Smart Structures and Systems

  • 제17권6호
  • /
  • Pages.995-1015
  • /
  • 2016
  • /
  • 1738-1584(pISSN)
  • /
  • 1738-1991(eISSN)
테크노프레스 (Techno-Press)
권호 표지
DOI QR코드

DOI QR Code

Extrapolation of extreme traffic load effects on bridges based on long-term SHM data

  • Xia, Y.X. (Department of Civil and Environmental Engineering, The Hong Kong Polytechnic University) ;
  • Ni, Y.Q. (Department of Civil and Environmental Engineering, The Hong Kong Polytechnic University)
  • 투고 : 2016.03.17
  • 심사 : 2016.04.30
  • 발행 : 2016.06.25
⟨ 이전 논문 다음 논문 ⟩

초록

In the design and condition assessment of bridges, it is usually necessary to take into consideration the extreme conditions which are not expected to occur within a short time period and thus require an extrapolation from observations of limited duration. Long-term structural health monitoring (SHM) provides a rich database to evaluate the extreme conditions. This paper focuses on the extrapolation of extreme traffic load effects on bridges using long-term monitoring data of structural strain. The suspension Tsing Ma Bridge (TMB), which carries both highway and railway traffic and is instrumented with a long-term SHM system, is taken as a testbed for the present study. Two popular extreme value extrapolation methods: the block maxima approach and the peaks-over-threshold approach, are employed to extrapolate the extreme stresses induced by highway traffic and railway traffic, respectively. Characteristic values of the extreme stresses with a return period of 120 years (the design life of the bridge) obtained by the two methods are compared. It is found that the extrapolated extreme stresses are robust to the extrapolation technique. It may owe to the richness and good quality of the long-term strain data acquired. These characteristic extremes are also compared with the design values and found to be much smaller than the design values, indicating conservative design values of traffic loading and a safe traffic-loading condition of the bridge. The results of this study can be used as a reference for the design and condition assessment of similar bridges carrying heavy traffic, analogous to the TMB.

