Concurrent fitness evaluations in searching for the optimal process conditions of Al matrix nanocomposites by linearly decreasing weight

In this article, the effect of nanoceramic reinforcements on the mechanical properties of aluminum matrix composites was critically reviewed. Reinforcement of an Al alloy with nanoceramic particulates is expected to improve its tensile strength. This article also reports the role of an integrated optimization approach using an artificial neural network and a modified particle swarm to solve a process parameter design problem in casting of this class of metal matrix nanocomposites. The artificial neural network is used to obtain the relationships between decision variables and the performance measures of interest, while the particle swarm is used to perform the optimization with multiple objectives.

[1]  M. Gupta,et al.  Enhancing physical and mechanical properties of Mg using nanosized Al2O3 particulates as reinforcement , 2005 .

[2]  Xiao‐nong Cheng,et al.  In situ (Al2O3 + Al3Zr)np/Al nanocomposites synthesized by magneto-chemical melt reaction , 2008 .

[3]  N. Varahram,et al.  Solidification of A356 Al alloy: Experimental study and modeling , 2011 .

[4]  A. Mazahery,et al.  Prediction of wear properties in A356 matrix composite reinforced with B 4C particulates , 2011 .

[5]  H. Yoshida,et al.  A particle swarm optimization for reactive power and voltage control considering voltage security assessment , 1999, 2001 IEEE Power Engineering Society Winter Meeting. Conference Proceedings (Cat. No.01CH37194).

[6]  Javad Olamaei,et al.  Optimal DG Allocation in Distribution Network , 2010 .

[7]  H. Ferkel,et al.  Magnesium strengthened by SiC nanoparticles , 2001 .

[8]  P. Davami,et al.  Silicon morphology modelling during solidification process of A356 Al alloy , 2012 .

[9]  Mohsen Ostad Shabani,et al.  Process conditions optimization in Al–Cu alloy matrix composites , 2012 .

[10]  M. Gupta,et al.  Enhancing compressive response of AZ31B using nano-Al2O3 and copper additions , 2010 .

[11]  M. P. Gómez-Carracedo,et al.  Linking chemical knowledge and genetic algorithms using two populations and focused multimodal search , 2007 .

[12]  M. Razavi,et al.  Effect of nanocrystalline TiC powder addition on the hardness and wear resistance of cast iron , 2007 .

[13]  Behrooz Karimi,et al.  Manufacturer-retailer supply chain coordination: A bi-level programming approach , 2012, Adv. Eng. Softw..

[14]  F. Pilo,et al.  A multiobjective evolutionary algorithm for the sizing and siting of distributed generation , 2005, IEEE Transactions on Power Systems.

[15]  A. Mazahery,et al.  Nano-sized silicon carbide reinforced commercial casting aluminum alloy matrix: Experimental and novel modeling evaluation , 2012 .

[16]  Atsushi Oshida,et al.  Fabrication process of metal matrix composite with nano-size SiC particle produced by vortex method , 1999 .

[17]  Mohsen Ostad Shabani,et al.  Influence of the hard coated B4C particulates on wear resistance of Al–Cu alloys , 2012 .

[18]  Jing J. Liang,et al.  Particle swarm optimization algorithms with novel learning strategies , 2004, 2004 IEEE International Conference on Systems, Man and Cybernetics (IEEE Cat. No.04CH37583).

[19]  W. Poole,et al.  Enhanced properties of Mg-based nano-composites reinforced with Al2O3 nano-particles , 2009 .

[20]  S. Sajjadi,et al.  Comparison of microstructure and mechanical properties of A356 aluminum alloy/Al2O3 composites fabricated by stir and compo-casting processes , 2012 .

[21]  B. Niroumand,et al.  Development of Al356/SiCp cast composites by injection of SiCp containing composite powders , 2011 .

[22]  J. Groza Densification of nanocrystalline powders. Field Activated Sintering of Tantalum nanopowders. , 2003 .

[23]  M. Babić,et al.  Structural, mechanical and tribological properties of A356 aluminium alloy reinforced with Al2O3, SiC and SiC + graphite particles , 2010 .

[24]  Mohsen Ostad The GA Optimization Performance in the Microstructure and Mechanical Properties of MMNCs , 2012 .

[25]  Ali Mazahery,et al.  Investigation on mechanical properties of nano-Al2O3-reinforced aluminum matrix composites , 2011 .

[26]  Parag C. Pendharkar,et al.  A threshold-varying artificial neural network approach for classification and its application to bankruptcy prediction problem , 2005, Comput. Oper. Res..

[27]  A. Gandomi,et al.  Imperialist competitive algorithm combined with chaos for global optimization , 2012 .

[28]  Mohsen Ostad Shabani,et al.  Application of Finite Element Model and Artificial Neural Network in Characterization of Al Matrix Nanocomposites Using Various Training Algorithms , 2012, Metallurgical and Materials Transactions A.

[29]  Farghalli A. Mohamed,et al.  Particulate reinforced metal matrix composites — a review , 1991, Journal of Materials Science.

[30]  M. Taha,et al.  Metal–matrix composites fabricated by pressure-assisted infiltration of loose ceramic powder , 1998 .

[31]  J. Kennedy,et al.  Population structure and particle swarm performance , 2002, Proceedings of the 2002 Congress on Evolutionary Computation. CEC'02 (Cat. No.02TH8600).

[32]  Mostafa Zandieh,et al.  A discrete colonial competitive algorithm for hybrid flowshop scheduling to minimize earliness and quadratic tardiness penalties , 2011, Expert Syst. Appl..

[33]  M. Kok,et al.  Production and mechanical properties of Al2O3 particle-reinforced 2024 aluminium alloy composites , 2005 .

[34]  Siamak Talatahari,et al.  Optimum design of skeletal structures using imperialist competitive algorithm , 2010 .

[35]  Chi-Yang Tsai,et al.  Particle swarm optimization with selective particle regeneration for data clustering , 2011, Expert Syst. Appl..

[36]  Zhifeng Xu,et al.  Effects of SiC volume fraction and aluminum particulate size on interfacial reactions in SiC nanoparticulate reinforced aluminum matrix composites , 2011 .

[37]  Mohsen Ostad Shabani,et al.  The ANN application in FEM modeling of mechanical properties of Al–Si alloy , 2011 .

[38]  Mohsen Ostad Shabani,et al.  A356 Reinforced with Nanoparticles: Numerical Analysis of Mechanical Properties , 2012 .

[39]  Feng Qian,et al.  Automatically extracting T-S fuzzy models using cooperative random learning particle swarm optimization , 2010, Appl. Soft Comput..