Reliable bridge condition assessment is considered the first step, and perhaps one of the most essential elements, of an efficient bridge management system. This consideration stems from the fact that available assessment inputs are constantly interpreted for maintenance decisions and budget allocation to the deserving, intervention-needy bridges within a region's inventory. Thus, carrying out effective bridge assessment is vital to ensure the safety and sustainability of the bridge infrastructure. In practice, the evaluation of concrete bridges is mostly conducted on the basis of visual inspection, associated with considerable uncertainty and subjectivity inherent in human judgments. Additionally, conclusions are often drawn in the absence of a thorough review of critical factors. Therefore, to circumvent the existing limitations, this study proposes a fuzzy hierarchical evidential reasoning approach for detailed condition assessment of concrete bridges under uncertainty. The essence of this framework addresses the treatment and aggregation of detected bridge defect measurements systematically to establish an enhanced platform for reliable bridge assessment. The proposed approach is facilitated by a hierarchy structure that models the several levels of a concrete bridge under assessment: bridge components, structural elements, and, most particularly, the measured defects. A belief structure is employed to grasp probabilistic uncertainty (ignorance) in the assessment, while fuzzy uncertainty (subjectivity) is processed through a set of collectively exhaustive fuzzy linguistic variables. Eventually, the Dempster-Shafer theory is used within the suggested framework for accumulating supporting pieces of evidence toward a comprehensive and educated overall condition assessment.
ASJC Scopus subject areas
- Civil and Structural Engineering
- Mechanical Engineering