2018
DOI: 10.1142/s0219455418501626
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Capacity Estimation of Beam-Like Structures Using Substructural Method

Abstract: Evaluating the performance of beam-like structures in terms of their current boundary conditions, stiffness and modal properties can be challenging as the structures behave differently from their designed conditions due to aging. The purpose of the current study is to determine the flexural rigidity of beam-like structures when their support conditions are not fully understood. A novel optimization scheme is proposed for estimation of the flexural stiffness and the capacity of the beam-like structures under mo… Show more

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Cited by 3 publications
(3 citation statements)
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“…for quick on-site estimation of bridge stiffness and capacity. 23,24 In-service monitoring could be short or long term, and it includes any data related to the performance of the bridge such as deflection due to traffic. The objective of in-service monitoring is largely dependent on the results of previous tiers, in which the appropriate monitoring plan is arranged to study the specific response of the bridge over time.…”
Section: Multi-tier Assessment Proceduresmentioning
confidence: 99%
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“…for quick on-site estimation of bridge stiffness and capacity. 23,24 In-service monitoring could be short or long term, and it includes any data related to the performance of the bridge such as deflection due to traffic. The objective of in-service monitoring is largely dependent on the results of previous tiers, in which the appropriate monitoring plan is arranged to study the specific response of the bridge over time.…”
Section: Multi-tier Assessment Proceduresmentioning
confidence: 99%
“…Process of numerical model creations, with advantages and limitations of each modeling technique, is detailed in the authors' previous works. 22,24,27 The hidden reserved capacity of the bridge is masked if the numerical model is not calibrated with existing bridge information. Nonlinear analysis can be carried out on the calibrated numerical model of the bridge using information gained from SHM data.…”
Section: Development Of the Modeling Techniquementioning
confidence: 99%
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