Assessment of compressive strength of jet grouting by machine learning

Jet grouting is one of the most popular soil improvement techniques,but its design usually involves great uncertainties that can lead to economic cost overruns in construction projects.The high dispersion in the properties of the improved material leads to designers assuming a conservative,arbitrary and unjustified strength,which is even sometimes subjected to the results of the test fields.The present paper presents an approach for prediction of the uniaxial compressive strength(UCS)of jet grouting columns based on the analysis of several machine learning algorithms on a database of 854 results mainly collected from different research papers.The selected machine learning model(extremely randomized trees)relates the soil type and various parameters of the technique to the value of the compressive strength.Despite the complex mechanism that surrounds the jet grouting process,evidenced by the high dispersion and low correlation of the variables studied,the trained model allows to optimally predict the values of compressive strength with a significant improvement with respect to the existing works.Consequently,this work proposes for the first time a reliable and easily applicable approach for estimation of the compressive strength of jet grouting columns.

Grouting theories and technologies for the reinforcement of fractured rocks surrounding deep roadways

Grouting is an effective method to improve the integrity and stability of fractured rocks that surround deep roadways.After years of research and practice,various theories and a complete set of grouting technologies for deep roadways with fractured rocks have been developed and are widely applied in Chinese coal mining production.This paper systematically summarizes and analyzes the research results concerning the theory,design,materials,processes,and equipment for the grouting and reinforcement of fractured rocks surrounding deep roadways.Specifically,in terms of grouting methods,pregrouting,groutingwhile-excavation,and postgrouting methods are explored;in terms of grouting theory,backfill grouting,compaction grouting,infiltration grouting,and fracture grouting theories are studied.In addition,this paper also studies grouting borehole arrangement,water-cement ratio,grouting pressure,grouting volume,grout diffusion radius,and other grouting parameters and their determination methods.On this basis,this paper explores the physical and mechanical properties of organic and organic-inorganic composite grouting materials,and assess grouting reinforcement quality testing methods and instruments.Taken as the field cases,the application of pregrouting in front of heading faces,groutingwhile-excavation,and postgrouting in the Kouzidong coal mine are then introduced,and the effects of the grouting reinforcements are evaluated.This paper proposes a development direction for grouting technology based on problems existing in the grouting reinforcement of fractured rocks surrounding deep roadways.

Theory,technology and application of grouted bolting in soft rock roadways of deep coal mines

The grouted bolt,combining rock bolting with grouting techniques,provides an effective solution for controlling the surrounding rock in deep soft rock and fractured roadways.It has been extensively applied in numerous deep mining areas characterized by soft rock roadways,where it has demonstrated remarkable control results.This article systematically explores the evolution of grouted bolting,covering its theoretical foundations,design methods,materials,construction processes,monitoring measures,and methods for assessing its effectiveness.The overview encompassed several key elements,delving into anchoring theory and grouting reinforcement theory.The new principle of high pretensioned high-pressure splitting grouted bolting collaborative active control is introduced.A fresh method for dynamic information design is also highlighted.The discussion touches on both conventional grouting rock bolts and cable bolts,as well as innovative grouted rock bolts and cables characterized by their high pretension,strength,and sealing hole pressure.An examination of the merits and demerits of standard inorganic and organic grouting materials versus the new inorganic–organic composite materials,including their specific application conditions,was conducted.Additionally,the article presents various methods and instruments to assess the support effect of grouting rock bolts,cable bolts,and grouting reinforcement.Furthermore,it provides a foundation for understanding the factors influencing decisions on grouted bolting timing,the sequence of grouting,the pressure applied,the volume of grout used,and the strategic arrangement of grouted rock bolts and cable bolts.The application of the high pretensioned high-pressure splitting grouted bolting collaborative control technology in a typical kilometer-deep soft rock mine in China—the soft coal seam and soft rock roadway in the Kouzidong coal mine,Huainan coal mining area,was introduced.Finally,the existing problems in grouted bolting control technology for deep soft rock roadways are analyzed,and the future development trend of grouted bolting control technology is anticipated.

