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The Scientific World Journal
Volume 2014 (2014), Article ID 126270, 9 pages
http://dx.doi.org/10.1155/2014/126270
Research Article

A Methodology for Multihazards Load Combinations of Earthquake and Heavy Trucks for Bridges

1Department of Lifeline Engineering, Institute of Engineering Mechanics, China Earthquake Administration, Harbin 150080, China
2State Key Laboratory Breeding Base of Mountain Bridge and Tunnel Engineering, Chongqing Jiaotong University, Chongqing 400074, China

Received 2 January 2014; Accepted 15 April 2014; Published 4 May 2014

Academic Editor: Ting-Hua Yi

Copyright © 2014 Dezhang Sun et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Issues of load combinations of earthquakes and heavy trucks are important contents in multihazards bridge design. Current load resistance factor design (LRFD) specifications usually treat extreme hazards alone and have no probabilistic basis in extreme load combinations. Earthquake load and heavy truck load are considered as random processes with respective characteristics, and the maximum combined load is not the simple superimposition of their maximum loads. Traditional Ferry Borges-Castaneda model that considers load lasting duration and occurrence probability well describes random process converting to random variables and load combinations, but this model has strict constraint in time interval selection to obtain precise results. Turkstra’s rule considers one load reaching its maximum value in bridge’s service life combined with another load with its instantaneous value (or mean value), which looks more rational, but the results are generally unconservative. Therefore, a modified model is presented here considering both advantages of Ferry Borges-Castaneda's model and Turkstra’s rule. The modified model is based on conditional probability, which can convert random process to random variables relatively easily and consider the nonmaximum factor in load combinations. Earthquake load and heavy truck load combinations are employed to illustrate the model. Finally, the results of a numerical simulation are used to verify the feasibility and rationality of the model.