Modified Best-Selection Method for Bridge Live-Load Model Development
Publication: ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering
Volume 8, Issue 3
Abstract
Due to the expanding availability of high-fidelity weigh-in-motion (WIM) data in recent years, various local agencies have modified bridge design and rating procedures to best reflect state-specific traffic loads. However, accurate procedures for load model revision are often accompanied by high computational cost and implementation complexity. To address this concern, a reliability-based approach is proposed for vehicular live-load model development that involves selecting an actual vehicle configuration from the WIM database to serve as the basis for the load model. The approach first determined the required live-load factor for each potential vehicle configuration such that all considered structures would meet a minimum level of reliability. Next, the set of potential models was screened by imposing a limit on the level of design or rating conservatism allowed for any individual structure. Finally, an optimal load model was selected from the remaining set based on a penalty point approach that accounted for the deviation of results for any single structure as well as the overall deviation across all structures. Relative to an ideal reliability-based design optimization (RBDO) solution, the proposed method requires low computational cost, is straightforward to implement, results in a realistic vehicle configuration for the live-load model, and provides reasonable accuracy. The method was found to be slightly superior to the existing best-selection approach for large databases, but significantly better for small databases.
Get full access to this article
View all available purchase options and get full access to this article.
Data Availability Statement
Some models, or code to develop the Modified Best-Selection method are available from the corresponding author upon reasonable request. Some or all data, models, or code used during the study were provided by a third party. Direct requests for these materials may be made to the provider as indicated in the Acknowledgements.
Acknowledgments
The weigh-in-motion data used in this study were provided by the Michigan Department of Transportation, whose support is greatly acknowledged.
References
AASHTO. 2018. Manual for bridge evaluation. 3rd ed. Washington, DC: AASHTO.
AASHTO. 2020. LRFD bridge design specifications. 8th ed. Washington, DC: AASHTO.
Anitori, G., J. R. Casas, and M. Ghosn. 2017. “WIM-based live-load model for advanced analysis of simply supported short-and medium-span highway bridges.” J. Bridge Eng. 22 (10): 04017062. https://doi.org/10.1061/(ASCE)BE.1943-5592.0001081.
Baghi, H., H. Baghi, and S. Siavashi. 2019. “Novel empirical expression to predict the shear strength of reinforced concrete walls based on particle swarm optimization.” ACI Struct. J. 116 (5): 247–260. https://doi.org/10.14359/51716773.
Baghi, H., and J. A. Barros. 2017. “Design approach to determine shear capacity of reinforced concrete beams shear strengthened with NSM systems.” J. Struct. Eng. 143 (8): 04017061. https://doi.org/10.1061/(ASCE)ST.1943-541X.0001793.
Collins, M. P. 2001. Evaluation of shear design procedures for concrete structures. Toronto: Canadian Standards Association Group.
Eamon, C., V. Kamjoo, and K. Shinki. 2014. Side by side probability for bridge design and analysis. Lansing, MI: Michigan DOT.
Eamon, C., V. Kamjoo, and K. Shinki. 2016. “Design live-load factor calibration for Michigan highway bridges.” J. Bridge Eng. 21 (6): 04016014. https://doi.org/10.1061/(ASCE)BE.1943-5592.0000897.
Eamon, C., and A. S. Nowak. 2005. “Effect of edge-stiffening and diaphragms on the reliability of bridge girders.” J. Bridge Eng. 10 (2): 206–214. https://doi.org/10.1061/(ASCE)1084-0702(2005)10:2(206).
Eamon, C., and S. Siavashi. 2018. Developing representative Michigan truck configurations for bridge load rating. Lansing, MI: Michigan DOT.
FHWA (Federal Highway Administration). 2015a. Bridge formula weights. Washington, DC: FHWA.
FHWA (Federal Highway Administration). 2015b. Code of federal regulations. Part 658: Truck size and weight, routine designations—Length, width, and weight limitations. Washington, DC: FHWA.
Fu, G., J. Chi, and Q. Wang. 2019. Illinois-specific LRFR live-load factors based on truck data. Springfield, IL: Illinois DOT.
