Seismic resilience analysis of high-speed railway tunnels across fault zones using ensemble learning approach

Abstract

Severe damage to the Daliang high-speed railway tunnel during earthquakes primarily results from the dynamic interplay between fault dislocation and intense seismic forces near fault lines, accompanied by their complex feedback mechanisms. This study introduces a novel hybrid finite element model to explore the impact of fault dislocation-induced earthquakes on tunnel lining integrity. The influence of seismic characteristics on factors such as peak ground acceleration, tunnel structure form, and the shear modulus of surrounding rock is analyzed. Extensive numerical simulations investigate the coupling effects of faults and various seismic motions on tunnel structures. Additionally, a rapid resilience assessment model for tunnels crossing strike-slip faults is developed using the Adaboost algorithm. This model evaluates the seismic fragility and resilience of such tunnels, offering insights into the anti-seismic behaviors of three distinct tunnel lining configurations under the combined stresses of fault dislocation and significant seismic activity. Furthermore, the fault damage characteristics of the crossing-fault high-speed railway tunnel are assessed, based on real earthquake damage classification and current seismic codes. Findings demonstrate that the evaluation model is both highly accurate and efficient, serving as an effective alternative to traditional nonlinear time-history analysis of tunnel structures. Research shows that critical factors influencing seismic fragility and resilience include the structural design of the tunnel, shear modulus of the surrounding rock, peak ground acceleration, and tunnel height. Simulations reveal that tensile and compressive damage are significantly reduced in circular tunnels with a shock-absorbing joint compared to original tunnel prototypes. Overall, damage assessments from actual faults in crossing-fault high-speed railway tunnels correlate well with numerical predictions, providing essential references for structural recovery and safety evaluations post-earthquake.

Keywords

Tunnel engineering / Lining structure / Strike-slip seismic fault / Ensemble learning / Seismic resilience

Data availability

The code developed in this study and sample data can be accessed from the GitHub repository: https://github.com/wangzhao0217/AdaBoost.RT_for_resilience-evaluation_of_high-speed_railway_tunnels. The data are provided under the Open Data Commons Attribution License.

CRediT authorship contribution statement

Lianjie Yang: Supervision, Project administration, Methodology, Investigation, Funding acquisition. Chunlei Xin: Writing - original draft. Zhao Wang: Writing - original draft, Methodology, Formal analysis, Data curation. Xinyuan Yu: Visualization, Methodology, Formal analysis. Iman Hajirasouliha: Writing - review & editing, Methodology. Wenkai Feng: Funding acquisition.

Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgement

This research was supported by the National Natural Science Foundation of China (Grant No. 52108361), the Sichuan Science and Technology Program of China (Grant Nos. 25CXCY0063 and 2024ZYD0154), and the State Key Laboratory of Geohazard Prevention and Geoenvironment Protection Independent Research Project (Grant No. SKLGP2022Z015).

References

[1] Adoko, A. C., Jiao, Y. Y., Wu, L., Wang, H., & Wang, Z. H. (2013). Predicting tunnel convergence using multivariate adaptive regression spline and artificial neural network. Tunnelling and Underground Space Technology, 38, 368-376.

[2] Alliance, A. L. (2001). Seismic fragility formulations for water systems: Part 1-guideline. American Society of Civil Engineers-FEMA.

[3] Argyroudis, S. A., & Pitilakis, K. D. (2012). Seismic fragility curves of shallow tunnels in alluvial deposits. Soil Dynamics and Earthquake Engineering, 35, 1-12.

[4] Argyroudis, S. A., Mitoulis, S. A., Hofer, L., Zanini, M. A., Tubaldi, E., & Frangopol, D. M. (2020). Resilience assessment framework for critical infrastructure in a multi-hazard environment: Case study on transport assets. Science of the Total Environment, 714.

[5] Aydan, Ö., Malistani, N., Ulusay, R., & Kumsar, H. (2024). The damage and response of some underground structures by the 2023 February 6 great Turkish earthquakes and some considerations. Engineering Geology, 336, 107549.

