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A novel seismic topographic effect prediction method based on neural network models

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Abstract

Topography has a great effect on ground motions, and may aggravate seismic hazards. The quantification of topographic effects is vital for hazard prevention in practice. A series of studies were conducted to achieve this quantification. First, three bell-shaped hills’ numerical models with three input motions for each were established and calculated using finite element method. Second, topographic variables that were closely related to the amplification factors were analysed and selected. Third, back propagation (BP) neural network models using different input variables were tested to quantify the topographic effect. Core methods used in this study were validated using recorded seismic data. The results showed that altitude, slope, aspect, and frequency are important variables that can affect topographic amplification factors. Thin hills or high frequencies of incident waves generally cause great amplification factors at crests. High-frequency waves tend to be captured by small-scale topography and induce amplifications of ground motions at these positions. Altitudes can be positively correlated with amplification factors when wavelengths of incident waves are apparently longer than the dimensions of local topography. Slopes generally do not have a good correlation with amplification factors for low hills until the upper part and lower part of a hill are separated for analysis, owing to slopes at the tops and feet of low hills being very similar. The BP neural network method is adequate for the quantification of the topographic effect. There are at least two combinations of input variables of BP models that can achieve good performance. One combination includes altitude, slope, aspect, and frequency, while the other includes altitude, x-axis gradient, y-axis gradient, and frequency. The former combination is less precise but has better expandability of the predictive region, while the latter combination is more precise but lacks expandability of the predictive region.

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Data Availability Statement

This manuscript has associated data in a data repository. [Authors’ comment: The datasets generated during and/or analysed during the current study are available from the corresponding author on reasonable request].

References

  1. S.A. Ashford, N. Sitar, J. Lysmer, N. Deng, Topographic effects on the seismic response of steep slopes. Bull. Seismol. Soc. Am.Seismol. Soc. Am. 87(3), 701–709 (1997). https://doi.org/10.1785/BSSA0870030701

    Article  ADS  Google Scholar 

  2. G.A. Athanasopoulos, P.C. Pelekis, E.A. Leonidou, Effects of surface topography on seismic ground response in the Egion (Greece) 15 June 1995 earthquake. Soil Dyn. Earthq. Eng. 18(2), 135–149 (1999). https://doi.org/10.1016/S0267-7261(98)00041-4

    Article  Google Scholar 

  3. D.M. Boore, A note on the effect of simple topography on seismic SH waves. Bull. Seismol. Soc. Am. 62(1), 275–284 (1972)

    Article  Google Scholar 

  4. M. Bouchon, J.S. Barker, Seismic response of a hill: the example of Tarzana, California. Bull. Seismol. Soc. Am. 86(1A), 66–72 (1996). https://doi.org/10.1785/BSSA08601A0066

    Article  Google Scholar 

  5. M. Bouchon, C.A. Schultz, M.N. Toksöz, Effect of three-dimensional topography on seismic motion. J. Geophys. Res. Solid Earth 101(B3), 5835–5846 (1996). https://doi.org/10.1029/95JB02629

    Article  Google Scholar 

  6. G.D. Bouckovalas, A.G. Papadimitriou, Numerical evaluation of slope topography effects on seismic ground motion. Soil Dyn. Earthq. Eng. 25(7–10), 547–558 (2005). https://doi.org/10.1016/j.soildyn.2004.11.008

    Article  Google Scholar 

  7. F. Buech, T.R. Davies, J.R. Pettinga, The little red hill seismic experimental study: topographic effects on ground motion at a bedrock-dominated mountain edifice. Bull. Seismol. Soc. Am. 100(5A), 2219–2229 (2010). https://doi.org/10.1785/0120090345

    Article  Google Scholar 

  8. A.G. Chanda, R. Sahoo, A study on the stress and vibration characteristics of laminated composite plates resting on elastic foundations using analytical and finite element solutions. Eur. Phys. J. Plus 136(11), 1186 (2021). https://doi.org/10.1140/epjp/s13360-021-02090-8

    Article  Google Scholar 

  9. L.L. Davis, L.R. West, Observed effects of topography on ground motion. Bull. Seismol. Soc. Am. 63(1), 283–298 (1973). https://doi.org/10.1785/BSSA0630010283

    Article  Google Scholar 

  10. V. Di Fiore, Seismic site amplification induced by topographic irregularity: results of a numerical analysis on 2D synthetic models. Eng. Geol. 114(3–4), 109–115 (2010). https://doi.org/10.1016/j.enggeo.2010.05.006

    Article  Google Scholar 

  11. X.L. Du, M. Zhao, J.T. Wang, A stress artificial boundary in FEA for near-field wave problem. Chin. J. Theor. Appl. Mech. 38(1), 49–56 (2006). (in Chinese with English Abstract)

    Google Scholar 

  12. Z. Du, J. Liu, Q. Wu, An efficient and accurate strategy of numerical simulation of 2D Rayleigh waves under arbitrary undulating surface conditions. Eur. Phys. J. Plus 137(6), 657 (2022). https://doi.org/10.1140/epjp/s13360-022-02847-9

