References
- Sarkar PP, De PS, Dhua SK, et al. Strain energy based low cycle fatigue damage analysis in a plain C-Mn rail steel. Mater Sci Eng A. 2017;707:125–135.
- Liu Y, Jiang XJ, Li QT, et al. Failure analysis and fatigue life prediction of high-speed rail clips based on DIC technique. Adv Mech Eng. 2021;13(12):1–13.
- Liu Z, Shi X, Tsang KS, et al. Dynamic finite element modeling and fatigue damage analysis of thermite welds. Fatigue Fract Eng Mater Struct. 2020;43(1):119–136.
- Liu Y, Tsang KS, Subramaniam NA, et al. Structural fatigue investigation of thermite welded rail joints considering weld-induced residual stress and stress relaxation by cyclic load. Eng Struct. 2021;235(6):1–16.
- Liu Y, Tsang KS, Hoh HJ, et al. Seismic fragility analysis of deteriorating recycled aggregate concrete bridge columns subjected to freeze-thaw cycles. Eng Struct. 2019;187:1–15.
- Martua L, Ng AK, Sun G. Prediction of rail rolling contact fatigue crack initiation life via three-dimensional finite element analysis). 2018 International Conference on intelligent rail Transportation (ICIRT); 2018.
- Srivastava JP, Sarkar PK, Meesala VRK, et al. Rolling contact fatigue life of rail for different slip conditions. Latin Am J Solids Struct. 2017;14(12):2243–2264.
- Nejad RM, Shariati M, Farhangdoost K. Prediction of fatigue crack propagation and fractography of rail steel. Theor Appl Fract Mech. 2019;101:320–331.
- Nejad R M, Liu Z. Analysis of fatigue crack growth under mixed-mode loading conditions for a pearlitic grade 900A steel used in railway applications. Eng Fract Mech. 2021;247:1–17.
- Meghoe A, Loendersloot R, Tinga T. Rail wear and remaining life prediction using meta-models. Int J Rail Transp. 2020;8(1):1–26.
- Bai W, Sun Q, Wang F, et al. A segmental evaluation model for determining residual rail service life based on a discrete-state conditional probabilistic method. Proc Inst Mech Eng, Part O:J Risk Reliab. 2019;233(2):211–225.
- Li CY, Dai WB, Duan F, et al. Fatigue life estimation of medium-carbon steel with different surface roughness. Appl Sci. 2017;7(4):1–11.
- Gao TC, Wang QH, Yang KH, et al. Estimation of rail renewal period in small radius curves: A data and mechanics integrated approach. Meas (Mahwah N J). 2021;185:1–11.
- Ren JX, Qie YH, Xie HX, et al. Fatigue analysis of 75kg/m-12 heavy-haul railway frog based on finite element simulation. Eng Fail Anal. 2020;117:1–23.
- Xin L, Markine V, Shevtsov I. Numerical procedure for fatigue life prediction for railway turnout crossings using explicit finite element approach. Wear. 2016;366-367(SI):167–179.
- Ma XC, Wang P, Xu JM, et al. Numerical simulation of rail surface-initiated rolling contact fatigue in the switch panel of railway turnouts. Proc Inst Mech Eng, Part F: J Rail Rapid Transit. 2021;235(2):155–165.
- Six K, Sazgetdinov K, Kumar N, et al. A whole system model framework to predict damage in turnouts. Veh Syst Dyn. 2021;21. doi:10.1080/00423114.2021.1988116
- Tian S, Sun XY, Xue SY, et al. Research on fatigue life of turnout outside locking device. international conference on measuring technology & mechatronics automation. IEEE Comput Soc. 2018: 65–68. doi:10.1109/ICMTMA.2018.00023
- Chen R, Chen JY, Wang P, et al. Impact of wheel profile evolution on wheel-rail dynamic interaction and surface initiated rolling contact fatigue in turnouts. Wear. 2019;438:1–14.
- Xu JM, Wang P, Ma XC, et al. Parameters studies for rail wear in high-speed railway turnouts by unreplicated saturated factorial design. J Central South Univ.2017;24(4): 988-1001.