[6] Ayvaz, S., & Alpay, K. (2021). Predictive maintenance system for production lines in manufacturing: A machine learning approach using IoT data in real-time. Expert Systems with Applications, 173, 114598.

[7] Bai, X. D., Cheng, W. C., Wu, B., Li, G., & Ong, D. E. L. (2023). Shield machine position prediction and anomaly detection during tunnelling in loess region using ensemble and deep learning algorithms. Acta Geotechnica, 18(11), 6175-6199.

[8] Bao, F., Zeng, X. F., Lin, R. B., Chi, B. X., Lu, H., & Sha, C. N. (2022). Detecting aftershocks of the M_S6.9 Menyuan earthquake and mapping blind faults by a distributed acoustic sensing array with an existing fiber-optic cable. Chinese Science Bulletin, 67(27), 3340-3347.

[9] Bigdeli, A., Shishegaran, A., Naghsh, M. A., Karami, B., Shishegaran, A., & Alizadeh, G. (2021). Surrogate models for the prediction of damage in reinforced concrete tunnels under internal water pressure. Journal of Zhejiang University: Science A, 22(8), 632-656.

[10] Cao, Y., Zhou, X. K., Yan, K., & Li, D. Y. (2021). Deep learning neural network model for tunnel ground surface settlement prediction based on sensor data. Mathematical Problems in Engineering, 2021(1), 9488892.

[11] Chai, W. G., Zheng, Y. X., Tian, L., Qin, J., & Zhou, T. (2023). GA-KELM: Genetic-algorithm-improved kernel extreme learning machine for traffic flow forecasting. Mathematics, 11(16).

[12] Chen, G., & Yu, H. T. (2024). Analytical solution for seismic response of composite tunnel liners with arbitrary section shape and embedded with an isolation layer. Tunnelling and Underground Space Technology, 150, 105821.

[13] Chen, J. T., Yu, H. T., Bobet, A., & Yuan, Y. (2020). Shaking table tests of transition tunnel connecting TBM and drill-and-blast tunnels. Tunnelling and Underground Space Technology, 96, 103197.

[14] Chen, P. L., Geng, P., He, D. W., Wang, T. Q., & He, C. (2024). A novel tool for seismic response analysis of tunnel in multilayered media based on kinematic earthquake source. Engineering Geology, 340, 107675.

[15] Chen, P. L., Geng, P., Chen, J. B., & Gu, W. Q. (2023a). The seismic damage mechanism of Daliang tunnel by fault dislocation during the 2022 Menyuan Ms6.9 earthquake based on unidirectional velocity pulse input. Engineering Failure Analysis, 145, 107047.

[16] Chen, X., Xiong, Z. M., Zhuge, Y., & Liu, Y. (2023b). Numerical analysis on the seismic performance of subway station in ground crack area. Tunnelling and Underground Space Technology, 134, 10501.

[17] Chen, X. S., Shen, J., Bao, X. H., Wu, X. L., Tang, W. C., & Cui, H. Z. (2023c). A review of seismic resilience of shield tunnels. Tunnelling and Underground Space Technology, 136, 105075.

[18] Chen, Z. W., & Wang, G. (2023). Comparison of empirically-based and physically-based analyses of coseismic landslides: A case study of the 2016 Kumamoto earthquake. Soil Dynamics and Earthquake Engineering, 172, 108009.

[19] China Merchants Chongqing Transportation Research andDesign Institute Co., Ltd. ( 2019). JTG 2232 — 2019: Specification for Seismic Design of Highway Tunnel (in Chinese).

[20] Cornell, C. A., Jalayer, F., Hamburger, R. O., & Foutch, D. A. (2002). Probabilistic basis for 2000 SAC federal emergency management agency steel moment frame guidelines. Journal of Structural Engineering, 128(4), 526-533.

