Artificial Intelligence and Reliability of Structures

Sudden damage is the main and most dangerous reason for structural failure. Therefore, structural health monitoring and reliability assessment of structures have been the center of attention during the past decades. Compared to other methods, it is fast, accurate, and economical. By starting the era of bigdata, more and more data is consistently being collected, which can improve the performance of such data-driven models.
This was the focus of my master’s thesis, and we published multiple research papers on this topic. Please refer to the publication tab for more detail. We deployed different neural networks to evaluate the risk of failure of structures and, combined with signal processing methods, to detect damages in structural frames.