Microstructure based material sensitive design by Dr. Yan Li
日期：2016 年 11 月 18 日 ( 星期五)
Time：11:00 am – 12:00 pm
Fracture toughness of a composite material is not a deterministic property. This is primarily due to the stochastic nature of its microstructure as well as the activation of different fracture mechanisms during the crack-microstructure interactions. Prediction of material fracture toughness as well as its scatter is one of the biggest challenges in material sensitive design. The crack interactions with microstructure can result in different failure mechanisms which ultimately determine the variation of fracture toughness. Weibull distribution has been widely used to determine the probability of material fracture. However, its role has been primarily confined to fitting fracture toughness data rather than providing predictive insight of material fracture toughness and its magnitude of scatter. Besides, the Weibull parameters which are obtained through curve fitting carry little physical significance. A multiscale framework is developed to predict material fracture toughness of composite materials in a statistical sense. The Weibull distribution parameters are correlated with the statistical measures of microstructure characteristics and the statistical characterization of the competition between crack deflection and crack penetration at matrix/reinforcement interfaces. The established correlations are useful for material sensitive design.
Dr. Yan Li joined the Department of Mechanical and Aerospace Engineering at California State University, Long Beach as an Assistant Professor in Fall 2014. She received her PhD degree in Mechanical Engineering from Georgia Institute of Technology in 2014. Dr. Li's primary research interests are in the area of mechanics of advanced materials, involving multiscale/multiphysics modeling, integrated computational/experimental approaches for next generation material design, and application of material science and solid mechanics in advanced manufacturing. Dr. Li has worked on research projects supported by NSF CCMD (Center for Computational Materials Design) and collaborated with industry partners including Boeing, Gulfstream and GE.