키워드

과제정보

연구 과제 주관 기관 : Council of the Hong Kong Special Administrative Region

참고문헌

  1. American Association of State Highway and Transportation Officials (AASHTO) (2011), Manual for Bridge Evaluation, Washington, USA.
  2. American Association of State Highway and Transportation Officials (AASHTO) (2015), LRFD Bridge Design Specifications, Washington, USA.
  3. Canadian Standards Association (CSA) (2006), Canadian Highway Bridge Design Code, Toronto, Canada.
  4. Bailey, S.F. (1996), "Basic principles and load models for the structural safety evaluation of existing road bridges", Ph.D. Dissertation, University of Southampton, Southampton, UK.
  5. Bailey, S.F. and Bez, R. (1999), "Site specific probability distribution of extreme traffic action effects", Probabilist. Eng. Mech., 14(1), 19-26. https://doi.org/10.1016/S0266-8920(98)00013-7
  6. Balkema, A.A. and De Haan, L. (1974), "Residual life time at great age", Ann. Probab., 2(5), 792-804. https://doi.org/10.1214/aop/1176996548
  7. Beirlant, J., Goegebeur, Y., Segers, J. and Teugels, J. (2006), Statistics of Extremes: Theory and Applications, John Wiley and Sons, Chichester, UK.
  8. Caprani, C.C. (2005), "Probalistic analysis of highway bridge traffic loading", Ph.D. Dissertation, Dublin Institute of Technology, Dublin, Ireland.
  9. Caprani, C.C., O'Brien, E.J. and McLachlan, G.J. (2008), "Characteristic traffic load effects from a mixture of loading events on short to medium span bridges", Struct. Saf., 30(5), 394-404. https://doi.org/10.1016/j.strusafe.2006.11.006
  10. Castillo, E. (1988), Extreme Value Theory in Engineering, Academic Press, San Diego, USA.
  11. Chan, T.H.T., Miao, T.J. and Ashebo, D.B. (2005), "Statistical models from weigh-in-motion data", Struct. Eng. Mech., 20(1), 85-110. https://doi.org/10.12989/sem.2005.20.1.085
  12. Coles, S. (2001), An Introduction to Statistical Modeling of Extreme Values, Springer, London, UK.
  13. Crespo-Minguillon, C. and Casas, J.R. (1997), "A comprehensive traffic load model for bridge safety checking", Struct. Saf., 19(4), 339-359. https://doi.org/10.1016/S0167-4730(97)00016-7
  14. Enright, B. (2010), "Simulation of traffic loading on highway bridges", Ph.D. Dissertation, Dublin Institute of Technology, Dublin, Ireland.
  15. Getachew, A. (2003), "Traffic load effects on bridges, statistical analysis of collected and Monte Carlo simulated data", Ph.D. Dissertation, Royal Institute of Technology, Stockholm, Sweden.
  16. Gilli, M. (2006), "An application of extreme value theory for measuring financial risk", Comput. Econ., 27(2-3), 207-228. https://doi.org/10.1007/s10614-006-9025-7
  17. Gilleland, E. and Katz, R.W. (2011), "New software to analyze how extremes change over time", Eos, 92(2), 13-14.
  18. Gindy, M. and Nassif, H.H. (2006), "Comparison of traffic load models based on simulation and measured data", Proceedings of the Joint International Conference on Computing and Decision Making in Civil Engineering, Montreal, Canada.
  19. Grave, S. (2002), "Modelling of site-specific traffic loading on short to medium span bridges", Ph.D. Dissertation, Trinity College Dublin, Dublin, Ireland.
  20. Gumbel, E.J. (1958), Extreme Value Theory, Columbia University Press, New York, USA.
  21. Harris, R. (1996), "Gumbel re-visited-a new look at extreme value statistics applied to wind speeds", J. Wind Eng. Ind. Aerod., 59(1), 1-22. https://doi.org/10.1016/0167-6105(95)00029-1
  22. Holmes, J. and Moriarty, W. (1999), "Application of the generalized Pareto distribution to extreme value analysis in wind engineering", J. Wind Eng. Ind. Aerod., 83(1), 1-10. https://doi.org/10.1016/S0167-6105(99)00056-2
  23. James, G. (2003), "Analysis of traffic load effects an railway bridges", Ph.D. Dissertation, Royal Institute of Technology, Sweden.
  24. Jenkinson, A.F. (1955), "The frequency distribution of the annual maximum (or minimum) values of meteorological elements", Q. J. Roy. Meteor. Soc., 81(348), 158-171. https://doi.org/10.1002/qj.49708134804
  25. Katz, R.W., Parlange, M.B. and Naveau, P. (2002), "Statistics of extremes in hydrology", Adv. Water Resour., 25(8), 1287-1304. https://doi.org/10.1016/S0309-1708(02)00056-8
  26. Ko, J.M. and Ni, Y.Q. (2005), "Technology developments in structural health monitoring of large-scale bridges", Eng. Struct., 27(12), 1715-1725. https://doi.org/10.1016/j.engstruct.2005.02.021
  27. Leadbetter, M.R., Lindgren, G. and Rootzen, H. (2012), Extremes and Related Properties of Random Sequences and Processes, Springer-Verlag, New York, USA.
