Advanced non-destructive assessment of concrete structures subject to reinforcing bar corrosion

Corrosion of steel reinforcement in concrete composite structures is one of the main contributors towards their unanticipated failure during service period. The costs of late repair and replacement for concrete structures degraded by steel corrosions are found to be costly. Also, any such attempt undertaken often causes disruptions to socio-economic activities. In order for steel corrosion to be detected and properly assessed at an early stage of structure deterioration process, strategies are adopted in assessment and maintenance practices by employing different kinds of techniques on the field. Nevertheless, there is still a lack of technical expertise in associating steel corrosion damage to the resulting change in mechanical and fracture behaviors of structure. More studies are hence essential to evaluate steel corrosion and its quantitative effect on overall structural integrity. In particular, a systematic approach to analyse and interpret large volume of field measurement data for risk probability analysis is highly sought after. These research gaps form the basis of this PhD project, which aims at developing a comprehensive condition assessment scheme to evaluate corrosion of steel reinforcement and predict structural behaviour of the deteriorated concrete structures. The assessment scheme consists of innovative use of advanced non-destructive evaluation (NDE) and structural health monitoring (SHM) methodologies such as acoustic emission (AE) technique and elastic wave tomography (EWT).

The student is expected to work as part of the team dedicated at developing measurement instrumentation, data processing and interpretation for corrosion damage identification and characterization. Analytical investigation by means of finite element modelling (FEM) would be necessary for examining fracture and failure of structural element under severe corrosion conditions. In addition to this, the student is expected to work on data clustering and statistical analysis for damage classification and risk probability analysis of structural failure.