[21] Cui, Z., Sheng, Q., Zhang, G. M., Zhang, M. C., & Mei, X. C. (2022a). Response and mechanism of a tunnel subjected to combined fault rupture deformation and subsequent seismic excitation. Transportation Geotechnics, 34, 100749.

[22] Cui, Z., Li, J. H., Fu, X. W., Sheng, Q., Zhou, G. X., Ma, Y. L. N., & Wang, T. Q. (2022b). Evaluating the response of a tunnel subjected to strike-slip fault rupture in conjunction with model test and hybrid discrete-continuous numerical modeling. Rock Mechanics and Rock Engineering, 55, 4743-4764.

[23] Dai, L., Zhu, Z. D., Zhang, C., & Zhu, D. (2023). Experimental study on the influence of glass fiber reinforced concrete isolation layer on the seismic dynamic response of tunnels. Case Studies in Construction Materials, 19, e02303.

[24] Deco`, A., Bocchini, P., & Frangopol, D. M. (2013). A probabilistic approach for the prediction of seismic resilience of bridges. Earthquake Engineering and Structural Dynamics, 42(10), 1469-1487.

[25] Du, L., Zhang, R., & Fu, Y. G. (2024). A robust evaluating strategy of tunnel deterioration using ensemble machine learning algorithms. Engineering Applications of Artificial Intelligence, 133.

[26] Du, X. L., & Zhao, M. (2010). A local time-domain transmitting boundary for simulating cylindrical elastic wave propagation in infinite media. Soil Dynamics and Earthquake Engineering, 30(10), 937-946.

[27] Fabozzi, S., Bilotta, E., Picozzi, M., & Zollo, A. (2018). Feasibility study of a loss-driven earthquake early warning and rapid response systems for tunnels of the italian high-speed railway network. Soil Dynamics and Earthquake Engineering, 112, 232-242.

[28] Federal Emergency Management Agency (FEMA). (2020). Hazus 4.2 SP3: Hazus earthquake model technical manual.

[29] Firouzi, N., Zur, K. K., Amabili, M., & Rabczuk, T. (2023). On the time-dependent mechanics of membranes via the nonlinear finite element method. Computer Methods in Applied Mechanics and Engineering, 407, 115903.

[30] Gu, B., Sheng, V. S., Wang, Z. J., Ho, D., Osman, S., & Li, S. (2015). Incremental learning for m-support vector regression. Neural Networks, 67, 140-150.

[31] Han, K. H., Zhang, D. M., Chen, X. S., Su, D., Ju, J. W. W., Lin, X. T., & Cui, H. Z. (2023). A resilience assessment framework for existing underground structures under adjacent construction disturbance. Tunnelling and Underground Space Technology, 141.

[32] Harati, M., & van de Lindt, J. W. (2024). Data-driven machine learning for multi-hazard fragility surfaces in seismic resilience analysis. Computer-Aided Civil and Infrastructure Engineering, 40(6), 698-720.

[33] Hasanpour, R., Rostami, J., Schmitt, J., Ozcelik, Y., & Sohrabian, B. (2020). Prediction of TBM jamming risk in squeezing grounds using Bayesian and artificial neural networks. Journal of Rock Mechanics and Geotechnical Engineering, 12(1), 21-31.

[34] Hong, H. Y., Liu, J. Z., Bui, D. T., Pradhan, B., Acharya, T. D., Pham, B. T., Zhu, A. X., Chen, W., & Ahmad, B. B. (2018). Landslide susceptibility mapping using J48 decision tree with AdaBoost, Bagging and Rotation Forest ensembles in the Guangchang area (China). Catena, 163, 399-413.

[35] Huang, D. W., Zhu, H. H., Shen, Y., Yan, Z. G., & Ju, J. W. W. (2022). Resilient analysis on tunnel structural serviceability based on lifetime dynamic prediction model. Tunnelling and Underground Space Technology, 129, 104690.

[36] Huang, H. W., & Zhang, D. M. (2016). Resilience analysis of shield tunnel lining under extreme surcharge: Characterization and field application. Tunnelling and Underground Space Technology, 51, 301-312.

