Description
The growth in the number of structural assessment and evaluation projects worldwide is attributed to the gradual aging of existing structures and the necessity to prolong the lifespan of deteriorating structures. Reinforced concrete (RC) structures are susceptible to deterioration as a result of concrete cracking and steel corrosion. Evaluations of current RC structures are undertaken to ascertain adherence to building codes, the necessity for enhancements, or to rectify structural inadequacies. Reliability techniques are utilized to quantitatively assess the structural integrity of existing RC structures, taking into account the inherent uncertainties related to the applied loads and the resistance of the structure. The main difficulty in evaluating the safety of current RC structures, namely in determining the reliability index, is to formulate accurate resistance models. This problem is particularly pronounced when observable indications of structural deterioration, such as cracking and steel corrosion, are evident.
The primary aim of this research is to develop, validate, and implement a new computational framework for evaluating the structural integrity of RC elements. This framework utilizes digital image processing (DIP) techniques in conjunction with random finite element (RFE) simulation. In this approach, actual images of the structure under investigation are employed to construct finite element (FE) models, while random fields are utilized to represent the spatial variability in material properties. The recommended framework is anticipated to enhance the accuracy of the reliability estimate by mitigating the uncertainty associated with the concrete crack pattern and minimizing the uncertainty related to the corrosion process in steel, if applicable.
