Preliminary Study of Assessment System for Subsurface Karst Development Degree

ZHANG Kai; HUO Xiaolong; CHEN Shougen; TU Peng; TAN Xinrong

doi:10.3969/j.issn.0258-2724.2018.03.018

Volume 31 Issue 3

Jun. 2018

Turn off MathJax

Article Contents

Abstract

References

Journal of Southwest Jiaotong University > 2018 > 53(3): 565-573.

WANG Jing, XIE Jianhua, YUE Yuan. Existence Problem of Invariant Torus Particle Motion in Rotating Nonlinear Dynamical Systems[J]. Journal of Southwest Jiaotong University, 2017, 30(5): 1015-1019. doi: 10.3969/j.issn.0258-2724.2017.05.024

Citation:

ZHANG Kai, HUO Xiaolong, CHEN Shougen, TU Peng, TAN Xinrong. Preliminary Study of Assessment System for Subsurface Karst Development Degree[J]. Journal of Southwest Jiaotong University, 2018, 53(3): 565-573. doi: 10.3969/j.issn.0258-2724.2018.03.018

Citation:

PDF( 1763 KB)

Preliminary Study of Assessment System for Subsurface Karst Development Degree

doi: 10.3969/j.issn.0258-2724.2018.03.018

Received Date: 01 Mar 2017
Publish Date: 25 Jun 2018

Abstract

Abstract

An attempt was made to establish an assessment system for subsurface karst development by combining quantitative and qualitative methods. The assessment results can assist the preliminary determination of the extent of underground karst development and guide the planning and construction of underground engineering projects. Firstly, the major factors influencing the karst development were selected as the assessment indices in the system, and the varying degrees of subsurface karst development are defined. Then, the weights of these assessment indices were determined using a synthetic weighting method, in which the fuzzy hierarchy analytic process determines the qualitative weights, while the quantitative weights were determined by a sensitivity analysis of the Bayesian belief network. The Fuzzy Analytic Hierarchy Process was used to determine the ratings of the karst development states in the assessment indices. Moreover, based on the statistical data, the quantitative assessment results belonging to each degree of karst development were determined by comparing the calculated assessment results with the real karst development status. The proposed assessment system was applied to a railway tunnelling project in China to evaluate the degree of surface karst development before tunnel construction. A comparative analysis of the assessment results with the recorded results shows that the assessment of the tunnel zone, accounting for 97.1% of the total tunnel length, is consistent with the recorded results. Assessment errors only occur in 2.9% of the tunnel zone, where the degree of karst development was assigned as "developed", while the records indicated it was "extremely developed". However, the quantitative assessment result of the karst development degree is 0.69, which is close to the value range of "extremely developed", 0.70-1.00. As this minor error is acceptable in the preliminary assessment of the degree of karst development, the proposed assessment system is verifiably reliable.
- subsurface karst development degree,
- synthetic weighting method,
- Fuzzy Analytic Hierarchy Process,
- Bayesian Belief Network

FullText(HTML)

References(23)

References

吴德胜, 苏有财, 丁建芳, 等.山区特长岩溶隧道施工阶段勘察方法探讨[J].西南交通大学学报, 2012(增刊):202-207. http://d.old.wanfangdata.com.cn/Conference/7913605

WU Desheng, SU Youcai, DING Jianfang, et al. The discussion of the surveying method during the construction of the mountainous long karst tunnel[J]. Journal of Southwest Jiaotong University, 2012(Sup.):202-207. http://d.old.wanfangdata.com.cn/Conference/7913605

SOKOLOV D S. Main conditions for karst development[M]. Moscow:GosGeolTechIzdat, 1962:320-323.

LEGRAND H E, STRINGFILD V T. Karst hydrology-areview[J]. Journal of Hydrology, 1973, 20(2):97-120. doi: 10.1016/0022-1694(73)90034-6

STRINGFIELD V T, RAPP J R, ANDERS R B. Effect of karst and geological structure on the circulation of water and permeability in carbonate aquifers[J]. Journal of Hydrology, 1979, 43(1/2/3/4):313-332. http://www.sciencedirect.com/science/article/pii/0022169479901781

FORD D, WILLIAMS P. Karst hydrogeology and geomorphology[M]. Chichester:John Wiley & Sons Ltd., 2007:9-38, 401-440.

中国科学院地质研究所.中国岩溶研究[M].北京:科学出版社, 1977:73-110.

任美锷, 刘振中.岩溶学概论[M].北京:商务印书馆.1983:21-59.

铁道部第二勘测设计院.岩溶工程地质[M].北京:中国铁道出版社, 1984:1-62.

袁道先.中国岩溶学[M].北京:地质出版社, 1993:9-52.

STOKES T R, GRIFFITHS P. A preliminary discussion of karst inventory systems and principles (KISP) for British Columbia[R]. Victoria: Ministry of Forests, Lands and Natural Resource Operations of British Columbia, 2000.

