Determining Methods for Soil Parameters Based on Field Measurements in Tunnel Engineering

doi:10.16183/j.cnki.jsjtu.2016.01.003

Abstract

Abstract:

In this paper, an efficient multi-objective back-analysis method of tunnel engineering was proposed by using the AMALGAM as the genetic algorithm, and by using the Pareto optimal theory as the evaluation criterion. The proposed method was applied to a test section of the West Changjiang Road tunnel project. Taking horizontal displacement as one objective, and ground settlement as the other, the soil parameters of the key layers were estimated using this method. The optimal solution was compared with the measured results, which proved that the multi-objective back analysis was superior to the single-objective back analysis in accuracy. Meanwhile, predictive analysis was taken based on the results of back analysis, and was verified as feasible. This method can provide references for environmental impact analysis of tunnel engineering.

Key words: tunnel engineering, environment effects, multi-objective, soil parameters

CLC Number:

TU745.3

REN Ying-nan, CHEN Jinjian, HUANG Zhonghui, WANG Jianhua. Determining Methods for Soil Parameters Based on Field Measurements in Tunnel Engineering[J]. Journal of Shanghai Jiao Tong University, 2016, 50(01): 17-21,29.

Figures/Tables 8

Fig. 1

Fig. 2

Fig. 3

Tab. 1

Fig. 4

Fig. 5

Fig. 6

Fig. 7

References 11

[1]	KAVANAGH K T, CLOUGH R W. Finite element applications in the characterization of elastic solids[J]. International Journal of Solids and Structures, 1971, 7(3): 11-23.
[2]	王登刚, 刘迎曦, 李守巨. 岩土工程位移反分析的遗传算法[J]. 岩石力学与工程学报, 2000, 19(增): 979-982.
	WANG Denggang, LIU Yingxi, LI Shouju. Genetic algorithms for inverse analysis of displacements in geotechnical engineering[J]. Chinese Journal of Rock Mechanics and Engineering, 2000, 19(Sup): 979-982.
[3]	高炜, 郑颖人. 采用快速遗传算法进行岩土工程反分析[J]. 岩土工程学报, 2001, 23(1): 120-122.
	GAO Wei, ZHENG Yingren. Back analysis in geotechnical engineering based on fast-convergent genetic algorithm[J]. Chinese Journal of Geotechnical Engineering, 2001, 23(1): 120-122.
[4]	冯建龙, 张孟喜. BP网络在双连拱隧道围岩参数反分析中的应用[J]. 上海大学学报(自然科学版), 2005, 11(3): 293-297.
	FENG Jianlong, ZHANG Mengxi. BP neural networks applied to displacement back-analysis for two-arch tunnel[J]. Journal of Shanghai University(Natural Science), 2005, 11(3): 293-297.
[5]	闫静雅, 张子新, 黄宏伟. 京珠高速公路温泉隧道的施工监测及位移反分析[J]. 公路交通科技, 2005, 22(8): 65-69.
	YAN Jingya, ZHANG Zixin, HUANG Hongwei. Monitoring and back analysis of displacement of Jing zhu Expressway Wenquan Tunnel[J]. Journal of Highway and Transportation Research and Development, 2005, 22(8): 65-69.
[6]	HUANG Zhonghui, ZHANG Lulu, CHENG Shiyuan. Back-analysis and parameter identification for deep excavation based on pareto multi-objective optimization[J]. Journal of Aerospace Engineering, 2014, 28(6): A4014007.
[7]	VRUGT J A, ROBINSON B A. Improved evolutionary optimization from genetically adaptive multimethod search[J]. Proceedings of the National Academy of Sciences of the United States of America, 2007, 104(3): 708-711.
[8]	陈鹏. 基于Pareto多目标遗传算法的CMOS运放优化设计[D]. 杭州: 杭州电子科技大学研究生院, 2012.
[9]	MADSEN H. Parameter estimation in distributed hydrological catchment modelling using automatic calibration with multiple objectives[J]. Advances in Water Resources, 2003, 26(2): 205-216.
[10]	MERTENS J, MADSEN H, FEYEN L, et al. Including prior information in the estimation of effective soil parameters in unsaturated zone modelling[J]. Journal of Hydrology, 2004, 294(4): 251-269.
[11]	LIU Chao, ZHANG Zixin, REGUEIRO R A. Pile and pile group response to tunneling using a large diameter slurry shield-case study in Shanghai[J]. Computers and Geotechnics, 2014, 59: 21-43.

