Application of fuzzy concepts to the visual assessment of deteriorating reinforced concrete structures

Data obtained using visual inspection are qualitative and subjective in nature. Reported methodology utilizes fuzzy sets for modeling qualitative data. Characteristic distress manifestations corresponding to various deterioration mechanisms in RC structures and associated repair priorities (conditions) are first classified. To deal with the subjective nature of associated data, independent responses on applicable repair priorities for different distress manifestations are obtained from experts through questionnaire survey. Data obtained from questionnaire responses are subsequently used for the development of corresponding fuzzy membership functions (MFs). Visual-inspection data for various characteristic distress manifestations (on the basis of deterioration mechanism) are recorded individually for every deteriorating element of the structure as per the prepared guidelines. Recorded data are used for the selection of corresponding MFs. Selected MFs are combined according to the proposed fuzzy rule using vertex method to obtain the element MFs individually for all specific deteriorations and for collective effect of all the deteriorations. Defuzzification using area-centroid method provides condition indices. These indices provide quantified measure of condition and repair needs of the elements. Element indices are further aggregated to obtain the indices for the structure as a whole. To explain the developed methodology, a brief case study on the assessment of a section of an industrial building is illustrated.