An efficient physics-guided Bayesian framework for predicting ground settlement profile during excavations in clay

Recently,the application of Bayesian updating to predict excavation-induced deformation has proven successful and improved prediction accuracy significantly.However,updating the ground settlement profile,which is crucial for determining potential damage to nearby infrastructures,has received limited attention.To address this,this paper proposes a physics-guided simplified model combined with a Bayesian updating framework to accurately predict the ground settlement profile.The advantage of this model is that it eliminates the need for complex finite element modeling and makes the updating framework user-friendly.Furthermore,the model is physically interpretable,which can provide valuable references for construction adjustments.The effectiveness of the proposed method is demonstrated through two field case studies,showing that it can yield satisfactory predictions for the settlement profile.

Effectiveness of predicting tunneling-induced ground settlements using machine learning methods with small datasets

Prediction of tunneling-induced ground settlements is an essential task,particularly for tunneling in urban settings.Ground settlements should be limited within a tolerable threshold to avoid damages to aboveground structures.Machine learning(ML)methods are becoming popular in many fields,including tunneling and underground excavations,as a powerful learning and predicting technique.However,the available datasets collected from a tunneling project are usually small from the perspective of applying ML methods.Can ML algorithms effectively predict tunneling-induced ground settlements when the available datasets are small?In this study,seven ML methods are utilized to predict tunneling-induced ground settlement using 14 contributing factors measured before or during tunnel excavation.These methods include multiple linear regression(MLR),decision tree(DT),random forest(RF),gradient boosting(GB),support vector regression(SVR),back-propagation neural network(BPNN),and permutation importancebased BPNN(PI-BPNN)models.All methods except BPNN and PI-BPNN are shallow-structure ML methods.The effectiveness of these seven ML approaches on small datasets is evaluated using model accuracy and stability.The model accuracy is measured by the coefficient of determination(R2)of training and testing datasets,and the stability of a learning algorithm indicates robust predictive performance.Also,the quantile error(QE)criterion is introduced to assess model predictive performance considering underpredictions and overpredictions.Our study reveals that the RF algorithm outperforms all the other models with the highest model prediction accuracy(0.9)and stability(3.0210^(-27)).Deep-structure ML models do not perform well for small datasets with relatively low model accuracy(0.59)and stability(5.76).The PI-BPNN architecture is proposed and designed for small datasets,showing better performance than typical BPNN.Six important contributing factors of ground settlements are identified,including tunnel depth,the distance between tunnel face and surface monitoring points(DTM),weighted average soil compressibility modulus(ACM),grouting pressure,penetrating rate and thrust force.

Study on influence of ground settlement in bored metro tunnel

At present the bored construction method is one of the main constructionmethods of metro and tunnel construction in China.The empirical estimated formuias oftunnel ground surface settlement using the bored construction method were obtained,combining the mechanical stimulant calculated result of tunnel model of different embed-ded depth,different cross section and different construction method and the actuai meas-urement data of Beijing metro construction.According to the regressed analysis of calcu-lated data,the calculated equations of ground surface settlement value and settlementrange of tunnel section under the condition of different embedded depth,different crosssection and different construction method were gained.Amongthem there are some em-pirical formulas can apply to the construction design of metro tunnel directly.

Ground settlement sedimentation time-space effect and ground settlement control standards

Since different underground engineering contains different geological conditions,structure and excavation methods,their disturbing degree on the ground also differs,but ground surface settlement caused by excavation has one common point that they will form a ground surface settlement curve.Based on data statistical analysis,the article puts forward the relationship between point of inflection in digging tunnels with shallowburied method and the span of tunnel excavation against typical geological conditions in Changchun so as to predict the impact of tunnel excavation and improve reasonable ground surface settlement control standard.Research result will be useful for study on ground surface control standard in digging tunnels with shallow-buried method and setting settlement standard.

