Databases for Data-Centric Geotechnics Databases for Data-Centric Geotechnics
Challenges in Geotechnical and Rock Engineering

Databases for Data-Centric Geotechnics

Geotechnical Structures

    • 62,99 €
    • 62,99 €

Publisher Description

Databases for Data-Centric Geotechnics forms a definitive reference and guide to databases in geotechnical and rock engineering, to enhance decision-making in geotechnical practice using data-driven methods. This second volume pertains to geotechnical structures. The opening chapter presents a substantial survey of performance databases and the effectiveness of our prediction models in matching the field measurements in these databases, based on (1) full-scale field tests, (2) 39 prediction exercises organized as a part of international conferences, and (3) comparison between numerical analyses and in-situ or field measurements conducted by the French LCPC. The focus is on the evaluation of the statistical degree of confidence in predicting various of quantities of interest such as capacity and deformation. The following 18 chapters then present databases on the performance of shallow foundations, spudcan foundations, deep foundations, anchors and pipelines, retaining systems and excavations, and landslides. The databases were compiled from studies undertaken in many countries such as Australia, Belgium, Bolivia, Brazil, Canada, China, Egypt, France, Germany, Hungary, Iran, Ireland, Japan, Kenya, Malaysia, Netherlands, Norway, Poland, Portugal, South Africa, the United Kingdom and the United States.

This volume on geotechnical structures is a companion to the volume on site characterization. Databases for Data-Centric Geotechnics represents 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.

GENRE
Computing & Internet
RELEASED
2024
20 December
LANGUAGE
EN
English
LENGTH
690
Pages
PUBLISHER
CRC Press
SIZE
36.3
MB
Model Uncertainties in Foundation Design Model Uncertainties in Foundation Design
2021
Databases for Data-Centric Geotechnics Databases for Data-Centric Geotechnics
2024
Bayesian Compressive Sensing for Site Characterization Bayesian Compressive Sensing for Site Characterization
2025
AI-Enhanced Safety Evaluation for Tunnelling in Rock AI-Enhanced Safety Evaluation for Tunnelling in Rock
2025
Model Uncertainties in Foundation Design Model Uncertainties in Foundation Design
2021
Bayesian Machine Learning in Geotechnical Site Characterization Bayesian Machine Learning in Geotechnical Site Characterization
2024
Databases for Data-Centric Geotechnics Databases for Data-Centric Geotechnics
2024