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A practical multi-lane factor model of bridges based on multi-truck presence considering lane load disparities

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Abstract

Many bridge design specifications consider multi-lane factors (MLFs) a critical component of the traffic load model. Measured multi-lane traffic data generally exhibit significant lane disparities in traffic loads over multiple lanes. However, these disparities are not considered in current specifications. To address this drawback, a multi-coefficient MLF model was developed based on an improved probabilistic statistical approach that considers the presence of multiple trucks. The proposed MLF model and approach were calibrated and demonstrated through an example site. The model sensitivity analysis demonstrated the significant influence of lane disparity of truck traffic volume and truck weight distribution on the MLF. Using the proposed approach, the experimental site study yielded MLFs comparable with those directly calculated using traffic load effects. The exclusion of overloaded trucks caused the proposed approach, existing design specifications, and conventional approach of ignoring lane load disparity to generate comparable MLFs, while the MLFs based on the proposed approach were the most comprehensive. The inclusion of overloaded trucks caused the conventional approach and design specifications to overestimate the MLFs significantly. Finally, the benefits of the research results to bridge practitioners were discussed.

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Abbreviations

N :

number of traffic lanes

W :

truck gross weight

c :

characteristic values

e :

extreme value

r :

lane-correction coefficient

η :

multi-lane combination coefficient

Q :

average daily lane traffic volume

F :

cumulative distribution function

L :

average truck length

v :

average truck speed

T :

bridge design period

K :

number of valid days over a year

R :

load return period

λ :

Poisson intensity factor

i :

lane label

u :

mean lane truck weight

Δt :

average truck passage time through a cross-section

p :

the occurrence probability of on-bridge multi-presence trucks

ξ :

the normalization factor of lane truck volume

ψ :

the normalization factor of lane truck weight

LE:

load effect

MLF:

multi-lane factor

WIM:

weigh-in-motion

IIID:

identical independent distribution

CDF:

cumulative distribution function

COV:

coefficient of variance

References

  1. Zhou J Y, Shi X F, Caprani C C, Ruan X. Multi-lane factor for bridge traffic load from extreme events of coincident lane load effects. Structural Safety, 2018, 72: 17–29

    Article  Google Scholar 

  2. Fu G, Liu L, Bowman M D. Multiple presence factor for truck load on highway bridges. Journal of Bridge Engineering, 2013, 18(3): 240–249

    Article  Google Scholar 

  3. Zhou J Y, Li T, Ye X J, Shi X F. Safety assessment of widened bridges considering uneven multilane traffic-load modeling: Case study in China. Journal of Bridge Engineering, 2020, 25(9): 05020008

    Article  Google Scholar 

  4. Zhou J Y, Caprani C C, Zhang L W. On the structural safety of long-span bridges under traffic loadings caused by maintenance works. Engineering Structures, 2021, 240: 112407

    Article  Google Scholar 

  5. Wu H, Zhao H, Liu J, Hu Z. A filtering-based bridge weigh-in-motion system on a continuous multi-girder bridge considering the influence lines of different lanes. Frontiers of Structural and Civil Engineering, 2020, 14(1): 1–15

    Article  Google Scholar 

  6. Algohi B, Bakht B, Khalid H, Mufti A. Design loading for bridges with traffic flowing in multiple lanes in the same direction. In: The 10th International Conference on Short and Medium Span Bridges. Quebec: Curran Associates, Inc., 2018

    Google Scholar 

  7. van der Spuy P, Lenner R, de Wet T, Caprani C C. Multiple lane reduction factors based on multiple lane weigh in motion data. Structure (London, England), 2019, 20: 543–549

    Google Scholar 

  8. Zhou J Y, Chen Z X, Yi J, Ma H Y. Investigation of multi-lane factor models for bridge traffic load effects using multiple lane traffic data. Structure (London, England), 2020, 24: 444–455

    Google Scholar 

  9. Zhou J Y, Hu C M, Chen Z X, Wang X M, Wang T. Extreme value modeling of coincident lane load effects for multi-lane factors of bridges using peaks-over-threshold method. Advances in Structural Engineering, 2021, 24(3): 539–555

