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3D geotechnical modeling of subsurface soils in Kerman city, southeast Iran

3D geotechnical modeling of subsurface soils in Kerman city, southeast Iran Subsurface stratigraphy has recently been a subject of intense research within the last two decades for dealing with the complicated nature of subsurface ground layers through building three-dimensional geological models. Considering the importance of subsurface soil characterization in urban areas in geotechnical and geological engineering projects, the present study was conducted to propose a three-dimensional (3D) geological engineering model using the sequential Gaussian simulation (SGS) approach for the subsurface soil of the city of Kerman, southeast Iran. Due to the intense variability of soil in the study area, civil engineering projects are sometimes encountered with severe problems in the city. Hence, a better understanding of the soil-related problems has to be gained for dealing with issues in the current and future civil engineering works. The main goal of the present research is to incorporate the SGS method for studying the spatial variability of soil through variograms and then forecasting the values of soil properties at unsampled locations. For this purpose, index geotechnical parameters, including standard penetration test number (SPTN), fine-grained material percentage, plasticity index (PI), and liquid limit (LL), were used as the input data. A database consisting of 700 borehole data was prepared. Then, the raw data were normalized prior to importing to the SGS model. Next, maps related to the average of all realizations along with the coefficient of variation (CV) were prepared for each variable. Finally, the prepared maps were interpreted based on the sedimentary environment of Kerman. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Bulletin of Engineering Geology and the Environment Springer Journals

3D geotechnical modeling of subsurface soils in Kerman city, southeast Iran

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References (43)

Publisher
Springer Journals
Copyright
Copyright © 2018 by Springer-Verlag GmbH Germany, part of Springer Nature
Subject
Earth Sciences; Geotechnical Engineering & Applied Earth Sciences; Geoengineering, Foundations, Hydraulics; Geoecology/Natural Processes; Nature Conservation
ISSN
1435-9529
eISSN
1435-9537
DOI
10.1007/s10064-018-1240-7
Publisher site
See Article on Publisher Site

Abstract

Subsurface stratigraphy has recently been a subject of intense research within the last two decades for dealing with the complicated nature of subsurface ground layers through building three-dimensional geological models. Considering the importance of subsurface soil characterization in urban areas in geotechnical and geological engineering projects, the present study was conducted to propose a three-dimensional (3D) geological engineering model using the sequential Gaussian simulation (SGS) approach for the subsurface soil of the city of Kerman, southeast Iran. Due to the intense variability of soil in the study area, civil engineering projects are sometimes encountered with severe problems in the city. Hence, a better understanding of the soil-related problems has to be gained for dealing with issues in the current and future civil engineering works. The main goal of the present research is to incorporate the SGS method for studying the spatial variability of soil through variograms and then forecasting the values of soil properties at unsampled locations. For this purpose, index geotechnical parameters, including standard penetration test number (SPTN), fine-grained material percentage, plasticity index (PI), and liquid limit (LL), were used as the input data. A database consisting of 700 borehole data was prepared. Then, the raw data were normalized prior to importing to the SGS model. Next, maps related to the average of all realizations along with the coefficient of variation (CV) were prepared for each variable. Finally, the prepared maps were interpreted based on the sedimentary environment of Kerman.

Journal

Bulletin of Engineering Geology and the Environment – Springer Journals

Published: Mar 2, 2018

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