土层	M	κ	μ
④	0.989 7	0.011	0.20
⑤	0.472 1	0.005	0.20
⑥	1.112 5	0.042	0.47

[1]	ZHANG Aoyuan, HU Xiaofeng, ZHANG Yahui. Rescheduling of Multi-Scenario and Multi-Objective Dynamic Changes of Ship Group Construction [J]. Journal of Shanghai Jiao Tong University, 2025, 59(4): 476-488.
[2]	MI Yang, CHEN Yuyang, CHEN Boyang, HAN Yunhao, YUAN Minghan. Shared Energy Storage Multi-Objective Allocation Strategy Considering Integrated Energy Microgrid Access to Active Distribution Network [J]. Journal of Shanghai Jiao Tong University, 2024, 58(9): 1309-1322.
[3]	ZHANG He(张赫), ZHOU Zhengkai(周正凯), LIN Huanyu（林环宇）, WANG Tianci（王天慈）. Optimization of Highway-Railway Level Crossing in Port Area with Priority of Key Lanes [J]. J Shanghai Jiaotong Univ Sci, 2024, 29(5): 791-800.
[4]	DU Haikuo^1,2 (杜海阔), GUO Zhengyu^3，4(郭正玉), ZHANG Lulu^1,2(章露露), CAI Yunze^1,2∗ (蔡云泽). Multi-Objective Loosely Synchronized Search for Multi-Objective Multi-Agent Path Finding with Asynchronous Actions [J]. J Shanghai Jiaotong Univ Sci, 2024, 29(4): 667-677.
[5]	MIAO Zhenhua(苗镇华), HUANG Wentao(黄文焘), ZHANG Yilian(张依恋), FAN Qinqin(范勤勤). Multi-Robot Task Allocation Using Multimodal Multi-Objective Evolutionary Algorithm Based on Deep Reinforcement Learning [J]. J Shanghai Jiaotong Univ Sci, 2024, 29(3): 377-387.
[6]	ZHANG Liang, ZHENG Lidong, LENG Xiangbiao, LÜ Ling, CAI Guowei. Multi-Objective Optimization Strategy for Wind-Photovoltaic-Pumped Storage Combined System Based on Gray Wolf Algorithm [J]. Journal of Shanghai Jiao Tong University, 2024, 58(10): 1554-1566.
[7]	ZHONG Kexing, DING Lesheng, ZHANG Cong, MAO Yandong, CHEN Jinlong. Optimization Design of Marine cable of Wind Farm Bend Restrictor Based on Neural Network [J]. Ocean Engineering Equipment and Technology, 2024, 11(1): 70-76.
[8]	PENG Bin, LIU Huixin, TAO Yaohui. Geometrical Model and Optimization of Scroll Compressor Based on Involute of Circle with Variable Radii [J]. Journal of Shanghai Jiao Tong University, 2023, 57(8): 1046-1054.
[9]	ZHU Hainan, WANG Juanjuan, CHEN Bingbing, ZHANG Houwang, CHEN Jian, WU Qiuwei. Multi-Objective Planning of Power-Gas Integrated Energy System Considering Economy and Carbon Emission [J]. Journal of Shanghai Jiao Tong University, 2023, 57(4): 422-431.
[10]	SHAO Ping, YANG Zhile, LI Kang, ZHU Xiaodong. Multi-Objective Optimization of Electric Vehicle Spare Capacity Based on User Wishes [J]. Journal of Shanghai Jiao Tong University, 2023, 57(11): 1501-1511.
[11]	MA Zhoujun, WANG Yong, WANG Jie, CHEN Shaoyu. A Dual Cooperative Optimization for Optimal Redundancy Quantity of MMC Submodules of Flexible Controller [J]. Journal of Shanghai Jiao Tong University, 2022, 56(3): 325-332.
[12]	ZENG Bo, MU Hongwei, DONG Houqi, ZENG Ming. Optimization of Active Distribution Network Operation Considering Decarbonization Endowment from 5G Base Stations [J]. Journal of Shanghai Jiao Tong University, 2022, 56(3): 279-292.
[13]	HE Wei, SUN Honglei, TAO Yuanqin, CAI Yuanqiang. Dynamic Multi-Objective Optimization Inverse Prediction of Excavation-Induced Tunnel Displacement [J]. Journal of Shanghai Jiao Tong University, 2022, 56(12): 1688-1699.
[14]	YANG Bo, WANG Junting, YU Lei, CAO Pulin, SHU Hongchun, YU Tao. Peafowl Optimization Algorithm Based Bi-Level Multi-Objective Optimal Allocation of Energy Storage Systems in Distribution Network [J]. Journal of Shanghai Jiao Tong University, 2022, 56(10): 1294-1307.
[15]	LI Lingfang, CHEN Zhanpeng, HU Yan, TAI Nengling, GAO Mengping, ZHU Tao. Expansion Planning of Renewable Energy Power System Considering Flexibility and Economy [J]. Journal of Shanghai Jiao Tong University, 2021, 55(7): 791-801.