On the application of genetic algorithm for predicting the strength of CNT/ABS filaments using multi-scale modeling

This article investigates the strength of nanocomposite filaments produced through extrusion. It involves incorporating carbon nanotubes (CNTs) into Acrylonitrile Butadiene Styrene (ABS) to produce printable nanocomposite filaments for filament fused fabrication technique and measuring their strengths. A multi-scale modeling procedure is developed to predict the strength of nanocomposite filaments through computational modeling. This model analyzes three sequential scales of micro, meso and macro. Determining effective parameter(s) of each scale, a proper representative volume element (RVE) is defied for each scale, seperately. CNT-polymer interaction, CNT length and CNT orientation are taken into account at the scale of micro; while CNT agglomeration is captured at the scale of meso. The strength of nanocomposite filament is finally estimated at the uppermost scale of macro. CNT length, orientation and agglomeration are all treated as random paramters, thus stochastic modeling is conducted in connection with genetic algorithm (GA) to reduce the required runtime of analysis. The outputs of this modeling procedure align closely with experimental observations.