长江科学院院报 ›› 2014, Vol. 31 ›› Issue (11): 125-130.DOI: 10.3969/j.issn.1001-5485.2014.11.0252014,31(11):125-130

• 地下洞室围岩稳定 • 上一篇    下一篇

双断层地下洞室稳定性快速分析方法研究

刘乃飞1,李宁1,2,菅强1,3   

  1. 1. 西安理工大学 岩土工程研究所,西安 710048;
    2.中国科学院 寒区旱区环境与工程研究所冻土工程国家重点实验室,兰州 730000;
    3. 中国电建集团 西北勘测设计研究院有限公司,西安 710065
  • 收稿日期:2014-08-10 修回日期:2014-11-05 出版日期:2014-11-01 发布日期:2014-11-05
  • 作者简介:刘乃飞(1985-),男,陕西榆林人,博士研究生,主要从事地下硐室及多场耦合方面的研究工作,(电话)029-83293863(电子信箱)liunaifei1985@126.com。
  • 基金资助:
    国家自然科学基金项目(50879068);西安理工大学博士学位论文创新基金(207-002J1306)

Rapid Analysis Method for the Stability of Underground Chambers with Double Faults

LI Ning1,2, LIU Nai-fei1, JIAN Qiang1,3   

  1. 1. Institute of Geotechnical Engineering, Xi’an University of Technology, Xi’an 710048, China;
    2. State Key Laboratory of Frozen Soil Engineering, Cold and Arid Regions Environmental and Engineering Research Institute,Chinese Academy of Sciences, Lanzhou 730000, China;
    3. Power China Xibei Engineering Corporation Limited, Xi’an 710065, China
  • Received:2014-08-10 Revised:2014-11-05 Online:2014-11-01 Published:2014-11-05

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摘要： 针对当前商业软件分析速度难以满足信息化施工时效性的这一关键难题,结合课题组多年的研究成果,提出了一种全新的解决思路。首先概化出对隧洞稳定性影响较大的4大类15个参数,并拟定系统的数值试验方案;然后建立数值分析结果和各影响因素的关系数据库,并以此为样本借助BP神经网络技术构建双断层洞室稳定性快速分析系统;最后用该系统对拉西瓦水电站厂房稳定性进行了分析。洞周变形误差小于20%,满足工程要求,表明该系统具有较好的可靠性。

关键词: 信息化施工, 双断层洞室, BP神经网络技术, 快速分析系统

Abstract: The analysis speed of commercial softwares cannot meet the timeliness requirements of information construction. In view of this, an entirely new idea is proposed in this paper. Firstly, 4 groups including 15 parameters which have significant impacts on the stability of tunnel are generalized and test plan is drawn up. Subsequently the relational database of numerical analysis results and the main influences is established, and the rapid analysis and evaluation system for underground chamber with double faults is built up with the help of BP neural network. This system is employed to analyze the stability of the powerhouse of Laxiwa hydropower station. The error of peripheral deformation is less than 20%, which meets the engineering requirements and shows a good reliability of this system.

Key words: information construction, chamber with double faults, BP neural network, rapid analysis system

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