Advertisement

KSCE Journal of Civil Engineering

, Volume 23, Issue 11, pp 4621–4630 | Cite as

Application of Subway Foundation Pit Engineering Risk Assessment: A Case Study of Qingdao Rock Area, China

  • Yuan-shun Shen
  • Peng WangEmail author
  • Mei-ping Li
  • Qi-wen Mei
Geotechnical Engineering
  • 5 Downloads

Abstract

The foundation pit construction risk of subway stations is affected by various uncertain factors, which cannot be analyzed quantitatively by current methods. A synthetic evaluation index system for foundation pit construction risk of subway stations is established by analyzing the factors that influence subway station construction. Based on the hierarchy of these factors, a model of three-stage fuzzy synthetic evaluation is proposed, an analytic hierarchy process is used to determine the weight of each stage factor, the fuzzy sets method is used to determine the membership function, and risk ranking is carried out. The proposed method is applied to a subway station construction of the Qingdao Subway Line No. 3 Project. The simulation results show that the method is reasonable and that it should be practical and helpful for other similar projects.

Keywords

foundation pit engineering fuzzy synthetic evaluation analytic hierarchy process risk evaluation subway construction management 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Notes

Acknowledgements

This work was supported by the National Natural Science Foundation of China (Grant No. 51908249), the Natural Science Foundation of the Jiangsu Higher Education Institutions of China (Grant No. 19KIB560012) and the High-level Scientific Research Foundation for the introduction of talent for Jiangsu University (Grant No. 18JDG038).

