Cambridge PhD candidate Ruodan Lu has been announced the winner of a celebratory award in the category of ‘Outstanding Student Research Project’.
With my project, we can improve the cost and benefit ratio by automating the process of virtual bridge model generation. This makes it possible to bring the on-site inspection work into the office.PhD candidate Ruodan Lu
Ruodan, who is part of the Department’s Construction Information Technology Laboratory, accepted the CETI: Celebration of Engineering & Technology Innovation Award at the Fiatech-Construction Industry Institute (CII) conference held in Texas recently.
Her winning PhD project – Automated Bridge Information Model Generation System – provides a step change in the way existing highway bridges are inspected, by automating the process of virtual bridge model generation. This makes it possible to bring the on-site inspection work into the office.
There are around half a million bridge inspections per year in the UK and the US, and all of these inspections are done manually by inspectors.
“Although we foresee that in the future all of our buildings and infrastructure are going to be digitised and managed in a 3D space, people are not creating such models as they perceive the cost of doing so outweighs its benefit,” said Ruodan.
“With my project, we can improve the cost and benefit ratio by automating the process of virtual bridge model generation. This makes it possible to bring the on-site inspection work into the office.”
Bridge Information Modelling (BrIM), as it is known, works by sharing knowledge with bridge management teams to help them make informed and reliable decisions which are required throughout the bridge life cycle.
Ruodan said: “Quite often, there is a gap between the qualified data available in Bridge Management Systems (BMS) and the reliable information needed for sound decision-making. This means that highway bridge owners face struggles in obtaining the data they require for rapid repair, maintenance and retrofit of bridges at a minimum cost. The proposed BrIM method differs from previous research because it uses human expertise for object detection guidance; processes the entire bridge point cloud data (PCD); and is robust in the absence of missing data.”
Dr Ioannis Brilakis, Laing O'Rourke Reader in Construction Engineering and Ruodan’s supervisor, added: “The impact of this work extends well beyond the world of bridges, as the hierarchical segmentation strategy devised can be easily modified and applied to tunnels, roads, other bridges, buildings, etc. Owners of infrastructure and buildings are now very likely to find commercial products in this space within the next five years.”
Ruodan, who is due to graduate this academic year, said she was ‘honoured and humbled’ to receive the Award.