Design of Deep Braced Excavation in Urban Geotechnical Environments - Couverture souple

Zhang; Li; Hong; Yuan

Couverture souple

ISBN 10 : 0443138826 ISBN 13 : 9780443138829

Editeur : Elsevier, 2024

Synopsis

Design of Deep Braced Excavation in Urban Geotechnical Environments presents the design and calculation of deep braced excavation in urban geotechnical environments, considering the soil characteristics of spatial variability and anisotropy, as well as excavation responses of urban adjacent utilities such as pipelines, tunnels, foundation piles, and buildings. The text begins with coverage of overall stability, earth pressure and strut force, retaining wall responses, and ground movements. Numerical modeling and computer codes are also outlined in detail. Final chapters conclude with an examination of the determination of excavation responses of urban adjacent utilities and failure analysis based on several case histories.

This book will be ideal for those that need the latest knowledge in both theory and practical application for deep excavation problems.

A propos du livre

À propos des auteurs

Prof. Wengang ZHANG is currently full professor in School of Civil Engineering, Chongqing University, China. His research interests focus on impact assessment on the built environment induced by underground construction, as well as big data and machine learning in geotechnics and geoengineering. He published more than 90 ISI papers in Web of Sciences and 27 conference papers. He is now the member of the ISSMGE TC304 (Reliability), TC309 (Machine Learning), and TC219 (System Performance of Geotechnical Structures), SRMEG, ISRM, IAEG, CISMGE . Dr Zhang has been selected as the World's Top 2% Scientists 2020.

Yanmei Zhang is currently Associate Professor in College of Aerospace Engineering, Chongqing University, China. She obtained her PhD in Nanyang Technological University in 2016. Her research interests focus on fatigue and failure assessment of engineering structures, fracture analyses of polymeric composites, and applications of machine learning technique in geoengineering. She is the member of Chinese Society of Theoretical and Applied Mechanics.

Dr. Runhong Zhang is presently Research Fellow in Chongqing University, China. She obtained her PhD in Chongqing University in 2021. She studied as an exchange student in Nanyang Technological University, Singapore, in Oct. 2018 to Apr. 2019, under the support of the project "Effect of deep excavations on the adjacent built-up environment and reliability analysis". Her research interest involves numerical modelling for braced excavation and reliability analysis, and she is also interested in stability evaluation of braced excavation, inverse analysis, spatial variability of soil properties. She is familiar with finite element analysis software Plaxis, and she has some experience on modeling braced excavation system adjacent to slopes, tunnels and passive piles. she has published several international research papers about the effect of deep excavations on the adjacent built-up environment and reliability analysis.

Yongqin Li is currently a PhD candidate of Chongqing University, China, received her B.Eng degree in China University of Geosciences Beijing in 2014. She is mainly engaged in the field of Braced excavation stability and environmental impact, interested in numerical analysis and surrogate model predictions of braced excavation induced deformation. Published academic papers with the related theme in several international journals, including Computers and Geotechnics, Underground Space, Geoscience Frontiers, Journal of Rock Mechanics and Geotechnical Engineering.

Li Hong is a Ph.D candidate of Chongqing University, China, majored in geotechnical civil engineering. He obtained his Bachelor of Engineering degree from Anhui Jianzhu University in 2014. He has been involved in research on reliability analysis and optimal design of deep excavations. During postgraduate period, he conducted research on system reliability analysis of deep excavation via random finite element and machine learning method, presented a multiple objectives optimization framework for design of retaining system.

Détails de l'édition

• Éditeur: Elsevier
• Date d'édition: 2024
• Langue: anglais
• ISBN 10: 0443138826
• ISBN 13: 9780443138829
• Reliure: Broché
• Nombre de pages: 482
• Coordonnées du fabricant: non disponible
• Personne responsable: Barbara Criscuolo; b.criscuolo@lswr.it; ; Via Spadolini, 7; Milano; 20141; Italie