期刊文献+

基于多因素的盾构施工诱发地表变形动态模拟 被引量:2

Study on Simulation of Ground Deformation Caused by Shield Construction Based on Analysis of Multi-factor
下载PDF
导出
摘要 盾构施工诱发地表变形与岩土介质条件有关,并受到隧道几何特征、施工工况、施工环境等因素变化的影响。本文以武汉地铁2号线项目为工程背景,根据地表变形监测数据,研究盾构施工中影响地表变形的因素,将地表变形分解为趋势变形与随机变形,建立地表变形与主要影响因素之间的非线性关系。采用改进的智能计算方法建立非线性系统进行智能辨识,用于构建多因素-双模的地表变形分析系统(MDIAS),模拟分析多个影响因素作用下的地表变形。结果表明,MDIAS系统在用于隧道施工诱发地表变形计算方面,不仅能够较好地反映各种因素对地表变形的影响作用,而且能够动态地模拟复杂条件下的地表变形演化规律,具有较高准确性与可靠性。 Ground deformations induced by tunneling is not only affected by rock soil media conditions, but also affected by the other factors (i. e. , tunnel geometry, shield operations and construction environment). Taking Wuhan subway line 2 as the background, the influence factors on effects of the deformation in tunneling are investigated based on the measured deformation data. And the ground deformations decomposed into trend deformation and stochastic deformation. The nonlinear relation between influence factors and ground is established. Meanwhile, an improved intelligent method is employed to identify the nonlinear system. And a multi-factor dual-mode intelligence analysis system (MDIAS) is constructed. The deformations are simulated by the MDIAS based on the variation factors. It is shown that MDIAS can not only preferably reflect the various factors in deformation calculation, but also dynamical simulate the deformation evolution in the complicated condition. MDIAS is an effective tool for estimating soil deformation.
出处 《土木工程与管理学报》 2013年第1期81-86,92,共7页 Journal of Civil Engineering and Management
基金 "十二五"国家科技支撑计划课题(2012BAK24B01)
关键词 地表变形 隧道工程 影响因素 非线性辨识 ground deformation tunneling engineering influence factors nonlinear identification
  • 相关文献

参考文献14

  • 1Ding Lieyun, Ma Ling, Luo Hanbin, et al. Wavelet a- nalysis for tunneling-induced ground settlement based on a stochastic model [ J ]. Tunnelling and Under- ground Space Technology, 2011, 26 (5) : 619-628.
  • 2Peck R B. Deep Excavations and Tunneling in Soft Ground [ C ] //J 7th International Conference on Soil Mechanics and Foundation Engineering. Stockholm, 1969, 7(3): 225-290.
  • 3Schmidt B. Settlements and Ground Movements Asso- ciated with Tunneling in Soils [ D ]. Urbana: Universi- ty of Illinois, 1969.
  • 4陶履彬 侯学渊.圆形隧道的应力场和位移场[J].隧道及地下工程,1986,7(1):9-19.
  • 5久武胜保,张金奎.软岩隧道的非线性弹塑性状态[J].隧道译丛,1992(1):11-18. 被引量:17
  • 6Resendiz D, Romo M P. Soft-ground Tunneling [ C ] ///Soft-ground Tunneling-failures and tunneling-failures and displacement, Rotterdam, 1982 : 65-74.
  • 7Fino G J, Clough G W. Evaluation of soil response to EPB shield tunneling [ J ]. Journal' of Geotechnical Engineering, 1985, 111 (2) : 155-173.
  • 8安红刚,孙钧,胡向东,赵其华.盾构法隧道施工地表变形的小样本智能预测[J].成都理工大学学报(自然科学版),2005,32(4):362-367. 被引量:6
  • 9梁桂兰,徐卫亚,何育智,赵延喜.PSO-RBFNN模型及其在岩土工程非线性时间序列预测中的应用[J].岩土力学,2008,29(4):995-1000. 被引量:12
  • 10Kennedy J, Eberhart R C. Swarm Intelligence [ M ]. San Francisco: Morgan Kaufmann Publishers, 2001.

二级参考文献19

  • 1刘海龙,唐奇伶.基于径向基函数神经网络的心电图ST段形态识别[J].生物物理学报,2005,21(6):457-463. 被引量:7
  • 2刘鑫朝,颜宏文.一种改进的粒子群优化RBF网络学习算法[J].计算机技术与发展,2006,16(2):185-187. 被引量:15
  • 3周希圣.盾构隧道施工多媒体监控与仿真系统研究[R].上海:同济大学地下建筑与工程系,2000..
  • 4冀树勇 陈锦清 詹君治.类神经网络于深开挖壁体变形预测之应用[J].地工技术期刊(台湾),2002,(91):55-55.
  • 5Shi Y, Eberhart R C. A Modified Particle Swarm Optimizer [C]//Proceedings of the IEEE Conference on Evolutionary Computation.Piscataway, NJ: IEEE Press, 1998, 69-73.
  • 6Shi Y, Eberhart R C. Fuzzy Adaptive Particle Swarm Optimization[C]//Proceedings of the IEEE Conference on Evolutionary Computation. Piscataway, NJ: IEEE Press, 2001, 101-106.
  • 7Kennedy J, Eberhart R C. Particle Swarm Optimization [C]//IEEE International Conference on Neural Networks. Piscataway, NJ:IEEE Press, 1995, 1942-1948.
  • 8Eberhart R C, Shi Y. Particle Swarm Optimization: developments,applications and resources [C]//Proc. 2001 Congress Evolutionary Computation. Piscataway, N J: IEEE Press, 2001, 81-86.
  • 9HAYKhN S.神经网络原理 a comprehensive foundation[M].北京:机械工业出版社,2004.
  • 10TRELEA I C. The particle swarm optimization algorithm convergence analysis and parameter selection [J]. Information Processing Letters, 2003, (85): 317-325.

共引文献156

同被引文献31

引证文献2

二级引证文献2

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部