|About this Abstract
||2017 TMS Annual Meeting & Exhibition
||Fatigue in Materials: Fundamentals, Multiscale Modeling and Prevention
||Statistical Prediction of Crack Initiating Rate from Pre-fractured Constituent Particles in High Strength Al Alloys
||Pei Cai, Yan Jin, Lin Yang, Tongguang Zhai
|On-Site Speaker (Planned)
Three types of fatigue crack initiation behaviors from pre-fractured constituent particles were observed in AA2024-T3 alloys, namely, non-propagating, arrested and propagating cracks. Statistical measurements of these particles revealed that their thickness beneath sample surface was a key parameter controlling the initiation behaviors in the alloys. A new model was established to quantify the growth behaviors of micro-cracks in these particles by considering both the driving force along irregular-shaped crack fronts and the local resistance due to particle/matrix interfaces and grain boundaries. The simulated growth behaviors demonstrated there were indeed three types of cracks evolved from the pre-fractured particles in the surface of the alloys. Statistical prediction of crack initiation types could also be quantified with given texture components. In AA2024-T3 alloys where the rolling-type of texture was dominant, the simulated results confirmed the strong dependence of crack initiation type on particle thickness, as observed in the experiments.
||Planned: Stand-alone book in which only your symposium’s papers would appear (indicate title in comments section below)