涂国强, 杨立中, 贺玉龙.铁路沿线岩溶塌陷预测模型[J].西南交通大学学报, 2001, 36(4):341-345. doi: 10.3969/j.issn.0258-2724.2001.04.002

TU Guoqiang, YANG Lizhong, HE Yulong. Prediction model for sinkholes along railways[J]. Journal of Southwest Jiaotong University, 2001, 36(4):341-345. doi: 10.3969/j.issn.0258-2724.2001.04.002

李术才, 石少帅, 李利平, 等.三峡库区典型岩溶隧道突涌水灾害防治与应用[J].岩石力学与工程学报, 2014, 33(9):1887-1896. http://d.old.wanfangdata.com.cn/Periodical/yslxygcxb201409022

LI Shucai, SHI Shaoshuai, LI Liping, et al. Control of water inrush in typical karst tunnels in three gorges reservoir area and its application[J]. Journal of Southwest Jiaotong University, 2014, 33(9):1887-1896. http://d.old.wanfangdata.com.cn/Periodical/yslxygcxb201409022

李苍松, 高波, 梅志荣.岩溶地质预报的分形理论应用基础研究[J].西南交通大学学报, 2007, 42(5):542-547. doi: 10.3969/j.issn.0258-2724.2007.05.005

LI Cangsong, GAO Bo, MEI Zhirong. Basic study on method of karst geology forecasting based on fractal theory[J]. Journal of Southwest Jiaotong University, 2007, 42(5):542-547. doi: 10.3969/j.issn.0258-2724.2007.05.005

刘招伟, 张民庆, 王树仁.岩溶隧道灾变预测与处置技术[M].北京:科学出版社, 2007:81-83.

CHANG Dayong. Application of the extent analysis method on fuzzy AHP[J]. European Journal of Operational Research, 1996, 95(3):649-655. doi: 10.1016/0377-2217(95)00300-2

SAATY T L. The analytic hierarchy process[M]. New York:McGrew-Hill International, 1980:271-278.

DENG H. Multicriteria analysis with fuzzy pair-wise comparison[J]. International Journal of Approximate Reasoning, 1999, 21(3):215-231. doi: 10.1016/S0888-613X(99)00025-0

WANG T C, CHEN Y H. Applying consistent fuzzy preference relations to partnership selection[J]. International Journal of Manage Science, 2007, 35(4):384-388. http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=164e5cba31c534205e0c29b1f4b3106c

KAHRANMAN C, RUAN D, DOGAN I. Fuzzy group decision making for facility location selection[J]. Information Sciences, 2003, 157:135-153. doi: 10.1016/S0020-0255(03)00183-X

NEZARAT H, SERESHKI F, ATAEI M. Rangking of geological risks in mechanized tunneling by using Fuzzy Analytical Hierarchy Process (FAHP)[J]. Tunneling and Underground Technology, 2015, 50:358-364. doi: 10.1016/j.tust.2015.07.019

KRAGT M E. A beginner's guide to Bayesian network modelling for integrated catchment management[R]. Huntly: Landscape Logic Research Hub, 2009.

PEARL J. Probabilistic reasoning in intelligent systems:networks of plausible inference[M]. San Mateo:Morgan Kaufmann Publishers, 1988:1022-1027.

SAATY T L. Decision making with the analytic hierarchy process[J]. International Journal of Services Science, 2008, 1(1):83-98. doi: 10.1504/IJSSCI.2008.017590

