Advertisement

International Journal of Steel Structures

, Volume 19, Issue 1, pp 181–192 | Cite as

Fatigue Reliability Evaluation of Orthotropic Steel Bridge Decks Based on Site-Specific Weigh-in-Motion Measurements

  • Naiwei LuEmail author
  • Yang Liu
  • Yang Deng
Article
  • 76 Downloads

Abstract

The fast-growing traffic loads may become a safety hazard for existing bridges especially in developing countries. One of the problems induced by heavy traffic loads is the fatigue damage accumulation of the welded joints in steel bridge decks. This study utilized a stochastic traffic flow model and a novel computational framework for estimating fatigue reliability of orthotropic steel bridge decks using site-specific traffic data. The stochastic traffic flow is demonstrated as an effective approach for converting the probabilistic characteristics of the site-specific traffic data into the fatigue stress spectrum modeling of steel bridge decks. In addition, the traffic growth and control measures can be considered in the stochastic traffic flow for lifetime fatigue reliability estimation of the bridge deck. The proposed computational framework involves a meta-model approximated by neural networks that can greatly reduce the computational effort. Orthotropic steel bridge decks in a long-span suspension bridge is chosen as prototype to illustrate the effective of the stochastic traffic flow model and the computational framework. Numerical results show the following conclusions: firstly, the efficiency and accuracy of the framework is associated with the number of training samples, where approximately 180 training samples is essential for training the 6-types of meta-models; secondly, a annual growth rate of the vehicle weight of 0.5% leads to the fatigue reliability index of the bridge in the 100th year decrease from 5.94 to 0.92. The numerical result may provide a theoretical basis for how to control overloaded trucks for ensuring the bridge safety.

Keywords

Fatigue reliability Orthotropic bridge deck Weigh-in-motion Gaussian mixture model Welded joint Gross vehicle weight Traffic volume 

Notes

Acknowledgements

The support from the National Basic Research Program of China (Grant No. 2015CB057705), and the Hunan Science Foundation (2018JJ3540) are highly acknowledged. The opinions and conclusions expressed in the paper are those of the authors and do not necessarily represent the views of the sponsors.

