From the millions of miles of aging pipelines to the intricate workings of a wind turbine, metals are ubiquitous. Of paramount importance in both the design and upkeep of these materials is a predictive capability for their failure. An improved understanding of ductile failure will offer increases in efficiency, reliability, and applicability of metals and their alloys.
The use of computational testing is quickly becoming a viable alternative to experimental testing procedures. These computational testing methods, besides being much cheaper, offer complete control of testing parameters and greater insight into the inner workings of the material.
This work investigates one such computational model for the ductile failure of metals. The model is based on a multi-scale approach, which means that the microstructure of the material is modeled and subsequently related to larger scales of interest. The results illustrate the importance of specific microstructural phenomena and confirm that their incorporation into the model will greatly enhance its predictive capabilities.
This student video was one of the 2013 IGERT Video and Poster Competitions winning submissions.
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