[37] Huang, H. W., Zhang, Y. J., Zhang, D. M., & Ayyub, B. M. (2017a). Field data-based probabilistic assessment on degradation of deformational performance for shield tunnel in soft clay. Tunnelling and Underground Space Technology, 67, 107-119.

[38] Huang, J. Q., Du, X. L., Zhao, M., & Zhao, X. (2017b). Impact of incident angles of earthquake shear (S) waves on 3-D non-linear seismic responses of long lined tunnels. Engineering Geology, 222, 168-185.

[39] Huang, P. F., Chen, Z. Y., & Liu, Z. Q. (2023). Nonparametric probabilistic seismic demand model and fragility analysis of subway stations using deep learning techniques. Underground Space, 11, 63-80.

[40] Huang, S., Xin, C. L., Song, D. Q., Feng, W. K., Liu, X. L., Wang, E. Z., Xu, T. H., & Xiong, X. H. (2024). Resilience assessment of the seismic damage mechanism of the Daliang high-speed railway tunnel in the 2022 Menyuan earthquake (Mw 6.7) in China. Transportation Geotechnics, 49, 101417.

[41] Huang, Z. K., Pitilakis, K., Tsinidis, G., Argyroudis, S., & Zhang, D. M. (2020). Seismic vulnerability of circular tunnels in soft soil deposits: The case of Shanghai metropolitan system. Tunnelling Underground Space Technology, 98, 103341.

[42] Huang, Z. K., Pitilakis, K., Argyroudis, S., Tsinidis, G., & Zhang, D. M. (2021). Selection of optimal intensity measures for fragility assessment of circular tunnels in soft soil deposits. Soil Dynamics and Earthquake Engineering, 145, 106724.

[43] Huang, Z. K., Argyroudis, S. A., Pitilakis, K., Zhang, D. M., & Tsinidis, G. (2022a). Fragility assessment of tunnels in soft soils using artificial neural networks. Underground Space, 7(2), 242-253.

[44] Huang, Z. K. (2022b). Resilience evaluation of shallow circular tunnels subjected to earthquakes using fragility functions. Applied Sciences, 12(9), 4728.

[45] Huang, Z. K., Zhang, D. M., Pitilakis, K., Tsinidis, G., Huang, H. W., Zhang, D. M., & Argyroudis, S. (2022c). Resilience assessment of tunnels: Framework and application for tunnels in alluvial deposits exposed to seismic hazard. Soil Dynamics and Earthquake Engineering, 162, 107456.

[46] Jiang, J. W., El Naggar, M. H., Huang, W. T., Xu, C. S., Zhao, K., & Du, X. L. (2022). Seismic fragility analysis for shallow-buried underground frame structure considering 18 existing subway stations. Soil Dynamics and Earthquake Engineering, 162, 107479.

[47] Jiang, J. W., Tao, R., El Naggar, M. H., Liu, H., & Du, X. L. (2024). Seismic performance and fragility analysis for bifurcated tunnels in soft soil. Computers and Geotechnics, 167, 106065.

[48] Karami, B., Shishegaran, A., Taghavizade, H., & Rabczuk, T. (2021). Presenting innovative ensemble model for prediction of the load carrying capacity of composite castellated steel beam under fire. Structures, 33, 4031-4052.

[49] Kuhlemeyer, R. L., & Lysmer, J. (1973). Finite element method accuracy for wave propagation problems. Journal of the Soil Mechanics and Foundations Division, 99(5), 421-427.

[50] Lin, X. T., Chen, X., Su, D., Han, K., & Zhu, M. (2022). An analytical model to evaluate the resilience of shield tunnel linings considering multistage disturbances and recoveries. Tunnelling and Underground Space Technology, 127, 104581.

