Stochastic Modeling Of Fatigue Crack Propagation In Concrete Beams Using Markov Chain Simulation

Abstract

Fatigue crack growth is a critical issue in the field of structural engineering, including concrete structures. Concrete is a heterogeneous quasi-brittle material and its behaviour is affected by various factors such as loading conditions, material properties, and environmental factors. Fatigue crack propagation in concrete is regarded as a random phenomenon because it depends on various factors that behave in a variable or unpredictable manner. These factors include the characteristics of the concrete, such as its stiffness and strength, dimensions, morphology, crack path, and loading conditions. It is essential to accurately model and predict the uncertain process of fatigue crack growth for designing and maintaining structures such as bridges, nuclear power plants, and offshore structures. In order to address this issue, the fatigue crack growth in concrete is modeled using Markov Chain simulation. The transition number of cycles from stable to unstable crack growth region is estimated by optimizing parameters of Paris' and Forman's laws. Also, the crack length prediction model is developed based on the principle of Markov chains.