Crack-based damage assessment of in-service reinforced concrete bridge members

Reinforced concrete bridge infrastructure is typically evaluated based on visually observed cracking/damage. However, traditional inspection procedures typically provide little-to-no insight into the remaining capacity of the inspected member. Although more rigorous methods have been proposed in the literature that offer quantitative insight into a structure’s health (with various levels of success), no procedure has been widely adopted. Furthermore, many of these proposed procedures have not been validated by experimental data. Experimental visual crack data were collected into a database to provide researchers and practitioners a means of developing and evaluating crack-based shear strength assessment procedures. The database has an emphasis on members which are similar in detail or scale to typical bridge elements. The database was subsequently used to evaluate a proposed mechanics-based damage assessment procedure based on an inverse solution of the modified compression field theory. In addition to visually observed crack characteristics (e.g., crack width and inclination), the proposed procedure relies upon basic material properties and design details. Average load proportions are estimated as a part of the procedure, therefore actual loading conditions (e.g., M/V∙d ratio for a beam) need not be known to calculate an estimate of an element’s residual capacity. Results from 420 analyses on beams from three experimental programs carried-out with the procedure show the potential of a mechanics-based procedure for the crack-based shear strength assessment of reinforced concrete bridge members. The average predicted-to-experimental ratio for normalized shear strength (i.e., capacity-in-use) was reasonable for two of the experimental series (0.98 – 1.17); however, results from the third group of beams trended much more conservatively (average predicted-to-experiment ratio of 1.43). Overall, the procedure is relatively simple and general in its application and shows promise as an evaluation tool.