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Prediction of shield tunneling-induced ground settlement using machine learning techniques

Renpeng CHEN, Pin ZHANG, Huaina WU, Zhiteng WANG, Zhiquan ZHONG

《结构与土木工程前沿（英文）》 2019年第13卷第6期页码 1363-1378 doi: 10.1007/s11709-019-0561-3

摘要： Predicting the tunneling-induced maximum ground surface settlement is a complex problem since the settlement depends on plenty of intrinsic and extrinsic factors. This study investigates the efficiency and feasibility of six machine learning (ML) algorithms, namely, back-propagation neural network, wavelet neural network, general regression neural network (GRNN), extreme learning machine, support vector machine and random forest (RF), to predict tunneling-induced settlement. Field data sets including geological conditions, shield operational parameters, and tunnel geometry collected from four sections of tunnel with a total of 3.93 km are used to build models. Three indicators, mean absolute error, root mean absolute error, and coefficient of determination the ( ) are used to demonstrate the performance of each computational model. The results indicated that ML algorithms have great potential to predict tunneling-induced settlement, compared with the traditional multivariate linear regression method. GRNN and RF algorithms show the best performance among six ML algorithms, which accurately recognize the evolution of tunneling-induced settlement. The correlation between the input variables and settlement is also investigated by Pearson correlation coefficient.

关键词： EPB shield shield tunneling settlement prediction machine learning

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Finite element prediction on the response of non-uniformly arranged pile groups considering progressive

Qian-Qing ZHANG, Shan-Wei LIU, Ruo-Feng FENG, Jian-Gu QIAN, Chun-Yu CUI

《结构与土木工程前沿（英文）》 2020年第14卷第4期页码 961-982 doi: 10.1007/s11709-020-0632-5

摘要： A uniform arrangement of individual piles is commonly adopted in the conventional pile group foundation, and basin-shaped settlement is often observed in practice. Large differential settlement of pile groups will decrease the use-safety requirements of building, even cause the whole-building tilt or collapse. To reduce differential settlement among individual piles, non-uniformly arranged pile groups can be adopted. This paper presents a finite element analysis on the response of pile groups with different layouts of individual piles in pile groups. Using the user-defined subroutine FRIC as the secondary development platform, a softening model of skin friction and a hyperbolic model of end resistance are introduced into the contact pair calculation of ABAQUS software. As to the response analysis of a single pile, the reliability of the proposed secondary development method of ABAQUS software is verified using an iterative computer program. The reinforcing effects of individual piles is then analyzed using the present finite element analysis. Furthermore, the response of non-uniformly arranged pile groups, e.g., individual piles with variable length and individual piles with variable diameter, is analyzed using the proposed numerical analysis method. Some suggestions on the layout of individual piles are proposed to reduce differential settlement and make full use of the bearing capacity of individual piles in pile groups for practical purposes.

关键词： numerical simulation non-uniformly arranged pile groups differential settlement pile-soil interaction

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Long-term settlement behavior of ground around shield tunnel due to leakage of water in soft deposit

Huaina WU, Yeshuang XU, Shui-long SHEN, Jin-chun CHAI

《结构与土木工程前沿（英文）》 2011年第5卷第2期页码 194-198 doi: 10.1007/s11709-011-0105-y

摘要： The lining of shield tunnel is usually composed of segments, in which the joints, cracks, and the grouting holes (hereafter called lining deficit) exist. During the long-term running, soils and groundwater may leak from these kinds of lining deficit. The leaking of soil and groundwater causes the long-term ground loss around tunnel and thus results in the settlement of ground surface. This paper aims to analyze the impact of the leakage of groundwater through segments on the long-term settlement of ground surface. The adopted analytical method is based on the theory of groundwater seepage by using numerical simulation. The analyzed results show that settlement of ground surface increases gradually with the increase of the leaked volume of tunnel segments. When the leaked volume was unevenly distributed, differential settlement occurred locally. Comparative analysis by changing the leaked volume was conducted. The results reveal that there is a linear relationship between settlement and leaked volume when the leaked volume was controlled within the allowable limit.

