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BIM authoring and Data Models for Bridge Maintenance Systems in Korea

 BIM authoring and Data Models for Bridge Maintenance Systems in Korea
Autor(en): , ,
Beitrag für IABSE Symposium: Challenges for Existing and Oncoming Structures, Prague, Czech Republic, 25-27 May 2022, veröffentlicht in , S. 1867-1872
DOI: 10.2749/prague.2022.1867
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A digital model-based bridge maintenance system (BMS) is a challenging mission due to large volume of bridge inventory and their data for long period. Building information modelling (BIM) provides ...
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Bibliografische Angaben

Autor(en): (Chung-Ang University, SEOUL, KOREA)
(Chung-Ang University, SEOUL, KOREA)
(Chung-Ang University, SEOUL, KOREA)
Medium: Tagungsbeitrag
Sprache(n): Englisch
Tagung: IABSE Symposium: Challenges for Existing and Oncoming Structures, Prague, Czech Republic, 25-27 May 2022
Veröffentlicht in:
Seite(n): 1867-1872 Anzahl der Seiten (im PDF): 6
Seite(n): 1867-1872
Anzahl der Seiten (im PDF): 6
DOI: 10.2749/prague.2022.1867
Abstrakt:

A digital model-based bridge maintenance system (BMS) is a challenging mission due to large volume of bridge inventory and their data for long period. Building information modelling (BIM) provides an efficient information delivery during life-cycle of bridge projects. In this paper, model authoring with visual programming for bridges is introduced to minimize the effort to create 3D models for the information delivery. A data model for a few bridge types is also suggested to deliver essential information for the bridge maintenance. During design and construction, digital engineering models are defined to accommodate information requirements from project participants. Changes of geometry and their properties are collected to revise the digital engineering models for reliable as- built models. Existing bridge maintenance systems in Korea need to be improved for nation-wide digitalized bridges. Two cases of BIM-based BMS on a cable-stayed bridge and common bridges are introduced. The new systems included point cloud data by scanning and data from non-destructive testing as a part of the data model. Through these efforts, data pipeline from data creation to data uses was attempted, and data-driven bridge maintenance can be realized in national scale

Copyright: © 2022 International Association for Bridge and Structural Engineering (IABSE)
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