NDLI: A case study on the utilization of tunnel face mapping data for a back analysis based on artificial neural network

Content Provider	Springer Nature Link
Author	You, Kwangho
Copyright Year	2014
Abstract	In designing a tunnel, numerical analyses play a very important role in assessing the influence of the excavation on the stability of the tunnel and the behavior of the surrounding ground. However, ground properties used for analysis include a lot of uncertainties because they are estimated through limited investigations and tests. For this reason, the behavior of a tunnel and the surrounding ground, and the rock class predicted at the design stage of the tunnel might be quite different from those measured during the tunnel excavation. In this study, a back analysis using not only tunnel measurement date but also face mapping data is performed to reduce the uncertainties included in ground properties. To this end, rock classes were inferred using face mapping data according to RMR (Rock Mass Rating) system and the possible ranges of ground properties were selected. They were utilized as bounds in constructing a training database for an artificial neural network analysis. To validate the proposed methodology, the results of this study were compared and analyzed with those of the previous studies.
Starting Page	751
Ending Page	759
Page Count	9
File Format	PDF
ISSN	12267988
Journal	KSCE Journal of Civil Engineering
Volume Number	18
Issue Number	3
e-ISSN	19763808
Language	English
Publisher	Korean Society of Civil Engineers
Publisher Date	2014-03-22
Publisher Place	Heidelberg
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	tunnel back analysis artificial neural network monitoring data face mapping data Civil Engineering Industrial Pollution Prevention Geotechnical Engineering & Applied Earth Sciences
Content Type	Text
Resource Type	Article
Subject	Civil and Structural Engineering

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

A MEMS-based commutation module with vibration sensor for wireless sensor network-based tunnel-blasting monitoring

Identification of water/cement ratio of cement pastes, basing on the microstructure image analysis data and using artificial neural network

Prediction of subgrade resilient modulus using artificial neural network

Regression versus artificial neural networks: Predicting pile setup from empirical data

Artificial neural network for modeling nitrate pollution of groundwater in marginal area of Zayandeh-rood River, Isfahan, Iran

Evaluating impact of waste factors on project performance cost in Vietnam

Discharge prediction of circular and rectangular side orifices using artificial neural networks

Analytical evaluation of load movement on flexible pavement and selection of optimum neural network algorithm

GIS-based landslide susceptibility mapping using analytic hierarchy process and artificial neural network in Jeju (Korea)

A case study on the utilization of tunnel face mapping data for a back analysis based on artificial neural network

Similar Documents

A MEMS-based commutation module with vibration sensor for wireless sensor network-based tunnel-blasting monitoring

Identification of water/cement ratio of cement pastes, basing on the microstructure image analysis data and using artificial neural network

Prediction of subgrade resilient modulus using artificial neural network

Regression versus artificial neural networks: Predicting pile setup from empirical data

Artificial neural network for modeling nitrate pollution of groundwater in marginal area of Zayandeh-rood River, Isfahan, Iran

Evaluating impact of waste factors on project performance cost in Vietnam

Discharge prediction of circular and rectangular side orifices using artificial neural networks

Analytical evaluation of load movement on flexible pavement and selection of optimum neural network algorithm

GIS-based landslide susceptibility mapping using analytic hierarchy process and artificial neural network in Jeju (Korea)

A case study on the utilization of tunnel face mapping data for a back analysis based on artificial neural network