Advertisement

An engineering site suitability index (ESSI) for the evaluation of geological situations based on a multi-factor interaction matrix

  • Kun LiEmail author
  • Yanjun Shang
  • Wantong He
  • Daming Lin
  • Muhammad Hasan
  • Kaiyang Wang
Original Paper
  • 106 Downloads

Abstract

The aim of this study is to determine how to evaluate the suitability of engineering sites quantitatively with the aid of multi-disciplines. This paper presents an engineering site suitability index (ESSI) system based on a multi-factor interaction matrix. This system was designed to define the principal causes related to suitability of engineering sites, quantify factor interactions, obtain the weight ratios and calculate the index of suitability. Recently, the ESSI system has been used successfully in the site selection for the China Spallation Neutron Source (CSNS) project. Firstly, the geomorphology, lithology, geological structure, hydrogeology, rock weathering and land use were selected as evaluation indices to compare the suitability of the five potential sites. Secondly, the relationship matrix was established, and then the weight ratios of six influential factors were computed comprehensively after the analysis of relationship among these six factors. The third site was selected for the suitability of CSNS as the most favorable engineering site after the evaluation of five potential sites for the engineering excavation and construction. This case study shows that the ESSI system is scientific, reasonable and applicable to provide a reference for similar large-scale geo-engineering sites.

Keywords

Engineering site suitability index (ESSI) Multi-factor interaction matrix Weight ratio China Spallation Neutron Source (CSNS) 

Notes

Acknowledgements

This work was financially supported by the National Natural Science Foundation of China (NSFC; no. 41372324), Opening Research Fund of National Engineering Laboratory for Surface Transportation Weather Impacts Prevention (no. NELXX201603), and Collaborative Innovation Center for Prevention and Control of Mountain Geological Hazards of Zhejiang Province (no. PCMGH-2016-Y03).