    Article  Google Scholar 

  13. L. Geli, P.-Y. Bard, B. Jullien, The effect of topography on earthquake ground motion: a review and new results. Bull. Seismol. Soc. Am. 78(1), 42–63 (1988). https://doi.org/10.1785/BSSA0780010042

    Article  Google Scholar 

  14. D.W. Griffiths, G.A. Bollinger, The effect of Appalachian mountain topography on seismic waves. Bull. Seismol. Soc. Am. 69(4), 1081–1105 (1979). https://doi.org/10.1785/BSSA0690041081

    Article  Google Scholar 

  15. S.H. Hartzell, D.L. Carver, K.W. King, Initial investigation of site and topographic effects at Robinwood Ridge, California. Bull. Seismol. Soc. Am. 84(5), 1336–1349 (1994). https://doi.org/10.1785/BSSA0840051336

    Article  Google Scholar 

  16. J. He, S. Qi, Y. Wang, C. Saroglou, Seismic response of the Lengzhuguan slope caused by topographic and geological effects. Eng. Geol. 265, 105431 (2019). https://doi.org/10.1016/j.enggeo.2019.105431

    Article  Google Scholar 

  17. F. Jafarzadeh, M.M. Shahrabi, H. Farahi Jahromi, On the role of topographic amplification in seismic slope instabilities. J. Rock Mech. Geotech. Eng. 7(2), 163–170 (2015). https://doi.org/10.1016/j.jrmge.2015.02.009

    Article  Google Scholar 

  18. H. Kumagai, T. Saito, G. O’Brien, T. Yamashina, Characterization of scattered seismic wavefields simulated in heterogeneous media with topography. J. Geophys. Res. 116(B3), B03308 (2011). https://doi.org/10.1029/2010JB007718

    Article  ADS  Google Scholar 

  19. S.-J. Lee, H.-W. Chen, Q. Liu, D. Komatitsch, B.-S. Huang, J. Tromp, Three-dimensional simulations of seismic-wave propagation in the Taipei basin with realistic topography based upon the spectral-element method. Bull. Seismol. Soc. Am. 98(1), 253–264 (2008). https://doi.org/10.1785/0120070033

    Article  Google Scholar 

  20. S.-J. Lee, D. Komatitsch, B.-S. Huang, J. Tromp, Effects of topography on seismic-wave propagation: an example from Northern Taiwan. Bull. Seismol. Soc. Am.Seismol. Soc. Am. 99(1), 314–325 (2009). https://doi.org/10.1785/0120080020

    Article  ADS  Google Scholar 

  21. H. Li, Y. Liu, L. Liu, B. Liu, X. Xia, Numerical evaluation of topographic effects on seismic response of single-faced rock slopes. Bull. Eng. Geol. Env. 78(3), 1873–1891 (2017). https://doi.org/10.1007/s10064-017-1200-7

    Article  Google Scholar 

  22. Y. Luo, X. Fan, R. Huang, Y. Wang, A.P. Yunus, H.B. Havenith, Topographic and near-surface stratigraphic amplification of the seismic response of a mountain slope revealed by field monitoring and numerical simulations. Eng. Geol. 271, 105607 (2020). https://doi.org/10.1016/j.enggeo.2020.105607

    Article  Google Scholar 

  23. Y.H. Luo, Y.S. Wang, Mountain slope ground motion topography amplification effect induced by Wenchuan earthquake. J. Mt. Sci. 31(2), 200–210 (2013). (in Chinese with English Abstract)

    Google Scholar 

  24. I.A. Mofor, L.C. Tasse, G.B. Tanekou, M.D. Wamba, R. Kengne, A. Tchagna Kouanou, M.T. Motchongom, D. Afungchui, F.B. Pelap, T.C. Kofane, Dynamics of modulated waves in the spring-block model of earthquake with time delay. Eur. Phys. J. Plus 138(3), 273 (2023). https://doi.org/10.1140/epjp/s13360-023-03863-z

    Article  Google Scholar 

  25. B. Moseley, A. Markham, T. Nissen-Meyer. Solving the wave equation with physics-informed deep learning. arXiv:2006.11894. http://arxiv.org/abs/2006.11894 (2020)

  26. B. Moseley, A. Markham, T. Nissen-Meyer, Finite basis physics-informed neural networks (FBPINNs): a scalable domain decomposition approach for solving differential equations. Adv. Comput. Math. 49(4), 62 (2023). https://doi.org/10.1007/s10444-023-10065-9

    Article  MathSciNet  MATH  Google Scholar 

  27. A.H. Namadchi, J. Alamatian, Explicit eigenanalysis in structural dynamics using viscous dynamic relaxation method. Eur. Phys. J. Plus 137(10), 1114 (2022). https://doi.org/10.1140/epjp/s13360-022-03333-y

