This paper illustrates how long-term measurements can be analysed to understand bridge behaviour under changing environmental conditions and how the developed understanding can help explain the performance of its critical components. Measurements from the Cleddau bridge, a structure that has been continuously monitored for more than two years, are used to investigate thermal effects in steel box-girder bridges and, in particular, their bearings. Observed temperature distributions are very different to the recommended distributions in design codes (BS EN 1991-5: 2003). These temperature distributions create plan bending of the box girder, which in turn impose forces at the bearings that have contributed to its wear. This paper investigates bearing movements of the bridge using numerical models, and estimates the resulting forces at the supports. A physics-based model of the bridge is created to which temperature distributions inferred from in situ measurements are supplied as input. Model predictions are validated against measured deformations at the bearings. Subsequently the model is used to predict forces at the bearings due to plan bending and bearing locking. Results quantify the impact that thermal effects have on the performance of the bearings. They also highlight the significance of considering a range of temperature distribution scenarios that go beyond those given in the design codes in order to reliably evaluate thermal effects at the design stage.

Engineers can today capture high-resolution video recordings of bridge movements during routine visual inspections using modern smartphones and compile a historical archive over time. However, the recordings are likely to be from cameras of different makes, placed at varying positions. Previous studies have not explored whether such recordings can support monitoring of bridge condition. This is the focus of this study. It evaluates the feasibility of an imaging approach for condition assessment that is independent of the camera positions used for individual recordings. The proposed approach relies on the premise that spatial relationships between multiple structural features remain the same even when images of the structure are taken from different angles or camera positions. It employs coordinate transformation techniques, which use the identified features, to compute structural displacements from images. The proposed approach is applied to a laboratory beam, subject to static loading under various damage scenarios and recorded using multiple cameras in a range of positions. Results show that the response computed from the recordings are accurate, with 5% discrepancy in computed displacements relative to the mean. The approach is also demonstrated on a full-scale pedestrian suspension bridge. Vertical bridge movements, induced by forced excitations, are collected with two smartphones and an action camera. Analysis of the images shows that the measurement discrepancy in computed displacements is 6%.