Suggestions for improved reinforced concrete half-joint bridge inspection in England

© 2018 The Authors, published by EDP Sciences. Asset management databases play a crucial role in the management of existing infrastructure assets. Highways England (HE) has a long history of using bridge management software to record the current state of bridges and to guide maintenance schemes and interventions. Reinforced concrete half-joints are amongst the most challenging structures to inspect and repair due to their susceptibility to deterioration and construction type. Hence, they require particular attention within asset management programmes. An Interim Management Strategy was developed by HE to identify all the structures on the Highways England road network with half-joint elements. These half-joint structures were then subjected to a special inspection regime. Out of the 428 half-joint structures with inspection data, 252 structures had defects associated with four existing HE defect classes. A review of the inspection database with a focus on half-joints led to an alternative classification of half-joint related defects based on a revised set of Defect Classes, the introduction of Defect Groups and the extraction of Defect Types specifically observed in half-joints. Using this new classification, the most common half-joint Defect Groups were found to be cracking, corrosion, spalling and deterioration mechanisms. In about half of the structures cracking and corrosion tended to be observed together. Correlations were also shown to exist between structural and deterioration, and constructional Defect Classes, emphasising the need for quality control and proper workmanship. Recommendations to address shortcomings in current inspection practice are proposed. Clearer defect definitions and decision-tree guidance for inspectors could enhance the consistency and repeatability of inspection data gathering thereby overcoming some of the limitations of subjective classifications. Acquiring additional information about the observed crack details including zonal information, crack patterns, crack extent, crack orientations and widths combined with local and global pictorial evidence would also be advantageous. This could then provide the basis for the automatic processing and identification of structures with specific half-joint related defects. In this way, asset managers would be better able to allocate limited resources to the most critical structures.