4.7 Article

Modeling 3D soil lithotypes variability through geostatistical data fusion of CPT parameters

Journal

SCIENCE OF THE TOTAL ENVIRONMENT
Volume 698, Issue -, Pages -

Publisher

ELSEVIER
DOI: 10.1016/j.scitotenv.2019.134340

Keywords

CPT profiles; Alluvial deposits; Ordinary kriging; Intrinsic random function theory; Stochastic model; Po plain

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The Cone Penetration Test (CPT) measures enable to recognize vertical lithological sequence at each investigated point. From the tip resistance q(c) and sleeve resistance f(s) profiles, the Soil Behavior Type index I-SBT has been calculated, in order to identify the lithotypes alongside depth. The present study focuses on the combination of different variables to provide a lithological and mechanical subsoil characterization. The main objectives of the paper are: (1) to model the 3D spatial variability structure of the soil lithotypes and mechanical properties using q(c) and f(s) profiles; 2) to evaluate the uncertainties of the estimates for designing purposes. 182 CPTs were collected in a 900 km(2) area (corresponding to a subsoil volume of about 12 km(3)) located in the study site in the Bologna province (Italy). The study area is made up of fine-grained soils, silt and clay mixtures that are intercalated at different depths by sandy and gravelly soils. These variations of each soil fraction affect the engineering properties of these alluvial deposits. For 3D modeling, two geostatistical methods, Ordinary Kriging (stationary method), and Intrinsic Random Function theory (non-stationary method) have been used. The results show that the non-stationary method allows to obtain more reliable q(c) and f(s) predicted values. The final stochastic mechanical and lithological model enables engineers and geologists to detect the emerging of fan and paleochannels bodies where mean resistance values can abruptly change in terms of bearing capacity, liquefaction potential and static and dynamic settlement occurrence. (C) 2019 Elsevier B.V. All rights reserved.

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