Seepage field distribution and water inflow laws of tunnels in water-rich regions

Currently,the water inrush hazards during tunnel construction,the water leakage during tunnel operation,and the accompanying disturbances to the ecological environment have become the main problems that affect the structural safety of tunnels in water-rich regions.In this paper,a tunnel seepage model testing system was used to conduct experiments of the grouting circle and primary support with different permeability coefficients.The influences of the supporting structures on the water inflow laws and the distribution of the water pressure in the tunnel were analyzed.With the decrease in the permeability coefficient of the grouting circle or the primary support,the inflow rate of water into the tunnel showed a non-linear decreasing trend.In comparison,the water inflow reduction effect of grouting circle was much better than that of primary support.With the increase of the permeability coefficient of the grouting ring,the water pressure behind the primary lining increases gradually,while the water pressure behind the grouting ring decreases.Thus,the grouting of surrounding rock during the construction of water-rich tunnel can effectively weaken the hydraulic connection,reduce the influence range of seepage,and significantly reduce the decline of groundwater.Meanwhile,the seepage tests at different hydrostatic heads and hydrodynamic heads during tunnel operation period were also conducted.As the hydrostatic head decreased,the water pressure at each characteristic point decreased approximately linearly,and the water inflow rate also had a gradual downward trend.Under the action of hydrodynamic head,the water pressure had an obvious lagging effect,which was not conducive to the stability of the supporting structures,and it could be mitigated by actively regulating the drainage rate.Compared with the hydrostatic head,the hydrodynamic head could change the real-time rate of water inflow to the tunnel and broke the dynamic balance between the water pressure and water inflow rate,thereby affecting the stress state on the supporting structures.

Detection and treatment of water inflow in karst tunnel：A case study in Daba tunnel

In a karst tunnel, fissures or cracks that are filled with weathered materials are a type of potential water outlet as they are easily triggered and converted into groundwater outlets under the influence of high groundwater pressure. A terrible water inrush caused by potential water outlets can seriously hinder the project construction. Potential water outlets and water sources that surrounding the tunnel must be detected before water inflow can be treated. This paper provides a successful case of the detection and treatment of water inflow in a karst tunnel and proposes a potential water outlet detection(PWOD) method in which heavy rainfall(>50 mm/d) is considered a trigger for a potential water outlet. The Daba tunnel located in Hunan province, China, has been constructed in a karst stratum where the rock mass has been weathered intensely by the influence of two faults. Heavy rain triggered some potential water outlets, causing a serious water inrush. The PWOD method was applied in this project for the treatment of water inflow, and six potential water outlets in total were identified through three heavy rains. Meanwhile, a geophysical prospecting technique was also used to detect water sources. The connections between water outlets and water sources were identified with a 3-D graphic that included all of them. According to the distribution of water outlets and water sources, the detection area was divided into three sections and separately treated by curtain grouting.

Water inflow forecasting for tunnel considering nonlinear variation of permeability coefficient

To assess the water inflow which is more suitable to the actual conditions of tunnel,an empirical correlation about the permeability coefficient changing with depth is introduced.Supposing that the surrounding rock is heterogeneous isotropy,the formula for calculating water inflow of tunnel with the nonlinear variation of permeability coefficient is deduced.By the contrast analysis with the existing formulas,the presented method has the similar value to them;moreover,the presented method has more simple form and easy to use.Due to parameter analysis,the water inflow decreases after considering the nonlinear variation of permeability coefficient.When the attenuation coefficient a>0,the water inflow increases first till reaches the maximum at a certain depth,then decreases and is close to 0 finally if deep enough.Thus,it is better to keep away from the certain depth where it is with the maximum water inflow for safe operation and economical construction,and reduce the water damage.Based on the analysis,the radius of tunnel has less impact on the amount of water inflow,and the water inflow just increases by 6.7% when the radius of tunnel increases by 1 m.

