Andreotti, G., Calvi, GM., Soga, K., Gong, C., & Ding, W. (2020). Cyclic model with damage assessment of longitudinal joints in segmental tunnel linings. Tunnelling Underground Space Technology, 103, 103472.
Azadi, M., & Mir Mohammad Hosseini, S.M. (2010). The uplifting behavior of shallow tunnels within the liquefiable soils under cyclic loadings. Tunnelling Underground Space Technology, 25, 158-67.
Azadi, M., & Bryson, LS. (2018). Effect of width variation of liquefiable sand lens on surface settlement due to shallow tunneling. In: International Congress of Exhibition Sustainable Civil Infrastructure: Innovative Infrastructure Geotechnology, 155-163.
Beheshti, K. (1998). The Investigation of the Behavior of Saturated Sand Lenses within the Soil Deposits under Dynamic Loading. Dissertation, Faculty of Amirkabir University of Technology.
Cetin, K.O., Cakir, E., Ilgac, M., Can, G., Soylemez, B., Elsaid, A., & et al. (2021). Geotechnical aspects of reconnaissance findings after 2020 January 24th, M6.8 Sivrice–Elazig–Turkey earthquake. Bulletin of Earthquake Engineering, 1-45.
Fattah, M.Y., Hamoo, M.J. & Dawood, S.H. (2015). Dynamic response of a lined tunnel with transmitting boundaries. Earthquakes and Structures, 8(1), 275-304.
Holchin, J., & Vallejo, L. (1995). The Liquefaction of Sand Lenses Due to Cyclic Loading.
Huang, G.B., Zhu, Q.Y., & Siew, C.K. (2004). Extreme learning machine: a new learning scheme of feedforward neural networks. In: IEEE International Joint Conference on Neural Networks (IEEE Cat. No. 04CH37541), 2, 985-990.
Jafarnia, M., & Varzaghani, M.I. (2016). Effect of near field earthquake on the monuments adjacent to underground tunnels using hybrid FEA-ANN technique. Earthquakes and Structures, 10(4), 757-768.
Kim, S., Tom, TH., Takeda, M., & Mase, H. (2021). A framework for transformation to nearshore wave from global wave data using machine-learning techniques: Validation at the Port of Hitachinaka, Japan. Ocean Engineering, 221, 108516.
Lin, SS., Shen, SL., Zhou, A., & Xu, YS. (2021). Risk assessment and management of excavation system based on fuzzy set theory and machine learning methods. Automation in Construction, 122, 103490.
Marcelino, P., de Lurdes Antunes, M., Fortunato, E., & Gomes, MC. (2021). Machine learning approach for pavement performance prediction. International Journal of Pavement Engineering, 22(3), 341-354.
Miranda, L., Caldeira, L., Serra, J., & Gomes, RC. (2020). Dynamic behaviour of Tagus River sand including liquefaction. Bulletin of Earthquake Engineering, 18(10), 4581-4604.
Mir Mohammad Hosseini, SM., & Azadi, M. (2012). Effect of the location of liquefiable sand lenses on shallow tunnels during earthquake loading. Arabian Journal of Science and Engineering, 37, 575-586.
Nguyen, H., Vu, T., Vo, TP., & Thai, HT. (2021). Efficient machine learning models for prediction of concrete strengths. Construction and Building Materials, 266, 120950.
Pashangpishe, Y. (2004). Mechanism of Soil Deformation due to Double Lenses Liquefaction and Critical Depth Determination. Dissertation, Amirkabir University of Technology.
Seyrfar, A., Ataei, H., Movahedi, A., & Derrible, S. (2021). Data-driven approach for evaluating the energy efficiency in multifamily residential buildings. Practice Periodical on Structural Design and Construction, 26(2), 04020074.
Shokri, M. (1996). Evaluation of the Liquefaction Potential of Sand Lenses. Dissertation, Amirkabir University of Technology.
Taylor, E.J., & Madabhushi, S.P.G. (2020). Remediation of liquefaction-induced floatation of non-circular tunnels. Tunnelling Underground Space Technology, 98,103301.
Tsinidis, G., de Silva, F., Anastasopoulos, I., Bilotta, E., Bobet, A., Hashash, Y.M.A., & et al. (2020). Seismic behaviour of tunnels: From experiments to analysis. Tunnelling Underground Space Technol, 99, 103334.
Vallejo, LE. (1998). Liquefaction of Sand Lenses During an Earthquake. Earthquake Engineering and Soil Dynamics II—Recent Advances in Ground-Motion Evaluation. Geotech. Spec. Publ., 493-507.
Zhao, K., Wang, Q., Wu, Q., Chen, S., Zhuang, H., & Chen, G. (2020). Stability of immersed tunnel in liquefiable seabed under wave loadings. Tunnelling Underground Space Technol, 102, 103449.
)