Cone penetration testing
(CPT) is a cost effective and popular tool for geotechnical site
characterization. CPT consists of pushing at a constant rate an electronic
penetrometer into penetrable soils and recording cone bearing (qc),
sleeve friction (fc) and dynamic pore pressure (u)
with depth. The measured qc, fs and u values are utilized to estimate soil type and associated soil properties. A
popular method to estimate soil type from CPT measurements is the Soil Behavior
Type (SBT) chart. The SBT plots cone resistance vs friction ratio, Rf [where: Rf = (fs/qc)100%].
There are distortions in the CPT measurements which can result in erroneous SBT
plots. Cone bearing measurements at a specific depth are blurred or averaged
due to qc values being strongly influenced by soils within 10
to 30 cone diameters from the cone tip. The qcHMM algorithm
was
References
[1]
Lunne, T., Robertson, P. K. and Powell, J.J.M. (1997) Cone Penetrating Testing: In Geotechnical Practice. Taylor & Francis Group, Oxfordshire.
[2]
Robertson, P.K., Campanella, R.G., Gillespie, D. and Greig, J. (1986) Use of Piezometer Cone Data. In-Situ’86 Use of In-Situ Testing in Geotechnical Engineering, ASCE, Reston, 1263-1280.
[3]
Robertson, P.K. (1990) Soil Classification Using the Cone Penetration Test. Canadian Geotechnical Journal, 27, 151-158. https://doi.org/10.1139/t90-014
[4]
ASTM D6067/D6067M-17 (2017) Standard Practice for Using the Electronic Piezocone Penetrometer Tests for Environmental Site Characterization and Estimation of Hydraulic Conductivity. ASTM Vol. 4.09, Soil and Rock (II), D5877-Latest.
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Cai, G.J., Liu, L.Y., Tong, L.Y. and Du, G.Y. (2006) General Factors Affecting Interpretation for the Piezocone Penetration Test (CPTU). Journal of Engineering Geology, 14, 632-636.
[6]
de Ruiter, J. (1971) Electric Penetrometer for Site Investigations. Journal of the Soil Mechanics and Foundations Division, 97, 457-472. https://doi.org/10.1061/JSFEAQ.0001552
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Jamiolkowski, M., Ladd, C.C., Germaine, J.T. and Lancellotta, R. (1985) New Developments in Field and Laborator Testing of Soils. 11th International Conference on Soil Mechanics and Foundation Engineering, San Francisco, 12-16 August 1985, 57-154.
[8]
Boulanger, R.W. and DeJong, T.J. (2018) Inverse Filtering Procedure to Correct Cone Penetration Data for Thin-Layer and Transition Effects. In: Hicks, P. and Peuchen, Eds., Cone Penetration Testing 2018, Delft University of Technology, The Netherlands, 25-44.
[9]
Baziw, E. and Verbeek, G. (2021) Cone Bearing Estimation Utilizing a Hybrid HMM and IFM Smoother Filter Formulation. International Journal of Geosciences, 12, 1040-1054. https://doi.org/10.4236/ijg.2021.1211055
[10]
Baziw, E. and Verbeek, G. (2022) Identification of Thin Soil Layers Utilizing the qmHMM-IFM Algorithm on Cone Bearing Measurements. Geo-Congress 2022, Charlotte, 20-23 March 2022, 505-514. https://doi.org/10.1061/9780784484036
[11]
Baziw, E. and Verbeek, G. (2022) Methodology for Obtaining True Cone Bearing Estimates from Blurred and Noisy Measurements. In: Gottardi, G. and Tonni, L., Eds., Cone Penetration Testing 2022, Baziw Consulting Engineers, Vancouver, 115-120. https://doi.org/10.1201/9781003308829-9
[12]
Susila, E. and Hryciw, R.D. (2003) Large Displacement FEM Modelling of the Cone Penetration Test (CPT) in Normally Consolidated Sand. International Journal for Numerical and Analytical Methods in Geomechanics, 27, 585-602. https://doi.org/10.1002/nag.287
[13]
Kiousis, P.D., Voyiadjis, G.Z. and Tumay, M.T. (1988) A Large Strain Theory and Its Application in the Analysis of the Cone Penetration Mechanism. International Journal for Numerical and Analytical Methods in Geomechanics, 12, 45-60. https://doi.org/10.1002/nag.1610120104
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Nelder, J.A. and Mead, R. (1965) A Simplex Method for Function Optimization. Computing Journal, 7, 308-313. https://doi.org/10.1093/comjnl/7.4.308
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Baziw, E., Nedilko, B. and Weir-Jones, I. (2004) Microseismic Event Detection Kalman Filter: Derivation of the Noise Covariance Matrix and Automated First Break Determination for Accurate Source Location Estimation. Pure and Applied Geophysics, 161, 303-329. https://doi.org/10.1007/s00024-003-2443-8
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Baziw, E. (2011) Incorporation of Iterative Forward Modeling into the Principle Phase Decomposition Algorithm for Accurate Source Wave and Reflection Series Estimation. IEEE Transactions on Geoscience and Remote Sensing, 49, 650-660. https://doi.org/10.1109/TGRS.2010.2058122