TECHNICAL PAPERS
Sep 4, 2010

Extrapolation for Future Maximum Load Statistics

Publication: Journal of Bridge Engineering
Volume 16, Issue 4

Abstract

The use of short-term load data to extrapolate or project remote future maximum load has been practiced in structural design code development and/or calibration. However, this approach has not been adequately evaluated or validated because of the absence of long-term data, which is important for the structures’ safety governed by these codes. In this paper, the application of such extrapolations to highway bridge design is studied by taking advantage of available long-term truck weight data obtained from the weigh-in-motion technique. A new extrapolation method is proposed from the understanding of the importance of the load probability distribution’s high tail. This approach significantly reduces the mathematical length of the extrapolation/projection and thus increases its reliability. Also presented in this paper are application examples. In addition, the extrapolation process proposed is evaluated with quantitative indexes. The application of a temporal extrapolation/projection can now be evaluated by using these indexes for its reliability and appropriateness.

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Acknowledgments

The financial support of the National Cooperative Highway Research Program, the Michigan Department of Transportation, and China Communications Construction is gratefully appreciated. Transportation agencies in the United States and China have generously provided the assistance of WIM data gathering and processing, without which the reported work could not have been completed. Mr.Tapan Bhatt and Ms. Lang Liu ably assisted with some of the calculation and draft work performed in this study, and their efforts are acknowledged.

References

AASHTO. (2003). Manual for condition evaluation and load and resistance factor rating (LRFR) of highway bridges, Washington, DC.
AASHTO. (2006). “LRFD bridge design specifications”. 4th Ed., Washington, DC.
Fu, G. (1994). “Variance reduction by truncated multimodal importance sampling.” Struct. Saf., 13(4), 267–283.
Gumbel, E. J. (1958). Statistics of extreme, Columbia University Press, New York.
Kulicki, J., Prucz, Z., Clancy, C. M., Mertz, D. R., and Nowak, A. S. (2007). “Updating the calibration report for AASHTO LRFD code.” Final Rep. for National Cooperative Highway Research Program (NCHRP) 20-7/186, AASHTO, Washington, DC.
Moses, F. (2001). “Calibration of load factors for LRFR bridge evaluation.” National Cooperative Highway Research Program (NCHRP) Rep. 454, Transportation Research Board, Washington, DC.
Nowak, A. S. (1999). “Calibration of LRFD bridge design code.” National Cooperative Highway Research Program (NCHRP) Rep. 368, Transportation Research Board, Washington, DC.
Sivakumar, B., Ghosn, M., and Moses, F. (2008). “Protocols for collecting and using traffic data in bridge design.” Draft Final Rep. for NCHRP Project 12-76, National Cooperative Highway Research Program (NCHRP), Washington, DC.

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Information

Published In

Go to Journal of Bridge Engineering
Journal of Bridge Engineering
Volume 16Issue 4July 2011
Pages: 527 - 535

History

Received: Feb 16, 2010
Accepted: Aug 26, 2010
Published online: Sep 4, 2010
Published in print: Jul 1, 2011

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Authors

Affiliations

Gongkang Fu, M.ASCE [email protected]
Chair Professor, Guangdong Univ. of Technology, Guangzhou, China; Fuzhou Univ., Fuzhou, China; and Tongji Univ., Shanghai, China; and Professor and Chairman, Dept. of Civil, Architectural, and Environmental Engineering, Illinois Institute of Technology, Chicago, IL 60616; formerly Professor and Director, Center for Advanced Bridge Engineering, Dept. of Civil and Environmental Engineering, Wayne State Univ., Detroit, MI 48202 (corresponding author). E-mail: [email protected]
Ji You
Ph.D. Candidate, Research Institute of Structural Engineering and Disaster Reduction, Tongji Univ., Shanghai 200092, China.

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