Prediction of surface settlement caused by synchronous grouting during shield tunneling in coarse-grained soils:A combined FEM and machine learning approach

This paper presents a surrogate modeling approach for predicting ground surface settlement caused by synchronous grouting during shield tunneling process.The proposed method combines finite element simulations with machine learning algorithms and introduces an intelligent optimization algorithm to invert geological parameters and synchronous grouting variables,thereby predicting ground surface settlement without conducting numerous finite element analyses.Two surrogate models based on the random forest algorithm are established.The first is a parameter inversion surrogate model that combines an artificial fish swarm algorithm with random forest,taking into account the actual number and distribution of complex soil layers.The second model predicts surface settlement during synchronous grouting by employing actual cover-diameter ratio,inverted soil parameters,and grouting variables.To avoid changes to input parameters caused by the number of overlying soil layers,the dataset of this model is generated by the finite element model of the homogeneous soil layer.The surrogate modeling approach is validated by the case history of a large-diameter shield tunnel in Beijing,providing an alternative to numerical computation that can efficiently predict surface settlement with acceptable accuracy.

In situ experimental study on TBM excavation with high-pressure water-jet-assisted rock breaking

China’s first high-pressure hydraulically coupled rock-breaking tunnel boring machine(TBM) was designed to overcome the rock breaking problems of TBM in super-hard rock geology, where high-pressure water jet system is configured, including high-flow pump sets, high-pressure rotary joint and high-pressure water jet injection device. In order to investigate the rock breaking performance of high-pressure water-jet-assisted TBM, in situ excavation tests were carried out at the Wan’anxi Water Diversion Project in Longyan, Fujian Province, China, under different water jet pressure and rotational speed. The rock-breaking performance of TBM was analyzed including penetration, cutterhead load, advance rate and field penetration index. The test results show that the adoption of high-pressure water-jet-assisted rock breaking technology can improve the boreability of rock mass, where the TBM penetration increases by 64% under the water jet pressure of 270 MPa. In addition, with the increase of the water jet pressure, the TBM penetration increases and the field penetration index decreases. The auxiliary rock-breaking effect of high-pressure water jet decreases with the increase of cutterhead rotational speed. In the case of the in situ tunneling test parameters of this study, the advance rate is the maximum when the pressure of the high-pressure water jet is 270 MPa and the cutterhead rotational speed is 6 r/min. The technical superiority of high-pressure water-jet-assisted rock breaking technology is highlighted and it provides guidance for the excavation parameter selection of high-pressure hydraulically coupled rock-breaking TBM.

矿物掺合料对全机制砂灌浆料的影响研究

试验采用普通硅酸盐水泥与快硬硫铝酸盐水泥的复合胶凝体系,选用石灰石机制砂作为细集料,制备全机制砂灌浆料。选用硅灰、粉煤灰与石粉作为矿物掺合料,研究矿物掺合料对全机制砂灌浆料流动度、抗压强度与竖向膨胀率的影响,并利用SEM电镜对全机制砂灌浆料进行微观机理分析。研究结果表明:矿物掺合料复掺有利于提高灌浆料的流动性能与力学性能,改善灌浆料的界面过渡区,通过正交试验优化机制砂灌浆料配方,得到的最优矿物掺合料掺量为硅灰5%、粉煤灰6%、矿粉8%。

