Concurrent n-scale modeling for non-orthogonal woven composite

Concurrent analysis of composite materials can provide the interaction among scales for better design, analysis, and performance prediction. A data-driven concurrent n-scale modeling approach ( $$\text {FExSCA}^\text {n-1}$$ ) is adopted in this paper woven composites utilizing a mechanistic reduced order model (ROM) called Self-consistent Clustering Analysis (SCA). We demonstrated multiscale theory with {FExSCA}^2$$ to study 3-scale carbon fiber reinforced polymer (CFRP) laminate structure. significantly expensive 3D nested representative volume element (RVE) computation unidirectional (UD) structures by developing material database. The procedure established integrating database into CFRP structural numerical model, formulating framework. This framework provides an accurate prediction (e.g., nonlinear behavior under tensile load), as well UD physics field evolution. results are validated against physical tests that link basic microstructures. proposed methodology comprehensive predictive applicable general aiming reduce laborious experiments needed.