References

  1. Bian, Y. H., Huang, H. W., and Li, J. (2006). “Risk analysis in the construction stage of deep excavation engineering based on dependability method.” Chinese Journal of Underground Space and Engineering, Vol. 2, No. 1, pp. 70–73.Google Scholar
  2. Einstein, H. H. (1996). “Risk and risk analysis in rock engineering.” Tunneling and Underground Space Technology, Vol. 11, No. 2, pp. 14–155, DOI:  https://doi.org/10.1016/0886-7798(96)00014-4..Google Scholar
  3. Einstein, H. H., Chiaverio, F. K., and Ppel, U. (1994). “Risk analysis for the adler tunnel.” Tunnels & Tunnelling, Vol. 26, No. 11, pp. 28–30.Google Scholar
  4. Einstein, H. H., Indermiue, C., and Sinifeld, J. (1996). “Decision aids for tunneling.” Journal of the Transportation Research Board, Vol. 20, No. 5, pp. 6–9.Google Scholar
  5. Einstein, S. D., Tengborg, P., and Kampmann, J. (2004). “Guidelines for tunnelling risk management: International tunnelling association, working group No. 2.” Tunnelling and Underground Space Technology, Vol. 19, No. 3, pp. 217–237, DOI:  https://doi.org/10.1016/j.tust.2004.01.001..Google Scholar
  6. Einstein, H. H., Xu, S., and Grasos, P. (1998). “Decision aids in tunneling.” World Tunneling, Vol., No. 4, pp. 157–159.Google Scholar
  7. Elsye, V., Latief, Y., and Sagita, L. (2018). “Development of work breakdown structure (WBS) standard for producing the risk based structural work safety plan of building.” MATEC Web of Conferences, Vol. 147, pp. 6003–6007, DOI:  https://doi.org/10.1051/matecconf/201814706003..CrossRefGoogle Scholar
  8. Gong, M. S. and Xu, S. B. (1986). Analytic hierarchy process, Tianjin University Press, Tianjin, China, pp. 59–61.Google Scholar
  9. Gupta, V. K. and Thakkar, J. J. (2018). “A quantitative risk assessment methodology for construction project.” Sadhan-Academy Proceedings in Engineering Sciences, Vol. 43, No. 7, DOI:  https://doi.org/10.1007/s12046-018-0846-6.
  10. Han, Y., Jin, R., Wood, H., and Yang, T. (2019). “Investigation of demographic factors in construction employees’safety perceptions.” KSCE Journal of Civil Engineering, KSCE, Vol. 23, No. 7, pp. 2815–2828, DOI:  https://doi.org/10.1007/s12205-019-2044-4..CrossRefGoogle Scholar
  11. Huang, H. W. (2006). “State-of-the-art of the research on risk management in construction of tunnel and underground works.” Chinese Journal of Underground Space and Engineering, Vol. 2, No. 1, pp. 13–20.Google Scholar
  12. Huang, H. W. and Bian, Y. H. (2005). “Risk management in the construction of deep excavation engineering.” Chinese Journal of Underground Space and Engineering, Vol. 1, No. 4, pp. 611–614.Google Scholar
  13. Jafar, K., Hamidi, B. R., Jamal, R., and Hadi, B. (2013). “Risk assessment based selection of rock TBM for adverse geological conditions using Fuzzy-AHP.” Bulletin of Engineering Geology and the Environment, Vol. 69, No. 4, pp. 523–532, DOI:  https://doi.org/10.1007/s10064-009-0260-8..Google Scholar
  14. Jiang, D. H. and Bian, L. M. (2012). “A study on the correlativity and date simulation between rock abrastivity and physical and mechanical indexes of rock in qingdao subway, China.” 3rd International Conference on Manufacturing Science and Engineering, Xiamen, China, DOI:  https://doi.org/10.4028/www.scientific.net/AMR.476-478.1718.Google Scholar
  15. Jung, I. S. and Lee, C. S. (2012). “Fuzzy inference and AHP-based alternative evaluation tool in the development of sustainable residential land.” KSCE Journal of Civil Engineering, KSCE, Vol. 16, No. 3, pp. 273–282, DOI:  https://doi.org/10.1007/s12205-012-1394-y..CrossRefGoogle Scholar
  16. Liu, W., Zhao T. S., Zhou, W., and Tang J. J. (2018). “Safety risk factors of metro tunnel construction in China: An integrated study with EFA and SEM.” Safety Scienc, Vol. 105, No. 6, pp. 98–133, DOI:  https://doi.org/10.1016/j.ssci.2018.01.009..CrossRefGoogle Scholar
  17. Ock, J. H. and Han, S. H. (2010). “Measuring risk-associated activity’s duration: A fuzzy set theory application.” KSCE Journal of Civil Engineering, KSCE, Vol. 14, No. 5, pp. 663–671, DOI:  https://doi.org/10.1007/s12205-010-1003-x..CrossRefGoogle Scholar
  18. PRC Ministry of Construction (2007). Guideline of risk management for construction of subway and underground works, China Architecture & Building Press, Beijing, Chinas.Google Scholar
  19. Qing, Y., Li, W., Zhou, Y. C., Ma, C. Y., and Wang, Y. F. (2015). “Maximum ground settlement prediction of deep foundation pits based on genetic algorithm support vector machine and rough Set BP Neural Network.” Electronic Journal of Geotechnical Engineering, Vol. 20, No. 23, pp. 146–158.Google Scholar
  20. Søren, D. E., Per, T., Jørgen, K., and Trine, H. V. (2004). “Guidelines for tunnelling risk management: International tunnelling association, Working Group No. 2.” Tunnelling and Underground Space Technology, Vol. 19, pp. 217–237, DOI:  https://doi.org/10.1016/j.tust.2004.01.001..CrossRefGoogle Scholar
  21. Tan, Y., Jiang, W. Z., Luo, W. J., Lu, Y., and Xu, C. J. (2018). “Longitudinal sliding event during excavation of feng-qi station of Hangzhou metro line 1: Postfailure investigation.” Journal of Perfrormance of Cinstructed Facilities, Vol. 32, No. 4, DOI:  https://doi.org/10.1061/(ASCE)CF.1943-5509.0001181.
  22. Zhou, Y., Su, W. J., Ding, L. Y., Luo, H. B., and Peter, E. D. L. (2017). “Predicting Safety Risks in Deep Foundation Pits in Subway Infrastructure Projects: Support Vector Machine Approach.” Journal of Computing in Civil Engineering, Vol. 31, No. 5, pp. 292–300, DOI:  https://doi.org/10.1061/(ASCE)CP.1943-5487.0000700..Google Scholar
  23. Zhou, H. B., Yao, H., and Lu, J. H. (2006). “Construction risk assessment on deep foundation pits of a metro line in Shanghai.” Chinese Journal of Geotechnical Engineering, Vol. 28, No. S, pp. 1902–1906.Google Scholar

Copyright information

© Korean Society of Civil Engineers 2019

Authors and Affiliations

  1. 1.Dept. of Engineering ManagementJiangsu UniversityZhenjiangChina
  2. 2.Dept. of Civil EngineeringJiangsu UniversityZhenjiangChina
  3. 3.Dept. of Environmental EngineeringUniversity of SeoulSeoulKorea

Personalised recommendations