The failure prediction of composite materials is crucial for advancing their use in aerospace, automotive, and structural applications. Multiscale modeling and experimental methods provide comprehensive insights into their complex failure mechanisms, bridging microscopic and macroscopic behaviors.  

This collection emphasizes the synergy between multiscale modeling and experimental techniques in advancing the failure prediction of composite materials. It highlights how multiscale modeling captures the hierarchical nature of composites, linking microscale phenomena like fiber-matrix interactions and void effects to macroscale structural behavior. 

High-fidelity models, ranging from micromechanical finite element simulations to ply-level and continuum approaches, are employed to predict crack initiation, propagation, and ultimate failure under complex loading conditions. Experimental techniques complement these models by providing critical data for validation and parameterization. Methods like in-situ x-ray micro-computed tomography (µCT) reveal internal damage evolution, while digital image correlation (DIC) maps full-field strain distributions. High-temperature and high-pressure tests replicate service conditions, enabling the evaluation of environmental effects such as moisture and thermal cycling on material performance. 

Together, multiscale modeling and experimental validation ensure accurate design and optimization of composite structures, addressing challenges related to lightweight and structural reliability. The collection underscores the importance of bridging scales and environments, paving the way for advancements in composite performance and durability in aerospace, automotive, and other high-performance applications.