Random field characterization of CPTU soil behavior type index of Jiangsu quaternary soil deposits
Tóm tắt
The soil behavior type index (I
c) obtained from piezocone penetration tests (CPTU) has been widely applied in a series of geotechnical issues including the identification of soil stratum, estimation of soil properties and liquefaction analysis. To provide spatial statistics of I
c for the probabilistic analysis of these geotechnical applications, this paper investigated the inherent vertical variability of the I
c data using Gaussian random field theory. To achieve the analysis, 134 CPTU soundings were performed at the sites of four typical geologic formations. These formations included marine, Yangtze River Delta, long river floodplain and abandoned Yellow River floodplain deposits in the Jiangsu Province, China. Statistically homogeneous soil units (HSUs) were firstly identified based on a screening procedure. Then the probability density distribution of the I
c data in each HSU was studied using a formal normality test and the quantile plot method. Afterwards, the method of moment was used to estimate the three random field model parameters of I
c, including the mean value (μ
Y
), coefficient of variation (COV), and vertical scale of fluctuation (δ
v). It was shown that the normality hypothesis may be suitable for both raw I
c and the fluctuation components of I
c data in a qualified sense, whereas, in a strict sense, the feasibility of this assumption is complicated with about 50 % data passing the formal normality test. The COV of I
c data of the Jiangsu soils varies from 1.9 to 14 %. The δ
v of I
c profile ranges from 0.1 to 1.17 m. The impacts of the geologic formation and soil behavior type on the probability density distribution and random field characteristics of I
c data were observed as the normality, COV and scale of fluctuation values of I
c tend to be similar, provided that the soils are of the same geologic formation. Finally, suggestions for future selections of the normality hypothesis, coefficient of variation and vertical scale of fluctuation of I
c data are proposed.
Tài liệu tham khảo
Baecher GB (1999) Discussion on ‘Inaccuracies associated with estimating random measurement errors’. J Geotech Geoenviron Eng 125:79–80
Baecher GB, Christian JT (2003) Reliability and statistics in geotechnical engineering. John Wiley and Sons, New York
Been K, Jefferies MG (1992) Towards Systematic CPT Interpretation. In: Proceedings of Wroth Memorial Symposium, Thomas Telford, London, pp 121–134
Cafaro F, Cherubini C (2002) Large sample spacing in evaluation of vertical strength variability of clayey soil. J Geotech Geoenviron Eng 128(7):558–568
Cai GJ, Liu SY, Puppala AJ (2011) Comparison of CPT charts for soil classification using PCPT data: Example from clay deposits in Jiangsu Province, China. Eng Geol 121:89–96
Cai GJ, Liu SY, Puppala AJ (2012) Reliability assessment of CPTU-based pile capacity predictions in soft clay deposits. Eng Geol 141:84–91
Campanella RG, Wickremesinghe DS, Robertson PK (1987) Statistical treatment of cone penetrometer test data. In: Proceedings of 5th International Conference on Applications of Statistics and Probability in Soil and Structural Engineering, Vancouver, 2, pp 1011–1019
Cao ZJ, Wang Y (2013) Bayesian approach for probabilistic site characterization using cone penetration tests. J Geotechn Geoenviron Eng 139(2):267–276
Ching JY, Phoon KK (2012a) Probabilistic model for overall shear strengths of spatially variable soil masses. GeoCongress 2012—State of the Art and Practice in Geotechnical Engineering (GSP 225), ASCE, Reston, pp 2866–2875
Ching JY, Phoon KK (2012b) Modeling parameters of structured clays as a multivariate normal distribution. Can Geotech J 49(5):522–545
