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Analysis of the influence of vibration frequency and amplitude on ballast bed tamping operation in railway turnout areas

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Abstract

Turnout is the essential track equipment to achieve train switching. To ensure a safe and stable railway operation, it is significant to carry out scientific tamping operations in the turnout areas. However, the tamping operation parameters of the large machine in the turnout areas are complex and diverse. The daily maintenance is mainly based on experience. In order to enhance the effectiveness of field maintenance operations, based on the DEM-MBD coupling algorithm, a simulation model of the tamping device-sleeper-ballast bed in the turnout areas was established and analyzed. The ballast material used is granite, commonly used in China, and the ballast particle gradation is the first-grade ballast commonly used in China's mainline railway and turnout areas. The correctness of the model was verified by field tests. On this basis, the influence of vibration frequency and amplitude on the tamping operation of the ballast bed in turnout areas is analyzed in detail from both macro and micro perspectives. Based on the response surface analysis method, parameter optimization suggestions are given. The results show that the vibration frequency significantly affects the vertical contact state of the particles, and the amplitude of the tamping device has a considerable influence on the contact state of particles along the line. The support stiffness of the ballast bed initially increases and later decreases with an increase in vibration frequency and amplitude. It is observed that tamping device amplitude has a greater influence on the support stiffness of the ballast bed than vibration frequency.

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References

  1. Wang R, Jing G, Wang B et al (2023) Under ballast mat–a review of recent developments, limitations, and future prospect. Proc Inst Mech Eng Part F J Rail Rapid Transit 09544097221150494

  2. Maramizonouz S, Nadimi S, Skipper WA et al (2023) Numerical modelling of particle entrainment in the wheel–rail interface. Comput Part Mech 1–11

  3. Guo Y, Markine V, Song J et al (2018) Ballast degradation: effect of particle size and shape using Los Angeles Abrasion test and image analysis. Constr Build Mater 169:414–424

    Article  Google Scholar 

  4. Ma X, Zi H, Liu C et al (2022) Study of problems related to Laying ballastless track in the turnout of ballasted track at high-speed railway stations. Adv Mater Sci Eng 2022:1–16

    Google Scholar 

  5. Guo Y, Markine V, Jing G (2021) Review of ballast track tamping: mechanism, challenges and solutions. Constr Build Mater 300:123940

    Article  Google Scholar 

  6. Zhang Z, Xiao H, Zhu Y et al (2022) Macro–meso mechanical properties of ballast bed during three-sleeper tamping operation. Int J Rail Transp 1–26

  7. McDowell GR, Lim WL, Collop AC et al (2005) Laboratory simulation of train loading and tamping on ballast. Proc Inst Civ Eng Transp 158(2):89–95

    Google Scholar 

  8. Aingaran S, Pen L, Zervos A et al (2018) Modelling the effects of trafficking and tamping on scaled railway ballast in triaxial tests. Transp Geotech 15:84–90

    Article  Google Scholar 

  9. Aursudkij B (2007) A laboratory study of railway ballast behaviour under traffic loading and tamping maintenance. University of Nottingham, Nottingham

    Google Scholar 

  10. Descantes Y, Perales R, Saussine G et al (2011) On the damaging effects of the ballast tamping operation. In: AIPCR

  11. Douglas SC (2013) Railroad ballast quality and break down during tamping. Indianapolis

  12. Wang W, Song S, Yan H et al (2018) Experimental study on resistance characteristics of ballast bed in different stamping stages. J Cent South Univ (Sci Technol) 49(08):2003–2008

    Google Scholar 

  13. Liu J, Wang P, Liu G et al (2019) Influence of a tamping operation on the vibrational characteristics and resistance-evolution law of a ballast bed. Constr Build Mater 239:117879

    Article  Google Scholar 

  14. Deiros I, Voivret C, Combe G et al (2016) Quantifying degradation of railway ballast using numerical simulations of micro-deval test and in-situ conditions. Procedia Eng 143:1016–1023

    Article  Google Scholar 

  15. Kim DS, Hwang SH, Kono A et al (2018) Evaluation of ballast compactness during the tamping process by using an image-based 3D discrete element method. Proc Inst Mech Eng Part F J Rail Rapid Transit 232(7):1951–1964

    Article  Google Scholar 

  16. Gao L, Shi S, Zhong Y et al (2023) Real-time evaluation of mechanical qualities of ballast bed in railway tamping maintenance. Int J Mech Sci 248:108192

    Article  Google Scholar 

  17. Shi S, Gao L, Cai X et al (2020) Effect of tamping operation on mechanical qualities of ballast bed based on DEM-MBD coupling method. Comput Geotech 124:103574

    Article  Google Scholar 

  18. Boler H, Mishra D, Tutumluer E et al (2019) Stone blowing as a remedial measure to mitigate differential movement problems at railroad bridge approaches. Proc Inst Mech Eng Part F J Rail Rapid Transit 233(1):63–72

