Engineered cementitious composite (ECC) is widely employed in engineering due to its high toughness and ductility. The Interfacial Transition Zone (ITZ) between the fibers and the matrix plays a vital role in influencing the strength and durability of ECC. This study introduces a numerical method to simulate fiber pull-out behaviors, specifically the fiber debonding and slipping. A birth-death method is proposed to account for the mechanical transition from fiber debonding stage to slipping stage. The contributions of various phases in the ITZ are explicitly considered. Furthermore, nanoindentation tests and Backscattered Electron (BSE) imaging were conducted to determine the microstructures of ITZ and local mechanical properties of each phase within the ITZ. A series of fiber pullout experiments with polyvinyl alcohol (PVA) fibers were conducted to calibrate and validate the model. Subsequently, the validated model was employed to explore the influence of w/c ratios, fiber orientations and bonding properties on the interfacial behavior. The microstructure-informed model proposed herein effectively predicts fiber pull-out behavior, facilitating a thorough exploration of fracture mechanisms throughout the pull-out process, and serves as the basis for multiscale modeling of ECC.

This review provides a comprehensive analysis of the fatigue behaviour of cementitious materials, focusing on the characterisation, modelling, and mechanisms underlying their fatigue properties. It begins with a detailed exploration of how material composition and loading conditions influence fatigue performance, along with the underlying mechanisms that govern fatigue fracture processes. The review also synthesises current advanced experimental methods for characterising fatigue damage evolution, highlighting significant achievements and methodological innovations. It also examines theoretical approaches, summarising prominent models and emerging theories that deepen the understanding of fatigue behaviour in cementitious materials. Meanwhile, the paper reviews computational techniques based on fracture mechanics, damage mechanics, statistical analysis, machine learning algorithms and multiscale modelling, assessing their potential to improve the accuracy of fatigue predictions. Lastly, the review identifies crucial research gaps and outlines future directions, particularly in understanding fatigue-related coupling mechanisms to enhance the fatigue resistance and durability of cementitious materials.