基于机器学习的水泥基灌浆料强度预测方法

针对采用小直径芯样法准确预测水泥基灌浆料抗压强度的问题,使用压力试验机分别对水泥基灌浆料标准尺寸试块和小直径芯样进行抗压强度试验,并基于试验数据,采用支持向量机回归(SVR)和随机森林回归(RFR)对水泥基灌浆料抗压强度进行回归预测。结果表明:标准尺寸试块均呈正反相接的四角锥体破坏形态,而高径比为0.7和1.0的小直径芯样呈正反相接的圆锥体破坏形态,高径比为1.2的小直径芯样呈斜裂缝剪切破坏形态;标准尺寸试块和小直径芯样的抗压强度值均服从正态分布,且无离群值;随着龄期的增长,标准尺寸试块和小直径芯样的抗压强度提高,且具有早期强度较高的特性;直径46 mm芯样的抗压强度较小,且更易受加工精度的影响;在给定的龄期和直径下,高径比为0.7的芯样抗压强度值最大,抗压强度离散程度最小;RFR预测模型对水泥基灌浆料抗压强度的预测效果更优。所提方法可较准确预测水泥基灌浆料抗压强度,为水泥基灌浆料抗压强度的预测研究提供了参考。

灰岩含水层定向钻孔注浆效果智能评价方法研究

基于黄河北煤田邱集煤矿现场注浆工程,通过XGboost、支持向量机、K近邻和BP人工神经网络四种算法,对灰岩定向钻孔的注浆效果进行科学分析。研究表明,XGboost、支持向量机、K近邻的模型精度均达不到0.9,而BP人工神经网络测试的拟合程度达0.93,使用现场数据测试准确度达0.9,证明了BP人工神经网络评价注浆效果的可行性和准确性;最后运用MATLAB提出了一种基于BP人工神经网络的注浆效果智能化评价方法,并根据模型制作了简单的演示平台,实现了注浆效果评价的智能化与快捷化。

岩石隧道掘进机不良地质施工处置技术

岩石隧道掘进机(Tunnel Boring Machine,TBM)凭借其高效优质、作业安全等特点在铁路、公路、地铁、水利水电等领域广泛应用,在普通地质环境下推广顺利。复杂地质环境下致灾源多,如硬岩岩爆、软岩大变形、断层破碎带、涌水突泥等不良地质使TBM施工频繁出现围岩坍塌、支护失效、卡机淹井、设备损伤等问题。本文结合工程案例,从超前主动加固、注浆及锚固、管片支护、撑靴加固4个方面总结现有施工技术,以应对TBM穿越不良地质导致的刀盘卡机、护盾抱死、初期支护变形过大、撑靴打滑等问题,提升TBM在不良地质环境下的适应能力,为类似工程提供参考。

高压富水硬岩地层双护盾TBM前置式超前注浆堵水技术研究

晋中引黄输水隧洞双护盾TBM施工穿越高压富水裂隙,掌子面高压大流量突涌水严重,采用常规后置式超前注浆技术对掌子面突涌水进行超前处置效果不佳,主要原因是受外插角影响,采用常规后置式超前注浆存在注浆目标区域受限、钻探效率低、超前注浆控制难度大等问题,难以形成有效的止水帷幕结构。对隧洞水文地质条件、突涌水情况及超前注浆技术进行系统研究分析,提出双护盾TBM前置式超前注浆堵水工艺,通过优化注浆设备,在掌子面处实施超前注浆堵水。开展现场注浆试验,对坚硬岩面钻孔施工、注浆材料、注浆参数控制及注浆段长优化等技术进行研究,并根据现场试验信息,不断优化注浆设备及工艺。通过对晋中引黄输水隧洞实施前置式超前注浆堵水技术,洞内平均出水量降至3 702m~3/d,降幅达75.9%,同时在一定程度上提高了TBM施工效率。实践证明该技术方法有效。

顶升式梯形钢管混凝土支架支护技术研究及应用

白芨沟煤矿0102303工作面运输巷道位于上分层采空区下方,顶板为金属网假顶,原支护受上分层采空区扰动影响,变形严重。为此设计顶升式梯形钢管混凝土支架,通过注浆顶升试验测试各型号支架顶升性能,试验结果表明:Φ194 mm×10 mm钢管注浆效果较好,接顶力达到3.93 kN,满足支架顶升和巷道假顶初撑要求。为增加钢管梁抗弯强度,在空钢管内设置抗弯圆钢,计算得支护反力为2.3 MPa,较原支护方式提高了5.4倍。同时,为解决巷道内各类支架安装困难,设计了一种举升式支架安装机,举升力可达6.8 kN。顶升式梯形钢管混凝土支架注浆30 d后,支架荷载基本区域稳定,安装半年内支架荷载最大值为0.8 MPa,现场监测顶底板移进和两帮收敛均小于50 mm,支护效果良好。

