Neural network based inspection of voids and karst conduits in hydro-electric power station tunnels using GPR

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Date

2018

Authors

Gokhan Kilic
Levent Eren

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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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, GPR, Karst Conduits, Neural Network, TBM, NDT

Fields of Science

0211 other engineering and technologies, 02 engineering and technology, 01 natural sciences, 0105 earth and related environmental sciences

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OpenCitations Citation Count
41

Source

Journal of Applied Geophysics

Volume

151

Issue

Start Page

194

End Page

204
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CrossRef : 41

Scopus : 48

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Mendeley Readers : 51

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