Advances in Applied Science Research Open Access

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Abstract

Comparison of porosity and density for (A384.1)1-x [(Reinforcement)p]x MMC system using Adaptive Neuro-Fuzzy Inference system

Nrip Jit, Anand K. Tyagi, Nirmal Singh, Amarpal Singh

In the present work, the reinforced MMC’s of Al/Al alloy-SiC system, with nominal composition (A384.1)1-x[(SiC)p]x were fabricated by using A384.1 Al Alloy as matrix and SiC with 0.220, 0.106 and 0.053 μm particle sizes as reinforcement in varying amounts. It is clear that with the change in particle size and %age of doping of reinforcement in Al Alloy matrix, the change in values of density and Porosity is registered. The overall maximum values of density is registered as 2490 gm/cm3 when the value of x= 0.08 and the particle size is 0.106 as compare to all other values of the MMCs for different values of ‘x’. Accordingly, the overall maximum values of porosity is registered as 3.25 when the value of x= 0.10 and the particle size is 0.0.53 as compare to all other values of the MMCs for different values of ‘x’. So, the density and porosity of the reinforced MMCs is more as compare to unreinforced Al alloys. Then fuzzy model of the system is developed using adaptive neuro-fuzzy inference system (ANFIS), for carrying out for density and porosity of the MMCs. Performance is evaluated by comparing experimental data with fuzzy model and good correlation is achieved between them.