A probabilistic model for CPT-based soil classification

Date

2003-07-09

Author

Çetin, Kemal Önder
Ozan, C

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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

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Due to lack of soil sampling during a conventional cone penetration testing, it is necessary to classify soils based on recorded tip and sleeve friction values. Currently available semi-empirical methods of Robertson and Wride (1997) and Olsen and Mitchell (1995) exhibit a significant variability in the estimation of soil type based on cone penetration test (CPT) data. Thus within the confines of this paper it is attempted to present a new probabilistic CPT-based soil classification methodology which addresses the uncertainties intrinsic to the problem. For this purpose, a database composed of 4 10 CPT data pairs of tip resistance (q(c)), friction ratio (R-f) and soil classification based on Unified Soil Classification System (USCS) was compiled. Soil classification was performed by laboratory testing of the disturbed samples retrieved from the boreholes within 2 in of each CPT hole. It is intended to develop a probabilistic model, which will correlate CPT tip and sleeve friction values to actual soil classification.

Subject Keywords

Cone penetration test, Soil classification, Maximum likelihood methodology, Limit state models

URI

https://hdl.handle.net/11511/52724

Collections

Department of Civil Engineering, Conference / Seminar