Ching JY, Phoon KK (2013a) Probability distribution for mobilized shear strengths of spatially variable soils under uniform stress states. GeoRisk 2013, Assessment and Management of Risk for Engineered Systems and Geohazards, London, Taylor and Francis, vol 7 no (3), pp 209–224
Ching JY, Phoon KK (2013b) Mobilized shear strength of spatially variable soils under simple stress states. Struct Saf 41:20–28
Ching JY, Phoon KK (2014) Correlations among some clay parameters—the multivariate distribution. Can Geotech J 51:686–704
Ching JY, Chen JR, Yeh JY, Phoon KK (2012) Updating uncertainties in friction angles of clean sands. J Geotech Geoenviron Eng ASCE 138(2):217–229
Ching JY, Phoon KK, Chen CH (2014) Modeling piezocone cone penetration (CPTU) parameters of clays as a multivariate normal distribution. Can Geotech J 51(1):77–91
Christian TJ, Baecher G (2011) Unresolved Problems in Geotechnical Risk and Reliability. In: Geo-Risk 2011, pp 50–63
DeGroot DJ, Baecher GB (1993) Estimating autocovariance of in situ soil properties. J Geotechn Eng ASCE 119(1):147–166
Elkateb T, Chalaturnyk R, Robertson PK (2003) An overview of soil heterogeneity: quantification and implications on geotechnical field problems. Can Geotech J 40:1–15
Fenton G (1999) Random field modeling of CPT data. J Geotechn Geoenviron Eng 125(6):486–498
Fenton GA, Griffiths DV (2008) Risk Assessment in Geotechnical Engineering. John Wiley and Sons, Hoboken
Fenton GA, Griffiths DV (2010) Reliability-based geotechnical engineering. GeoFlorida 2010: Advances in Analysis, Modeling and Design, pp 14–52
Jaksa MB (1995) The Influence of Spatial Variability on the Geotechnical Design Properties of a Stiff, Overconsolidated Clay. Ph.D. Thesis, Faculty of Engineering, University of Adelaide
Jaksa MB (2007) Modeling the natural variability of over-consolidated clay in Adelaide, South Australia. In: Proceedings of the Second International Workshop on Characterisation and Engineering Properties of Natural Soils, Taylor and Francis, London, pp 2721–2751
Jaksa MB, Fenton GA (2002) Assessment of fractal behavior of soils. In: Pöttler R, Klapperich H, Schweiger H (eds) Proceedings of International Conference on Probabilistics in GeoTechnics: Technical and Economic Risk Estimation. United Engineering Foundation, New York, pp 47–54
Jaksa MB, Brooker PI, Kaggwa WS (1997) Inaccuracies associated with estimating random measurement errors. J Geotech Geoenviron Eng 123(5):393–401
Jaksa MB, Kaggwa WS, Brooker PI (2000) Experimental Evaluation of the Scale of Fluctuation of a Stiff Clay. In: Proceedings of the 8th International Conference on Applications of Statistics and Probability in Soil and Structural Engineering. Balkema, Rotterdam, pp 415–422
Jaksa MB, Yeong KS, Wong KT, Lee SL (2004) BLM spatial variability of elastic modulus in sand from the Dilatometer. In: Proceedings of 9th Australia New Zealand Conference on Geomechanics, Auckland, pp 289–294
Jefferies MG, Davies MP (1991) Soil classification by the cone penetration test: Discussion. Can Geotech J 28(1):173–176
Jefferies MG, Davies MP (1993) Use of CPTU to estimate equivalent SPT N60. Geotech Test J 16(4):458–468
Juang CH, Fang SY, Khor EH (2006) First-order reliability method for probabilistic liquefaction triggering analysis using CPT. J Geotech Geoenviron Eng 132(3):337–350
Juang CH, Chen CH, Mayne PW (2008) CPTU simplified stress-based model for evaluating soil liquefaction potential. Soils Found 48(6):755–770
Juang CH, Ching JY, Ku CS, Hsieh YH (2012) Unified CPTu-based probabilistic model for assessing probability of liquefaction of sand and clay. Géotechnique 62(10):877–892
Ku CS, Juang CH, Ou CY (2010) Reliability of CPT I c as an index for mechanical behaviour classification of soils. Géotechnique 60(11):861–875
