and the design of supporting structure. (3) through numerical calculation and field monitoring data, we can know that the convergence-constraint method is suitable for the design of surrounding rock supporting structure of large section weak tunnel. The 3D numerical model of tunnel is constructed by FLAC3D finite difference software, and the interaction relationship between surrounding rock and supporting structure of different excavation methods is obtained, and the safety factor of surrounding rock of each excavation scheme is put forward. The existing support schemes and excavation methods are optimized, and the reliability of the optimization design is verified by field monitoring data. A GA-BP neuronal algorithm coupled with the BP neural network algorithm is proposed, which is coupled with the evolutionary neuron algorithm (ENA) and the BP neural network algorithm (BP neural network algorithm). The method is applied to the prediction of large deformation of surrounding rock in the construction of Pu Zishan Tunnel. The multi-step rolling prediction of the monitoring data of surrounding rock deformation of the tunnel is carried out. The comparison between the measured data and the prediction results shows that the algorithm has a very high prediction accuracy. It can be used for reference for similar projects.
【學位授予單位】：遼寧工程技術(shù)大學
【學位級別】：博士
【學位授予年份】：2015
【分類號】：U451.2

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