Influence of Ramjets’ Water Inflow on Supercavity Shape and Cavitator Drag Characteristics

Water ramjets using outer water as an oxidizer have been demonstrated as a potential propulsion mode for underwater High Speed Supercavitating Vehicles (HSSVs) because of their higher energy density, power density, and specific impulse, but water flux changes the shapes of supercavity. To uncover the cavitator drag characteristics and the supercavity shape of HSSVs with water inflow for ramjets, supercavitation flows around a disk cavitator with inlet hole are studied using the homogenous model. By changing the water inflow in the range of 0-10 L/s through cavitators having different water inlet areas, a series of numerical simulations of supercavitation flows was performed. The water inflow flux of ramjets significantly influences the drag features of disk cavitators and the supercavity shape, but it has little influence on the slender ratio of supercavitaty. Furthermore, as the water inlet area increases, the drag coefficient of the cavitators' front face decreases, but this increase does not influence the diameter of the supercavity's maximum cross section and the drag coefficient of the entire cavitator significantly. In addition, with increasing waterflux of the ramjet, both the drag coefficient of cavitators and the maximum diameter of supercavities decrease stably. This research will be helpful for layout optimization and supercavitaty scheme design of HSSVs with water inflow for ramjets.

Support Vector Machines(SVM)-Markov Chain Prediction Model of Mining Water Inflow

This study was conducted to establish a Support Vector Machines(SVM)-Markov Chain prediction model for prediction of mining water inflow. According to the raw data sequence, the Support Vector Machines(SVM) model was built, and then revised by means of a Markov state change probability matrix. Through dividing the state and analyzing absolute errors and relative errors and other indexes of the measured value and the fitted value of SVM, the prediction results were improved. Finally,the model was used to calculate relative errors. Through predicting and analyzing mining water inflow, the prediction results of the model were satisfactory. The results of this study enlarge the application scope of the Support Vector Machines(SVM) prediction model and provide a new method for scientific forecasting water inflow in coal mining.

Key issues in water sealing performance of underground oil storage caverns: Advances and perspectives

Water sealing performance is important for underground water-sealed oil storage(UWSOS).The key issues concerning water sealing performance mainly include the permeability of fractured rock mass(FRM),water-sealed safety(WSS),water curtain performance,and prediction and control of water inflow.This paper reviews the progress of above four key issues on water sealing performances.First,the permeability of an FRM is the basis of water sealing performance,and several commonly used permeability test methods and spatial variation characteristics of permeability are outlined.Second,the current water sealing criteria are compared,and the evaluation methods of WSS are summarized.Third,the design parameters and efficiency evaluation of water curtain systems(WCSs)are introduced.The water inflow of oil storage caverns(OSCs)can reflect the water sealing effect,and the prediction methods and control measures of water inflow are also summarized.Finally,the advantages and disadvantages of the current research are discussed,and the potential research directions are pointed out,such as optimization of water sealing criteria and FRM model,quantitative evaluation of WCS efficiency,accurate prediction of water inflow,and improvement of grouting technology.

Geochemical characteristics and source analysis of inflow of mine water in Wang’ershan Gold Mine, Shandong

Through a systematic observation of water level and temperature, and a comprehensive analysis of the data on major/trace elements, nitrite, hydrogen-oxygen isotopes, the conclusion has been drawn that there are two relatively independent groundwater systems (cool water and hot water), and the geochemical indicators of hot/cool waters are described. The cool water system is relatively enriched in Ca2+, Mg2+ and HCO3-. Its TDS is relatively low, about 1400–1800 mg/L. The hot water system is relatively enriched in K+, Na+, Cl- and SO42-. Its TDS is relatively high, about 2200–2300 mg/L. The cool water system is enriched in Ba, Ga, Cd, and the hot water system is enriched in B, Ti, Cr, Ni, Cu, Mo, Rb, and Cs, relatively. Especially, the contents of Rb and Cs in the hot water system are more than five times as high as those in the cool water system. The NO3- contents of cool water discharged from the gold mine are relatively high, and those of hot water are extremely low. The δD and δ18O values follow an increasing order of surface water>mine cool water>mine hot water. The cool water comes mainly from the lateral supply of phreatic water, while the hot water comes mainly from the vertical supply of deeply circulating structure-fracture water. The ratio of cool water over hot water was estimated to be about 1:1 by a water quality model..

