Numerical and monitoring based Markov Chain approaches for the fatigue life prediction of concrete structures

Highlight
• A semi Markov Chain approach can be used for the characterization of the transition probability matrices of fatigue and redistribution processes in concrete structures. Semi-Markov Chain prediction can be improved by periodical including monitoring information in the form of Bayesian updating procedures.

The design of special concrete structures, such as foundations for offshore wind turbines, has to be carried out against complex requirements and under challenging environmental conditions. Among these are for example dynamic and cyclic loadings caused by wind and sea waves. Concrete fatigue processes are dominant degradation processes (a) that determine the technical lifetime of such foundations, and (b) that are difficult to determine in occurrence, severity and with regard to the redistribution characteristics in the cross section or structure using classical inspection or monitoring programs. Semi-Markov Chain approaches, which are based on process sojourn time considerations, combined with smart monitoring sensor systems and advanced nonlinear Finite Element simulation methods, present very promising approaches for the realistic description of concrete fatigue processes and their redistribution characteristics and in consequence for the prediction of the remaining lifetime. The objectives of the current work are (a) to present a Semi-Markov Chain approach that is based on smart monitoring information and on advanced nonlinear Finite Element simulations for the realistic assessment and the prediction of concrete fatigue processes, and (b) to demonstrate the Semi-Markov Chain approach on an offshore wind energy tower concrete foundation in Cuxhaven. This work presents a further step toward developing a software tool that can be used to perform reliability assessments of aging concrete structures and to update their reliability with inspection and monitoring data.