Abstract
The cone tip resistance data available for the clay site at Texas A&M University, USA (one of the National Geotechnical Experimentation Sites) are used to show how the spatial variation of a soil property can be quantified. It is suggested that the first step in quantifying the spatial variation of a soil property should be the identification or selection of the statistically homogeneous soil layers. A new simple procedure is suggested to identify statistically homogeneous layers in a soil profile. Through examples it is shown that the procedure works extremely well in identifying the statistically homogeneous layers. For the chosen statistically homogeneous layers, the spatial variation of cone tip resistance with depth is quantified in terms of a constant mean or a mean trend, variance/standard deviation/coefficient of variation or a variance around the mean trend, and a correlation or variogram function. Correlation distances in the depth direction were found to be between 0.1 and 0.5 m for the two soil layers investigated. It was shown that the correlation distance decreases in the presence of a global mean trend for the soil property. In such cases, it is important to note that a part of the correlation is automatically included in the mean trend function.
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References
Alonso, E.E.and Krizek, R.J.: Stochastic formulation of soil properties, In: Proc. Second Int. Conf. on Applications of Statistics and Probability in Soil and Struct. Engrg., Aachen, Germany, 1975, pp. 10–32.
Asaoka, A. and Grivas, D.A.: Spatial variability of the undrained strength of clays, J. Geotech. Engrg., ASCE, 108(5), (1982), 743–745.
Baecher, G.B.: On estimating auto-covariance of soil properties, Specialty Conference on Probabilistic Mechanics and Structural Reliability, ASCE, 110, (1984), 214–218.
Baker, R.: Modelling soil variability as a random field, Math. Geol., 16(5), (1984), 435–448.
Benoit, J. and Alba, P.: Catalog of National Geotechnical Experimentation Sites, Report to the National Science Foundation and the Federal Highway Administration, 1993.
Briaud, J.L.: The National Geotechnical Experimentation Sites at Texas A&M University: Clay and Sand: A summary, Report NGES-TAMU 007, Civil Engineering, Texas A&M University, 1997.
De Groot, D.J.: Analyzing spatial variability of in situ soil properties, Proc. of the Conference on Uncertainty in the Geologic Environment—From Theory to Practice (GSP 58), (eds.) C.D. Shackelford, P.P. Nelson and M.J.S. Roth, ASCE, New York, 1996, pp. 210–238.
Delhomme, J.P.: Spatial variability and uncertainty in groundwater flow parameters: A geostatistical approach, Water Resour. Res., 15(2), (1979), 269–280.
Fugro-McClelland (Southwest), Inc. Laboratory testing data report National Geotechnical Experimentation Sites Texas A&M University College Station, Texas, Technical Report submitted to Texas A&M University, 1996.
Gambolati, F. and Volpi, G.: Groundwater contour mapping in Venice by stochastic interpolators 1. Theory, Water Resour. Res., 15(2), (1979), 281–290.
Hegazy, Y.A., Mayne, P.W. and Rouhani, S.: Geostatiscal assessment of spatial variability in piezocone tests, Proc. Conference on Uncertainty in the Geologic Environment—Form Theory to Practice (GSP 58), C.D. Shackelford, P.P. Nelson and M.J.S. Roth, (eds.) ASCE, New York, 1996, pp. 254–268.
Journel, A.G. and Huijbregts, C.: Mining Geostatistics, Academic Press, Inc., New York, N.Y., 1978.
Kulatilake, P.H.S.W.: Probabilistic potentiometric surface mapping, J. Geotech. Engrg., ASCE, 115(11), (1989), 1569–1587.
Kulatilake, P.H.S.W. and Miller, K.M.: A scheme for estimating the spatial variation of soil properties in three dimensions, In Proc. Fifth Int. Conf. on Applications of Statistics and Probabilities in Soil and Struct. Engrg., Vancouver, British Columbia, Canada, 1987, pp. 669–677.
Kulatilake, P.H.S.W. and Ghosh, A.: An investigation into accuracy of spatial variation estimation using static cone penetrometer data, Proc. First Int. Symp. on Penetration Testing, Orlando, Fla., 1988, 815–821.
Lumb, P.: Spatial variability of soil properties, In Proc. Second Int. Conf. on Applications of Statistics and Probability in Soil and Struct. Engrg. Aachen, Germany, 1975, pp. 397–421.
Matheron, G.: The theory of regionalized variables and its applications, Les Cahiers du Center Morphologie Mathematique de Fountainbleau, Ecole des Mines, Fountainbleau, France, 1971, 221.
Orey, S.: Gaussian sample functions and Housdorff dimension of level crossings, x. Wahrsheninkeits theorie verw, Gebierte 15, (1970), 249–256.
Phoon, K.K., Quek, S.T. and An, P.: Modified Bartlett Test for Geostatistical Analysis, Proc. Eighth Int. Conference on Applications of Statistics and Probability (1), Sydney, 1999, pp. 439–444.
Simon, P. and Briaud, J.L.: National Geotechnical Experimentation Sites at Texas A&M University: Clay and Sand. Soil Data in Electronic Form, 1995–1996, Report No. NGESTAMU-006, Dept. of Civil Engineering, Texas A&M University, College Station, 1996.
Tabba, M.M. and Yong, R.N.: Mapping and predicting soil properties: Theory,J. Engrg. Mech., ASCE, 107(5), (1981), 773–793.
Tang, W.H.: Probabilistic evaluation of penetration resistances, J. of Geotech. Engrg., ASCE, 105(GT10), (1979), 1173–1191.
Tumay, M.T. and Bynoe, Y.: In situ testing at the National Geotechnical Experimentation Sites (Phase 2), Report to the Federal Highway Administration, 1998.
VanMarcke, E.H.: Probabilistic modeling of soil profiles, J. Geotech. Engrg., ASCE, 102(11), (1977), 1247–1265.
VanMarcke, E.H.: Random fields: Analysis and synthesis, The MIT Press, Cambridge, Mass, 1983.
Wickremesinghe, D.S. and Campanella, R.G.: Statistical methods for soil layer boundary location using the cone penetration test, Proc. Sixth Int. Conf. on Applications of Statistics and Probability to Civil Engineering, Mexico City, 1991, pp. 636–643.
Wu, T.H. and Wong, K.: Probabilistic soil exploration: a case history, J. of Geotech. Engrg., ASCE, 107(GT12), (1981), 1693–1711.
Yaglom, A.M. Theory of stationary random functions, Prentice-Hall, Inc., Englewood Cliffs, N.J., 1962.
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Kulatilake, P.H.S.W., Um, JG. Spatial variation of cone tip resistance for the clay site at Texas A&M University. Geotechnical and Geological Engineering 21, 149–165 (2003). https://doi.org/10.1023/A:1023526614301
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DOI: https://doi.org/10.1023/A:1023526614301