Relative Articles

[1]	XU Xikun, HONG Yu, XU Jingye, ZHOU Zhida, PU Qianhui, WEN Xuguang. Finite Element Model Updating for Bridges Based on Adaptive Nested Sampling and Bayesian Theory[J]. Journal of Southwest Jiaotong University. doi: 10.3969/j.issn.0258-2724.20230358
[2]	ZHANG Cong, YAO Lingkan, HUANG Yidan, QIU Yanling, TAN Li. Evaluation Method of Railway Schemes Along Rivers in Risk Areas of Moraine-Dammed Lake Outburst[J]. Journal of Southwest Jiaotong University, 2022, 57(6): 1311-1318, 1341. doi: 10.3969/j.issn.0258-2724.20200696
[3]	LYU Biao, LIU Yumeng. Resilience Assessment Based on Bayesian Network for on-Board Subsystem of CTCS-3 Train Control System[J]. Journal of Southwest Jiaotong University, 2022, 57(5): 949-959. doi: 10.3969/j.issn.0258-2724.20210102
[4]	CHEN Dan, HU Minghua, ZHANG Honghai, YIN Jianan. Short-Term Traffic Flow Prediction of Airspace Sectors Based on Bayesian Estimation Theory[J]. Journal of Southwest Jiaotong University, 2016, 29(4): 807-814. doi: 10.3969/j.issn.0258-2724.2016.04.028
[5]	ZHAO Jianjun, HE Yuhang, HUANG Runqiu, JU Nengpan. Weights of Slope Stability Evaluation Indexes Based on Factor Analysis Method[J]. Journal of Southwest Jiaotong University, 2015, 28(2): 325-330. doi: 10.3969/j.issn.0258-2724.2015.02.018
[6]	ZHANG Shuaiyi, LI Yongshu, CAI Guolin. Aerial Image Registration Based on Bayesian Decision Theory[J]. Journal of Southwest Jiaotong University, 2015, 28(1): 161-166. doi: 10.3969/j.issn.0258-2724.2015.01.024
[7]	HUO Zhiqin, RU Yi, HAN Songchen. Analysis Model of Transport Aircraft Veering off Runway during Landing Phase[J]. Journal of Southwest Jiaotong University, 2012, 25(5): 895-900. doi: 10.3969/j.issn.0258-2724.2012.05.026
[8]	HE Zhaocheng, LI Zhitao, ZHAO Jianming. Traffic Flow Time Series Periodicity Based on Recurrence Quantitative Analysis[J]. Journal of Southwest Jiaotong University, 2010, 23(6): 946-951. doi: 10.3969/j.issn.0258-2724.2010.06.021
[9]	GUO Zhizheng, CHEN Chongshuang, WANG Xin. Risk Identification for Driving Behaviors Based on Bayesian Discrimination[J]. Journal of Southwest Jiaotong University, 2009, 22(5): 771-775.
[10]	CHEN Lei, ZENG Yuqing, YU Weidong. Bayesian Estimation of Vehicle Dynamic Performance by Rail Measurement[J]. Journal of Southwest Jiaotong University, 2009, 22(6): 893-899.
[11]	JIA Hong, ZHOU Bo, LIU Guangbing. Advantage Analysis of Risk Model Based on Analytic Hierarchy Process[J]. Journal of Southwest Jiaotong University, 2009, 22(1): 72-76.
[12]	SONG Lei, HUANG Teng, FANG Jian, ZHOU Xuhua. Conversion of GPS Height Based on Bayesian Regularization BP Neural Network[J]. Journal of Southwest Jiaotong University, 2008, 21(6): 724-728.
[13]	BUXiang-zhi, WANG Wen-bin, WUZhen-ye. Strategic Partner Selection in Agile Supply Chain[J]. Journal of Southwest Jiaotong University, 2004, 17(2): 239-243.
[14]	TANG Yi-ke, LIANG Feng. Application of Time-Frequency Analysis Method to Start-up Process Analysis of High-Pressure Hydraulic Pump[J]. Journal of Southwest Jiaotong University, 2003, 16(5): 525-527.
[15]	ZHANG Fei-qiao, ZHANG Ze-long. Cost-Benefit Analysis of GNSS Non-precision Approach on Feeder-Route Aerodromes[J]. Journal of Southwest Jiaotong University, 2002, 15(1): 57-60.
[16]	SONGJiu-peng, DONGDa-wei, GAO Guo-an. A Decision Model for Product Scheme Evaluation Based on AHP and Degree of Gray Incidence[J]. Journal of Southwest Jiaotong University, 2002, 15(4): 463-466.

Supplements(0)

Cited By

Cited by

Periodical cited type(7)

1.	申梁，陈立强，黄勇. 基于模糊层次分析法和熵权法的岩溶发育强度评价方法探讨. 勘察科学技术. 2024(02): 30-35 .
2.	孙克国，甄映州，魏勇，肖支飞，杨朋，方纯彬，蔡定淮，刘广明. 富水岩溶区基坑稳定性影响规律与分析. 现代隧道技术. 2023(01): 149-158+194 .
3.	刘权，邓忠，卢丹美，夏源，杨鹏飞，覃佳肖. 广西黔江水位抬升影响下盘龙铅锌矿涌突水风险评估. 地下水. 2023(06): 13-17+96 .
4.	杨宁，史猛，殷焘，于林弘，王元峰，张杰，冯培培. 胶东半岛岩溶发育程度分区研究-以烟台市中桥地区为例. 中国岩溶. 2023(05): 956-968 .
5.	贾龙，雷明堂，程小杰. 基于井中超声波成像的岩溶特征高精度探测和评价. 地质通报. 2022(Z1): 453-460 .
6.	盛建龙，乔宇，俞栋华，王平，张彦文. 基于模糊神经网络的岩溶发育预测研究. 水力发电. 2022(07): 28-33 .
7.	李录娟，贾龙，殷仁朝. 基于孔中雷达反射成像特征的岩溶定量化评价. 中国岩溶. 2021(05): 901-906 .

Other cited types(9)

Proportional views

Proportional views

通讯作者: 陈斌, bchen63@163.com

1.
沈阳化工大学材料科学与工程学院沈阳 110142

Figures(2) / Tables(11)

Get Citation

PDF

XML

Article views(508) PDF downloads(84)

Preliminary Study of Assessment System for Subsurface Karst Development Degree

doi: 10.3969/j.issn.0258-2724.2018.03.018