ABSTRACT
Reinforced concrete structures form the backbone of our aging infrastructure. Most of these existing structures have experienced damage or deterioration. As part of ongoing condition assessment it is necessary to identify the extent, nature, cause and prognosis of deterioration using a range of tools and methods, including prediction models. Deterioration of reinforced concrete structures is often attributed to reinforcement corrosion initiated due to application of deicing salt during wintertime or chlorides from marine environment. Thus, corrosion detection, e.g. half-cell potential measurement, is of major importance for condition assessment. The information gained during corrosion detection can be used for updating the probabilistic service life prediction at time of inspection. Major impact on the accuracy of the updated service life prediction besides the probabilistic model itself is the reliability of the used inspection methods. Since first results on the reliability of half-cell potential measurements are published this data can be used to update corrosion probability taking into account not only the temporal aspect but also the spatial variability of reinforcement corrosion. This paper presents a case study for updating the corrosion probability with half-cell potential measurement data.
INTRODUCTION
The determination of the remaining service life of existing reinforced concrete structures is one of the major tasks after inspection. Generally, the service life refers to the period during which the structural safety satisfies the demands. The level of serviceability can also be included with this. However, deterioration processes do not develop homogeneously along a structure. The intensity of deterioration can vary from point to point and it can be expected that there is considerable variation of the degree of deterioration in different areas of the structure. Therefore, it’s rather difficult to define an instant in time that the structural safety is no longer sufficient. The spatial variability of deterioration processes have to be taken into account when determining the residual service life of the structure. The estimated current condition by inspection data and the prediction of future behavior should enable probability-based decision-making for future inspection schedules and if needed for interventions.
