Investigation on the accuracy of ground penetrating radar in the tunnel based on improved analectic hierarchy process

International Nano Letters volume 11, pages69–83(2021)Cite this article

Abstract

With the rapid development of tunnel engineering in China, geological conditions encountered in tunnel construction are becoming more and more complex. Construction safety has become the top priority of tunnel construction. To avoid geological hazards such as landslides, water inrush, and mud gushing caused by blind construction, ground penetrating radar (GPR) is widely used in the medium distance ahead of a tunnel face. The advanced prediction of GPR is often interfered by factors such as environment, operation, data processing, image interpretation, and other factors, which cause final results to have errors. Therefore, it is highly necessary to track and test prediction effects, and also, to choose scientific and effective evaluation methods for accuracy of the prediction result. Based on the geological radar forecast data of the Yujiashan tunnel, this paper sums up the interference factors of the ground radar forecast and discusses the advantages and disadvantages of different evaluation methods. On this basis, the analytic hierarchy process (AHP) which has many applications in earth sciences, physics, nanotechnology and etc., is improved by integrating the principle of maximum membership of fuzzy comprehensive evaluation. Then, a four-level evaluation model is established, which judges the accuracy of GPR geological prediction. Meanwhile, two geological predictions in the Yujiashan tunnel are selected to be applied in the model. Finally, the recognition level of the accuracy evaluation model is more accurate. The comparison between the actual excavation exposure and the radar image interpretation results shows that the geological radar advance prediction results are more accurate. This verifies the rationality and applicability of using the improved AHP to evaluate the accuracy of geological radar advance prediction.

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References

  1. 1.

    Li, S., Liu, B., Xu, X., Nie, L., Liu, Z., Song, J., Sun, H., Chen, L., Fan, K.: An overview of ahead geological prospecting in tunneling. Tunnel Undergr Space Technol. 63, 69–94 (2017). https://doi.org/10.1016/j.tust.2016.12.011

    Article  Google Scholar 

  2. 2.

    De Domenico, D., Teramo, A., Campo, D.: GPR surveys for the characterization of foundation plinths within a seismic vulnerability analysis. J. Geophys. Eng. (2013). https://doi.org/10.1088/1742-2132/10/3/034007

    Article  Google Scholar 

  3. 3.

    Pegah, E., Liu, H.B., Dastanboo, N.: Evaluation of the lateral earth pressure coefficients at-rest in granular soil deposits using the anisotropic components of S-wave velocity. Eng. Geol. 230, 55–63 (2017)

    Article  Google Scholar 

  4. 4.

    Pegah, E., Liu, H.B.: Evaluating the overconsolidation ratios and peak friction angles of granular soil deposits using noninvasive seismic surveying. Acta Geotech. 15(11), 3193–3209 (2020)

    Article  Google Scholar 

  5. 5.

    Yu, Q.M., Zhou, H.L., Wang, Y.H., Duan, R.X.: Quality monitoring of metro grouting behind segment using ground penetrating radar. Constr Build Mater. 110, 189–200 (2016)

    Article  Google Scholar 

  6. 6.

    Chen, Q., Huang, X., Li, J.: Application of Ground Penetrating Radar in detection of tunnel lining structure fracture and processing measures. Prog Ind Civil Eng. 204–208, 1318–1322 (2012)

    Google Scholar 

  7. 7.

    Saaty, T.L.: A scaling method for priorities in a hierarchichal structure. J. Math. Psychol. 15(3), 234–281 (1977)

    Article  Google Scholar 

  8. 8.

    Saaty, T.L.: An exposition of the AHP in reply to the paper `remarks on the analytic hierarchy process’. Manage. Sci. 36, 259–268 (1990)

    Article  Google Scholar 

  9. 9.

    Feizabadi, A., Salehi Doolabi, M., Sadrnezhaad, S.K., Zafarani, H.R., Salehi Doolabi, D., AsadiZarch, M.: MCDM selection of pulse parameters for best tribological performance of CreAl2O3 nano-composite co-deposited from trivalent chromium bath. J. Alloy. Compd. 727, 286–296 (2017)

    CAS  Article  Google Scholar 

  10. 10.

    Rezaei, A., Noori, L.: Modeling of relative intensity noise and terminal electrical noise of semiconductor lasers using artificial neural network. Int Nano Lett. 6, 147–152 (2016)

    CAS  Article  Google Scholar 

  11. 11.

    Rostamizadeh, K., Abdollahi, H., Parsajoo, C.: Synthesis, optimization, and characterization of molecularly imprinted nanoparticles. Int Nano Lett 3, 20–29 (2013)

    Article  Google Scholar 

  12. 12.

    Li, A.-T., Lin, J.-W.: Constructing core competency indicators for clinical teachers in Taiwan: a qualitative analysis and an analytic hierarchy process. BMC Med. Educ. (1990). https://doi.org/10.1186/1472-6920-14-75

    Article  Google Scholar 

  13. 13.

    Skibniewski, M., Chao, L.C.: Evaluation of advanced construction technology with AHP method. J Constr Eng Manag. 118(3), 577–593 (1992)

    Article  Google Scholar 

  14. 14.

    Lee, S., Chang, L.M.: Bid-markup determination for microtunneling projects. Tunn. Undergr. Space Technol. 19, 151–163 (2004)

    Article  Google Scholar 

  15. 15.

    Shapira, A., Goldenberg, M.: AHP-based equipment selection model for construction projects. J Constr Eng Manag ASCE 131, 1263–1273 (2005)

    Article  Google Scholar 

  16. 16.

    Cheng-Wei, S., Min-Yuan, C., Feng-Bor, L.: Simulation-enhanced approach for ranking major transport projects. J Civil Eng Manag. 12, 285–291 (2006)

    Article  Google Scholar 

  17. 17.