    Article  Google Scholar 

  10. Bakht B, Jaeger L G. Bridge evaluation for multipresence of vehicles. Journal of Structural Engineering, 1990, 116(3): 603–618

    Article  Google Scholar 

  11. Jaeger L G, Bakht B. Bridges and Transmission Line Structures. New York: ASCE, 1987, 47–59

    Google Scholar 

  12. Bao W G, Li Y H, Zhang S T, Zheng B Q, Ning P H. On the reduction coefficients of traffic loading laterally and longitudinally on bridges. China Journal of Highway and Transport, 1995, 8(1): 80–86 (in Chinese)

    Google Scholar 

  13. Nowak A S. Calibration of LRFD Bridge Design Code. NCHRP Report 368. 1999

  14. Gindy M, Nassif H H. Multiple presence statistics for bridge live load based on weigh-in-motion data. Transportation Research Record: Journal of the Transportation Research Board, 2007, 2028(1): 125–135

    Article  Google Scholar 

  15. Committee on Loads and Forces on Bridges of the Committee on Bridges of the Structural Division. Recommended design loads for bridges. Journal of the Structural Division, 1981, 107(7): 1161–1213

    Article  Google Scholar 

  16. Prat M. Traffic load models for bridge design: Recent developments and research. Progress in Structural Engineering and Materials, 2001, 3(4): 326–334

    Article  Google Scholar 

  17. OBrien E J, Enright B, Getachew A. Importance of the tail in truck weight modeling for bridge assessment. Journal of Bridge Engineering, 2010, 15(2): 210–213

    Article  Google Scholar 

  18. Anitori G, Casas J R, Ghosn M. Methodology for development of live load models for refined analysis of short and medium-span highway bridges. Structure and Infrastructure Engineering, 2018, 14(4): 477–490

    Article  Google Scholar 

  19. Zhou J Y, Liu Y Y, Yi J. Effect of uneven multilane truck loading of multigirder bridges on component reliability. Structural Concrete, 2020, 21(4): 1644–1661

    Article  Google Scholar 

  20. Kwon O S, Kim E, Orton S, Salim H, Hazlett T. Calibration of the live load factor in LRFD design guidelines. Report No. OR 11-003. 2010

  21. Caprani C C. Lifetime highway bridge traffic load effect from a combination of traffic states allowing for dynamic amplification. Journal of Bridge Engineering, 2013, 18(9): 901–909

    Article  Google Scholar 

  22. OBrien E J, Enright B. Modeling same-direction two-lane traffic for bridge loading. Structural Safety, 2011, 33(4–5): 296–304

    Article  Google Scholar 

  23. Ministry of Transport of China. General Code for Design of Highway Bridges and Culverts, JTG D60-2004. Beijing: China Communications Press, 2004 (in Chinese)

    Google Scholar 

  24. Ministry of Transport of China. General Code for Design of Highway Bridges and Culverts, JTG D60-2015. Beijing: China Communications Press, 2015 (in Chinese)

    Google Scholar 

  25. American Association of State Highway and Transportation Officials. AASHTO LRFD Bridge Design Specifications. 3rd ed. Washington, D.C.: American Association of State Highway and Transportation Officials, 2004

    Google Scholar 

  26. CAN/CSA-S6-06. Canadian Highway Bridge Design Code. Toronto: Canadian Standards Association (CSA), 2006

    Google Scholar 

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Acknowledgements

This work was supported by the National Natural Science Foundation of China (Grant No. 51808148), Natural Science Foundation of Guangdong Province, China (No. 2019A1515010701) and Guangzhou Municipal Science and Technology Project (No. 201904010188).

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Authors and Affiliations

  1. School of Civil Engineering, Guangzhou University, Guangzhou, 510006, China

    Junyong Zhou

  2. Department of Civil Engineering, Monash University, Melbourne, 3800, Australia

    Colin C. Caprani

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  1. Junyong Zhou
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  2. Colin C. Caprani
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Correspondence to Junyong Zhou.

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Zhou, J., Caprani, C.C. A practical multi-lane factor model of bridges based on multi-truck presence considering lane load disparities. Front. Struct. Civ. Eng. 15, 877–894 (2021). https://doi.org/10.1007/s11709-021-0756-2

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  • DOI: https://doi.org/10.1007/s11709-021-0756-2

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