CPT-Based Probabilistic Characterization of Three-Dimensional Spatial Variability Using MLE
Publication: Journal of Geotechnical and Geoenvironmental Engineering
Volume 144, Issue 5
Abstract
Engineering geological characterization, subject to spatial variability of soil properties, is a three-dimensional (3D) problem in reality, although it is often simplified as one- or two-dimensional. Direct characterization of 3D spatial variability is a challenging task due to the scarcity of geotechnical data and a satisfactory characterization method. To address such a problem, this paper develops a cone penetration test (CPT)–based probabilistic approach for characterizing 3D spatial variability underlying the framework of maximum likelihood estimation (MLE). A matrix decomposition technique is applied to enhance the practical application of MLE for high-dimensional and spatially correlated data. Results of a case study and three virtual site analyses indicate that MLE provides more accurate estimates of random field parameters with smaller statistical uncertainty than the commonly used method of moments with best fitting, particularly for the estimation of scale of fluctuation. In addition, simultaneous vertical and horizontal characterization based on multiple CPTs is a feasible way for 3D spatial variability characterization in the presence of limited data, such as the limited sounding issue and the thin layer issue. The sampling strategy having some closely located CPTs is preferable for 3D spatial variability characterization.
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Acknowledgments
This work was supported by the National Key R&D Program of China (Project No. 2017YFC1501301), the National Natural Science Foundation of China (Project Nos. 51579190, 51528901, and 51679174) and the Research Grants Council of the Hong Kong Special Administrative Region (Project No. 16202716). The first author wishes to thank the Department of Civil and Environmental Engineering, Hong Kong University of Science and Technology, for hosting his visit as an exchange Ph.D. student.
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Published In
Journal of Geotechnical and Geoenvironmental Engineering
Volume 144 • Issue 5 • May 2018
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©2018 American Society of Civil Engineers.
History
Received: Mar 20, 2017
Accepted: Nov 8, 2017
Published online: Mar 10, 2018
Published in print: May 1, 2018
Discussion open until: Aug 10, 2018
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