Kulhawy FH, Birgisson B, Grigoriu MD (1992) Reliability-based foundation design for transmission line structures: Transformation models for in situ tests. Report EL-5507(4). Palo Alto, CA: Electric Power Research Institute
Liu CN, Chen CH (2006) Mapping liquefaction potential considering spatial correlations of CPT measurements. J Geotech Geoenviron Eng 132(9):1178–1187
Liu CN, Chen CH (2010) Spatial correlation structures of CPT data in a liquefaction site. Eng Geol 111:43–50
Lunne T, Robertson PK, Powell JJM (1997) Cone penetration testing in geotechnical practice. Blackie Academic and Professional, London
Mayne PW (2007) Cone Penetration Testing: a synthesis of highway practice. NCHRP Report, Transportation Research Board, National Academies Press, Washington, D.C
Park HM (2008) Univariate analysis and normality test using SAS, Stata, and SPSS. Technical Working Paper. The University Information Technology Services (UITS) Center for Statistical and Mathematical Computing, Indiana University
Phoon KK, Ching J (2012) Beyond coefficient of variation for statistical characterization of geotechnical parameters. Keynote lecture of Geotechnical and Geophysical Site Characterization 4, ISC 4, pp 113–130
Phoon KK, Kulhawy FH (1999a) Characterization of geotechnical variability. Can Geotech J 36(4):612–624
Phoon KK, Kulhawy FH (1999b) Evaluation of geotechnical property variability. Can Geotech J 36(4):625–639
Phoon KK, Quek ST, An P (2003a) Identification of statistically homogeneous soil layers using modified Bartlett statistics. J Geotech Geoenviron Eng 129(7):649–659
Phoon KK, Kulhway FH, Grigoriu MD (2003b) Multiple resistance factor design for shallow transmission line structure foundation. J Geotech Geoenviron Eng 129(9):807–818
Phoon KK, Ching JY, Chen JR (2013) Performance of reliability-based design code formats for foundations in layered soils. Comput Geotech 126:100–106
Razali NM, Wah YB (2011) Power comparisons of Shapiro–Wilk, Kolmogorov–Smirnov, Lilliefors and Anderson–Darling tests. J Stat Model Anal 2(1):21–33
Robertson PK (2009a) Interpretation of cone penetration tests—a unified approach. Can Geotech J 46(11):1337–1355
Robertson PK (2009b) Performance based earthquake design using the CPT. Keynote lecture in IS-Tokyo
Robertson PK, Campanella RG (1983a) Interpretation of cone penetration tests. Part I: sand. Can Geotech J 20(4):718–733
Robertson PK, Campanella RG (1983b) Interpretation of cone penetration tests. Part II: clay. Can Geotech J 20(4):734–745
Robertson PK, Wride CE (1998) Evaluating cyclic liquefaction potential using the cone penetration test. Can Geotech J 35(3):442–459
Schnaid F (2009) In-situ testing in geomechanics: the main tests. Taylor and Francis, London
Spry MJ, Kulhawy FH, Grigoriu MD (1988) Reliability based foundation design for transmission line structures: geotechnical site characterization strategy. Report EL-5507(1), Electric Power Research Institute, Palo Alto, Calif
Stuedlein AW (2011) Random field model parameters for Columbia river silt. GeoRisk 2011, Risk Assessment and Management, American Society of Civil Engineers, pp 209–224
Stuedlein AW, Kramer SL, Arduino P, Holtz RD (2012) Geotechnical characterization and random field modeling of desiccated clay. J Geotech Geoenviron Eng 138(11):1301–1313
Uzielli M (2004) Variability of stress-normalized CPT parameters and application to seismic liquefaction initiation analysis. PhD dissertation, University of Florence
Uzielli M, Vannucchi G, Phoon KK (2005) Random field characterization of stress-normalized cone penetration testing parameters. Géotechnique 55(1):3–20
Vanmarcke EH (1977) Probabilistic modeling of soil profiles. J Geotech Eng Div ASCE 103(GT11):1227–1246
Zhu H, Zhang LM (2013) Characterizing geotechnical anisotropic spatial variations using random field theory. Can Geotech J 50(7):723–734