富水裂隙围岩隧道涌水量计算方法与规律分析

富水裂隙区隧道涌水量预测精度较差,涌水问题尚未得到较好的解决。针对此问题,视裂隙围岩及注浆区为非均质各向异性介质,初期支护及二次支护结构为均质各向同性介质,构建了裂隙围岩下隧道涌水简化计算模型,基于地下水力学理论及流体质量守恒定律推导了富水裂隙区隧道涌水量计算公式。通过退化分析及案例工程现场实测数据验证了构建富水裂隙区隧道涌水简化计算模型的合理性及涌水量计算式求解的正确性,最后基于解析解揭示了各特征参数对富水裂隙区隧道涌水的影响规律,探讨了富水裂隙区隧道涌水机制。结果表明:理论计算值与现场实测值最大相对误差为8.1%,验证了构建模型的合理性及公式推导的正确性;隧道涌水量随裂隙最大宽度的增加而增大,受堵水结构的联合制约,两者近似呈线性关系;注浆区厚度与隧道半径比值在2倍以内时,隧道涌水量受注浆区厚度的影响显著;富水裂隙区隧道涌水受裂隙分布规律及支护结构的制约,应重视对裂隙分布的调查。

富水岩溶地区隧道涌水预测与施工处置技术研究

针对贵州某隧道施工过程中遭遇一处连通地下暗河的大型溶洞引起隧道内大规模涌水的灾害进行研究,结合水文地质情况对涌水量进行预测和分析后,现场先对岩溶水进行初步释压,后采用水泥砂浆分步回填隧道上伏溶腔以封堵岩溶出水口;进一步采用集水管引排岩溶水的方式对剩余地下水进行二次加强处理,同时将集水管与隧道外侧的泄水洞相连,二者构成一套完整的引排水系统的处治手段。采用堵排相结合的原则有效地达到涌水处置目的,确保了隧道的安全施工,可为类似地层的隧道施工提供有益的借鉴。

彬长大佛寺矿井涌水量时序预测

为提高矿井涌水量预测精度,解决矿井涌水量预测无法及时响应动态变化的问题,构建一种基于模态分解和深度学习的矿井涌水量多因素时间序列组合预测模型。使用变分模态分解和灰色关联分析筛选主控因素,通过双向长短期记忆网络和卷积长短期记忆网络对高、低频模态分量进行预测。结果表明:对比不同时序预测模型,变分模态分解可以有效捕捉时序数据中的长期依赖关系,提供了更加准确的长期时序数据预测能力;经过鲸鱼优化、贝叶斯优化算法对不同频率模态分量的处理,有效降低了高频部分的无序性、复杂性并优化了较为线性、缓慢的低频部分;验证了矿井涌水量时序预测中的变分模态深度学习组合模型的有效性和适用性,预测精度满足生产需求。该理论丰富了矿井涌水量时序预测方法,对煤矿水害预防具有一定的理论意义。

煤矿充水因素评价及涌水量预测

含水层、老窖水以及采空区积水等水源对煤矿安全生产带来威胁。以山西省某煤矿为例,分析充水因素,并对采用富水系数比拟法对涌水量进行预测,有利于煤矿防治水工作开展,对井下安全生产具有重要意义。

