Probabilistic models for characteristic bond stresses of steel-concrete in steel reinforced concrete structures

Abstract

Steel-reinforced concrete (SRC) composite structures are widely employed in modern buildings because of their elevated load-carrying capacity, robust stability and remarkable resilience to corrosion and fire. To safely utilize SRC composite structures, reliable bonding between steel and concrete is crucial in designing and constructing SRC members and connections. With this objective in mind, the current study aims to establish accurate models for estimating the characteristic bond stresses (i.e., initial, peak and residual bond stresses) and determining the necessary anchorage length between the profiled steel and the adjacent concrete. To realize these goals, a total of 660 push-out tests and their results were compiled from existing literature for model development. Probabilistic bond stress models were created by integrating existing models with key variables related to the mechanical properties and geometrical characteristics of concrete, steel section and stirrup. Bayesian theory and the Markov Chain Monte Carlo (MCMC) method were utilized to refine and select the most precise model. The evaluation results demonstrate that the probabilistic models provide more accurate predictions for initial, peak and residual bond stresses compared to existing models. With the assistance of this reliable analytical technique, the established model for peak bond strength was finally applied to determine the minimum required anchorage length for steel within concrete.