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Boulanger, R.W. and DeJong, T.J. (2018) Inverse Filtering Procedure to Correct Cone Penetration Data for Thin-Layer and Transition Effects. In: Hicks, M.A., Pisanò, F. and Peuchen, J., Eds., Cone Penetration Testing 2018, CRC Press, London, 25-44.

has been cited by the following article:

• TITLE: Technique for Estimating the Cone Bearing Smoothing Parameters

  AUTHORS: Erick Baziw

  KEYWORDS: Cone Penetration Testing (CPT), Geotechnical Site Characterization, Optimal Estimation, Iterative Forward Modelling (IFM), Monte Carlo Techniques, Calibration

  JOURNAL NAME: International Journal of Geosciences, Vol.14 No.7, July 25, 2023

  ABSTRACT: Cone penetration testing (CPT) is an extensively utilized and cost effective tool for geotechnical site characterization. CPT consists of pushing at a constant rate an electronic cone into penetrable soils and recording the resistance to the cone tip (qc value). The measured qc values (after correction for the pore water pressure) are utilized to estimate soil type and associated soil properties based predominantly on empirical correlations. The most common cone tips have associated areas of 10 cm2 and 15 cm2. Investigators also utilized significantly larger cone tips (33 cm2 and 40 cm2) so that gravelly soils can be penetrated. Small cone tips (2 cm2 and 5 cm2) are utilized for shallow soil investigations. The cone tip resistance measured at a particular depth is affected by the values above and below the depth of interest which results in a smoothing or blurring of the true bearing values. Extensive work has been carried out in mathematically modelling the smoothing function which results in the blurred cone bearing measurements. This paper outlines a technique which facilitates estimating the dominant parameters of the cone smoothing function from processing real cone bearing data sets. This cone calibration technique is referred to as the so-called CPSPE algorithm. The mathematical details of the CPSPE algorithm are outlined in this paper along with the results from a challenging test bed simulation.