References

  1. Barton N (1991) Geotechnical design. World Tunnelling, pp 406–410Google Scholar
  2. Barton N (1995) The influence of joint properties in modelling jointed rock masses, keynote lecture, 8th congress of ISRM, Tokyo, vol 3. Balkema, RotterdamGoogle Scholar
  3. Barton N (2002) Some new q-value correlations to assist in site characterisation and tunnel design. Int J Rock Mech Min Sci 39(2):185–216CrossRefGoogle Scholar
  4. Barton N, Lien R, Lunde J (1974) Engineering classification of rock masses for the design of tunnel support. Rock Mech Rock Eng 6(4):189–236CrossRefGoogle Scholar
  5. Benardos AG, Kaliampakos DC (2004) Modelling tbm performance with artificial neural networks. Tunn Undergr Space Technol 19(6):597–605CrossRefGoogle Scholar
  6. Bieniawski ZT (1973) Engineering classification of jointed rock masses. Civil Eng S Afr 15:335–343Google Scholar
  7. Bieniawski ZT (1984) Rock mechanics design in mining and tunneling. Balkema, Rotterdam, p 272Google Scholar
  8. Bieniawski ZT (1989) Engineering rock mass classification. Wiley, New York, p 251Google Scholar
  9. Budetta P, Santo A, Vivenzio F (2008) Landslide hazard mapping along the coastline of the Cilento region (Italy) by means of a gis-based parameter rating approach. Geomorphology 94(3–4):340–352CrossRefGoogle Scholar
  10. Caunhye AM, Li M, Nie X (2015) A location-allocation model for casualty response planning during catastrophic radiological incidents. Socio Econ Plan Sci 50:32–44CrossRefGoogle Scholar
  11. Ceryan N, Ceryan S (2008) An application of the interaction matrices method for slope failure susceptibility zoning: dogankent settlement area (giresun, ne Turkey). Bull Eng Geol Environ 67(3):375–385CrossRefGoogle Scholar
  12. Chu SCK, Chu L (2006) A modeling framework for hospital location and service allocation. Int Trans Oper Res 7(6):539–568CrossRefGoogle Scholar
  13. Deere DU (1964) Technical description of rock cores for engineer purposes. Rock Mech Eng Geol 1:17–22Google Scholar
  14. Faramarzi F, Mansouri H, Farsangi MAE (2013) A rock engineering systems based model to predict rock fragmentation by blasting. Int J Rock Mech Min Sci 60(8):82–94Google Scholar
  15. Frough O, Torabi SR (2013) An application of rock engineering systems for estimating TBM downtimes. Eng Geol 157(6):112–123CrossRefGoogle Scholar
  16. Frough O, Torabi SR, Ramezanzadeh A, Yagiz S (2011) Effect of rock mass condition on TBM downtimes in Karaj water conveyance tunnel. In: First Asian and 9th Iranian Tunneling Symposium, IranGoogle Scholar
  17. Gorsevski PV, Donevska KR, Mitrovski CD, Frizado JP (2012) Integrating multi-criteria evaluation techniques with geographic information systems for landfill site selection: a case study using ordered weighted average. Waste Manag 32(2):287–296CrossRefGoogle Scholar
  18. Hoek E, Brown ET (1997) Practical estimates of rock mass strength. Int J Rock Mech Min Sci 34(8):1165–1186CrossRefGoogle Scholar
  19. Hu H (1983) “Safety Island”—Preliminary application relatively stable (rock) block siting of nuclear power plants in Guangdong. Geotech Invest Surv 04:25–29 (in Chinese) Google Scholar
  20. Huang R, Huang J, Li Y, Ju N (2013) Automated tunnel rock classification using rock engineering systems. Eng Geol 156(2):20–27CrossRefGoogle Scholar
  21. Hudson JA (1992) Rock engineering systems : theory and practice. In: Mathematical Analysis. Ellis Horwood, ChichesterGoogle Scholar
  22. Hudson JA, Harrison JP (1992) A new approach to studying complete rock engineering problems. Quart J Eng Geol Hydrogeol 25(2):93–105 CrossRefGoogle Scholar
  23. Hudson J, Harrison J, Popescu M (2002) Engineering rock mechanics: an introduction to the principles. Appl Mech Rev 55(2):72CrossRefGoogle Scholar
  24. Khalokakaie R, Naghadehi MZ (2012) The assessment of rock slope instability along the Khosh-Yeylagh main road (Iran) using a systems approach. Environ Earth Sci 67(3):665–682CrossRefGoogle Scholar
  25. Liang J, Huang D, Xing N, Lin X (1992) Cybernetics of engineering geological bodies. Chin J Rock Mech Eng 11(2):117–129Google Scholar
  26. Lindsay MD, Aillères L, Jessell MW, Kemp EAD, Betts PG (2012) Locating and quantifying geological uncertainty in three-dimensional models: analysis of the Gippsland Basin, southeastern Australia. Tectonophysics 546–547(3):10–27CrossRefGoogle Scholar
  27. Liu G (1959) The principles of engineering geology division of China. Hydrogeol Eng Geol 07:22–24 (in Chinese) Google Scholar
  28. Liu C, Hu H (1993) The “Safety Island” theory by multi-scale approaching and optimum seeking in engineering site selection. Chin J Geol Hazard Control 01:30–39+64 (in Chinese) Google Scholar
  29. Lu C, Shi BX (2001) Circuit design of a lsi neural network using bp-ga algorithm. J Tsinghua UniversityGoogle Scholar
  30. Mazzoccola DF, Hudson JA (1996) A comprehensive method of rock mass characterization for indicating natural slope instability. Quart J Eng Geol Hydrogeol 29(1):37–56CrossRefGoogle Scholar
  31. Mosadeghi R, Warnken J, Tomlinson R, Mirfenderesk H (2015) Comparison of fuzzy-ahp and ahp in a spatial multi-criteria decision making model for urban land-use planning. Comput Environ Urban Syst 49:54–65CrossRefGoogle Scholar
  32. Naghadehi MZ, Jimenez R, Khalokakaie R, Jalali SME (2011) A probabilistic systems methodology to analyze the importance of factors affecting the stability of rock slopes. Eng Geol 118(3–4):82–92CrossRefGoogle Scholar
  33. Naghadehi MZ, Jimenez R, Khalokakaie R, Jalali SME (2013) A new open-pit mine slope instability index defined using the improved rock engineering systems approach. Int J Rock Mech Min Sci 61(61C):1–14CrossRefGoogle Scholar
  34. Palmström A (2009) Combining the RMR, Q, and RMi classification systems. Tunn Undergr Space Technol 24(4):491–492CrossRefGoogle Scholar
  35. Rozos D, Pyrgiotis L, Skias S, Tsagaratos P (2008) An implementation of rock engineering system for ranking the instability potential of natural slopes in Greek territory. an application in Karditsa County. Landslides 5(3):261–270CrossRefGoogle Scholar
  36. Shang YJ, Wang SJ, Li GC, Yang ZF (2000) Retrospective case example using a comprehensive suitability index (CSI) for siting the Shisan-Ling power station, China. Int J Rock Mech Min Sci 37(5):839–853CrossRefGoogle Scholar
  37. Shang Y, Park HD, Yang Z (2005) Engineering geological zonation using interaction matrix of geological factors: an example from one section of Sichuan-Tibet Highway. Geosci J 9(4):375–387CrossRefGoogle Scholar
  38. Shin HS, Kwon YC, Jung YS, Bae GJ, Kim YG (2009) Methodology for quantitative hazard assessment for tunnel collapses based on case histories in Korea. Int J Rock Mech Min Sci 46(6):1072–1087CrossRefGoogle Scholar
  39. Stille H, Palmström A (2003) Classification as a tool in rock engineering. Tunn Undergr Space Technol 18(18):331–345CrossRefGoogle Scholar
  40. Sun G (1988) Rock mass structural mechanics. Science Press, Beijing (in Chinese)Google Scholar
  41. Sun G (1993) On the theory of structure-controlled rockmass. J Eng Geol 1:14–18 (in Chinese) Google Scholar
  42. Weber A (1909) Über den Standort der Industrien. Erster Teil: Reine Theorie des Standorts, Tübingen, Mohr. (trad. anglaise de C. J Friedrich: Alfred Weber’s Theory of Location of Industries, Chicago, University of Chicago Press, 1929)Google Scholar

Copyright information

© Springer-Verlag GmbH Germany 2017

Authors and Affiliations

  • Kun Li
    • 1
    • 2
    Email author
  • Yanjun Shang
    • 1
  • Wantong He
    • 3
  • Daming Lin
    • 4
  • Muhammad Hasan
    • 1
  • Kaiyang Wang
    • 1
    • 2
  1. 1.Key Laboratory of Shale Gas and Geoengineering, Institute of Geology and GeophysicsChinese Academy of SciencesBeijingChina
  2. 2.National Engineering Laboratory for Surface Transportation Weather Impacts PreventionBroadvision Engineering ConsultantsKunmingChina
  3. 3.China Renewable Energy Engineering InstituteBeijingChina
  4. 4.Research Institute of Highway, Ministry of TransportBeijingChina

Personalised recommendations