Queens University of Belfast and the Department for Infrastructure (DfI) who are the local road authority in Northern Ireland have undertaken a joint project to develop a new bridge management system to cover the inspection and maintenance of DfI bridges and associated structures. An initial review of the asset data held by DfI, including bridge properties and current and legacy inspection data has been undertaken for the entire network. This paper primarily focuses on 3,437 masonry arch bridges which make up nearly 53% of the total bridge stock in NI. It will presents data which has been classified into groups in order to explore trends in condition rating of various structural component types. A discussion on the most prevalent defects and the overall condition of the bridge stock will beare also presented. This will forms the a basis for identifying the critical defects and structural components in order to target maintenance spend in a timely and effective manner in the future. The fundamental aspect of this research is the input and use of Structural Health Monitoring (SHM) data to inform a decision-making framework. The greatest limitation of SHM data is the lack of historical data, in order to make our bridge inspections more efficient, economical and effective at a local and global level we need to establish baseline data sets. The analysis of historical data has led to the identification of key performance indicators for monitoring through SHM to allow for live automatic updates on bridge condition.
|Publication status||Published - 01 Sep 2020|
|Event||CERI 2020 : Civil Engineering Research Ireland - Cork Institute of Technology , Cork, Ireland|
Duration: 27 Aug 2020 → 28 Aug 2020
|Conference||CERI 2020 : Civil Engineering Research Ireland|
|Period||27/08/2020 → 28/08/2020|