鄂尔多斯盆地北部直罗组古河道砂体分布区矿井涌水模式

近十几年来,鄂尔多斯盆地北部煤矿开采频频受到了直罗组地下水的威胁,甚至出现了突水事故。区内以直罗组地下水为充水水源的大水矿井连片分布,且与直罗组古河道砂体关系密切。为阐释神府南区直罗组古河道砂体分布区矿井涌水模式,在直罗组古河道砂体空间分布及其对地下水赋存控制作用研究的基础上,从研究区尺度、井田尺度和工作面尺度,分析了直罗组古河道砂体与矿井涌水的关系,提出了直罗组古河道砂体下矿井涌水模式。结果表明:神府南区直罗组古河道冲刷带沿红碱淖—尔林兔—锦界一线发育,冲刷带内延安组第5段几乎被冲刷剥蚀殆尽,在局部地区延安组第4段也遭受了冲刷。根据砂分散体系分析和隔水岩组发育特征,将冲刷带内充填沉积的古河道砂体分为3级。直罗组古河道砂体富水性的强弱主要受控于砂体规模、物性特征和风化作用,一级砂体(主河道)区域富水性强于二级砂体(分支河道)及三级砂体(三角洲间湾、分流间湾)区域,当砂体遭受风化后,其富水性将进一步增强。基于不同尺度下砂体分级、风化砂体厚度与矿井涌水关系的分析,提出了研究区东部现阶段古河道砂体下生产矿井的3种涌水模式。强涌水模式,主要位于一级砂体分布区,风化砂体厚度一般≥30 m。中等涌水模式,主要位于一级砂体的边缘或二级砂体区域,风化砂体厚度一般10~30 m。弱涌水模式,主要位于三级砂体区域,风化砂体厚度一般<10 m。

基于SSA-CG-Attention模型的多因素采煤工作面涌水量预测

矿井工作面涌水量预测对确保矿山安全、优化资源配置、提高工作效率等都具有重要作用。为提高预测结果的准确性和稳定性,基于钻孔水位和微震能量数据与涌水量的强关联性,选择其作为多因素特征变量,提出SSA-CG-Attention多因素矿井工作面涌水量预测模型。该模型在门控循环单元(GatedRecurrentUnit,GRU)提取时序特征的基础上,与卷积神经网络(ConvolutionalNeuralNet-work,CNN)融合形成新的网络结构提取数据的有效非线性局部特征,并且加入注意力机制(Atten-tion),在预测过程中将注意力集中在输入元素上,提高模型的准确性。最后通过麻雀搜索算法(Spar-row Search Algorithm,SSA)优化模型参数,避免局部最优解的问题。将提出的模型分别与传统的BP神经网络、LSTM、GRU单因素涌水量预测模型以及MLP、SLP、SVR、LSTM、GRU、SSA-LSTM、SSA-GRU多因素涌水量预测模型的预测结果进行对比分析,结果表明:SSA算法以最少迭代次数快速寻优,避免了局部最优解的缺陷;SSA-CG-Attention多因素涌水量预测模型整体预测指标绝对误差(E_(MA))、均方根误差(E_(RMS))以及平均绝对百分比误差(E_(MAP))分别为5.24 m^(3)/h、7.25 m^(3)/h、6%,指标方差和为8.90。相较于其他预测模型预测精度更高,相较于单因素涌水量预测模型,多因素涌水量预测模型预测结果更加稳定。研究结果为矿井工作面涌水量预测提供了新的思路与方法,对矿井工作面涌水量预测及防控有着借鉴与指导作用,具有一定的理论价值和现实意义。

基于CEEMDAN和改进的混合时间序列模型工作面涌水量预测研究

为提高采煤工作面涌水量预测准确度,收集大量工作面涌水量观测数据进行整理、统计、分析,将涌水量稳定性、周期性和季节性特征考虑在内,提出1种基于数据驱动的完全自适应模态分解算法(CEEMDAN)和改进的混合时间序列模型工作面涌水量预测方法。该方法利用CEEMDAN处理涌水量数据,构建麻雀搜索算法(SSA)优化的长短期记忆网络(LSTM)和自回归移动平均模型(ARIMA)并行级联而成的混合时间序列模型对工作面涌水量进行预测。研究结果表明:该模型预测结果与真实数据相差更小,平均绝对误差为6.36 m 3/h,均方根误差为10.6 m 3/h,模型拟合系数为0.95,更适用于工作面涌水量预测。研究结果可为矿井工作面涌水量预测及防控提供参考。

