Abstract
Chloride-induced corrosion is regarded as one of the most important sources of deterioration in reinforced concrete (RC) structures, whose maintenance during their service life is of foremost importance in order to avoid unnecessary human risks and economic losses. The availability of effective mechanisms for quantifying the condition and performance of these structures is, therefore, indispensable. The search for improved methods to assess this type of corrosion and its impact on tensile mechanical properties is the main objective of this research. Time variant non-spatial models are currently the methods of choice for the assessment of the effect of corrosion on the mechanical properties of reinforcing bars. Although these models, based on the relationship between mechanical properties and critical points in the geometry, give fairly good predictions, they still leave room for improvement. The consideration of the spatial component of corrosion has barely been addressed in relation to reinforcing bars embedded in concrete. Thus, the present study focuses on the spatial structure of chloride-induced corrosion on steel reinforcing bars and its effects on mechanical properties using a variety of approaches. The use of innovative techniques, originating from different disciplines and applications, has offered new possibilities in tackling this problem. First, based on the application of anodic current to steel reinforcing bars embedded in concrete from an external power source, a set of artificially corroded bars, at different degrees of severity, was produced. The use of a three-dimensional (3D) computerized imaging methodology was utilised to characterise these rebars in terms of a grid of corrosion depth measurements. After the acquisition of these measurements, use was made of a variety of surface metrology and image analysis techniques, through which a number of intensity, texture and shape corrosion quantifiers have been proposed for the spatial characterisation of corrosion patterns. Surface-metrological based parameters and image analysis-based features were found to yield useful metrics to investigate the corrosion structure of corroded rebars. The lack of an objective definition for a pit could be overcome with the characterisation of corrosion defects in terms of their depth and size using image segmentation. All the corroded bars were subjected to a uniaxial tension test and the relevant tensile mechanical properties throughout the strain-stress response were recorded. It was confirmed that traditional non-spatial corrosion models had limitations in terms of identifying and utilising a single corrosion quantifier, and, as a result, the introduction of different possible spatial corrosion quantifiers was investigated, in order to improve the model performance. It was concluded that the addition of spatial quantifiers as predictors, resulted in improved predictions of mechanical properties, compared to the currently used non-spatial models. However, for the range of corrosion levels examined in this study, the improvement in the prediction was relatively modest (circa 10% on the coefficient of determination), confirming the maximum corrosion depth or the minimum cross-sectional area as the pre-eminent quantifiers. The range of techniques developed in this thesis can be implemented in other applications where spatial corrosion characteristics need to be explored.