Advances in digital computing and information technology (IT) over the last few decades have had a pronounced impact on how civil engineers develop and deliver solutions for the community – particularly in how we manage, monitor and maintain bridges.
We now have small powerful computers that enable us to solve complex bridge engineering equations and model the behaviour of construction materials. Building information modelling (BIM) is now mandatory for all bridge project funded by the public purse in the UK, which includes existing as well as new structures.
Satellite positioning systems, fast laser scanners, sophisticated sensor networks and drones are all part of the increasing digital armoury available to civil engineers who ensure the structural health of a nation’s bridge infrastructure. To keep them up to date with the latest advances in IT, ICE has just published a themed issue of its Bridge Engineering journal.
BIM for existing infrastructure
McKenna et al. (2017) explain how they applied laser scanning techniques to ascertain the full geometric profile of a historic viaduct in Ireland. Once calibrated using targeted site measurements, they developed a three-dimensional BIM model using the point cloud data generated from the laser scan. They then describe their method of associating attributes to complete a model that embedded all information necessary for ongoing management of the bridge.
Hendy et al. (2017) provide a summary of their work developing a BIM-based system to monitor and manage elements of the M4 elevated motorway in London, UK. They describe gathering site data using laser scanning techniques, undertaking complex non-linear finite-element assessment and strengthening design of reinforced-concrete crossheads. They also explain and how they applied BIM to document design solutions as well as incorporate site measurements, including crack widths and chloride levels.
Delgado et al. (2017) focus on the fact that there are currently no prescribed standards for the implementation of structural health monitoring (SHM) data into BIM models. They present a rational method of embedding SHM data into a BIM model and explore the benefits of such a system in regular structures for ongoing asset management.
Digital sensing techniques
Lydon et al. (2017) look at one of the older methods of SHM: bridge weigh-in-motion. They acknowledge that conventional strain gauge-based systems are often less reliable in remote areas where mains power supply is not available. They present a fibre optic-based system with lower power usage than the conventional system, which they developed and tested on a bridge in Northern Ireland.
Hoag et al. (2017) explain how they used digital image correlation to validate effectiveness of remedial works to an existing lifting bridge. Their need for an innovative technology-based approach to measuring displacements arose as they sought to find a means of validating whether their strengthening measures had been installed correctly in a manner that was safe for site teams to undertake.
Finally, Giaccio et al. (2017) explain how they used digital technology to demonstrate code compliance for a new steel cable-stayed pedestrian and cycle bridge. They analysed the data from electronic velocity meters to ascertain cable damping ratios and verify there was no risk from overlapping frequencies between the deck and cables.
