By integrating a multi-scale simulation with the pseudo-cracking method, the remaining fatigue life of in-service reinforced concrete (RC) bridge decks can be estimated based upon their site-inspected crack patterns. But, it still takes time for computation. In order to achieve a quick deterioration-magnitude assessment of RC decks based upon their crack patterns, two evaluation methods are proposed. A predictive correlation between the remaining fatigue life and the cracks density (both cracks length and width) is presented as a fast judgment. For fair-detailed judgment, an artificial neural network (ANN) model is also introduced which is the basis of the machine learning. Both assessment methods are built commonly by thousands of artificial random crack patterns to cover all possible ranges since the variety of the real crack patterns on site is more or less limited. The built ANN performances are examined by k-fold cross-validation besides checking the prediction accuracy of real crack patterns of bridge RC decks. Finally, the hazard map of the deck’s bottom surface is introduced to indicate the location of higher risk cracking, which derives from the estimated weight of individual neuron in the built artificial neural network.

In visual inspection of bridges at sites, much attention is given to the density and width of cracks of concrete, but little attention is paid to crack orientation for the diagnosis of bridge performance. In this research, the effect of crack orientation on the remaining fatigue life of reinforced concrete (RC) bridge decks is investigated for crack patterns with a wide range of possible crack orientations. The data assimilation technology of multi-scale simulation and the pseudo-cracking method, which are widely validated for fatigue-lifetime simulation, are utilized in this study. The impact of the crack direction on fatigue life is found to be associated with the coupled flexure-shear mode of failure, and the mechanism to arrest shear cracking by preceding cracks is quantitatively estimated. This mechanism is similar to the stop-hole to prevent fatigue cracks in steel structures, and it enables us to enhance the fatigue life of RC decks. It is demonstrated that the crack orientations that approximate the longitudinal and transverse directions of RC decks are the ones that most extend remaining fatigue life. Finally, the higher risk cracking locations on the bottom surface of RC decks are discussed, presenting information of use to site inspectors.

Unreinforced load-bearing masonry (URM) buildings represent a significant portion of the non-engineered old buildings in many developing countries aiming to reduce the construction cost. The walls of those buildings are developed to resist gravity loads. Lateral loads induced by earthquakes or wind may cause severe their damage. In the current study, a numerical investigation is carried out for a seismic assessment of a typical four-story, load-bearing building in Giza, Egypt. The full 3D nonlinear dynamic analysis is carried out using the Applied Element Method (AEM), which proved to be efficient in such case where partial or total collapse is expected. The study includes two earthquake zones in Egypt called zone (3) and zone (5B), which are the actual studied building seismic zone and the highest seismic activity zone in Egypt, respectively. Carbon fiber reinforced polymers (CFRP) laminates with different thicknesses and different configurations are used in strengthening unreinforced masonry walls to study the efficiency of the proposed rehabilitation technique on a realistic structure.