• Journal of the Korea institute for structural maintenance and inspection
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• v.15 no.2
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• pp.70-78
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• 2011

The paper aims at developing a more reliable and accurate BWIM(Bridge Weigh-In-Motion) algorithm using measured strain data and examining its efficiency with various tests on bridges. It proposes a BWIM algorithm using density estimation function and average modification factor for moment-strain relationship. Density estimation function has been proved to be reliably applied when multiple axle loads are estimated. An average modification factor is applied to minimize overall error that can be encountered between theoretically computed moments and measured strains at multiple locations in a bridge. The developed algorithm has been successfully examined through numerical simulations, laboratory tests, and also by field tests on a multi-girder composite bridge.

• Computational Structural Engineering
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• v.10 no.3
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• pp.233-240
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• 1997

The study presents the linear dynamic analysis of multi-girder steel bridges under vehicular movement to examine the performance characteristics due to the various structural and loading conditions. The road surface roughness and bridge-vehicle interactions are considered. The road surface profiles for the approaching roadway and bridge decks are generated from power spectral density functions for different road roughness conditions. A new filtering method using the wheel trace is proposed to obtain the more rational bridge-vehicle interactions from the randomly generated road surface. The possible settlement condition between the bridge deck and approaching roadway is also included. The dynamic responses of various bridges designed according to current design practice are examined, in which important structural parameters(such as span length, girder spacing, etc.) are considered systematically. In addition to the basic loading conditions due to a single truck passing on the bridge, the traffic conditions of multi-truck traveling either consecutively on the same lane or side-by-side on the adjacent lanes are also evaluated.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.19 no.2 s.72
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• pp.125-138
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• 2006

The use of system identification approaches for damage detection has been expanded in recent years owing to the advancements in data acquisition system andinformation processing techniques. Soft computing techniques such as neural networks and genetic algorithm have been utilized increasingly for this end due to their excellent pattern recognition capability. In this study, damage detection of bridge structures using neural networks technique based on the modal properties is presented, which can effectively consider the modeling uncertainty in the analysis model from which the training patterns are to be generated. The differences or the ratios of the mode shape components between before and after damage are used as the input to the neural networks in this method, since they are found to be less sensitive to the modeling errors than the mode shapes themselves. Two numerical example analyses on a simple beam and a multi-girder bridge are presented to demonstrate the effectiveness and applicability of the proposed method.

• Journal of Korean Society of Steel Construction
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• v.14 no.6
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• pp.691-699
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• 2002

A study on the evaluationof the proper spacing and required bending rigidity of cross beams in composite multiple I-girder bridge without lateral and sway bracing system was performed. For the purpose, a two-lane 40m simple span and 40+50+40m continuous sample bridge with four girders was designed. For the sample bridges, structural analysis under the design loads including dead load before and after composite, live load, and seismic loads has been performed. The material and geometric nonlinear analysis under dead load before composite has also been performed to evaluate lateral buckling strength of the steel-girder-cross beam grillage. Based on the two phase anlayses, proper spacing and bending righidity of cross beams were proposed.