河下浅埋厚煤层采动覆岩裂隙-涌水量时空演化的FDEM-CFD耦合分析

河下浅埋厚煤层采动覆岩裂隙分布与涌水量是工作面安全生产的决定性因素之一。数值模拟是二者重要预测方法,其合理性的关键在于建立岩体破坏-裂隙流体耦合理论及相应的模拟方法。以路家村矿15404工作面为研究背景,构建拉/剪应力下非贯通裂隙开裂、贯通裂隙的法向与切向本构关系,并基于二相流质量守恒、动量守恒与状态方程,结合增强的浸没边界算法识别流-固界面,通过流体体积法实现裂隙内流体自由面的追踪和重构。在此基础上形成FDEM-CFD河下采煤覆岩裂隙与涌水量预测数值模型耦合程序,通过相邻工作面地面钻孔冲洗液消耗量观测法验证导水裂隙带发育高度,以及采用大井法理论对涌水量结果进行对比。结果表明:采动岩体破坏-裂隙流体耦合理论及相应的FDEM-CFD程序,可数值实现河下浅埋厚煤层采动覆岩裂隙形成,以及裂隙内流体运移过程。当工作面推进至80~120 m时覆岩内形成贯通地表的导水裂隙。招山河水的主要下泄路径为工作面后方8~20 m位置处的导水裂隙,其斜向采空区、倾角65°~72°。模拟所得采空区涌水量为18.78 m^(3)/h,与大井法计算结果接近。上述成果在路家村矿区得到初步应用,为进一步开展河下浅埋厚煤层防治水工程提供理论支撑。

博斯腾湖COD_(Cr)污染现状及影响因素分析

近几年博斯腾湖COD_(Cr)污染问题突出,制约了区域社会经济的可持续发展。目前有关博斯腾湖COD_(Cr)的研究,主要集中于非长序列的COD_(Cr)时空特征分析,而对造成这种时空特征的成因缺乏定量化分析研究。鉴于此,在收集分析博斯腾湖COD_(Cr)长序列变化特征的基础上,通过统计分析和模型模拟等方法,系统探讨了博斯腾湖COD_(Cr)污染的主要影响因素及其作用机理。主要研究结论为:入湖负荷和湖泊水位对COD_(Cr)的影响存在共轭作用,主导作用取决于水位阈值;当水位低于1047.1 m,水位稀释作用占主导,当水位高于1047.1 m时,入湖负荷占主导;湖泊水动力条件主要受风生流控制,近年来风速呈上升趋势,增强了湖区内部的水循环,进而影响西部湖区COD_(Cr)浓度;湖泊藻类浓度与水位呈负相关,而与COD_(Cr)浓度呈正相关,COD_(Cr)与藻类浓度显著相关性的内在机制是两者均受水位影响。该研究为博斯腾湖COD_(Cr)污染治理提供了科学依据,同时提出未来研究的关注点是加强对底泥、水温和溶解氧的垂向相关数据的监测,以进一步分析底泥对水体COD_(Cr)的影响。

西南地区典型河道型水库水温结构及水动力机制研究

大型河道型水库在发挥水电效益的同时,其特有的水温分层对水环境的影响不容忽视。现有研究多偏重于水温垂向差异及时空演变规律研究,对于其形成过程的水动力影响研究尚不够深入。本研究利用数学模型模拟分析西南地区典型河道型水库—乌东德水库水温结构变化过程,发现水动力条件是水温结构形成的决定性因素,主温跃层的形成和演变取决于温差异重流导致的水动力机制。2—3月来水下潜于水库底部,二者界面形成主温跃层,并不断向库区下游发展;4—6月来流形成中间流,其上和其下分别形成两个温跃层;7月入库水流为上浮流,其下形成主温跃层;坝前局部区域水体主温跃层因取水孔口动力抽吸作用等温线出现局部收缩。