Sequential approximate optimization-based robust design of SiC-Si 3N4 nanocomposite microstructures Article uri icon

abstract

  • A simulation-based robust design optimization methodology to predict the most suitable microstructures of SiC-Si3N4 nanocomposites for desired high-temperature toughness is presented. The focus is on finding robust nanocomposite microstructures with maximum toughness at two temperatures: 1500°C and 1600°C. Within this context a sequential approximate optimization algorithm under uncertainty is applied to six different test problems addressing different aspects of robust microstructure generation. During optimization, statistical uncertainties inherent to the computational microstructural generation are quantified and introduced in the optimization framework. The results show that the SiC volume fraction, the number of Si 3N4 grains, the grain size distribution of the Si 3N4 grains, and the grain size of the SiC particles have varied effects on the microstructure toughness at different temperatures. At 1500°C, the preferred microstructure is the one with higher Si 3N4 volume fraction, whereas at 1600°C, the preferred microstructure is the one with higher SiC volume fraction. © 2013 Copyright Taylor and Francis Group, LLC.

publication date

  • 2013-01-01