Piezocone and Cone Penetration Test (CPTu and CPT) Applications in Foundation Engineering



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Éditeur :

Butterworth-Heinemann


Paru le : 2019-11-23



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Description
Piezocone and cone penetration tests (CPTu and CPT) applications in foundation engineering includes different approaches for determining the bearing capacity of shallow foundations, along with methods for determining pile bearing capacity and settlement concepts. The use of soft computing (GMDH) neural networks related to CPT records and Geotechnical parameters are also discussed. In addition, different cases regarding the behavior of foundation performance using case records, such as shallow foundation, deep soil improvement, soil behavior classification (SBC), and bearing capacity are also included. - Provides the latest on CPT and CPTu performance in geotechnical engineering, i.e., bearing capacity, settlement, liquefaction, soil classification and shear strength prediction - Introduces soft computing methods for processing soil properties and pile bearing capacity via CPT and CPTu - Explains CPT and CPTu testing methods which allows for the continuous, or virtually continuous, record of ground conditions
Pages
390 pages
Collection
n.c
Parution
2019-11-23
Marque
Butterworth-Heinemann
EAN papier
9780081027660
EAN EPUB SANS DRM
9780081028742

Prix
179,35 €

Abolfazl Eslami, Professor, Department of Geotechnical Engineering, Amirkabir University of Technology, Tehran, Iran.Sara Moshfeghi, Department of Geotechnical Engineering, Amirkabir University of Technology, Tehran, IranHossein MolaAbasi received his MSc and PhD in Geotechnical Engineering from the University of Guilan and Babol University of Technology, Iran, in 2010 and 2016 respectively, and he works as an Assistant Professor at Gonbad University. He is currently working on the soil improvement, particularly zeolite or/ and cement improved soils, the basis of which is laboratory-based and has a noticeable number of students in this field. He has published numerous articles which subjects revolve around the experimental tests that can be found in Google Scholar. Furthermore, he seeks to develop a relationship based on neural networks in his articles.Mohammad M. Eslami, Department of Civil and Environmental Engineering, University of California, Los Angeles

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