    Article  Google Scholar 

  19. Wang Y, Xiao H, Ling X et al (2022) 2D ballast particle contour generation based on the random midpoint displacement algorithm. Comput Part Mech 10:1–17

    Google Scholar 

  20. DEM Hossain Z (2007) analysis of angular ballast breakage under cyclic loading. Geomech Geoeng 2(3):175–181

    Article  Google Scholar 

  21. Zhang Z, Zhang X, Qiu H et al (2016) Dynamic characteristics of track-ballast-silty clay with irregular vibration levels generated by high-speed train based on DEM. Constr Build Mater 125:564–573

    Article  Google Scholar 

  22. Lu M, McDowell GR (2007) The importance of modelling ballast particle shape in the discrete element method. Granul Matter 9:69–80

    Article  Google Scholar 

  23. Kumara JJ, Hayano K (2016) Importance of particle shape on stress-strain behaviour of crushed stone-sand mixtures. Geomech Eng 10(4):455–470

    Article  Google Scholar 

  24. Aela P, Zong L, Yin ZY et al (2023) Calibration method for discrete element modeling of ballast particles. Comput Part Mech 10(3):481–493

    Article  Google Scholar 

  25. Mahmoud E, Papagiannakis AT, Renteria D (2016) Discrete element analysis of railway ballast under cycling loading. Procedia Eng 143:1068–1076

    Article  Google Scholar 

  26. Chen C, Indraratna B, McDowell G et al (2015) Discrete element modelling of lateral displacement of a granular assembly under cyclic loading. Comput Geotech 69:474–484

    Article  Google Scholar 

  27. Zhang X, Zhao C, Zhai W (2017) DEM analysis of ballast breakage under train loads and its effect on mechanical behaviour of railway track. In: Proceedings of the 7th international conference on discrete element methods. Springer, Singapore, pp 1323–1333

  28. Lane JE, Metzger PT, Wilkinson RA (2010) A review of discrete element method (DEM) particle shapes and size distributions for lunar soil

  29. Neto AG, Wriggers P (2022) Discrete element model for general polyhedra. Comput Part Mech 9:1–28

    Google Scholar 

  30. Santasusana M, Irazábal J, Oñate E et al (2016) The Double Hierarchy Method. A parallel 3D contact method for the interaction of spherical particles with rigid FE boundaries using the DEM. Comput Part Mech 3:407–428

    Article  Google Scholar 

  31. Nassauer B, Kuna M (2015) Impact of micromechanical parameters on wire sawing: a 3D discrete element analysis. Comput Part Mech 2:63–71

    Article  Google Scholar 

  32. Alonso-Marroquin F, Wang Y (2009) An efficient algorithm for granular dynamics simulation with complex-shaped objects. Granul Matter 11(5):317–329

    Article  Google Scholar 

  33. Eliáš J (2014) Simulation of railway ballast using crushable polyhedral particles. Powder Technol 264:458–465

    Article  Google Scholar 

  34. Ahmed S, Harkness J, Le Pen L et al (2016) Numerical modelling of railway ballast at the particle scale. Int J Numer Anal Methods Geomech 40(5):713–737

    Article  Google Scholar 

  35. Zhang Z, Xiao H, Wang Y et al (2023) Numerical simulation of the three-sleeper asynchronous tamping operation of ballast bed based on the virtual unit module and polyhedral ballast model. Transp Geotech 40:100964

    Article  Google Scholar 

  36. Tutumluer E, Qian Y, Hashash YMA et al (2013) Discrete element modelling of ballasted track deformation behaviour. Int J Rail Transp 1(1–2):57–73

    Article  Google Scholar 

  37. Rao C, Tutumluer E, Stefanski JA (2001) Coarse aggregate shape and size properties using a new image analyzer. J Test Eval 29(5):461–471

    Article  Google Scholar 

  38. Moaveni M, Wang S, Hart J (2013) Size and shape by means evaluation of aggregate of segmentation techniques and aggregate image algorithms processing. Transp Res Rec 2335:50–59

    Article  Google Scholar 

  39. Saussine G, Cholet C, Gautier PE et al (2006) Modelling ballast behaviour under dynamic loading. Part 1: a 2D polygonal discrete element method approach. Comput Methods Appl Mech Eng 195(19–22):2841–2859

    Article  Google Scholar 

  40. Jiang MJ, Yu HS, Harris D (2005) A novel discrete model for granular material incorporating rolling resistance. Comput Geotech 32(5):340–357

    Article  Google Scholar 

  41. Irazábal J, Salazar F, Oñate E (2017) Numerical modelling of granular materials with spherical discrete particles and the bounded rolling friction model. Application to railway ballast. Comput Geotech 85:220–229

    Article  Google Scholar 

  42. Indraratna B, Ngo NT, Rujikiatkamjorn C et al (2014) Behavior of fresh and fouled railway ballast subjected to direct shear testing: discrete element simulation. Int J Geomech 14(1):34–44

