Predicting dynamic failure in armor ceramic using efficient initial flaw statistics

Abstract eng:
The failure process in armor ceramic under an impact event is fundamentally linked to the type and distribution of subscale defect population in the material. For many armor ceramics the controlling defects that causes significant microcracking are crack-like defects or flaws. The current modeling framework uses micromechanics damage models with an input statistical samplings from the parent flaw distribution of the material to represent the subscale processes (e.g. microcracking) and a conventional continuum mechanics code is used for the macro-scale problem. The initial input flaw statistics is divided into a smaller number of groups or bins and each bin has its characteristic flaw size and fraction of flaws associated with it. An efficient numerical method has been used to obtain the characteristic flaw size and flaw fraction associated with each group or bin in order to increase the computational efficiency while retaining the desired level of accuracy.

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