NDLI: The displacement computation and construction pre-control of a foundation pit in Shanghai utilizing FEM and intelligent methods

Content Provider	Springer Nature Link
Author	Chen, You Liang Azzam, Rafig Zhang, Fu Bo
Copyright Year	2006
Abstract	Controlling the displacements of foundation pit walls and supporting structures is one of the most effective measures for ensuring safety of foundation pit construction. Because of this, the accurate displacement computation of foundation pit walls and supporting structures is paid great attention by geotechnical scientists and engineers. In this paper, the three-dimensional displacement field of Deping Station foundation pit, which is part of Shanghai Track Traffic Line 6 project, is computed by means of ANSYS software. Artificial neural networks (ANNs) are a broad category of computer algorithms which have the ability to learn some target values (desired output) from a set of chosen input data that has been introduced to the network. The ANNs have very excellent ability in simulating nonlinear and complicated problems. In the current paper, the authors try to combine FEM method with ANNs so as to improve the computational accuracy. Basing on the computed results, fuzzy control theory is applied to construction pre-control. The application effect is satisfactory. The research result of current paper is very helpful for geotechnical construction and the development of geotechnical theory.
Starting Page	1781
Ending Page	1801
Page Count	21
File Format	PDF
ISSN	09603182
Journal	Geotechnical and Geological Engineering
Volume Number	24
Issue Number	6
e-ISSN	15731529
Language	English
Publisher	Kluwer Academic Publishers
Publisher Date	2006-01-01
Publisher Place	Dordrecht
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	foundation pit FEM method artificial neural networks fuzzy logic construction pre-control Hydrogeology Geotechnical Engineering Civil Engineering Terrestrial Pollution Waste Management/Waste Technology
Content Type	Text
Resource Type	Article
Subject	Soil Science Geology Architecture Geotechnical Engineering and Engineering Geology

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

Studies on Construction Pre-control of a Connection Aisle Between Two Neighbouring Tunnels in Shanghai by Means of 3D FEM, Neural Networks and Fuzzy Logic

Modeling soil collapse by artificial neural networks

Geotechnical applications in open pit mining

An intelligent approach to prediction and control ground vibration in mines

The artificial neural network as a tool for assessing geotechnical properties

Prestressed Foundation Beams on Elastic Layered Soil

Environmental Effects Induced by Deep Subway Foundation Pit Excavation in Yellow River Alluvial Landforms

A study of slope stability prediction using neural networks

Artificial Neural Network Prediction Models for Soil Compaction and Permeability

The displacement computation and construction pre-control of a foundation pit in Shanghai utilizing FEM and intelligent methods

Similar Documents

Studies on Construction Pre-control of a Connection Aisle Between Two Neighbouring Tunnels in Shanghai by Means of 3D FEM, Neural Networks and Fuzzy Logic

Modeling soil collapse by artificial neural networks

Geotechnical applications in open pit mining

An intelligent approach to prediction and control ground vibration in mines

The artificial neural network as a tool for assessing geotechnical properties

Prestressed Foundation Beams on Elastic Layered Soil

Environmental Effects Induced by Deep Subway Foundation Pit Excavation in Yellow River Alluvial Landforms

A study of slope stability prediction using neural networks

Artificial Neural Network Prediction Models for Soil Compaction and Permeability

The displacement computation and construction pre-control of a foundation pit in Shanghai utilizing FEM and intelligent methods