Skip to main content
SpringerLink
Log in

Probabilistic evaluation of primary consolidation settlement of Songdo New City by using kriged estimates of geologic profiles

  • Research Paper
  • Published:
Acta Geotechnica Aims and scope Submit manuscript

Abstract

The uncertainty in the spatial distributions of consolidation settlement (s c) and time (t p) for Songdo New City is evaluated by using a probabilistic procedure. Ordinary kriging and three theoretical semivariogram models are used to estimate the spatial distributions of geo-layers which affect s c and t p in this study. The spatial map of mean (μ) and standard deviation (σ) for s c and t p are determined by using a first-order second moment method based on the evaluated statistics and probability density functions (PDFs) of soil properties. It is shown that the coefficients of variation (COVs) of the compression ratio [C c/(1 + e 0)] and the coefficient of consolidation (c v) are the most influential factors on the uncertainties of s c and t p, respectively. The μ and σ of the s c and t p, as well as the probability that s c exceeds 100 cm [P(s c > 100 cm)] and the probability that t p exceeds 36 months [P(t p > 36 months)] in Sect. 1, are observed to be larger than those of other sections because the thickness of the consolidating layer in Sect. 1 is the largest in the entire study area. The area requiring additional fill after the consolidation appears to increase as the COV of C c/(1 + e 0) increases and as the probabilistic design criterion (α) decreases. It is also shown that the area requiring the prefabricated vertical drains installation increases as the COV of c v increases and as the α decreases. The design procedure presented in this paper could be used in the decision making process for the design of geotechnical structures at coastal reclamation area.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14
Fig. 15
Fig. 16
Fig. 17

Similar content being viewed by others

References

  1. Ang AH-S, Tang WH (1975) Probability concepts in engineering planning and design, Vol. 1-Basic principles. Wiley, New York

    Google Scholar 

  2. Athanasiou-Grivas D, Harr ME (1978) Consolidation—a probabilistic approach. J Eng Mech Division ASCE 104(EM3):681–690

    Google Scholar 

  3. Baecher GB, Christian JT (2003) Reliability and statistical in geotechnical engineering. Wiley, New York, pp 177–203

    Google Scholar 

  4. Baise LG, Higgins RB, Brankman CM (2006) Liquefaction hazard mapping-statistical and spatial characterization of susceptible units. J Geotech Geoenviron Eng ASCE 132(6):705–715

    Article  Google Scholar 

  5. Benjamin JR, Cornell CA (1970) Probability, statistics, and decision for civil engineers. McGraw-Hill Book Company, New York

    Google Scholar 

  6. Chang CS (1985) Uncertainty of one-dimensional consolidation analysis. J Geotech Eng ASCE 111(12):1411–1424

    Article  Google Scholar 

  7. Chiasson P, Lafleur J, Soulie M, Law KT (1995) Characterizing spatial variability of a clay by geostatistics. Can Geotech J 32(1):1–10

    Article  Google Scholar 

  8. Christakos G (1985) Modern statistical analysis and optimal estimation of geotechnical data. Eng Geol 22:175–200

    Article  Google Scholar 

  9. Corotis RB, Krizek RJ, El-Moursi HH (1975) Probabilistic approach to prediction of consolidation settlement. TRB Transportation Research Board 548:47–61

    Google Scholar 

  10. Cressie N (1991) Statistics for spatial data. Wiley, New York

    MATH  Google Scholar 

  11. Duncan J (2000) Factors of safety and reliability in geotechnical engineering. J Geotech Geoenviron Eng ASCE 126(4):307–316

    Article  Google Scholar 

  12. Deutsch CV (1989) DECLUS: a Fortran 77 program for determining optimum spatial declustering weights. Comput Geosci 15(3):325–332

    Article  Google Scholar 

  13. Deutsch CV, Journel AG (1992) GSLIB: Geostatistical software library and user’s guide. Oxford University Press, New York