[51] Liu, J. H., Hu, J., Li, Z. W., Ma, Z. F., Shi, J. W., Xu, W. B., & Sun, Q. (2022). Three-dimensional surface displacements of the 8 January 2022 Mw6.7 Menyuan earthquake, China from Sentinel-1 and ALOS-2 SAR observations. Remote Sensing, 14(6), 1404.

[52] Long, X. H., Ma, Y. T., Miao, Y., & Ruan, B. (2023). An innovative shape memory alloy flexible circumferential joint for tunnel seismic mitigation. Tunnelling and Underground Space Technology, 131, 104783.

[53] Lyu, S., Qi, Q., Huang, X. M., Peng, S. N., Yang, D., & Chen, L. Y. (2024). Machine learning-based method for gas leakage source term estimation in highway tunnels. Tunnelling and Underground Space Technology, 154, 106114.

[54] Meng, S. B., Li, W. X., Liu, Z. X., Liu, J. Q., He, W. G., Yang, C. W., Zhao, J. W., & Wei, S. T. (2024). Rapid resilience assessment framework for mountain tunnels subjected to near-fault seismic ground motions. Soil Dynamics and Earthquake Engineering, 182, 108746.

[55] Moayedifar, A., Nejati, H. R., Goshtasbi, K., & Khosrotash, M. (2019). Seismic fragility and risk assessment of an unsupported tunnel using incremental dynamic analysis (IDA). Earthquakes and Structures., 16(6), 705-714.

[56] Naghsh, M. A., Shishegaran, A., Karami, B., Rabczuk, T., Shishegaran, A., Taghavizadeh, H., & Moradi, M. (2021). An innovative model for predicting the displacement and rotation of column-tree moment connection under fire. Frontiers of Structural and Civil Engineering, 15, 194-212.

[57] Qu, L. M., Ding, X. M., Zheng, C. J., Wu, C. R., & Cao, G. W. (2021). Numerical and test study on vertical vibration characteristics of pile group in slope soil topography. Earthquake Engineering and Engineering Vibration, 20(2), 377-390.

[58] Rabczuk, T., & Belytschko, T. (2004). Cracking particles: A simplified meshfree method for arbitrary evolving cracks. International Journal for Numerical Methods in Engineering, 61(13), 2316-2343.

[59] Rabczuk, T., Zi, G., Bordas, S., & Nguyen-Xuan, H. (2010). A simple and robust three-dimensional cracking-particle method without enrichment. Computer Methods in Applied Mechanics and Engineering, 199(37/38/39/40), 2437-2455.

[60] Reddy, A. D., & Singh, A. (2024). A simplistic method for assessing seismic damage in rock tunnels before earthquake: Part 1—damage prediction and validation using seismic damage classification of tunnels. Rock Mechanics and Rock Engineering, 57(12), 11001-11032.

[61] Samaniego, E., Anitescu, C., Goswami, S., Nguyen-Thanh, V. M., Guo, H., Hamdia, K., Zhuang, X., & Rabczuk, T. (2020). An energy approach to the solution of partial differential equations in computational mechanics via machine learning: Concepts, implementation and applications. Computer Methods in Applied Mechanics and Engineering, 362, 112790.

[62] Shishegaran, A., Boushehri, A. N., & Ismail, A. F. (2020a). Gene expression programming for process parameter optimization during ultrafiltration of surfactant wastewater using hydrophilic polyether-sulfone membrane. Journal of Environmental Management, 264, 110444.

[63] Shishegaran, A., Khalili, M. R., Karami, B., Rabczuk, T., & Shishegaran, A. (2020b). Computational predictions for estimating the maximum deflection of reinforced concrete panels subjected to the blast load. International Journal of Impact Engineering, 139, 103527.

[64] Shishegaran, A., Saeedi, M., Kumar, A., & Ghiasinejad, H. (2020c). Prediction of air quality in Tehran by developing the nonlinear ensemble model. Journal of Cleaner Production, 259, 120825.

