Open Access
Issue
E3S Web of Conf.
Volume 544, 2024
8th International Symposium on Deformation Characteristics of Geomaterials (IS-Porto 2023)
Article Number 01020
Number of page(s) 8
Section Experimental Investigations From Very Small Strains to Beyond Failure - Advances in Laboratory Testing Techniques (Equipment and Procedures)
DOI https://doi.org/10.1051/e3sconf/202454401020
Published online 02 July 2024
  1. Blewett, J., Blewett, I. J. and Woodward, P. K. 2000. “Phase and amplitude responses associated with the measurement of shear-wave velocity in sand by bender elements.” In Canadian Geotechnical Journal; Revue Canadienne De Géotechnique. 37 (6), 1348–1357. https://doi.org/10.1139/t00-047 [CrossRef] [Google Scholar]
  2. Dyvik, R. and Madshus, C. 1985. “Lab measurements of Gmax using bender elements.” In Proc., ASCE Convention on Advances in the Art of Testing Soils under Cyclic Conditions, 186–196. Available at: [https://cedb.asce.org/CEDBsearch/record.jsp?dockey=0046357] [Google Scholar]
  3. Fernandez Lavin, A. and Ovando Shelley, E. 2020 “Haar wavelet transform for arrival time identification in bender element tests.” In Geotechnical Testing Journal. 43 (4), 937–949. http://doi.org/10.1520/GTJ20180400 [CrossRef] [Google Scholar]
  4. Finas, M., Ali, H., Cascante, G. and Vanheeghe, P. 2016. “Automatic shear wave velocity estimation in bender element testing.” In Geotechnical Testing Journal. 39 (4), 557–567. http://doi.org/10.1520/GTJ20140197 [CrossRef] [Google Scholar]
  5. Greening, P. D. and Nash, D. F. T. 2004. “Frequency domain determination of G0 using bender elements.” In Geotechnical Testing Journal. 27 (3), 288–294. http://doi.org/10.1520/GTJ11192 [CrossRef] [Google Scholar]
  6. Gu, J., Wang, Z., Kuen, J., Ma, L., Shahroudy, A., Shuai, B., Liu, T., Wang, X., Wang, G., Cai, J. and Chen, T. 2018. “Recent Advances in Convolutional Neural Networks.” In Pattern Recognition. 77 354–377. http://doi.org/10.1016/j.patcog.2017.10.013 [Google Scholar]
  7. Gu, X., Yang, J., Huang, M. and Gao, G. 2015 “Bender element tests in dry and saturated sand: signal interpretation and result comparison.” In Soils and Foundations.55 (5), 951–962. https://doi.org/10.1016/j.sandf.2015.09.002 [Google Scholar]
  8. Hardin, B. O. 1978. “The nature of stress-strain behaviour for soils.” Proc. Geot. Div. Specialty Conf. on Earthquake Engineering and Soil Dynamics, Pasadena 1, 3–39. Available at: [https://trid.trb.org/view/74543] [Google Scholar]
  9. Hinton, G. E., Srivastava, N., Krizhevsky, A., Sutskever, I. and Salakhutdinov, R. R. 2012. “Improving neural networks by preventing co-adaptation of feature detectors”. https://doi.org/10.48550/arXiv.1207.0580 [Google Scholar]
  10. Kawaguchi, T., Ogino, T., Yamashita, S. and Kawajiri, S. 2016. “Identification method for travel time based on the time domain technique in bender element tests on sandy and clayey soils.” In Soils and Foundations. 56 (5), 937–946. http://doi.org/10.1016/j.sandf.2016.08.017 [CrossRef] [Google Scholar]
  11. Kingma, D. P. & Ba, J. 2014. “Adam: A method for stochastic optimization.” http://doi.org/arXiv:1412.6980 [Google Scholar]
  12. Kiranyaz, S., Avci, O., Abdeljaber, O., Ince, T., Gabbouj, M. and Inman, D. J. 2021. “1D Convolutional neural networks and applications: a survey.” In Mechanical Systems and Signal Processing. 151 107398. http://doi.org/10.1016/j.ymssp.2020.107398. [Google Scholar]
  13. Kiranyaz, S., Ince, T., Abdeljaber, O., Avci, O. and Gabbouj, M. 2019. “1-D Convolutional neural networks for signal processing applications.” ICASSP, IEEE. pp. 8360–8364. http://doi.org/10.1109/ICASSP.2019.8682194 [Google Scholar]
