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Total Size:
185.5 MB
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1C447D1B79BE8999B33EAC0F49C845AFC885BE80
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April 22, 2026, 5:14 p.m.
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(Last updated: April 22, 2026, 5:14 p.m.)
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| ['Phoon K. Databases for Data-Centric Geotechnics. Site Characterization 2025.pdf'] | 0 bytes |
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185.5 MB
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| Uploaded by andryold1 | Size 185.5 MB | Health [ 21 /44 ] | Added 2026-04-22 |
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382.1 MB
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| Uploaded by NoMercyReal | Size 382.1 MB | Health [ 102 /22 ] | Added 2023-06-02 |
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| Uploaded by Silmarillion | Size 382.1 MB | Health [ 9 /3 ] | Added 2023-06-02 |
NOTE
SOURCE: Phoon K. Databases for Data-Centric Geotechnics. Site Characterization 2025
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COVER
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MEDIAINFO
Textbook in PDF format Databases for Data-Centric Geotechnicsforms a definitive reference and guide to databases in geotechnical and rock engineering, to enhance decision-making in geotechnical practice using data-driven methods. This first volume pertains to site characterization. The opening chapter presents an in-depth analysis of site data attributes, including the establishment of a new taxonomy of site data under “4S” (site generalizations, spatial features, sampling characteristics, and smart data) to provide a novel agenda for data-driven site characterization. Type 3 machine learning methods (disruptive value) are possible as sensors become more pervasive and more intelligent. A comprehensive overview of site characterization information is also presented with a focus on its availability, coverage, value to decision making, and challenges. The remaining13 chapters cover databases of soil and rock properties and the application of these databases to rock socket behavior, rock classification, settlement on soft marine clays, permeability of fine-grained soils, and liquefaction among others. The databases were compiled from studies undertaken in many countries including Austria, Australia, Brazil, Canada, China, France, Finland, Germany, India, Iran, Japan, Korea, Malaysia, Mexico, New Zealand, Norway, Singapore, Sweden, Thailand, the United Kingdom, and the United States. This volume on site characterization is a companion to the volume on geotechnical structures. Databases for Data-Centric Geotechnicsrepresents the most diverse and comprehensive assembly of database research in a single publication (consisting of two volumes) to date. It follows from Model Uncertainties for Foundation Design, also published by CRC Press, and suits specialist geotechnical engineers, researchers and graduate students. About the Author Kok-Kwang Phoon is Cheng Tsang Man Chair Professor and President of the Singapore University of Technology and Design. He was awarded the ASCE Norman Medal twice in 2005 and 2020, the Humboldt Research Award in 2017, and the ASCE Alfredo Ang Award in 2024. He is the Founding Editor of Georisk and Geodata and AI. He is a Fellow of the Academy of Engineering Singapore and Singapore National Academy of Science. Chong Tang is Professor at Dalian University of Technology in China and a former senior research fellow at the National University of Singapore. He was awarded the ASCE Norman Medal in 2020
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