    Google Scholar 

  14. Freeze RA (1977) Probabilistic one-dimensional consolidation. J Geotech Eng Div ASCE 103(GT7):725–741

    Google Scholar 

  15. Goovaerts P (1997) Geostatistics for natural resources evaluation. Oxford University Press, New York

    Google Scholar 

  16. Holtz RD, Kovacs WD, Sheahan TC (2011) An introduction to geotechnical engineering, 2nd edn. Pearson, New York

    Google Scholar 

  17. Hong HP, Shang JQ (1998) Probabilistic analysis of consolidation with prefabricated vertical drains for soil improvement. Can Geotech J 35(4):666–677

    Article  Google Scholar 

  18. Huang J, Griffiths DV, Fenton GA (2010) Probabilistic analysis of coupled soil consolidation. J Geotech Geoenviron Eng ASCE 136(3):417–430

    Article  Google Scholar 

  19. Isaaks EH, Srivastava RM (1989) Applied geostatistics. Oxford University Press, New York

    Google Scholar 

  20. Jaksa MB, Brooker PI, Kaggwa WS (1997) Modeling the spatial variation of the undrained shear strength of clays soils using geostatistics. In: Proceedings of 5th international Geostatistics Congress, Kulwer Academic, Dordrecht, The Netherlands, pp 1284–1295

  21. Journel AG, Huijbregts CJ (1978) Mining geostatistics. Academic Press, London

    Google Scholar 

  22. Kim D, Kim KS, Ko S, Choi Y, Lee W (2012) Assessment of geotechnical variability of Songdo silty clay. Eng Geol 133–134:1–8

    Article  Google Scholar 

  23. Marache A, Breysse D, Piette C, Thierry P (2009) Geotechnical modeling at the city scale using statistical and geostatistical tools: the Pressac case (France). Eng Geol 107:67–76

    Article  Google Scholar 

  24. Mendes RM, Lorandi R (2008) Analysis of spatial variability of SPT penetration resistance in collapsible soils considering water table depth. Eng Geol 101:218–225

    Article  Google Scholar 

  25. Mesri G, Choi YK (1985) Settlement analysis of embankments on soft clays. J Geotech Eng ASCE 111(4):441–464

    Article  Google Scholar 

  26. Parsons RL, Frost JD (2002) Evaluating site investigation quality using GIS and geostatistics. J Geotech Geoenviron Eng ASCE 128(6):451–461

    Article  Google Scholar 

  27. Phoon KK, Kulhawy FH (1999) Characterization of geotechnical variability. Can Geotech J 36(4):612–624

    Article  Google Scholar 

  28. Santra P, Chopra UK, Chakraborty D (2008) Spatial variability of soil properties and its application in predicting surface map of hydraulic parameters in agricultural farm. Curr Sci 95(7):937–945

    Google Scholar 

  29. Soulie M, Montes P, Silvestri V (1990) Modelling spatial variability of soil parameters. Can Geotech J 27(5):617–630

    Article  Google Scholar 

  30. Taylor DW (1948) Fundamentals of soil mechanics. Wiley, New York

    Google Scholar 

  31. Zhou W, Hong HP, Shang JQ (1999) Probabilistic design method of prefabricated vertical drains for soil improvement. J Geotech Geoenviron Eng ASCE 125(8):659–664

    Article  Google Scholar 

Download references

Acknowledgments

This paper was financially supported by a POSCO E&C grant and the authors wish to thank POSCO E&C Co.

Author information

Authors and Affiliations

  1. Infrastructure Engineering Team, SK E&C, Seoul, 100-021, Korea

    Donghee Kim

  2. KIGAM, Daejeon, 305-350, Korea

    Dongwoo Ryu

  3. School of Civil, Environmental, and Architectural Engineering, Korea University, Seoul, 136-713, Korea

    Changho Lee & Woojin Lee

Authors
  1. Donghee Kim
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Dongwoo Ryu
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Changho Lee
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Woojin Lee
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Woojin Lee.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Kim, D., Ryu, D., Lee, C. et al. Probabilistic evaluation of primary consolidation settlement of Songdo New City by using kriged estimates of geologic profiles. Acta Geotech. 8, 323–334 (2013). https://doi.org/10.1007/s11440-012-0192-5

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11440-012-0192-5

Keywords

Search

Navigation