本文關(guān)鍵詞：基于BP神經(jīng)網(wǎng)絡(luò)下的深長(zhǎng)隧道突水預(yù)測(cè)分析與數(shù)值模擬研究　出處：《中南大學(xué)》2014年碩士論文　論文類型：學(xué)位論文

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【摘要】：隧道突水突泥一直以來都是隧道施工過程中的重大難題,突水突泥可能會(huì)導(dǎo)致隧道工期延誤,造成巨大的財(cái)產(chǎn)損失,甚至還可能成為隧道塌方的誘因,導(dǎo)致人員傷亡,施工機(jī)械損壞,對(duì)整個(gè)社會(huì)造成不利的影響。過往的研究表明,地質(zhì)構(gòu)造、地下水源和開挖擾動(dòng)成為深長(zhǎng)隧道突水突泥災(zāi)害發(fā)生的三大原因。為了保障隧道施工的安全性,減少不必要的財(cái)產(chǎn)損失,加強(qiáng)對(duì)隧道突水突泥前兆信息的研究是十分必要的。在隧道施工過程中,綜合分析隧道突水突泥災(zāi)害誘因,預(yù)測(cè)突水突泥發(fā)生的可能性,采取針對(duì)性的控制措施,從而保障隧道的順利施工和人員的安全。 本文以江西鐘家山隧道為依托工程,通過收集工程中突水突泥災(zāi)害發(fā)生時(shí)的現(xiàn)場(chǎng)數(shù)據(jù),運(yùn)用BP神經(jīng)網(wǎng)絡(luò)對(duì)深長(zhǎng)隧道的突水突泥前兆信息進(jìn)行預(yù)測(cè),并采用數(shù)值模擬的方法對(duì)隧道突水過程進(jìn)行了分析,論文主要完成了以下幾方面的工作： (1)根據(jù)國(guó)內(nèi)外有關(guān)深長(zhǎng)隧道突水突泥涌水量預(yù)測(cè)的研究,探討了深長(zhǎng)隧道涌水預(yù)測(cè)過程中的影響因素,結(jié)合鐘家山隧道現(xiàn)場(chǎng)的施工情況,確定了涌水量預(yù)測(cè)的六個(gè)變量參數(shù)。 (2)依據(jù)鐘家山隧道施工過程中采集的數(shù)據(jù),利用BP神經(jīng)網(wǎng)絡(luò)建立突水突泥的災(zāi)害預(yù)測(cè)模型。通過對(duì)現(xiàn)場(chǎng)觀測(cè)點(diǎn)涌水量的預(yù)測(cè),驗(yàn)證了該預(yù)測(cè)模型的有效性和正確性。 (3)運(yùn)用MIDAS和FLAC3D數(shù)值模擬軟件對(duì)深長(zhǎng)隧道的突水情況進(jìn)行數(shù)值模擬分析,研究了隧道突水前兆信息的演化規(guī)律,分析了隧道開挖過程中滲流速度、滲透水壓力、孔隙水壓力的變化情況。
[Abstract]:Water and mud inrush has always been a major problem in tunnel construction, which may lead to the delay of tunnel construction period, cause huge property losses, and even may become the inducement of tunnel collapse. Causes casualties, construction machinery damage, to the entire society has a negative impact. Previous studies show that the geological structure. The underground water source and excavation disturbance are the three main causes of water inrush and mud inrush in deep tunnel. In order to ensure the safety of tunnel construction and reduce unnecessary property losses. It is necessary to strengthen the study on the precursor information of water and mud inrush in tunnel. In the process of tunnel construction, the inducement of water and mud inrush in tunnel is analyzed synthetically, and the possibility of water inrush is predicted. Take targeted control measures to ensure the smooth construction of the tunnel and the safety of personnel. Based on the project of Zhongjiashan Tunnel in Jiangxi Province, this paper uses BP neural network to predict the precursor information of water inrush mud in deep long tunnel by collecting the field data of water inrush and mud inrush disaster. The water inrush process of tunnel is analyzed by numerical simulation. The main work of this paper is as follows: 1) based on the domestic and foreign research on the prediction of water inrush and mud inrush from deep long tunnel, the influencing factors in the process of water inrush prediction in deep long tunnel are discussed, combined with the construction situation of Zhongjiashan tunnel site. Six variable parameters of water inflow prediction are determined. 2) based on the data collected during the construction of Zhongjiashan Tunnel, a disaster prediction model of water inrush and mud inrush is established by using BP neural network. The validity and correctness of the prediction model are verified. 3) using MIDAS and FLAC3D software to simulate the water inrush of the deep tunnel, and study the evolution rule of the precursor information of water inrush in the tunnel. The variation of seepage velocity, seepage water pressure and pore water pressure during tunnel excavation are analyzed.
【學(xué)位授予單位】：中南大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2014
【分類號(hào)】：U456.3

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