    Bertolini, M., Braglia, M., Carmignani, G.: Application of the AHP methodology in making a proposal for a public work contract. Int. J. Project Manage. 24, 422–430 (2006)

    Article  Google Scholar 

  18. 18.

    Shariati, S., Abedi, M., Saedi, A., Yazdani-Chamzini, A., Tamosaitienė, J., Saparauskas, J., Stupak, S.: Critical factors of the application of nanotechnology in construction industry by using ANP technique under fuzzy intuitionistic environment. J Civil Eng Manag. 23(7), 914–925 (2017)

    Article  Google Scholar 

  19. 19.

    Cooksey, S.R., Jeong, D.H.S., Chae, M.J.: Asset management assessment model for state departments of transportation. J Manag Eng. 27, 159–169 (2011)

    Article  Google Scholar 

  20. 20.

    Xu, K., Xu, J.: A direct consistency test and improvement method for the analytic hierarchy process. Fuzzy Optim. Decis. Making (2020). https://doi.org/10.1007/s10700-020-09323-y

    Article  Google Scholar 

  21. 21.

    Vasudeo, A.D., Katpatal, Y.B., Ingle, R.N.: Uses of dielectric constant reflection coefficients for determination of ground-penetrating radar. World Appl Sci J. 6(10), 1321–1325 (2009)

    Google Scholar 

  22. 22.

    Li, C., Li, M.-J., Zhao, Y.-G., Liu, H., Wan, Z., Xu, J.-C., Xu, X.-P., Chen, Y., Wang, B.: Layer recognition and thickness evaluation of tunnel lining based on ground penetrating radar measurements. J. Appl. Geophys. 73, 45–48 (2011)

    Article  Google Scholar 

  23. 23.

    Kanga, S., Sharma, L.K., Pandey, P.C., Nathawat, M.S., Sharma, S.K.: Forest fire modeling to evaluate potential hazards to tourism sites using geospatial approach. J. Geomat. 7, 93–99 (2013)

    Google Scholar 

  24. 24.

    Mahdavi, A., Shamsi, S.R.F., Nazari, R.: Forests and rangelands’ wildfire risk zoning using GIS and AHP techniques. Casp. J. Environ. Sci. 10, 43–52 (2012)

    Google Scholar 

  25. 25.

    Topuz, E., Gestel, C.A.M.: An approach for environmental risk assessment of engineered nanomaterials using Analytical Hierarchy Process (AHP) and fuzzy inference rules. Environ. Int. 92–93, 334–347 (2016)

    Article  Google Scholar 

  26. 26.

    Kamali, M., Persson, K.M., Costa, M.E., Capela, I.: Sustainability criteria for assessing nanotechnology applicability in industrial wastewater treatment: Current status and future outlook. Environ Int 125, 261–276 (2019)

    CAS  Article  Google Scholar 

  27. 27.

    Kayastha, P., Dhital, M.R., De Smedt, F.: Application of the analytical hierarchy process (AHP) for landslide susceptibility mapping: a case study from the Tinau watershed, west Nepal. Comput. Geosci. 52, 398–408 (2013)

    Article  Google Scholar 

  28. 28.

    Srivanit, M.: Community risk assessment: Spatial patterns and GIS-based model for fire risk assessment—a case study of Chiang Mai Municipality. J. Archit. Plan. Res. Stud. 8, 113–126 (2011)

    Google Scholar 

  29. 29.

    Malczewski, J., Moreno-Sanchez, R., Bojórquez-Tapia, L.A., Ongay-Delhumeau, E.: Multicriteria group decision making model for environmental conflict analysis in the Cape Region. Mexico. J. Environ. Plan. Manag. 40, 349–374 (1997)

    Article  Google Scholar 

  30. 30.

    Ramanathan, R.: A note on the use of the analytic hierarchy process for environmental impact assessment. J. Environ. Manage. 63, 27–35 (2001)

    CAS  Article  Google Scholar 

  31. 31.

    Rahimdel, M.J., Ataei, M.: Application of analytical hierarchy process to selection of primary crusher. Int J Min Sci Technol. 24(4), 519–523 (2014)

    Article  Google Scholar 

  32. 32.

    Saaty, T.L., Vargas, L.G.: Models, Methods, Concepts & Applications of the Analytic Hierarchy Process. Springer New York Heidelberg Dordrecht London, Second Edition. 175, 9 (2012)

  33. 33.

    Zheng, L., Li, X.Q., Liu, Z., Huang, D., Tang, Z.: Accuracy evaluation of advanced geological prediction based on improved AHP and GPR. Math Prob Eng (2020). https://doi.org/10.1155/2020/8617165

    Article  Google Scholar 

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Author information

Affiliations

  1. School of Civil and Hydraulic Engineering, Huazhong University of Science and Technology, Wuhan, 430074, China

    Nima Dastanboo

  2. Faculty of School of Civil and Hydraulic Engineering, Huazhong University of Science and Technology, Wuhan, 430074, China

    Xiao-Qing Li

  3. Institute of Geosciences, Friendrich Schiller University Jena, Jena, Germany

    Hamed Gharibdoost

Authors
  1. Nima Dastanboo
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  2. Xiao-Qing Li
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  3. Hamed Gharibdoost
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Correspondence to Nima Dastanboo or Xiao-Qing Li.

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Dastanboo, N., Li, XQ. & Gharibdoost, H. Investigation on the accuracy of ground penetrating radar in the tunnel based on improved analectic hierarchy process. Int Nano Lett 11, 69–83 (2021). https://doi.org/10.1007/s40089-020-00324-8

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Keywords

  • Ground penetrating radar
  • Tunnel geological prediction
  • Fuzzy decision
  • Analectic hierarchy process
  • Yujiashan tunnel