Ground settlement and tunnel response due to twin-curved shield tunnelling in soft ground with small clear distance

Twin curved tunnels are often encountered in shield tunnelling,where significant complexities in densely exploited underground space are observed.In this study,the ground settlement and tunnel deformation due to twin-curved shield tunnelling in soft ground were investigated using numerical simulation and field monitoring.Different curvature radii of twin curved tunnels and subsequent effects of tunnel construction were considered to reveal the tunnelling effect on ground surface settlement and tunnel deformation.The results show that the settlement trough yields one offset towards inside of curved shield tunnelling.The location of settlement trough and maximum settlement were affected by curvature radius but except for the shape and width of settlement trough.Adjacent parallel twin-curved shield tunnelling could increase the offset of existing settlement trough and maximum settlement.Then,an empirical prediction of surface settlement trough due to twin-curved shield tunnelling with same tunnel diameters in soft clay was proposed,which was applicable to curvature radius less than 800 m.Finally,a minimum radius of 600 m of curvature tunnel was proposed in terms of allowable convergence deformation of tunnel.The result could provide guidance on safety evaluation for twin curved shield tunnelling construction.

Analytical solutions of ground settlement induced by yaw in a space curved shield tunnel

This paper aims to provide the analytical solutions of the ground settlement for a space curved shield tunnel in the case of yaw construction.Settlement inducements include ground loss and construction loads,and two corresponding analytical models have been proposed in this study.Three-dimensional image theory has been adopted to calculate the ground settlement due to ground loss.Yawrelated parameters are introduced into the calculation model to deduce the relevant laws of the ground settlement.Based on modified Mindlin solutions,analytical models are established to calculate the ground settlement induced by construction loads,such as the frontal additional thrust,axial friction of shield shell,and the grouting pressure.The method of calculating the position of the shield machine in the ground is refined,and the influence area of construction loads from the shield machine is optimized.Subsequently,the obtained solutions are validated by a numerical model and field data.Besides,a comparison reveals that the proposed model is the composition of three classical analytical models,thus it excels them in solving the problem mentioned.Finally,parametric analyses of yaw are conducted to examine yaw angle and pitch angle on ground settlement.The proposed model can effectively predict ground settlement caused by the spatial linear shield tunneling process.

Shallow Tunneling Method and Control Measure for Ground Surface Settlement

In order to ensure that the tunnel deformation and surface settlement are controlled within the allowable range during the construction process,the design unit has compiled technical measures and monitoring schemes for ground settlement control of this project.Based on the example of a shallow tunneling project on Subway line 8,this paper analyzes and discusses the shallow tunneling method in detail and puts forward corresponding technical measures for ground settlement control.

Analytical solutions to ground settlement induced by ground loss and construction loadings during curved shield tunneling

This paper focuses on the ground settlement induced by the construction of a curved shield tunnel.Ground loss and construction loadings are the two factors causing ground settlement,and two corresponding analytical models were developed.First,the ground settlement due to ground loss was analyzed based on 3D image theory.The"integrative gap at shield tail"(IGST)and overcutting gap of a curved tunnel were considered.Second,the ground settlement due to construction loadings was analyzed by modifying Mindlin's solutions.The additional thrust,frictional force,and grouting pressure were considered.Subsequently,a case study and a parameter analysis were conducted.Finally,the obtained solutions were compared with a classical analytical solution,numerical simulations,and monitored results.The proposed model could effectively predict the ground settlement in-duced during curved shield tunneling.

Ground settlement during tunneling in groundwater drawdown environment-Influencing factors

In this paper,the results of a parametric study on groundwater drawdown-induced surface settlement during tunneling in waterbearing ground are presented.A calibrated stress–pore pressure coupled finite element model was adopted for the parametric analysis.The results were analyzed to establish the relationships between key design issues,such as the ground surface settlement and groundwater drawdown,and influencing factors.An artificial neural network(ANN)-based sensitivity analysis was performed to obtain insight into the relative importance of the influencing factors.The results indicated that the primary influencing factors on the settlement development are the thickness and stiffness of the soil layer within the drawdown zone and the lining permeability,while the initial void ratio and the permeability of the soil layer were considered secondary influencing factors.Practical implications and findings of the study are discussed.

