Probabilistic Stratification Modeling in Geotechnical Site Characterization
Publication: ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering
Volume 3, Issue 4
Abstract
Stratification in geologic profiles is one of the most significant uncertainties in geotechnical site characterization. In this paper, a three-level probabilistic framework is proposed for geotechnical stratification modeling considering stratigraphic uncertainty. The framework consists of model parameter identification, conditional simulation, and stratigraphic uncertainty quantification. Both boundary-based and category-based stratigraphic models are adopted in the framework, and a heuristic combination model is further recommended to combine the advantages of the boundary-based and category-based models. The geological stratification at a construction site in Hong Kong is characterized to illustrate the probabilistic framework. Results indicate that probabilistic stratification modeling quantifies stratigraphic uncertainty in a rigorous manner. Additionally, the heuristic combination model has the ability to generate almost arbitrary geotechnical strata and to account for material spatial distribution trends and engineering judgment to a certain degree.
Get full access to this article
View all available purchase options and get full access to this article.
Acknowledgments
This work was supported by the Research Grants Council of Hong Kong (Nos. 16202716 and C6012-15G) and the National Natural Science Foundation of China (Nos. 51329901, 51509188, and 51579190). The first author wishes to thank the Department of Civil and Environmental Engineering, Hong Kong University of Science and Technology, for hosting his visit as an exchange Ph.D. student.
References
Baecher, G. B., and Christian, J. T. (2003). Reliability and statistics in geotechnical engineering, Wiley, Hoboken, NJ.
Cao, Z., and Wang, Y. (2013). “Bayesian approach for probabilistic site characterization using cone penetration tests.” J. Geotech. Geoenviron. Eng., 267–276.
Cao, Z., Wang, Y., and Li, D. (2016). “Quantification of prior knowledge in geotechnical site characterization.” Eng. Geol., 203, 107–116.
Ching, J., Wang, J. S., Juang, C. H., and Ku, C. S. (2015). “Cone penetration test (CPT)-based stratigraphic profiling using the wavelet transform modulus maxima method.” Can. Geotech. J., 52(12), 1993–2007.
Dasaka, S. M., and Zhang, L. M. (2012). “Spatial variability of in situ weathered soil.” Géotechnique, 62(5), 375–384.
Elfeki, A., and Dekking, M. (2001). “A Markov chain model for subsurface characterization: Theory and applications.” Math. Geol., 33(5), 569–589.
Elfeki, A. M. M., and Dekking, F. M. (2005). “Modelling subsurface heterogeneity by coupled Markov chains: Directional dependency, Walther’s law and entropy.” Geotech. Geol. Eng., 23(6), 721–756.
Elkateb, T., Chalaturnyk, R., and Robertson, P. K. (2003). “An overview of soil heterogeneity: Quantification and implications on geotechnical field problems.” Can. Geotech. J., 40(1), 1–15.
Fenton, G. A., and Griffiths, D. V. (2008). Risk assessment in geotechnical engineering, Wiley, Hoboken, NJ.
Forrester, A., Sobester, A., and Keane, A. (2008). Engineering design via surrogate modelling: A practical guide, Wiley, Chichester, U.K.
He, Y., et al. (2009). “Sequential indicator simulation and indicator kriging estimation of 3-dimensional soil textures.” Soil Res., 47(6), 622–631.
Houlsby, N. M. T., and Houlsby, G. T. (2013). “Statistical fitting of undrained strength data.” Géotechnique, 63(14), 1253–1263.
Li, D. Q., Qi, X. H., Cao, Z. J., Tang, X. S., Phoon, K. K., and Zhou, C. B. (2016a). “Evaluating slope stability uncertainty using coupled Markov chain.” Comput. Geotech., 73, 72–82.
Li, D. Q., Xiao, T., Cao, Z. J., Zhou, C. B., and Zhang, L. M. (2016b). “Enhancement of random finite element method in reliability analysis and risk assessment of soil slopes using subset simulation.” Landslides, 13(2), 293–303.
Li, J. H., Cassidy, M. J., Huang, J. S., Zhang, L. M., and Kelly, R. (2016c). “Probabilistic identification of soil stratification.” Géotechnique, 66(1), 16–26.
Li, W. (2007). “Markov chain random fields for estimation of categorical variables.” Math. Geol., 39(3), 321–335.
Li, X. Y., Zhang, L. M., and Li, J. H. (2016d). “Using conditioned random field to characterize the variability of geologic profiles.” J. Geotech. Geoenviron. Eng., 04015096.
