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

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Publicly Funded

No
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Top 10%
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Top 10%
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Top 10%

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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
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OpenCitations Citation Count
40

Source

Journal of Applıed Geophysıcs

Volume

151

Issue

Start Page

194

End Page

204
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Citations

CrossRef : 41

Scopus : 48

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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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4.9804

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