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Reliability analysis for running safety of vehicle on slab track via an improved second-order fourth-moment approach

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  • Lou, Ping
  • Shi, Tao
  • Yang, T.Y.

Abstract

The reliability assessment for running safety of vehicle on slab track under temperature action and seismic excitation is challenging due to the extensive computational efforts. This study proposes an improved second-order fourth-moment (ISOFM) approach for the reliability analysis for running safety of vehicle on slab track under temperature action and seismic excitation. The dimensionless limit state function (LSF) for running safety of vehicle on slab track is formulated considering four failure modes. The proposed ISOFM approach is verified by the Monte Carlo simulation (MCS) method. The proposed ISOFM approach greatly reduces the number of computations of nonlinear LSF. The merit of the proposed ISOFM approach lies in significantly enhancing the computation efficiency and precision of reliability considering nonlinear LSF with multi-failure modes. Additionally, the influences of temperature action and seismic excitation on the reliability for running safety of vehicle on slab track are discussed. The reliability for vehicle running safety decreases more significantly with the increment in overall temperature compared to the positive temperature gradient (PTG). The reliability for running safety of vehicle on slab track decreases nonlinearly with the increase of the earthquake intensity.

Suggested Citation

  • Lou, Ping & Shi, Tao & Yang, T.Y., 2025. "Reliability analysis for running safety of vehicle on slab track via an improved second-order fourth-moment approach," Reliability Engineering and System Safety, Elsevier, vol. 253(C).
    • Handle: RePEc:eee:reensy:v:253:y:2025:i:c:s0951832024006276
    DOI: 10.1016/j.ress.2024.110555
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    References listed on IDEAS

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    Cited by:

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    2. Li, Zheng & Mao, Jianfeng & Yu, Zhiwu, 2026. "Deep learning-driven efficient running safety assessment and reliability analysis for the stochastic train-track-bridge system," Reliability Engineering and System Safety, Elsevier, vol. 266(PB).
    3. Lu, Peng & Chen, Yong-Jing & Dong, Rui-Yi, 2026. "Moving regression artificial neural network framework for reliability evaluation of complex structure/system," Reliability Engineering and System Safety, Elsevier, vol. 267(PA).
    4. Keramatinejad, Mahdi & Karbasian, Mahdi & Alimohammadi, Hamidreza & Atashgar, Karim, 2025. "A hybrid approach of adaptive surrogate model and sampling method for reliability assessment in multidisciplinary design optimization," Reliability Engineering and System Safety, Elsevier, vol. 261(C).
    5. Cai, Xiaopei & Wang, Yuqi & Tang, Xueyang & Wang, Yi & Wang, Tao, 2026. "PEDRA-VTB: A precision-efficient framework for dynamic reliability assessment of vehicle-track-bridge system under extreme disasters," Reliability Engineering and System Safety, Elsevier, vol. 267(PB).

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