Thickness regression for backfill grouting of shield tunnels based on GPR data and CatBoost&BO-TPE:A full-scale model test study

Ground penetrating radar(GPR)is a vital non-destructive testing(NDT)technology that can be employed for detecting the backfill grouting of shield tunnels.To achieve intelligent analysis of GPR data and overcome the subjectivity of traditional data processing methods,the CatBoost&BO-TPE model was constructed for regressing the grouting thickness based on GPR waveforms.A full-scale model test and corresponding numerical simulations were carried out to collect GPR data at 400 and 900 MHz,with known backfill grouting thickness.The model test helps address the limitation of not knowing the grout body condition in actual field detection.The data were then used to create machine learning datasets.The method of feature selection was proposed based on the analysis of feature importance and the electromagnetic(EM)propagation law in mediums.The research shows that:(1)the CatBoost&BO-TPE model exhibited outstanding performance in both experimental and numerical data,achieving R^(2)values of 0.9760,0.8971,0.8808,and 0.5437 for numerical data and test data at 400 and 900 MHz.It outperformed extreme gradient boosting(XGBoost)and random forest(RF)in terms of performance in the backfill grouting thickness regression;(2)compared with the full-waveform GPR data,the feature selection method proposed in this paper can promote the performance of the model.The selected features within the 5–30 ns of the A-scan can yield the best performance for the model;(3)compared to GPR data at 900 MHz,GPR data at 400 MHz exhibited better performance in the CatBoost&BO-TPE model.This indicates that the results of the machine learning model can provide feedback for the selection of GPR parameters;(4)the application results of the trained CatBoost&BO-TPE model in engineering are in line with the patterns observed through traditional processing methods,yet they demonstrate a more quantitative and objective nature compared to the traditional method.

Understanding microstructure-property relationships of HPDC Al-Si alloy based on machine learning and crystal plasticity simulation

Al-Si alloys manufactured via high-pressure die casting(HPDC)are suitable for a wide range of applications.However,the heterogeneous microstructure and unpredictable pore distribution of Al-Si high-pressure die castings result in significant variations in the mechanical properties,thus leading to a complicated microstructure-property relationship that is difficult to capture.Hence,a computational framework incorporating machine learning and crystal plasticity method is proposed.This framework aims to provide a systematic and comprehensive understanding of this relationship and enable the rapid prediction of macroscopic mechanical properties based on the microstructure.Firstly,we select eight variables that can effectively characterize the microstructural features and then obtain their statistical information.Subsequently,based on 160 samples obtained via the Latin hypercube sampling method,representative volume elements are constructed,and the crystal plasticity fast Fourier transformation method is executed to obtain the macroscopic mechanical properties.Next,the yield strength,elastic modulus,strength coefficient,and strain-hardening exponent are used to characterize the stress-strain curve,and Gaussian process regression models and microstructural variables are developed.Finally,sensitivity and univariate analyses based on these machine-learning models are performed to obtain insights into the microstructure-property relationships of the HPDC Al-Si alloy.The results show that the Gaussian process regression models exhibit high accuracy(R2 greater than 0.84),thus confirming the viability of the proposed method.The results of sensitivity analysis indicate that the pore size exerts the most significant effect on the mechanical properties.Furthermore,the proposed framework can not only be transferred to other alloys but also be employed for material design.