Analysis of ground surface settlement in anisotropic clays using extreme gradient boosting and random forest regression models

Excessive ground surface settlement induced by pit excavation(i.e.braced excavation) can potentially result in damage to the nearby buildings and facilities.In this paper,extensive finite element analyses have been carried out to evaluate the effects of various structural,soil and geometric properties on the maximum ground surface settlement induced by braced excavation in anisotropic clays.The anisotropic soil properties considered include the plane strain shear strength ratio(i.e.the ratio of the passive undrained shear strength to the active one) and the unloading shear modulus ratio.Other parameters considered include the support system stiffness,the excavation width to excavation depth ratio,and the wall penetration depth to excavation depth ratio.Subsequently,the maximum ground surface settlement of a total of 1479 hypothetical cases were analyzed by various machine learning algorithms including the ensemble learning methods(extreme gradient boosting(XGBoost) and random forest regression(RFR)algorithms).The prediction models developed by the XGBoost and RFR are compared with that of two conventional regression methods,and the predictive accuracy of these models are assessed.This study aims to highlight the technical feasibility and applicability of advanced ensemble learning methods in geotechnical engineering practice.

Failure mechanism of large-diameter shield tunnels and its effects on ground surface settlements

A new technique for the analysis of the three-dimensional collapse failure mechanism and the ground surface settlements for the large-diameter shield tunnels were presented.The technique is based on a velocity field model using more different truncated solid conical blocks to clarify the multiblock failure mechanism.Furthermore,the shape of blocks between the failure surface and the tunnel face was considered as an entire circle,and the supporting pressure was assumed as non-uniform distribution on the tunnel face and increased with the tunnel embedded depth.The ground surface settlements and failure mechanism above large-diameter shield tunnels were also investigated under different supporting pressures by the finite difference method.

墙顶支撑对开挖前抽水引发基坑变形控制效果研究

基坑内抽水可诱发基坑围挡向坑内偏转并进而导致坑外土体随动沉降;在基坑土方开挖前,由于基坑内的支撑体系尚不能被完整架设,仅坑内土体可起到约束围挡变形的作用,此时,坑内抽水引起的围挡偏转十分明显。本文系统研究了围挡顶部支撑对土方开挖前抽水引发基坑变形的控制效果,首先通过抽水试验探究了坑内外强水力连通时墙顶支撑对抽水引发基坑变形的影响,并建立了三维数值计算模型,研究了若干典型参数(如,坑内降水深度等)对围挡顶部支撑控制基坑变形效果的影响。研究发现,围挡顶部支撑仅能有效限制浅埋范围内的围挡侧移(本文约埋深11 m范围内),对深埋位置围挡侧移的限制效果十分有限,且随着降水深度的增加,变形控制效果越弱;对于开挖前抽水深度较大的工程,仅采用围挡顶部设置支撑的方法可能无法有效限制围挡侧移的发展;另外,围挡顶部支撑仅能有效限制基坑围挡后方一定范围内(本文约10 m)的地表沉降,且当坑内外有水力联系时,由于坑外水位下降是引起地面沉降的主导因素,围挡顶部支撑并不能明显体现限制坑外最大地面沉降的作用,此时,应结合坑外地下水回灌进行沉降控制。

