J. Winkler, M. D. Havelykke, Denmark


The Outstanding Paper Award (OPA) is remitted each year to the author(s) of a paper published in the preceding year’s issues of the IABSE Journal Structural Engineering International (SEI), encouraging and rewarding contributions of the highest quality. Starting with the 2011 Outstanding Paper Award, it is presented in the categories ‘Technical Report’ and ‘Scientific Paper’. The Outstanding Paper Award Selection Committee was chaired by Prof. Dr. Andreas Lampropoulos.


For ‘Technical Report’ category the Outstanding Paper Award 2019 is presented to: SEI, Nr. 3, August 2018, Innovative Long-Term Monitoring of the Great Belt Bridge Expansion Joint Using Digital Image Correlation.

Jan Winkler, Dr, Professional Head of Geomatics, ATKINS SNC-Lavalin—Transportation, Copenhagen, Denmark; Martin Duus Havelykke, Maintenance Manager, Sund & Bælt Holding A/S—Structures and Landworks, Copenhagen, Denmark. DOI: 10.1080/10168664.2018.1461539

Summary: Making informed decisions on timely intervention for effective bridge maintenance activities relies on good quality, accurate, reliable data. Although the proper functioning of expansion joints is critical to bridge performance, long-term monitoring of their condition is challenging due to the cost of sensors and data processing. Digital image correlation (DIC) is a non-contact photogrammetry technique that can image a bridge component periodically and compute strain and deformation from images previously recorded. This paper describes a one-month-long monitoring campaign wherein a DIC system was used as a cost-effective tool for gathering data on the movement and rotation of one of the Great Belt Bridge’s expansion joints. The monitoring provided previously unavailable data, helped improve understanding of the behaviour of the joint and informed the next steps for the maintenance strategy. The results show good agreement between the DIC data and measured temperature data. A mathematical model was established which relates the air temperature to expansion joint deformation, enabling the real-time evaluation of monitoring data and the cost-efficient identification of problems in the functioning of expansion joints. This is one of the first applications of a DIC technique to the long-term monitoring of a suspension bridge.

Keywords: suspension bridge; expansion joint; monitoring; digital image correlation; performance assessment; asset management; probabilistic modelling.



         
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