[65] Shishegaran, A., Moradi, M., Naghsh, M. A., Karami, B., & Shishegaran, A. (2021a). Prediction of the load-carrying capacity of reinforced concrete connections under post-earthquake fire. Journal of Zhejiang University: Science A, 22(6), 441-466.

[66] Shishegaran, A., Karami, B., Safari Danalou, E., Varaee, H., & Rabczuk, T. (2021b). Computational predictions for predicting the performance of steel 1 panel shear wall under explosive loads. Engineering Computations, 38(9), 3564-3589.

[67] Shishegaran, A., Varaee, H., Rabczuk, T., & Shishegaran, G. (2021c). High correlated variables creator machine: Prediction of the compressive strength of concrete. Computers & Structures, 247.

[68] Shishegaran, A., Saeedi, M., Mirvalad, S., & Korayem, A. H. (2023). Computational predictions for estimating the performance of flexural and compressive strength of epoxy resin-based artificial stones. Engineering with Computers, 39(1), 347-372.

[69] Sun, W. Y., Lin, J. C., Ma, Q. G., Yan, S. H., Tong, H., & Liang, Q. G. (2024). Seismic fragility assessment of circular metro tunnels in loess deposit. Journal of Central South University, 31(3), 950-964.

[70] Sun, Y., Feng, X. D., Yang, L. Q., & Chastre, C. (2018). Predicting tunnel squeezing using multiclass support vector machines. Advances in Civil Engineering, 2018(1).

[71] Tian, H. X., & Mao, Z. Z. (2010). An ensemble ELM based on modified AdaBoost.RT algorithm for predicting the temperature of molten steel in ladle furnace. IEEE Transactions on Automation Science and Engineering, 7(1), 73-80.

[72] Tian, J. W., Liu, Y., Zheng, W. F., & Yin, L. R. (2022). Smog prediction based on the deep belief - BP neural network model (DBN-BP). Urban Climate, 41, 101078.

[73] Tsinidis, G., Karatzetzou, A., Stefanidou, S., & Markogiannaki, O. (2022). Developments in seismic vulnerability assessment of tunnels and underground structures. Geotechnics, 2(1), 209-249.

[74] Tsinidis, G., Stefanidou, S., & Karatzetzou, A. (2024a). New limit states for the seismic fragility assessment of circular tunnels: Application in case of tunnels in clayey soil deposits. Tunnelling and Underground Space Technology, 154, 106129.

[75] Tsinidis, G., Karatzetzou, A., & Stefanidou, S. (2024b). On the effects of salient parameters for an efficient assessment of seismic response and fragility of circular tunnels in clayey deposits. Soil Dynamics and Earthquake Engineering, 178, 108490.

[76] Wang, L. J., Geng, P., Chen, J. B., & Wang, T. Q. (2023a). Machine learning-based fragility analysis of tunnel structure under different impulsive seismic actions. Tunnelling and Underground Space Technology, 133, 104953.

[77] Wang, Q., Geng, P., Li, P. S., He, D. W., & Shen, H. M. (2024). Failure analysis of circumferential joints and preferable bolt form of shield tunnel under normal fault dislocation. Tunnelling and Underground Space Technology, 146, 105648.

[78] Wang, Y., Wang, Q., Zhong, X. M., & Deng, J. (2023b). Seismic response analysis of the Daliang tunnel during the Menyuan M_S6.9 earthquake. China Earthquake Engineering Journal, 45(6), 1315-1323, 1332 (in Chinese).

[79] Wen, Y. M., Xin, C. L., Shen, Y. S., Huang, Z. M., & Gao, B. (2021). The seismic response mechanisms of segmental lining structures applied in fault-crossing mountain tunnel: The numerical investigation and experimental validation. Soil Dynamics and Earthquake Engineering, 151, 107001.

[80] Wu, Y. L., Ke, Y. T., Chen, Z., Liang, S. Y., Zhao, H. L., & Hong, H. Y. (2020). Application of alternating decision tree with AdaBoost and bagging ensembles for landslide susceptibility mapping. Catena, 187.

