Performance decay analysis of cementitious composite cladding structure under stochastic aging. (15th December 2022) - Yu, Yuguo; Zhang, Y.X.; Liu, Airong; Fu, Jiyang
Highlights: A computational architecture for stochastic aging fracture analysis is developed. Chemo-physical–mechanical aging and phase field fracture models are integrated. Novel machine learning is incorporated for substantial efficiency enhancement. The proposed method may advance future durability-based structural designs. Abstract: Façade cladding structure made of cementitious composite is prone to cracking due to its brittle characteristics, despite being a non-load-bearing member. Served as building exteriors, aging of cementitious composite may further raise the risk of fracture failure under accidental loads, causing both financial loss and safety hazards. To address this issue, a computational approach, fusing together a novel physics-based stochastic aging model and phase field fracture model, is developed to assess the mechanical performance decay of aging cladding structure. In this study, stochastic leaching under inherent material uncertainty is taken as the primary aging concern, and the analysis is assisted with extended support vector regression for substantial efficiency enhancements. The proposed method is carefully validated against two designed benchmark problems and a real-life application. It is demonstrated to be able to predict the time-dependent reliability of cementitious composite cladding structures precisely and efficiently under stochastic leaching-induced aging.