Al-enabled properties distribution prediction for high-pressure die casting Al-Si alloy

High-pressure die casting(HPDC)is one of the most popular mass production processes in the automotive industry owing to its capability for part consolidation.However,the nonuniform distribution of mechanical properties in large-sized HPDC products adds complexity to part property evaluation.Therefore,a methodology for property prediction must be developed.Material characterization,simulation technologies,and artificial intelligence(AI)algorithms were employed.Firstly,an image recognition technique was employed to construct a temperature-microstructure characteristic model for a typical HPDC Al7Si0.2Mg alloy.Moreover,a porosity/microstructure-mechanical property model was established using a machine learning method based on the finite element method and representative volume element model results.Additionally,the computational results of the casting simulation software were mapped with the porosity/microstructure-mechanical property model,allowing accurate prediction of the property distribution of the HPDC Al-Si alloy.The AI-enabled property distribution model developed in this study is expected to serve as a foundation for intelligent HPDC part design platforms in the automotive industry.

WSS追踪式注浆法在盾构气压作业地层加固中的应用探讨

WSS追踪式注浆法,是为了在盾构气压作业时,更加高效地完成地层加固,创造安全带压开仓条件。充分利用既有技术资料和动态的施工参数,通过追寻地下岩隙、孔洞、地下水通道等的分布情况,利用WSS注浆法进行相对目标准确的追踪式注浆封堵,可以极大地减少加固工作量,提高加固工作效率和质量,缩短工期,节约成本。

基于耐久性能的机制砂灌浆料复合配比研究

为研究机制砂灌浆料的力学性能和耐久性能,通过试验方法,配制C60、C80、C100三种强度灌浆料,对所配制的机制砂灌浆材料进行工作性能、力学性能、耐久性能测试。结果表明,同类型混凝土中,高强度等级混凝土抗渗性能好于低强度等级混凝土;水胶比、电通量与抗压强度呈负相关关系,机制砂混凝土强度等级越高,它的电通量越小,氯离子渗透能力越低;影响机制砂混凝土耐久性能最主要的因素是水胶比,其次是矿粉掺量,最后是粉煤灰掺量。高比例的粉煤灰掺量有助于提高机制砂灌浆料的抗硫酸盐侵蚀能力。

双护盾TBM管片壁后豆砾石与底部灌浆同步回填技术研究——以青岛地铁6号线某工程为例

为解决双护盾TBM管片壁后回填豆砾石不及时、回填效果差、灌浆滞后等问题,考虑TBM盾尾的结构形式、与围岩和管片的位置关系,针对性设计一种耐磨、易拆卸、高弹性、封堵效果良好的新型TBM盾尾封堵板,提出豆砾石与底部灌浆同步回填技术,并在青岛地铁6号线某区间进行现场试验,验证该技术的可行性,得到浆液配比、灌浆量、灌浆点位等关键指标。结果表明:1)封堵板的安装能够使豆砾石提前吹填,实现底部同步灌浆;2)采用水灰比为2.3∶5的浆液稠度低于13 cm,能够满足向豆砾石孔隙渗透的要求,又能避免因稠度不足而导致的灌浆过程中的流失;3)灌浆点位建议设在管片4点钟和8点钟(时钟方位)位置,位置过高或过低都容易导致浆液流失。

盾构区间下穿既有线工程参数分析

研究分析了盾构区间下穿既有线的施工方法及各项施工参数,通过对正在施工的盾构区间下穿既有线的研究现状及经验总结,分析其存在的问题及其原因,提出适合本地实际的盾构区间下穿既有建、构筑物对应的施工工法及参数。同时结合实际工程实例进行了论证与验证。

自动压浆机校准方法探讨及不确定度分析

本文对自动压浆机的运用及校准方法进行探讨,并分析和评定其压力示值误差的不确定度。

水平注浆技术在盾构接收端头加固中的运用

为解决绍兴市轨道交通2号线某区间盾构接收端头地面加固区域因存在大量抛石、方桩、管桩等障碍物而不具备地面加固条件的难题,采取水平注浆技术对盾构接收端头的土体进行加固,以保证盾构顺利接收,缩短施工工期。经检测,盾构接收端头水平注浆加固的强度满足规范要求,洞门探孔和洞门破除后均未出现涌水现象,证明了水平注浆技术在地下水、地层固结、增强地基强度上起到了良好的效果,有效提高了盾构接收端头土体的自稳能力和止水效果,可为后续类似工程提供借鉴。