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contributor authorMaurizio Morgese
contributor authorChengwei Wang
contributor authorTodd Taylor
contributor authorMahmoud Etemadi
contributor authorFarhad Ansari
date accessioned2024-04-27T22:42:04Z
date available2024-04-27T22:42:04Z
date issued2024/01/01
identifier other10.1061-JBENF2.BEENG-6454.pdf
identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4297292
description abstractA bridge monitoring approach is proposed for the distributed detection and quantification of crack opening displacements (CODs) along the lengths of large bridges. The proposed method does not require a priori knowledge of traffic loads and is applicable under normal operational conditions of bridges. A damage index is introduced, using the difference between crack-induced strain peak values and bridge base strains caused by moving loads. The applicability of the proposed approach for quantification of the detected cracks is demonstrated in terms of CODs at a number of locations in a multispan bridge. Six field tests were performed on a 332 m, five-span precast post-tensioned concrete box girder bridge for this purpose. The bridge was tested under operational conditions; thus, random daily traffic loads were employed as external forces. Two distributed optical fiber sensors based on the Brillouin scattering system were adhered to the external and internal surfaces of the box girder bridge. Fiber Bragg grating crack sensors were also employed for verification of the COD measurements, based on direct acquisition of distributed strains over the 332-m length of the bridge. By using this approach, it is possible to detect and quantify cracks with CODs larger than 5 µm.
publisherASCE
titleDistributed Detection and Quantification of Cracks in Operating Large Bridges
typeJournal Article
journal volume29
journal issue1
journal titleJournal of Bridge Engineering
identifier doi10.1061/JBENF2.BEENG-6454
journal fristpage04023101-1
journal lastpage04023101-16
page16
treeJournal of Bridge Engineering:;2024:;Volume ( 029 ):;issue: 001
contenttypeFulltext


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