Bayesian identification of soil stratigraphy based on soil behaviour type index

Canadian Geotechnical Journal - Tập 56 Số 4 - Trang 570-586 - 2019
Zi-Jun Cao1, Shuo Zheng1, Dianqing Li1, Kok‐Kwang Phoon2
1State Key Laboratory of Water Resources and Hydropower Engineering Science, Institute of Engineering Risk and Disaster Prevention, Wuhan University 8 Donghu South Road, Wuhan 430072, P.R. China.
2Department of Civil and Environmental Engineering, National University of Singapore, Blk E1A, #07-03, 1 Engineering Drive 2, Singapore 117576.

Tóm tắt

The cone penetration test (CPT) has been widely used to determine the soil stratigraphy (including the number N and thicknesses HNof soil layers) during geotechnical site investigation because it is rapid, repeatable, and economical. For this purpose, several deterministic and probabilistic approaches have been developed in the literature, but these approaches generally only give the “best” estimates (e.g., the most probable values) of N and HNbased on CPT data according to prescribed soil stratification criteria, providing no information on the identification uncertainty (degrees-of-belief) in these “best” estimates. This paper develops a Bayesian framework for probabilistic soil stratification based on the profile of soil behaviour type index Iccalculated from CPT data. The proposed Bayesian framework not only provides the most probable values of N and HN, but also quantifies their associated identification uncertainty based on the Icprofile and prior knowledge. Equations are derived for the proposed approach, and they are illustrated and validated using real and simulated Icprofiles. Results show that the proposed approach properly identifies the most probable soil stratigraphy based on the Icprofile and prior knowledge, and rationally quantifies the uncertainty in identified soil stratigraphy with consideration of inherent spatial variability of Ic.

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Canadian Geotechnical Journal

Tập 56 Số 4

570-586

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