Ghosn, M., B. Sivakumar, and F. Miao. 2011. Load and resistance factor rating (LRFR) in NYS. Albany, NY: New York State DOT.
Kamjoo, V., and C. Eamon. 2018. “Reliability-based design optimization of a vehicular live load model.” Eng. Struct. 168 (Aug): 799–808. https://doi.org/10.1016/j.engstruct.2018.05.033.
Kamyab, M., S. Remias, E. Najmi, S. Rabinia, and J. M. Waddell. 2020. “Machine learning approach to forecast work zone mobility using probe vehicle data.” Transp. Res. Rec. 2674 (9): 157–167.
Kassem, W. 2015. “Non-linear analysis of shear-critical reinforced concrete beams using the softened membrane model.” Struct. Concr. 16 (4): 524–536. https://doi.org/10.1002/suco.201400093.
Kwon, O. S., S. Orton, H. Salim, E. Kim, and T. Hazlett. 2010. Calibration of the live load factor in LRFD design guidelines. Jefferson City, MO: Missouri DOT.
Neto, B. N. M., J. A. Barros, and G. S. A. Melo. 2013. “Model for the prediction of the punching resistance of steel fibre reinforced concrete slabs centrically loaded.” Constr. Build. Mater. 46 (Sep): 211–223. https://doi.org/10.1016/j.conbuildmat.2013.04.034.
Nowak, A. S. 1993. “Live load model for highway bridges.” Struct. Saf. 13 (1): 53–66. https://doi.org/10.1016/0167-4730(93)90048-6.
Nowak, A. S. 1999. Calibration of LRFD bridge design code. Washington, DC: Transportation Research Board.
Oller Ibars, E., D. Cobo del Arco, and A. R. Marí Bernat. 2009. “Design proposal to avoid peeling failure in FRP-strengthened reinforced concrete beams.” J. Compos. Constr. 13 (5): 384–393. https://doi.org/10.1061/(ASCE)CC.1943-5614.0000038.
Pelphrey, J., and C. Higgins. 2006. Calibration of LRFR live load factors using weigh-in- motion data. Washington, DC: Federal Highway Administration.
Siavashi, S. 2019. Optimal assessment of weigh-in-motion data for structural reliability based rating of bridge superstructures. Detroit: Wayne State Univ.
Siavashi, S., and C. Eamon. 2019. “Development of traffic live-load models for bridge superstructure rating with RBDO and best selection approach.” J. Bridge Eng. 24 (8): 04019084. https://doi.org/10.1061/(ASCE)BE.1943-5592.0001457.
Siavashi, S., and C. Eamon. 2020. “Load truncation approach for development of live-load factors for bridge rating.” J. Bridge Eng. 25 (7): 04020039. https://doi.org/10.1061/(ASCE)BE.1943-5592.0001559.
Sivakumar, B., and M. Ghosn. 2011. Recalibration of LRFR live load factors in the AASHTO manual for bridge evaluation. Washington, DC: Transportation Research Board.
Sivakumar, B., M. Ghosn, and F. Moses. 2011. Protocols for collecting and using traffic data in bridge design. Washington, DC: Transportation Research Board.
Information & Authors
Information
Published In
Copyright
© 2022 American Society of Civil Engineers.
History
Received: Jan 1, 2022
Accepted: Mar 13, 2022
Published online: May 17, 2022
Published in print: Sep 1, 2022
Discussion open until: Oct 17, 2022
ASCE Technical Topics:
- Bridge design
- Business management
- Computing in civil engineering
- Databases
- Design (by type)
- Engineering fundamentals
- Engineering mechanics
- Highway transportation
- Information Technology (IT)
- Infrastructure
- Live loads
- Load factors
- Management methods
- Model accuracy
- Models (by type)
- Optimization models
- Practice and Profession
- Ratings
- Static loads
- Statics (mechanics)
- Structural design
- Transportation engineering
- Vehicles
Authors
Metrics & Citations
Metrics
Citations
Download citation
If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.