As highway tunnel construction is greatly affected by karst geological condition, karst indexes should be considered in addition to conventional indicators in surrounding rock classification. In this research, a model of surrounding rock classification was set up, in which rock hardness, rock mass integrity, groundwater status, structural plane occurrence and karst status are included. The expert system based on three tunnel projects in Guangxi Province for surrounding rock classification was designed by embedding normalization algorithm for the indexes using MatLab and C++. The expert system software was applied to engineering and the consistence between software results and actual survey reached 80.89%.
Key words
karst /
highway tunnel /
classification of surrounding rock /
expert system /
neural network
{{custom_sec.title}}
{{custom_sec.title}}
{{custom_sec.content}}
References
[1] 邹成杰. 水利水电岩溶工程地质[M]. 北京: 水利电力出版社, 1994.
[2] 李大通, 罗 雁. 中国碳酸盐分布面积测量[J]. 中国岩溶, 1983, 2(2): 147-150.
[3] 袁道先. 中国岩溶学[M]. 北京: 地质出版社, 1993.
[4] 宣佳良. 岩溶区公路隧道围岩分级专家系统研发与应用[D].南宁:广西大学,2014.
[5] 李苍松,高 波,王石春.岩溶围岩分级初步探讨[J].工程地质学报,2006,14(6): 808-814.
[6] 管洪良.岩溶隧道围岩分级系统研究[D].重庆:重庆大学,2011.
[7] 张 凯.岩溶隧道围岩动态分级方法及应用研究[D].成都:成都理工大学,2012.
[8] 王明年,李玉文.公路隧道围岩亚级分级方法[M] .成都:西南交通大学出版社,2008.
[9] 陈安凡.公路隧道围岩分级专家系统研究[D].成都:重庆大学,2013.
[10]GB/T 50218—2014,工程岩体分级标准[S]. 北京: 中国计划出版社,2015.
[11]关宝树. 铁路隧道围岩分类[M]. 北京: 人民交通出版社, 2004.
[12]李苍松. 岩溶地质分形预报方法的应用研究[D]. 成都: 西南交通大学, 2006.
[13]王石春.隧道工程岩体分级[M]. 成都:西南交通大学出版社,2007.
PDF(1517 KB)
