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GPR Forward Modelling and Imaging Analysis for Boulder Detection

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Iranian Journal of Science and Technology, Transactions of Civil Engineering Aims and scope Submit manuscript

Abstract

Boulders are incompletely weathered and “nearly spherical” granite, which widely distributes in fully weathered granite strata. If a tunnelling shield machine is driving in fully weathered granite strata, it frequently encounters boulders. In such circumstances, the cutter heads usually get stuck and the body of tunnelling shield machine is damaged by boulders. Therefore, it is highly essential to detect the boulders before tunnelling through the face. To accurately obtain the location and size information of the boulders, the ground-penetrating radar forward modelling and imaging analysis in boulder detection were conducted. First, a series of forwarding modelling was carried out to demonstrate the influence of boulder size and burial depth on the reflection curves. Then, the reflection curves caused by boulders were characterized, which was proved to be hyperbolic curves. Second, imaging analysis was set up to determine the location and size information of boulders. Based on the principle of portable ground-penetrating radar, the theoretical calculation method was derived for determining the reflection points. Comparing the numerical analysis results, the rationality of the theoretical method was verified. Subsequently, by evaluating the inverse of the theoretical calculation method, the imaging method to determine the location and size information of boulders was derived. In the end, an example was used to examine the accuracy of the imaging method. In a word, the imaging method could accurately determine the boulder size and location information from the ground-penetrating radar detection result, which provided a reliable basis for boulder treatment and disaster prevention.

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Data Availability

The datasets used or analysed during the current study are available from the corresponding author on reasonable request.

Code Availability

In this paper, an open-source software, gprMax, was used to model GPR detection. The homepage link is “http://www.gprmax.com/”, and the repository link is “https://github.com/gprmax/gprMax” where the download is anonymous.

References

  • Akinsunmade A, Karczewski J, Mazurkiewicz E et al (2019) Finite-difference time domain (FDTD) modeling of ground penetrating radar pulse energy for locating burial sites. Acta Geophys 67(6):1945–1953

    Article  Google Scholar 

  • Alnuaimy W, Huang Y, Nakhkash M et al (2000) Automatic detection of buried utilities and solid objects with GPR using neural networks and pattern recognition. J Appl Geophys 43(2):157–165

    Article  Google Scholar 

  • Benson AK (1995) Applications of ground penetrating radar in assessing some geological hazards: examples of groundwater contamination, faults, cavities. J Appl Geophys 33(1–3):177–193

    Article  Google Scholar 

  • Bruschini C, Gros B, Guerne F et al (1998) Ground penetrating radar and imaging metal detector for antipersonnel mine detection. J Appl Geophys 40(1–3):59–71

    Article  Google Scholar 

  • Cardarelli E, Marrone C, Orlando L (2003) Evaluation of tunnel stability using integrated geophysical methods. J Appl Geophys 52(2–3):93–102

    Article  Google Scholar 

  • Cardoso BB, Dagnese LL, Martins MAI et al (2021) The use of GPR technologies for utility mapping in underground distribution grid conversion - Brazil use case. 2021 international conference on electrical, communication and computer engineering (ICECCE), 1–4

  • Dou Q, Wei L, Magee DR et al (2016) Real-time hyperbola recognition and fitting in GPR data. IEEE Trans Geosci Remote Sens 1:1–12

    Google Scholar 

  • Felletti F, Beretta GP (2009) Expectation of boulder frequency when tunneling in glacial till: a statistical approach based on transition probability. Eng Geol 108(1–2):43–53

    Article  Google Scholar 

  • Gao W, Karbasi M, Hasanipanah M et al (2017) Developing GPR model for forecasting the rock fragmentation in surface mines. Eng Comput 34:339–345

    Article  Google Scholar 

  • Lalagüe A, Lebens MA, Hoff I et al (2016) Detection of rockfall on a tunnel concrete lining with ground-penetrating radar (GPR). Rock Mech Rock Eng 49(7):2811–2823