河南地矿CORS省域地面沉降监测与机理分析

为了进一步研究省域尺度范围地面沉降,分析河南地矿CORS省域地面沉降的监测方法与其形成机理:针对河南省地面沉降分布特征,采用河南省地质信息连续采集运行系统(HNGICS)的62个基准站数据,时间序列为2012—2019年,获得国际地球参考框架下无净旋转条件的河南省三维速度场;然后分解三维速度场获得河南垂直速度场,发现河南省地面沉降呈现“西稳东沉”的现象,开封附近出现沉降漏斗;最后将河南省地质图、河南省耕地面积占比、河南省年均降雨量与沉降等值线对比分析。结果表明:不同地质条件下,河南省地面沉降分布于豫东地区的第四系冲积层,而相同地质条件下,耕地占比和区域年均降雨量是地表差异性沉降的主要原因,如豫东地区耕地约占总面积的70%,地下水用于农业灌溉是豫东平原出现沉降漏斗的主要原因。

砂卵石地层矿山法隧道长管棚支护机理及应用

研究目的:砂卵石地层由于卵石强度高且颗粒分布无序,因此长管棚施工地层扰动大且支护效果难以保证,已成为制约隧道实际应用的一大瓶颈。本文以某轨道交通暗挖法车站为依托工程,采用理论分析、现场测试与数值模拟相结合的方法,对不同直径、不同环向间距条件下长管棚的支护效果进行了深入研究,以期揭示砂卵石地层矿山法隧道长管棚支护机理,提出最佳支护参数。研究结论:(1)砂卵石地层,暗挖隧道管棚超前支护条件下,地层沉降变形在向地表传递过程中,沿高度方向的折减率约为0.91 mm/m;(2)管棚超前支护效果对矿山法隧道工程安全具有决定性作用,须采取措施减小管棚施工扰动及相应地层变形;(3)根据单因素敏感性分析结果,地表沉降随管棚支护长度的增加而增大,随管棚环向间距的增大而增加,且基本呈正相关;(4)为有效控制地表沉降并提高工程经济效益,建议直径127 mm管棚环向间距宜为35 cm,支护长度宜为40 m;直径159 mm管棚建议环向间距宜为40 cm,支护长度宜为40 m;直径209 mm管棚建议环向间距宜为45 cm,支护长度宜为50 m;管棚直径与其最佳打设长度正相关;(5)本研究结论可为砂卵石地层矿山法隧道支护措施提供借鉴与参考。

基于多域物理信息神经网络的复合地层隧道掘进地表沉降预测

复合地层中盾构掘进诱发地表沉降的准确预测是隧道工程安全建设与施工决策的关键问题。基于隧道施工诱发地层变形机制构建隧道收敛变形与掘进位置的联系,并将其耦合至深度神经网络(deep neural network,简称DNN)框架,建立了预测盾构掘进诱发地层变形的物理信息神经网络(physics-informed neural network,简称PINN)模型。针对隧道上覆多个地层的地质特征,提出了多域物理信息神经网络(multi-physics-informed neural network,简称MPINN)模型,实现了在统一的框架内对不同地层的物理信息分区域表达。结果表明:MPINN模型高度还原了有限差分法的计算结果,可以准确预测复合地层中隧道开挖诱发的地表沉降;由于融入了物理机制,MPINN模型对隧道施工诱发地表沉降的问题具有普适性,可应用于不同地质和几何条件下隧道诱发地表沉降的预测;基于工程实测数据,提出的MPINN模型准确预测了监测断面的地表沉降曲线,可为复合地层下盾构掘进过程中地表沉降的预测预警提供参考。

埋地燃气PE管道在地面沉降作用下的应力分析

为了研究在地面沉降作用下PE燃气管道的受力特性及失效原因,借助ANSYS软件,探究了在地面沉降作用下PE100、管径DN110、e=10的燃气PE管道的应力-应变响应情况,分析了管道失效影响因素以及失效原因,并得出管道的失效危险点、管道极限沉降位移及极限截面变化率。结果表明:在地面沉降作用下管道的失效危险点出现在沉降区与非沉降区交接处的管道内表面;且在地面沉降作用下,管道产生的压缩变形是导致管道失效的主要原因,管道弯曲变形的存在会使管道的压缩变形更加严重。这为防治埋地燃气聚乙烯管道在地面沉降作用下的管道安全评估提供理论参考。

