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Volume: 29 | Article ID: art00009
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Comparative visualization of the geometry of a hollow box girder using 3D-LiDAR – Part 2: Reconstruction of 3D Geometric Model
  DOI :  10.2352/ISSN.2470-1173.2017.6.MOBMU-308  Published OnlineJanuary 2017
Abstract

With the mandatory introduction of the May 2011 directive for reassessment of bridges in Germany, the administrations of the federal and state governments have the duty to prove the stability of their bridge stock. Verification of bridge stability will be realized with consideration of the newly increased traffic loads. Particularly in older bridges, the verification can only be achieved if calculative surplus load capacity of the original structural design is taken into account in the recalculation. One option for considering these reserves is the exact determination of the dead weight of the bridge. Within this case study, it will be demonstrated how the problem can be practically solved. In order to determine the dead weight of a concrete bridge, its volume has to be calculated. as a first step, a 3D laser scanner is used to record the internal geometry of a hollow box bridge girder. For the determination of the thickness of the concrete member, the non-destructive technique ultrasonic echo is applied. The construction must be segmented in approximately equidistant parts in order to be able to carry out an economic and efficient investigation. The description of the segmentation of the point cloud, carried out in a 2D model, was presented in the first part of the publication. The subject of this presentation is the merging of 2D cross sections into a 3D model, from which the weight of the bridge can be calculated.

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Stefan Maack, Jenny Knackmuß, Reiner Creutzburg, "Comparative visualization of the geometry of a hollow box girder using 3D-LiDAR – Part 2: Reconstruction of 3D Geometric Modelin Proc. IS&T Int’l. Symp. on Electronic Imaging: Mobile Devices and Multimedia: Enabling Technologies, Algorithms, and Applications,  2017,  pp 54 - 64,  https://doi.org/10.2352/ISSN.2470-1173.2017.6.MOBMU-308

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