In this paper, a statistical pattern recognition method based on time series analysis is implemented in flexible risers. This method uses a combination of Auto-Regressive (AR) and Auto-Regressive with eXogenous inputs (ARX) prediction models. The flexible riser model used in this paper is experimentally validated employing a proposed numerical scheme for dynamic response of flexible risers. A modal-based damage detection approach is also implemented in the flexible riser model and its results are compared with the ones obtained from time series analysis. The numerical results show that the time series analysis presented in this paper is able to detect and locate structural deterioration related to fatigue damage in flexible risers. Finally, considering the case study results presented in this paper, the presented AR-ARX prediction model works better than the modal-based damage detection method.
The ultimate flexural strength of composite steel girders with compact sections is examined through experimental investigation and elasto-plastic finite displacement analyses to develop a reduction factor of the ultimate flexural strength. A two-point loading test of a composite girder was carried out to verify the numerical modeling by comparing the experimental and numerical results. Then, a parametric study was performed using finite element analyses to investigate the effect of concrete crushing on the flexural strength of composite girders constructed using SM570 grade steel. Observations made by comparison of the ultimate flexural strength obtained from the experimental and numerical results with that according to the AASHTO and Eurocode show that the existing reduction factor equations are conservative and can be relaxed when the strength is controlled by crushing of concrete slab. A new reduction factor for the ultimate flexural strength for composite I-girders under positive bending is proposed.