The increasing complexity associated with the maintenance of bridges with post-tensioning tendons, along with growing public awareness to ensure higher levels of safety in bridges, has put additional pressure on the designers and the owners to find innovative solutions to ensure safe as well as economically viable solutions. Risk-based inspection and maintenance helps in finding such solutions and, thus, it is gaining more importance in the field of infrastructure management. Within the framework of current risk-based inspection methodologies, it is normally assumed that the method by which the inspection is performed is known beforehand. However, the selection of the inspection method by itself should be given importance and viewed as the first key step for any inspection. The lack of quantitative data in the initiation step makes this selection uncertain and the decision making rather subjective. Despite recent release of comprehensive reports and other publications on condition assessment of bridges with post-tensioning systems, a quantitative approach and a decision-making framework for the selection of the inspection method and associated protocol are still missing, and the inspection strategy and methods are determined purely by the experience of the inspector or the owner. In this paper, a simple and structured risk-based selection methodology is presented that can bridge the existing knowledge gap. The proposed methodology uses a statistical approach to quantify the likelihood of the inspection error utilizing a variety of applicable NDE (Non-destructive Evaluation) methods. To give the methodology both accuracy and practicality, the specifications for the national bridge inventory (SNBI) condition rating was incorporated in this methodology and the accuracy of the inspection methods are measured against determining the correct SNBI condition. Application and effectiveness of the proposed methodology are demonstrated using a case study inspection conducted earlier by the authors. The results, in this case, converged to the selection of one of the NDE methods, which consequently was accepted by the bridge stakeholders.
Read full abstract