  28. Lubliner, J. (2008), Plasticity Theory, Courier Corporation, New York, USA.
  29. Messervey, T.B., Frangopol, D.M. and Casciati, S. (2011), "Application of the statistics of extremes to the reliability assessment and performance prediction of monitored highway bridges", Struct. Infrastruct. E., 7(1-2), 87-99. https://doi.org/10.1080/15732471003588619
  30. Miao, T.J. and Chan, T.H.T. (2002), "Bridge live load models from WIM data", Eng. Struct., 24(8), 1071-1084. https://doi.org/10.1016/S0141-0296(02)00034-2
  31. Ni, Y.Q., Wong, K.Y. and Xia, Y. (2011), "Health checks through landmark bridges to sky-high structures", Adv. Struct. Eng., 14(1), 103-119. https://doi.org/10.1260/1369-4332.14.1.103
  32. Ni, Y.Q., Xia, H.W., Wong, K.Y. and Ko, J.M. (2012), "In-service condition assessment of bridge deck using long-term monitoring data of strain response", J. Bridge Eng., 17(6), 876-885. https://doi.org/10.1061/(ASCE)BE.1943-5592.0000321
  33. Ni, Y.Q. and Xia, Y.X. (2016), "Strain-based condition assessment of a suspension bridge instrumented with structural health monitoring system", Int. J. Struct. Stab. Dy., 16(4), Paper No. 1640027 (23 pages). https://doi.org/10.1142/S0219455416400277
  34. O'Brien, E., Schmidt, F., Hajializadeh, D., Zhou, X.Y., Enright, B., Caprani, C., Wilson, S. and Sheils, E. (2015), "A review of probabilistic methods of assessment of load effects in bridges", Struct. Saf., 53, 44-56. https://doi.org/10.1016/j.strusafe.2015.01.002
  35. O'Connor, A.J. (2001), "Probabilistic traffic load modelling for highway bridges", Ph.D. Dissertation, Dublin Institute of Technology, Dublin, Ireland.
  36. Pickands III, J. (1975), "Statistical inference using extreme order statistics", Ann. Stat., 3(1), 119-131. https://doi.org/10.1214/aos/1176343003
  37. Poon, S.H., Rockinger, M. and Tawn, J. (2004), "Extreme value dependence in financial markets: diagnostics, models, and financial implications", Rev. Financ. Stud., 17(2), 581-610. https://doi.org/10.1093/rfs/hhg058
  38. R Development Core Team (2014), R: A Language and Environment for Statistical Computing, Vienna, Austria.
  39. Reiss, R.D., Thomas, M. and Reiss, R. (2001), Statistical Analysis of Extreme Values, Springer Basel AG, Washington D.C., USA.
  40. Simiu, E., Heckert, N., Filliben, J. and Johnson, S. (2001), "Extreme wind load estimates based on the Gumbel distribution of dynamic pressures: an assessment", Struct. Saf., 23(3), 221-229. https://doi.org/10.1016/S0167-4730(01)00016-9
  41. Tawn, J.A. (1990), "Modelling multivariate extreme value distributions", Biometrika, 77(2), 245-253. https://doi.org/10.1093/biomet/77.2.245
  42. Treacy, M.A., Bruhwiler, E. and Caprani, C.C. (2014), "Monitoring of traffic action local effects in highway bridge deck slabs and the influence of measurement duration on extreme value estimates", Struct. Infrastruct. E., 10(12), 1555-1572. https://doi.org/10.1080/15732479.2013.835327
  43. Tsimplis, M. and Blackman, D. (1997), "Extreme sea-level distribution and return periods in the Aegean and Ionian Seas", Estuar. Coast. Shelf S., 44(1), 79-89. https://doi.org/10.1006/ecss.1996.0126
  44. Wong, K.Y. (2004), "Instrumentation and health monitoring of cable-supported bridges", Struct. Control Health., 11(2), 91-124. https://doi.org/10.1002/stc.33
  45. Xia, H.W., Ni, Y.Q., Wong, K.Y. and Ko, J.M. (2012), "Reliability-based condition assessment of in-service bridges using mixture distribution models", Comput.Struct., 106, 204-213.

피인용 문헌

  1. Threshold selection for extreme strain extrapolation due to vehicles on bridges vol.5, 2017, https://doi.org/10.1016/j.prostr.2017.07.030
  2. Threshold selection for extreme value estimation of vehicle load effect on bridges vol.14, pp.2, 2018, https://doi.org/10.1177/1550147718757698
  3. Temperature effect analysis of a long-span cable-stayed bridge based on extreme strain estimation vol.20, pp.1, 2017, https://doi.org/10.12989/sss.2017.20.1.011
  4. A sensor fault detection strategy for structural health monitoring systems vol.20, pp.1, 2016, https://doi.org/10.12989/sss.2017.20.1.043
  5. Evaluating Probabilistic Traffic Load Effects on Large Bridges Using Long-Term Traffic Monitoring Data vol.19, pp.22, 2016, https://doi.org/10.3390/s19225056
  6. Long term structural health monitoring for old deteriorated bridges: a copula-ARMA approach vol.25, pp.3, 2020, https://doi.org/10.12989/sss.2020.25.3.285
  7. Extreme value modeling of structural load effects with non-identical distribution using clustering vol.74, pp.1, 2016, https://doi.org/10.12989/sem.2020.74.1.055