References

  1. Chen, Z. W., Xu, Y. L., Xia, Y., Li, Q., & Wong, K. Y. (2011). Fatigue analysis of long-span suspension bridges under multiple loading: case study. Engineering Structures, 33(12), 3246–3256.Google Scholar
  2. Cheng, B., Cao, X., Ye, X., & Cao, Y. (2017a). “Fatigue tests of welded connections between longitudinal stringer and deck plate in railway bridge orthotropic steel decks. Engineering Structures, 153, 32–42.Google Scholar
  3. Cheng, B., Ye, X., Cao, X., Mbako, D. D., & Cao, Y. (2017b). Experimental study on fatigue failure of rib-to-deck welded connections in orthotropic steel bridge decks. International Journal of Fatigue, 103, 157–167.Google Scholar
  4. Cheng, J. (2010). An artificial neural network based genetic algorithm for estimating the reliability of long span suspension bridges. Finite Elements in Analysis and Design, 46(8), 658–667.Google Scholar
  5. Cui, C., Bu, Y., Bao, Y., Zhang, Q., & Ye, Z. (2017). Strain energy-based fatigue life evaluation of deck-to-rib welded joints in OSD considering combined effects of stochastic traffic load and welded residual stress. Journal of Bridge Engineering, 23(2), 04017127.Google Scholar
  6. Deng, L., He, W., Yu, Y., & Cai, C. S. (2018). Equivalent shear force method for detecting the speed and axles of moving vehicles on bridges. Journal of Bridge Engineering, 23(8), 04018057.Google Scholar
  7. Dung, C. V., Sasaki, E., Tajima, K., & Suzuki, T. (2015). Investigations on the effect of weld penetration on fatigue strength of rib-to-deck welded joints in orthotropic steel decks. International Journal of Steel Structures, 15(2), 299–310.Google Scholar
  8. European Committee for Standardization (ECS). (2005). Eurocode 3: Design of steel structures—Part 1-9: Fatigue EN1993-1-9. Brussels: Belgium.Google Scholar
  9. Frangopol, D. M., Strauss, A., & Kim, S. (2008). Bridge reliability assessment based on monitoring. Journal of Bridge Engineering, 13(3), 258–270.Google Scholar
  10. Fu, Z., Ji, B., Zhang, C., & Li, D. (2018). Experimental study on the fatigue performance of roof and U-rib welds of orthotropic steel bridge decks. KSCE Journal of Civil Engineering, 22(1), 270–278.Google Scholar
  11. Gokanakonda, S., Ghantasala, M. K., & Kujawski, D. (2016). Fatigue sensor for structural health monitoring: Design, fabrication and experimental testing of a prototype sensor. Structural Control and Health Monitoring, 23(2), 237–251.Google Scholar
  12. Guo, T., & Chen, Y. W. (2013). Fatigue reliability analysis of steel bridge details based on field-monitored data and linear elastic fracture mechanics. Structure and Infrastructure Engineering, 9(5), 496–505.Google Scholar
  13. Guo, T., Frangopol, D. M., & Chen, Y. (2012). Fatigue reliability assessment of steel bridge details integrating weigh-in-motion data and probabilistic finite element analysis. Computers & Structures, 112, 245–257.Google Scholar
  14. Guo, T., Li, A., & Wang, H. (2008). Influence of ambient temperature on the fatigue damage of welded bridge decks. International Journal of Fatigue, 30(6), 1092–1102.Google Scholar
  15. Han, Y., Li, K., He, X., et al. (2018a). Stress analysis of a long-span steel-truss suspension bridge under combined action of random traffic and wind loads. Journal of Aerospace Engineering, 31(3), 04018021.Google Scholar
  16. Han, Y., Shen, L., Xu, G., Cai, C. S., Hu, P., & Zhang, J. (2018b). Multiscale simulation of wind field on a long-span bridge site in mountainous area. Journal of Wind Engineering and Industrial Aerodynamics, 177, 260–274.Google Scholar
  17. Han, Y., Liu, S., Cai, C. S., et al. (2015). The influence of vehicles on the flutter stability of a long-span suspension bridge. Wind & Structures An International Journal, 20(2), 275–292.Google Scholar
  18. Ji, B., Liu, R., Chen, C., Maeno, H., & Chen, X. (2013). Evaluation on root-deck fatigue of orthotropic steel bridge deck. Journal of Constructional Steel Research, 90, 174–183.Google Scholar
  19. Lalthlamuana, R., & Talukdar, S. (2013). Rating of steel bridges considering fatigue and corrosion. Structural Engineering and Mechanics, 47(5), 643–660.Google Scholar
  20. Liu, Y., Deng, Y., & Cai, C. S. (2015). Deflection monitoring and assessment for a suspension bridge using a connected pipe system: A case study in China. Structural Control and Health Monitoring, 22(12), 1408–1425.Google Scholar
  21. Liu, Y., Lu, N., & Yin, X. (2016). A hybrid method for structural system reliability-based design optimization and its application to trusses. Quality and Reliability Engineering International, 32(2), 595–608.Google Scholar
  22. Lu, N., Noori, M., & Liu, Y. (2017). Fatigue reliability assessment of welded steel bridge decks under stochastic truck loads via machine learning. Journal of Bridge Engineering, 22(1), 04016105.Google Scholar
  23. Marques, F., Moutinho, C., Hu, W. H., Cunha, Á., & Caetano, E. (2016). Weigh-in-motion implementation in an old metallic railway bridge. Engineering Structures, 123, 15–29.Google Scholar
  24. Miner, M. (1945). Cumulative damage in fatigue. Journal of Applied Mechanics, 12(3), 159–164.Google Scholar
  25. Ministry of Communications and Transportation (MOCAT). (2004). Limits of dimensions, axle load and masses for road vehicles GB 1589-2004. Beijing: China Communications Press.Google Scholar
  26. OBrien, E. J., Cantero, D., Enright, B., & González, A. (2010). Characteristic dynamic increment for extreme traffic loading events on short and medium span highway bridges. Engineering Structures, 32(12), 3827–3835.Google Scholar
  27. OBrien, E. J., & Enright, B. (2013). Using weigh-in-motion data to determine aggressiveness of traffic for bridge loading. Journal of Bridge Engineering, 18(3), 232–239.Google Scholar
  28. Sim, H. B., & Uang, C. M. (2012). Stress analyses and parametric study on full-scale fatigue tests of rib-to-deck welded joints in steel orthotropic decks. Journal of Bridge Engineering, 17(5), 765–773.Google Scholar
  29. Wang, D., Zhang, D., Wang, S., & Ge, S. (2013). Finite element analysis of hoisting rope and fretting wear evolution and fatigue life estimation of steel wires. Engineering Failure Analysis, 27, 173–193.Google Scholar
  30. Xia, H. W., Ni, Y. Q., Wong, K. Y., & Ko, J. M. (2012). Reliability-based condition assessment of in-service bridges using mixture distribution models. Computers & Structures, 106, 204–213.Google Scholar
  31. Ye, X. W., Ni, Y. Q., Wong, K. Y., & Ko, J. M. (2012). Statistical analysis of stress spectra for fatigue life assessment of steel bridges with structural health monitoring data. Engineering Structures, 45, 166–176.Google Scholar
  32. Ye, X. W., Su, Y. H., & Xi, P. S. (2018). Statistical analysis of stress signals from bridge monitoring by FBG system. Sensors, 18(2), 1–14.Google Scholar
  33. Ye, X. W., Yi, T. H., Wen, C., & Su, Y. H. (2015). Reliability-based assessment of steel bridge deck using a mesh-insensitive structural stress method. Smart Structures and Systems, 16(2), 367–382.Google Scholar
  34. Zhang, J., & Au, F. (2016). Fatigue reliability assessment considering traffic flow variation based on weigh-in-motion data. Advances in Structural Engineering.  https://doi.org/10.1177/1369433216646011.Google Scholar
  35. Zhang, W., & Cai, C. S. (2011). Fatigue reliability assessment for existing bridges considering vehicle speed and road surface conditions. Journal of Bridge Engineering, 17(3), 443–453.MathSciNetGoogle Scholar
  36. Zhao, J., & Tabatabai, H. (2012). Evaluation of a permit vehicle model using weigh-in-motion truck records. Journal of Bridge Engineering, 17(2), 389–392.Google Scholar
  37. Zhou, Y., & Chen, S. (2015). Dynamic Simulation of a long-span bridge-traffic system subjected to combined service and extreme loads. Journal of Structural Engineering.  https://doi.org/10.1061/(ASCE)ST.1943-541X.0001188.Google Scholar
  38. Zhu, J., & Zhang, W. (2018). Probabilistic fatigue damage assessment of coastal slender bridges under coupled dynamic loads. Engineering Structures, 166, 274–285.Google Scholar

Copyright information

© Korean Society of Steel Construction 2018

Authors and Affiliations

  1. 1.School of Civil EngineeringChangsha University of Science and TechnologyChangshaChina
  2. 2.Institute for Risk and ReliabilityLeibniz Universität HannoverHannoverGermany
  3. 3.Beijing Advanced Innovation Center for Future Urban DesignBeijing University of Civil Engineering and ArchitectureBeijingChina

Personalised recommendations