Refined microstructure of compo cast nanocomposites: the performance of combined neuro-computing, fuzzy logic and particle swarm techniques

Shabani, M. O ; Sharif University of Technology

333 Viewed
  1. Type of Document: Article
  2. DOI: 10.1007/s00521-014-1724-8
  3. Abstract:
  4. Aluminum metal matrix composites (MMCs) reinforced with nanoceramics are ideal materials for the manufacture of lightweight automotive and other commercial parts. Adaptive neuro-fuzzy inference system combined with particle swarm optimization method is implemented in this research study in order to optimize the parameters in processing of aluminum MMCs. In order to solve the problems associated with poor wettability, agglomeration and gravity segregation of nanoparticles in the melt, a mixture of alumina and aluminum particles was used as the reinforcement instead of raw nanoalumina. Microstructural characterization shows dendritic microstructure for the sand cast and non-dendritic microstructure for the compo cast samples. The fine equiaxed structure of compo cast nanocomposite arises from copious nucleation triggered by a pressure
  5. Keywords:
  6. Optimum conditions ; PSO ; Nano ; Neurocomputing ; Particle swarm ; Refined microstructure
  7. Source: Neural Computing and Applications ; 2014 ; ISSN: 09410643
  8. URL: http://link.springer.com/article/10.1007%2Fs00521-014-1724-8