Study on Ground Deformation during Shield Tunnel Construction

Through the systematic analysis of the ground settlement generated by the process of shield tunneling,the relationships between ground deformation and construction parameters are studied in this paper.Based on the assumption of linear small deformation,a mathematical model of the relationship between ground deformation and construction parameters is set up.The principle and method of optimization for estimating ground deformation is studied.The actual measured data are compared with the results of theoretical analysis in a case.Considering different ground formations in different construction sites with different adverse effects on surface and underground structures,the ground surface deformations caused by shield tunneling is an aimed topic in this paper.The contributions and research implications are the revealed relationships between the ground deformation and the shield tunneling parameters during construction.

软土地层基坑群模型试验相似材料研制及应用

针对基坑群连续开挖存在的耦合效应问题,首先确定相似材料配比方案,通过正交试验得出合理的配比材料,进而设计基坑群模型试验来研究两侧基坑叠加作用影响下车站基坑的围护结构和土体表层变形.研究结果表明:满足该软土地层相似常数的土层材料配比为(石英砂∶滑石粉∶双飞粉∶膨润土∶水=0.27∶0.27∶0.232∶0.058∶0.17);基坑群开挖时由于相邻墙体引起的墙后土拱效应叠加导致坑间土体水平应力降低,围护结构受力和变形量减小,坑间土体沉降量增大;基坑间距是支护结构变形的主要影响因素,两侧基坑间距位于1H~2H之间(H为基坑深度),接近1倍开挖深度一侧的叠加影响大于接近2倍开挖深度一侧.

基于约束随机场的基坑开挖变形概率评估方法

为综合考虑岩土参数的空间变异性以及前期地质勘查所获取钻孔数据的确定性,提升基坑开挖变形风险评估的准确性,提出基于约束随机场的基坑开挖变形概率评估方法。所提方法利用克里金(Kriging)理论和随机场理论,生成考虑地勘钻孔数据的约束随机场,并结合数值分析和蒙特卡洛(Monte-Carlo)方法建立基坑开挖的概率评估模型,分析参数空间变异性对基坑开挖引起的环境效应和围护结构变形的影响规律。与传统确定性分析和基于传统随机场的概率分析进行对比,结果表明:基于约束随机场的概率分析方法能够很好地避免传统确定性分析低估风险以及传统随机场方法高估风险的问题,从而更合理地评估工程风险。研究成果可以为进一步制定基坑开挖风险的应对措施提供有益参考。

盾构隧道下穿对高速铁路CFG桩复合路基影响规律研究

针对城市地铁隧道下穿高速铁路的施工过程中,CFG桩复合路基对地层沉降的响应机理不明确、路基的沉降预测与控制理论缺乏的问题,依托郑州轨道交通8号线盾构区间下穿郑州东站咽喉区工程,提出CFG桩复合路基沉降预测方法 .基于地基加固理论,分析CFG桩对路基的加固效果,并通过物理模型试验,研究盾构隧道下穿对高速铁路CFG桩复合路基的影响规律.研究结果表明:CFG桩可以大幅提升路基压缩模量,盾构隧道下穿不会影响CFG桩复合路基的整体性,复合路基的变形规律符合Peck沉降曲线;CFG桩复合路基能够将地层的等效内摩擦角提高约50%,降低约23%的地层沉降量;盾构隧道下穿引起CFG桩复合路基的沉降量最大值为1.65 mm,在盾构隧道掌子面距离路基中线10 m时地层开始发生显著沉降变形,其中83.6%沉降量发生在盾构穿越阶段;盾构远离阶段,路基沉降量仍会继续增大,建议沉降监测持续到沉降稳定.研究结果可为盾构隧道下穿高速铁路CFG桩复合路基的沉降预测和加固处理提供参考.