Stochastic modelling of crackwidth in reinforced concrete beams subjected to fatigue loading

Markov chain modeling of evolution of strains in reinforced concrete flexural beams

“…It is also noted that after cracking, variation in depth of neutral axis with increase in loading is not significant even at higher stages of loading (the maximum variation in neutral axis depth with increase in loading are 3.27%, 7.11% and 6.57% of total depth of beam for KB1, KB2 and KB3, respectively). Hence, strain in the steel (ε s ) at any given load step is computed assuming a linear strain variation across the depth of beam as [13]:…”

“…Markov chain (MC) models are the simplest stochastic models that are extensively applied in engineering (7)(8)(9)(10)(11). MC models have been successfully used for modeling crackwidths in RC flexural members under monotonic and fatigue loading (12,13), for modeling load-deflection behavior of ferrocement elements (14), for condition assessment of RC bridge girders based on limited inspection data (15) and for condition assessment and remaining life assessment of RC flexural members subjected to corrosion of reinforcement (16). Prakash Desayi and Balaji Rao (12) proposed the use of nonhomogeneous Markov chains for modeling the cracking behavior of reinforced concrete beams subjected to monotonically increasing loads, wherein the elements of Transition Probability Matrix (TPM) are computed using Monte Carlo simulation.…”