关键词： lining deficit leakage of water shield tunnel settlement soft deposit

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Reliability-based settlement analysis of embankments over soft soils reinforced with T-shaped deep cement

Chana PHUTTHANANON; Pornkasem JONGPRADIST; Daniel DIAS; Xiangfeng GUO; Pitthaya JAMSAWANG; Julien BAROTH

《结构与土木工程前沿（英文）》 2022年第16卷第5期页码 638-656 doi: 10.1007/s11709-022-0825-1

摘要： This paper presents a reliability-based settlement analysis of T-shaped deep cement mixing (TDM) pile-supported embankments over soft soils. The uncertainties of the mechanical properties of the in-situ soil, pile, and embankment, and the effect of the pile shape are considered simultaneously. The analyses are performed using Monte Carlo Simulations in combination with an adaptive Kriging (using adaptive sampling algorithm). Individual and system failure probabilities, in terms of the differential and maximum settlements (serviceability limit state (SLS) requirements), are considered. The reliability results for the embankments supported by TDM piles, with various shapes, are compared and discussed together with the results for conventional deep cement mixing pile-supported embankments with equivalent pile volumes. The influences of the inherent variabilities in the material properties (mean and coefficient of variation values) on the reliability of the piled embankments, are also investigated. This study shows that large TDM piles, particularly those with a shape factor of greater than 3, can enhance the reliability of the embankment in terms of SLS requirements, and even avoid unacceptable reliability levels caused by variability in the material properties.

关键词： T-shaped deep cement mixing piles piled embankments settlement reliability analysis soil uncertainties

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区域性沉降对高速铁路基础设施影响的研究

康高亮

《工程（英文）》 2016年第2卷第3期页码 374-379 doi: 10.1016/J.ENG.2016.03.014

摘要：

本文对高速铁路线路基础沉降及差异沉降的主要影响因素进行了分析，提出局部地下水开采是影响线路差异沉降的直接诱因。通过对不同差异沉降量下无砟轨道附加荷载及高速行车过程中车辆、轨道和桥梁动力响应的研究，初步提出了运营期线路基础差异沉降控制标准。

关键词：区域沉降差异沉降无砟轨道附加荷载车辆&ndash 轨道动力学

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DX桩单桩沉降的理论计算研究

欧阳义,陈立宏,张德华

《中国工程科学》 2012年第14卷第1期页码 74-79

摘要：

DX桩由于承力盘的存在，改变了桩的荷载传递机理，在提高承载力的同时，沉降变形也显著减小。在桩的现场试验基础上，分析了DX桩与等截面桩的桩顶荷载的分配特性，进而依据Mindlin解和Geddes解求解桩端土的附加应力，编制了相应的程序，计算结果表明在同样的荷载条件下，DX桩的沉降是等截面桩的0.55~0.80倍，并对承力盘的变化引起的DX桩的沉降变化进行了分析。

关键词： DX桩承力盘沉降附加应力

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DX桩单桩沉降分析

唐松涛,袁希雨,陈立宏

《中国工程科学》 2012年第14卷第1期页码 41-45

摘要：

DX桩作为变截面桩型的典型代表，具有与普通直孔灌注桩不同的荷载传递机理，使桩基的承载力大大提高，沉降变形显著减小。多点支承的特点使得DX桩的沉降机理变得十分复杂，计算分析困难。通过对DX单桩沉降的实例分析，对DX桩与直孔桩的沉降特性进行对比，验证了设计规程中DX桩的沉降计算公式和修正系数的可靠性。

关键词： DX桩直孔桩沉降修正系数

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山水城市——21世纪中国的人居环境

鲍世行

《中国工程科学》 2002年第4卷第9期页码 19-23

摘要：

20世纪90年代，中国掀起了一场关于21世纪社会主义中国城市发展模式的大讨论。钱学森教授提出的山水城市概念是把中国传统文化中的山水诗词、山水画和中国古典园林与现代城市建设结合起来。山水城市的核心思想是，兼顾城市生态和历史文化，兼顾现代科技和环境美学；它考虑未来城市生产、生活发展的需要；它是为中国老百姓享受的生活、工作环境。21世纪是城市的世纪，主要是发展中国家的城市化。中国已经开始进入城市化高速发展的时期，世界关注中国城市化发展的道路。这是山水城市讨论的时代背景。中华民族对山水有特殊的感情，山水意识几乎融入中华民族的遗传基因，山水文化的特色之一是综合艺术，这是山水城市的文化背景。

关键词：山水城市钱学森人居环境

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京津城际铁路桥梁沉降观测与评估技术

丁愿文

《中国工程科学》 2009年第11卷第1期页码 43-47

摘要：

以京津城际铁路工程为例，系统地介绍了无碴轨道客运专线（高速铁路）桥梁沉降观测的具体要求、方法，并提出了沉降评估的数学模型和判定条件。

关键词：京津城际铁路桥梁沉降观测评估

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客运专线路基动态施工控制及沉降预测

王国体,吴吉祥,李刚,王轶昕

《中国工程科学》 2011年第13卷第3期页码 50-55

摘要：

依据合武（合肥-武汉）Ⅰ标段设置路基沉降观测的数据，提出了对高速铁路路基施工进行动态控制方程的公式形式和工后路基沉降预测的依据与具体实现，并结合典型观测数据进行分析和路基施工控制，确保路基质量、沉降、工期要求。