    Article  Google Scholar 

  28. K.-V. Nguyen, B. Gatmiri, Evaluation of seismic ground motion induced by topographic irregularity. Soil Dyn. Earthq. Eng. 27(2), 183–188 (2007). https://doi.org/10.1016/j.soildyn.2006.06.005

    Article  Google Scholar 

  29. A. Pignalosa, G. Forte, P. Budetta, A. Santo, Topographic amplification and debris remobilization as a cause for increasing rockfall hazard in seismic areas: a case study in Central Italy. Geomorphology 403, 108160 (2022). https://doi.org/10.1016/j.geomorph.2022.108160

    Article  Google Scholar 

  30. B. Poursartip, A. Fathi, L.F. Kallivokas, Seismic wave amplification by topographic features: a parametric study. Soil Dyn. Earthq. Eng. 92, 503–527 (2017). https://doi.org/10.1016/j.soildyn.2016.10.031

    Article  Google Scholar 

  31. I. Primofiore, J. Baron, P. Klin, G. Laurenzano, C. Muraro, F. Capotorti, M. Amanti, G. Vessia, 3D numerical modelling for interpreting topographic effects in rocky hills for seismic microzonation: the case study of Arquata del Tronto hamlet. Eng. Geol.Geol. 279, 105868 (2020). https://doi.org/10.1016/j.enggeo.2020.105868

    Article  Google Scholar 

  32. M. Shafique, M. van der Meijde, N. Kerle, F. van der Meer, Impact of DEM source and resolution on topographic seismic amplification. Int. J. Appl. Earth Obs. Geoinf. 13(3), 420–427 (2011). https://doi.org/10.1016/j.jag.2010.09.005

    Article  ADS  Google Scholar 

  33. S.M. Sivalingam, P. Kumar, V. Govindaraj, A novel numerical scheme for fractional differential equations using extreme learning machine. Physica A 622, 128887 (2023). https://doi.org/10.1016/j.physa.2023.128887

    Article  MathSciNet  MATH  Google Scholar 

  34. S.M. Sivalingam, P. Kumar, V. Govindaraj, A novel optimization-based physics-informed neural network scheme for solving fractional differential equations. Eng. Comput. (2023). https://doi.org/10.1007/s00366-023-01830-x

    Article  MATH  Google Scholar 

  35. H. Tang, X.J. Li, Y.Q. Li, Site effect of topography on ground motions of Xishan Park of Zigong City. J. Vib. Shock 31(8), 74–79 (2012). (in Chinese with English Abstract)

    Google Scholar 

  36. H.Y. Wang, L.L. Xie, Effects of topography on ground motion in the Xishan park, Zigong city. Chin. J. Geophys. 53(7), 1631–1638 (2010). (in Chinese with English Abstract)

    Google Scholar 

  37. M. Wang, A. Zheng, W. Zhang, Effect of local mountain topography on strong ground motion. Chin. J. Geophys. 60(12), 4655–4670 (2017)

    Google Scholar 

  38. C.B. Wen, F. Ru, Y.Y. Liu et al., Artificial neural network theory and its applications (Xidian University Press, Xi’an, 2021), p.104

    Google Scholar 

  39. H. Zhou, J.T. Li, X.F. Chen, Establishment of a seismic topographic effect prediction model in the Lushan Ms 7.0 earthquake area. Geophys. J. Int. 221(1), 273–288 (2020)

    Article  ADS  Google Scholar 

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Acknowledgements

We thank Strong Motion Observation Center, Institute of Engineering Mechanics, China Earthquake Administration for providing the acceleration time histories of the mainshock of the Wenchuan earthquake, recorded by the Zigong topographic array. Part of the topographic data were provided by the Geospatial Data Cloud site, Computer Network Information Center, Chinese Academy of Sciences.

Funding

This research was partially supported by Spark Program of Earthquake Sciences (XH24024YC), Special project for cultivating scientific and technological innovation teams of Shandong Earthquake Agency (TD202303), National Key R&D Program of China (2022YFC3003503), Key Projects of Key Laboratory of Urban Security and Disaster Engineering of China Ministry of Education (2023), the Method and Demonstration of Earthquake-landslide Disaster Risk Zonation (Grant No. ZDJ2021-12).

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Authors and Affiliations

  1. Shandong Earthquake Disaster Prevention Center, Shandong Earthquake Agency, Jinan, 250014, China

    Qifeng Jiang & Hongtai Xu

  2. Shandong Institute of Earthquake Engineering, Jinan, 250021, China

    Qifeng Jiang & Hongtai Xu

  3. Publicity and Education Center, Shandong Earthquake Agency, Jinan, 250014, China

    Wei Wei

  4. Shandong Earthquake Station, Shandong Earthquake Agency, Jinan, 250014, China

    Tengchao Dong

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  1. Qifeng Jiang
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Correspondence to Hongtai Xu.

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Jiang, Q., Wei, W., Xu, H. et al. A novel seismic topographic effect prediction method based on neural network models. Eur. Phys. J. Plus 138, 1032 (2023). https://doi.org/10.1140/epjp/s13360-023-04662-2

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