    Article  Google Scholar 

  43. Huang H, Tutumluer E (2011) Discrete element modeling for fouled railroad ballast. Constr Build Mater 25(8):3306–3312

    Article  Google Scholar 

  44. Sakaguchi H, Ozaki E, Igarashi T (1993) Plugging of the flow of granular materials during the discharge from a silo. Int J Mod Phys B 7(09n10):1949–1963

    Article  Google Scholar 

  45. Ai J, Chen JF, Rotter JM et al (2011) Assessment of rolling resistance models in discrete element simulations. Powder Technol 206(3):269–282

    Article  Google Scholar 

  46. Zhai W, Wang K, Cai C (2009) Fundamentals of vehicle–track coupled dynamics. Veh Syst Dyn 47(11):1349–1376

    Article  Google Scholar 

  47. Zhai W, Wang Q, Lu Z et al (2001) Dynamic effects of vehicles on tracks in the case of raising train speeds. Proc Inst Mech Eng Part F J Rail Rapid Transit 215(2):125–135

    Article  Google Scholar 

  48. Jing G, Zhang X, Jia W (2019) Lateral resistance of polyurethane-reinforced ballast with the application of new bonding schemes: laboratory tests and discrete element simulations. Constr Build Mater 221:627–636

    Article  Google Scholar 

  49. Zhou P, Li Y, Liang R et al (2023) Calibration of contact parameters for particulate materials in residual film mixture after sieving based on EDEM. Agriculture 13(5):959

    Article  Google Scholar 

  50. Rothenburg L, Bathurst RJ (1989) Analytical study of induced anisotropy in idealized granular materials. Geotechnique 39(4):601–614

    Article  Google Scholar 

  51. O’sullivan C, Cui L, O’neill SC (2008) Discrete element analysis of the response of granular materials during cyclic loading. Soils Found 48(4):511–530

    Article  Google Scholar 

  52. Asadzadeh M, Soroush A (2016) Fundamental investigation of constant stress simple shear test using DEM. Powder Technol 292:129–139

    Article  Google Scholar 

  53. Xiao H, Fang J, Chi Y et al (2022) Discrete element analysis of the effect of manual tamping operation on the mechanical properties of ballast bed. Constr Build Mater 361:129557

    Article  Google Scholar 

  54. Guo Y, Jia W, Markine V et al (2021) Rheology study of ballast-sleeper interaction with particle image Velocimetry (PIV) and discrete element modelling (DEM). Constr Build Mater 282:122710

    Article  Google Scholar 

  55. Gu Q, Liu H, Wu Y et al (2022) Evolution of trackbed performance and ballast degradation due to passages of million train wheel axle loads. Transp Geotech 34:100753

    Article  Google Scholar 

  56. Tong Y, Liu G, Yousefian K et al (2022) Track vertical stiffness—value, measurement methods, effective parameters and challenges: a review. Transp Geotech 37:100833

    Article  Google Scholar 

  57. Xiao J, Liu G, Liu J et al (2019) Parameters of a discrete element ballasted bed model based on a response surface method. J Zhejiang Univ Sci A (Appl Phys Eng) 20(9):685–700

    Article  Google Scholar 

  58. Kim SH, Na SW (1997) Response surface method using vector projected sampling points. Struct Saf 19(1):3–19

    Article  Google Scholar 

  59. Bar-Gera H (2017) The target parameter of adjusted r-squared in fixed-design experiments. Am Stat 71(2):112–119

    Article  MathSciNet  Google Scholar 

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Acknowledgements

The authors gratefully acknowledge the project supported by the National Natural Science Foundation of China (Grant Number 51978045) and the Fundamental Research Funds for the Central Universities (Science and technology leading talent team project) (Grant Number 2022JBXT010).

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Authors and Affiliations

  1. School of Civil Engineering, Beijing Jiaotong University, Beijing, 100044, China

    Yihao Chi, Hong Xiao, Zhihai Zhang & Zhongxia Qian

  2. Beijing Key Laboratory of Track Engineering, Beijing Jiaotong University, Beijing, 100044, China

    Yihao Chi, Hong Xiao, Zhihai Zhang & Zhongxia Qian

  3. Department of Mechanical Engineering, KLSGIT, Belgaum, Karnataka, 590008, India

    M. M. Nadakatti

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  1. Yihao Chi
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Contributions

YC: conceptualization, methodology, formal analysis, writing—original draft. HX: Conceptualization, project administration, funding acquisition, supervision. ZZ: Formal analysis, validation, software, data curation. MMN: writing—review and editing. ZQ: software, data curation.

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Correspondence to Hong Xiao.

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Chi, Y., Xiao, H., Zhang, Z. et al. Analysis of the influence of vibration frequency and amplitude on ballast bed tamping operation in railway turnout areas. Comp. Part. Mech. 11, 771–788 (2024). https://doi.org/10.1007/s40571-023-00652-4

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