Li, Z., Wang, X., Wang, H., and Liang, R. Y. (2016e). “Quantifying stratigraphic uncertainties by stochastic simulation techniques based on Markov random field.” Eng. Geol., 201, 106–122.
Liang, Y. R., Wang, Z. Z., and Guo, J. H. (2014). “Reservoir lithology stochastic simulation based on Markov random fields.” J. Cent. South Univ., 21(9), 3610–3616.
Liao, T., and Mayne, P. W. (2007). “Stratigraphic delineation by three-dimensional clustering of piezocone data.” Georisk, 1(2), 102–119.
Liu, Y., Jiang, Y. J., Xiao, H., and Lee, F. H. (2017). “Determination of representative strength of deep cement-mixed clay from core strength data.” Géotechnique, 67(4), 350–364.
Nobre, M. M., and Sykes, J. F. (1992). “Application of Bayesian kriging to subsurface characterization.” Can. Geotech. J., 29(4), 589–598.
Park, E. (2010). “A multidimensional, generalized coupled Markov chain model for surface and subsurface characterization.” Water Resour. Res., 46(11), W11509.
Phoon, K. K., et al. (2016). “Some observations on ISO2394: 2015 annex D (reliability of geotechnical structures).” Struct. Saf., 62, 24–33.
Phoon, K. K., Quek, S. T., and An, P. (2003). “Identification of statistically homogeneous soil layers using modified Bartlett statistics.” J. Geotech. Geoenviron. Eng., 649–659.
Qi, X. H., Li, D. Q., Phoon, K. K., Cao, Z. J., and Tang, X. S. (2016). “Simulation of geologic uncertainty using coupled Markov chain.” Eng. Geol., 207, 129–140.
Schöbi, R., and Sudret, B. (2015). “Application of conditional random fields and sparse polynomial chaos expansions to geotechnical problems.” Proc., 5th Int. Symp. on Geotechnical Safety and Risk, T. Schweckendiek, et al., eds., IOS Press, Rotterdam, Netherlands, 441–446.
Schöbi, R., Sudret, B., and Marelli, S. (2017). “Rare event estimation using polynomial-chaos kriging.” ASCE-ASME J. Risk Uncertainty Eng. Syst., Part A Civil Eng., 3(2), D4016002.
Sitharam, T. G., Samui, P., and Anbazhagan, P. (2008). “Spatial variability of rock depth in Bangalore using geostatistical, neural network and support vector machine models.” Geotech. Geol. Eng., 26(5), 503–517.
Vardanega, P. J., and Bolton, M. D. (2016). “Design of geostructural systems.” ASCE-ASME J. Risk Uncertainty Eng. Syst., Part A Civil Eng., 2(1), 04015017.
Wang, Y., Akeju, O. V., and Cao, Z. J. (2016a). “Bayesian equivalent sample toolkit (BEST): An excel VBA program for probabilistic characterization of geotechnical properties from limited observation data.” Georisk, 10(4), 251–268.
Wang, Y., Cao, Z., and Li, D. (2016b). “Bayesian perspective on geotechnical variability and site characterization.” Eng. Geol., 203, 117–125.
Wang, Y., Huang, K., and Cao, Z. (2014). “Bayesian identification of soil strata in London clay.” Géotechnique, 64(3), 239–246.
Xiao, T., Li, D. Q., Cao, Z. J., Au, S. K., and Phoon, K. K. (2016). “Three-dimensional slope reliability and risk assessment using auxiliary random finite element method.” Comput. Geotech., 79, 146–158.
Xiao, T., Li, D. Q., Cao, Z. J., and Tang, X. S. (2017). “Full probabilistic design of slopes in spatially variable soils using simplified reliability analysis method.” Georisk, 11(1), 146–159.
Zhang, L. M., and Dasaka, S. M. (2010). “Uncertainties in geologic profiles versus variability in pile founding depth.” J. Geotech. Geoenviron. Eng., 1475–1488.
Zhu, H., and Zhang, L. M. (2013). “Characterizing geotechnical anisotropic spatial variations using random field theory.” Can. Geotech. J., 50(7), 723–734.
Zhu, H., Zhang, L. M., Xiao, T., and Li, X. Y. (2017). “Generation of multivariate cross-correlated geotechnical random fields.” Comput. Geotech., 86, 95–107.
Information & Authors
Information
Published In
ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering
Volume 3 • Issue 4 • December 2017
Copyright
©2017 American Society of Civil Engineers.
History
Received: Dec 20, 2016
Accepted: Apr 17, 2017
Published online: Jul 22, 2017
Published in print: Dec 1, 2017
Discussion open until: Dec 22, 2017
Authors
Metrics & Citations
Metrics
Citations
Download citation
If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.