Abstract
Many historic masonry arch bridges experience damage due to support movements during their lifetime. This damage may influence the performance of the bridge and reduce its load carrying capacity. This paper proposes a new method to quantify past support movements by investigating distortions in bridge geometry. In this method, the bridge geometry is recorded in point cloud format and segmented into different structural components (e.g. 3D piers and barrels or 2D pier and barrel cross-sections). The geometry of each component is investigated further by fitting primitive shapes (e.g. 3D planes and cylinders or 2D lines and arcs) which represent the design intent. The discrepancy between these fitted shapes and the point clouds reveals a characteristic distortion signature. This signature is compared with theoretical distortion traces, which are obtained from kinematical analyses of the arch subjected to a range of support movements. The most likely support movement scenarios identified from these comparisons are then validated with visual indications of damage, such as crack location and size, and other geometric quantities, such as the change of the bedding joint elevations along the bridge. The proposed technique is applied to two masonry rail viaducts in the UK, which demonstrate different evidence of damage. Using the proposed method, past support movements of both bridges, which led to the observed damage, are inferred.
Highlights
Masonry arch bridges are an integral part of Europe’s rail, road and waterway infrastructure
Since detailed construction drawings are rarely available for masonry arch bridges, laser scanning has been widely used to quantify the external geometry of the structure
This paper proposes a new assessment method, which aims to infer potential historic support movements of masonry arch bridges from laser scan point clouds of their current geometry
Summary
Masonry arch bridges are an integral part of Europe’s rail, road and waterway infrastructure. Before carrying out an assessment of the capacity of a bridge, it is necessary to identify its loading history and model the existing damage [3]. Engineering Structures 173 (2018) 530–545 environmental effects and cyclic loading of foundations These movements may not be visible to the naked eye, and may have different influences on the response mechanisms of the bridge [7], and the resulting observable damage. This paper proposes a new assessment method to map 3D deformations and identify the historic support movements of a bridge by evaluating existing bridge distortions. In this method, the distorted bridge geometry is quantified using laser scanning technology and point cloud processing. The proposed technique is applied to two damaged masonry rail viaducts in the UK: Marsh Lane Viaduct in Leeds and Stapleton Road Viaduct in Bristol
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