    Article  Google Scholar 

  • Li B, Wu L, Xu CM, Zuo QJ et al (2016) The detection of the boulders in metro tunneling in granite strata using a shield tunneling method and a new method of coping with boulders. Geotech Geol Eng 34(4):1155–1169

    Article  Google Scholar 

  • Li S, Liu B, Xu X et al (2017) An overview of ahead geological prospecting in tunneling. Tunn Undergr Space Technol 63(3):69–94

    Article  Google Scholar 

  • Lin C, Wang X, Li Y et al (2019) Forward modelling and GPR imaging in leakage detection and grouting evaluation in tunnel lining. KSCE J Civ Eng 24(1):278–294

    Article  MathSciNet  Google Scholar 

  • Liu L, Yi SU, Mao J (2008) FDTD analysis of ground-penetrating radar antennas with shields and absorbers. Front Electr Electron Eng China 3(1):90–95

    Article  Google Scholar 

  • Luo T, Lai W (2020a) GPR pattern recognition of shallow subsurface air voids. Tunnel Undergr Space Technol 99:103355

    Article  Google Scholar 

  • Lyu YZ, Wang HH and Gong JB (2020) GPR detection of tunnel lining cavities and reverse-time migration imaging. Appl Geophys (6)

  • Maas C, Schmalzl J (2013) Using pattern recognition to automatically localize reflection hyperbolas in data from ground penetrating radar. Comput Geosci 58:116–125

    Article  Google Scholar 

  • Słowik M (2011) Reconstructing migration phases of meandering channels by means of ground-penetrating radar (GPR): the case of the Obra River, Poland. J Soils Sediment 11:1262–1278

    Article  Google Scholar 

  • Swinnen G, Thorbecke JW, Drijkoningen GG (2007) Seismic imaging from a TBM. Rock Mech Rock Eng 40(6):577–590

    Article  Google Scholar 

  • Warren C, Giannopoulos A, Giannakis I (2016) gprMax: Open source software to simulate electromagnetic wave propagation for ground penetrating radar. Comput Phys Commun 209:163–170

    Article  Google Scholar 

  • Xie P, Wen H, Xiao P et al (2018) Evaluation of ground-penetrating radar (GPR) and geology survey for slope stability study in mantled karst region. Environ Earth Sci 77(4):1221–12212

    Google Scholar 

  • Yuan D, Fan D (2018) Salient map of hyperbolas in GPR images. Eurasip J Image Video Process 65:1–8

    Google Scholar 

  • Zhang F, Xie X, Huang H (2010) Application of ground penetrating radar in grouting evaluation for shield tunnel construction. Tunn Undergr Space Technol 25(2):99–107

    Article  Google Scholar 

Download references

Funding

This project was supported by the National Natural Science Foundation of China (No. 52078286) and Project Technology Development of China Railway 20 Bureau Group Corporation (CR2005-Foguan-KJYF-SJ2016-001).

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Authors and Affiliations

  1. School of Mechanics and Engineering Science, Shanghai University, 99 Shangda Road, Shanghai, 200444, China

    Zhiheng Dai, Mengxi Zhang & Jie Gu

Authors
  1. Zhiheng Dai
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  2. Mengxi Zhang
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  3. Jie Gu
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Contributions

ZHD completed the theoretical analysis and drafted this manuscript. MXZ provided funding, ideas and guidance for this manuscript. JG carefully checked and revised the manuscript.

Corresponding author

Correspondence to Mengxi Zhang.

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The authors declare that there is no conflict of interest regarding the publication of this article.

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Written informed consent for publication was obtained from all participants.

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Dai, Z., Zhang, M. & Gu, J. GPR Forward Modelling and Imaging Analysis for Boulder Detection. Iran J Sci Technol Trans Civ Eng 46, 3193–3202 (2022). https://doi.org/10.1007/s40996-021-00804-7

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  • DOI: https://doi.org/10.1007/s40996-021-00804-7

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