[81] Xin, C. L., Wang, Z. Z., Zhou, J. M., & Gao, B. (2019). Shaking table tests on seismic behavior of polypropylene fiber reinforced concrete tunnel lining. Tunnelling and Underground Space Technology, 88, 1-15.

[82] Xin, C. L., Wang, Z. Z., & Gao, B. (2018). Shaking table tests on seismic response and damage mode of tunnel linings in diverse tunnel-void interaction states. Tunnelling and Underground Space Technology, 77, 295-304.

[83] Xin, C. L., Wang, Z. Z., & Yu, J. (2020). The evaluation on shock absorption performance of buffer layer around the cross section of tunnel lining. Soil Dynamics and Earthquake Engineering, 131, 106032.

[84] Xin, C. L., Wang, Z., Hajirasouliha, I., Yang, F., Li, W. H., Chen, T., & Gao, B. (2022). Seismic response mechanisms of casing-shape composite tunnel lining: Theoretical analysis and shaking table test verification. Soil Dynamics and Earthquake Engineering, 162, 107440.

[85] Xin, C. L., Shuai, Y. X., Song, D. Q., & Liu, X. L. (2024a). Dynamic interaction and failure mechanism in tunnel-slope systems: Mitigation insights from shaking table tests and numerical analysis. Tunnelling and Underground Space Technology, 152, 105940.

[86] Xin, C. L., Feng, W. K., Song, D. Q., Huang, S., & Liu, X. L. (2024b). Seismic damage to non-fault-crossing and fault-crossing tunnels: Comparative study of the 2008 Wenchuan earthquake (Mw 7.9) and the 2022 Menyuan earthquake (Mw 6.7). Engineering Failure Analysis, 166, 108843.

[87] Xing, H. J., Liu, W. T., & Wang, X. Z. (2024). Bounded exponential loss function based AdaBoost ensemble of OCSV Ms. Pattern Recognition, 148, 110191.

[88] Yu, H. T., Chen, J. T., Bobet, A., & Yuan, Y. (2016). Damage observation and assessment of the Longxi tunnel during the Wenchuan earthquake. Tunnelling and Underground Space Technology, 54, 102-116.

[89] Zhang, C. L., Zhang, B., Zhang, D. M., Huang, Z. K., & Huang, H. W. (2025). Machine learning-based resilience assessment of tunnel under explosions: Integrating post-explosion loss and recovery models. Computers and Geotechnics, 179, 107008.

[90] Zhang, Y. F., Yuan, K., Zhou, W. J., & Fan, J. W. (2023a). Study on structural deformation characteristics and surface crack distribution of Daliang tunnel across Lenglongling fault caused by Menyuan earthquake. Chinese Journal of Rock Mechanics and Engineering, 42(5), 1055-1069 (in Chinese).

[91] Zhang, Y. F., Chen, J., Gong, W. Y., Han, N. N., Liu, Y. H., & Shan, X. J. (2023b). Geodetic modelling of the 2022 Mw6.6 Menyuan earthquake: Insight into the strain-partitioned northern Qilian Shan fault system and implications for regional tectonics and seismic hazards. Geophysical Journal International, 233(3), 1987-2003.

[92] Zhong, Z. L., Wang, Z., Zhao, M., & Du, X. L. (2020). Structural damage assessment of mountain tunnels in fault fracture zone subjected to multiple strike-slip fault movement. Tunnelling and Underground Space Technology, 104, 103527.

[93] Zhou, H., He, C. D., Wang, X., Chen, Y. J., & Li, J. (2021). Assessment of the Seismic Response of Shallow buried Elliptical Tunnels. Journal of Earthquake Engineering, 27(3), 465-487.

[94] Zhu, H. H., Yu, H. T., Han, F. Q., Wei, Y. B., & Yuan, Y. (2023). Seismic Resilience Design Principles and Key Issues for Tunnels Crossing active Faults. China Journal of Highway and Transport, 36(11), 193-204 (in Chinese).