关键词：高速铁路客运专线路基施工施工动态控制沉降预测

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非工程因素引发的高速铁路沉降问题及其对策探讨

尤昌龙

《中国工程科学》 2014年第16卷第2期页码 106-112

摘要：

结合当前非工程因素引发的高速铁路线路沉降问题相关案例，分析了线路沉降超标产生的原因及其危害，归纳了相关问题类型，提出了解决问题的相关建议和意见，希冀有助于类似问题的解决。

关键词：高速铁路线路非工程因素非工程因素沉降

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Spatial prediction of soil contamination based on machine learning: a review

《环境科学与工程前沿（英文）》 2023年第17卷第8期 doi: 10.1007/s11783-023-1693-1

摘要：

● A review of machine learning (ML) for spatial prediction of soil contamination.

关键词： Soil contamination Machine learning Prediction Spatial distribution

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基于拱顶沉降控制的卵砾石地层浅埋隧道施工优化

喻军,刘松玉,龚晓南

《中国工程科学》 2013年第15卷第10期页码 97-102

摘要：

某卵砾石地层浅埋公路隧道施工开挖，围岩的稳定性与拱顶沉降存在密切的关系，因此采用仿真分析法以拱顶沉降为控制目标，确保围岩的稳定，分析不同的施工方案得到拱顶沉降规律，达到优化施工的目的；同时，分析了不同的开挖路径和台阶长度，提出了一种最佳的施工方案。结果表明：在浅埋隧道开挖时容易引起拱顶沉降，并且随着施工方案的不同，拱顶沉降有较大的差异。在几种施工方法中，发现CRD法（交叉中隔墙法）比较适合，原因是拱顶沉降最小，应力释放较慢，在渐近的过程中有效地实现了应力的转移，较台阶法和CD法（中隔墙法）有大的优势，并与现场监测进行了对比分析，结果较为吻合。得到的结论可为类似工程提供参考。

关键词：卵砾石隧道围岩数值分析施工优化拱顶沉降现场监测

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Hybrid deep learning model for risk prediction of fracture in patients with diabetes and osteoporosis

《医学前沿（英文）》 2022年第16卷第3期页码 496-506 doi: 10.1007/s11684-021-0828-7

摘要： The fracture risk of patients with diabetes is higher than those of patients without diabetes due to hyperglycemia, usage of diabetes drugs, changes in insulin levels, and excretion, and this risk begins as early as adolescence. Many factors including demographic data (such as age, height, weight, and gender), medical history (such as smoking, drinking, and menopause), and examination (such as bone mineral density, blood routine, and urine routine) may be related to bone metabolism in patients with diabetes. However, most of the existing methods are qualitative assessments and do not consider the interactions of the physiological factors of humans. In addition, the fracture risk of patients with diabetes and osteoporosis has not been further studied previously. In this paper, a hybrid model combining XGBoost with deep neural network is used to predict the fracture risk of patients with diabetes and osteoporosis, and investigate the effect of patients’ physiological factors on fracture risk. A total of 147 raw input features are considered in our model. The presented model is compared with several benchmarks based on various metrics to prove its effectiveness. Moreover, the top 18 influencing factors of fracture risks of patients with diabetes are determined.

关键词： XGBoost deep neural network healthcare risk prediction

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Position-varying surface roughness prediction method considering compensated acceleration in milling

《机械工程前沿（英文）》 2021年第16卷第4期页码 855-867 doi: 10.1007/s11465-021-0649-z

摘要： Machined surface roughness will affect parts’ service performance. Thus, predicting it in the machining is important to avoid rejects. Surface roughness will be affected by system position dependent vibration even under constant parameter with certain toolpath processing in the finishing. Aiming at surface roughness prediction in the machining process, this paper proposes a position-varying surface roughness prediction method based on compensated acceleration by using regression analysis. To reduce the stochastic error of measuring the machined surface profile height, the surface area is repeatedly measured three times, and Pauta criterion is adopted to eliminate abnormal points. The actual vibration state at any processing position is obtained through the single-point monitoring acceleration compensation model. Seven acceleration features are extracted, and valley, which has the highest R-square proving the effectiveness of the filtering features, is selected as the input of the prediction model by mutual information coefficients. Finally, by comparing the measured and predicted surface roughness curves, they have the same trends, with the average error of 16.28% and the minimum error of 0.16%. Moreover, the prediction curve matches and agrees well with the actual surface state, which verifies the accuracy and reliability of the model.

关键词： surface roughness prediction compensated acceleration milling thin-walled workpiece