Neural Network Based Inspection of Voids and Karst Conduits in Hydro-Electric Power Station Tunnels Using Gpr
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Date
2018
Authors
Kilic, Gokhan
Eren, Levent
Journal Title
Journal ISSN
Volume Title
Publisher
Elsevier Science Bv
Open Access Color
Green Open Access
Yes
OpenAIRE Downloads
OpenAIRE Views
Publicly Funded
No
Abstract
This paper reports on the fundamental role played by Ground Penetrating Radar (GPR), alongside advanced processing and presentation methods, during the tunnel boring project at a Dam and Hydro -Electric Power Station. It identifies from collected GPR data such issues as incomplete grouting and the presence of karst conduits and voids and provides full details of the procedures adopted. In particular, the application of collected GPR data to the Neural Network (NN) method is discussed. (C) 2018 Elsevier B.V. All rights reserved.
Description
Keywords
GPR, TBM, NDT, Karst conduits, Neural network, Concrete, Sites, Radar
Fields of Science
0211 other engineering and technologies, 02 engineering and technology, 01 natural sciences, 0105 earth and related environmental sciences
Citation
WoS Q
Q2
Scopus Q
Q2

OpenCitations Citation Count
40
Source
Journal of Applıed Geophysıcs
Volume
151
Issue
Start Page
194
End Page
204
PlumX Metrics
Citations
CrossRef : 41
Scopus : 48
Captures
Mendeley Readers : 48
SCOPUS™ Citations
48
checked on Apr 08, 2026
Web of Science™ Citations
39
checked on Apr 08, 2026
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