  14. Maas, A. L., Hannun, A. Y. and Ng, A. Y. 2013. “Rectifier nonlinearities improve neural network acoustic models.” Proc. Icml, Volume 30. Available at: [https://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.693.1422&rank=1&q=Rectifier%20nonlinearities%20improve%20neural%20network%20acoustic%20models&osm=&ossid=] [Google Scholar]
  15. Ogino, T., Kawaguchi, T., Yamashita, S. and Kawajiri, S. 2015. “Measurement deviations for shear wave velocity of bender element test using time domain, cross-correlation, and frequency domain approaches.” In Soils and Foundations. 55 (2), 329–342. https://doi.org/10.1016/j.sandf.2015.02.009 [CrossRef] [Google Scholar]
  16. Russakovsky, O., Deng, J., Su, H., Krause, J., Satheesh, S., Ma, S., Huang, Z., Karpathy, A., Khosla, A., Bernstein, M., Berg, A. C. and Fei-Fei, L. 2015. “ImageNet large scale visual recognition challenge.” In International Journal of Computer Vision. 115 (3), 211–252. https://doi.org/10.1007/s11263-015-0816-y [CrossRef] [MathSciNet] [Google Scholar]
  17. Sanchez-Salinero, I., Roesset, J. M., Stokoe, I. I. and Kenneth, H. 1986. “Analytical studies of body wave propagation and attenuation”, report GR 86–15. Civil Engineering Department, University of Texas at Austin. Available at: [https://apps.dtic.mil/sti/citations/ADA179487] [Google Scholar]
  18. Shirley, D. J. and Hampton, L. D. 1978. “Shear-Wave Measurements in Laboratory Sediments.” In The Journal of the Acoustical Society of America.63 (2), 607–613. https://doi.org/10.1121/1.381760 [Google Scholar]
  19. Simonyan, K. and Zisserman, A. 2014. “Very deep convolutional networks for large-scale image recognition.” https://doi.org/10.48550/arXiv.1409.1556 [Google Scholar]
  20. Styler, M. A. and Howie, J. A. 2013. “Combined time and frequency domain approach to the interpretation of benderelement tests on sand.” In Geotechnical Testing Journal. ASTM, 36 (5), 1–11. http://doi.org/10.1520/GTJ20120081. [Google Scholar]
  21. Tang, W., Long, G., Liu, L., Zhou, T., Jiang, J. and Blumenstein, M., 2020. “Rethinking 1d-cnn for time series classification: A stronger baseline.” https://doi.org/10.48550/arXiv.2002.10061 [Google Scholar]
  22. Viana da Fonseca, A., Ferreira, C. and Fahey, M. 2009. “A framework interpreting bender element tests, combining time-domain and frequency-domain methods.” In Geotechnical Testing Journal. 32 (2), 1–17. http://doi.org/10.1520/GTJ100974 [Google Scholar]
  23. Viggiani, G. and Atkinson, J. H. 1995. “Interpretation of bender element tests.” In Géotechnique. 45 (1), 149–154. http://doi.org/10.1680/geot.1995.45.1.149 [CrossRef] [Google Scholar]
  24. Wenzhang, X. 2022. “Use of machine learning in determining Gmax from bender element tests.” MSc dissertation. Department of Civil and Environmental Engineering, Imperial College London [Google Scholar]
  25. Yamashita, S., Kawaguchi, T., Nakata, Y., Mikami, T., Fujiwara, T. and Shibuya, S. 2009 “Interpretation of international parallel test on the measurement of Gmax using bender elements”. In Soils and Foundations. 49 (4), 631–650. http://doi.org/10.3208/sandf.49.631 [CrossRef] [Google Scholar]
  26. Yang, J. and Gu, X. Q. 2013. “Shear stiffness of granular material at small strains: Does It Depend on Grain Size?” In Géotechnique. 63 (2), 165–179. https://doi.org/10.1680/geot.11.P.083 [CrossRef] [Google Scholar]
  27. Zeiler, M. D., Ranzato, M., Monga, R., Mao, M., Yang, K., Le, Q. V., Nguyen, P., Senior, A., Vanhoucke, V. and Dean, J. 2013. “On rectified linear units for speech processing.” 2013 IEEE International Conference on Acoustics, Speech and Signal Processing. IEEE. pp. 3517–3521. http://doi.org/10.1109/ICASSP.2013.6638312 [Google Scholar]

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