Volume 4, Issue 1, June 2020, Pages: 7-13
Received: Dec. 30, 2019;
Accepted: Jan. 9, 2020;
Published: Jan. 21, 2020
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Jimoh Olugbenga Hamed, African Regional Centre for Space Science and Technology Education in English, Obafemi Awolowo University Campus, Ile-Ife, Nigeria
Ganiyu Ishola Agbaje, African Regional Centre for Space Science and Technology Education in English, Obafemi Awolowo University Campus, Ile-Ife, Nigeria
Abdullahi Ikani Bakwo, Centre for Space Transport and Propulsion, Lagos State University Campus, Epe, Lagos, Nigeria
Bisola Abigail Olaniyi, Engineering Space System, National Space Research and Development Agency, Abuja, Nigeria
Ismail Olusegun Lawal, Advanced Aerospace Engines Laboratory, Oka-Akoko, Ondo, Nigeria
Adekunle Benjamin Falade, African Regional Centre for Space Science and Technology Education in English, Obafemi Awolowo University Campus, Ile-Ife, Nigeria
There is a strong agitation from rocket designer for a highly reinforced metal matrix composites for rocket chamber to curtail the effect of high temperature and pressure from gaseous product of combustion process. This study has been designed to evaluate the surface roughness of an aluminum reinforced metal matrix composites produced by stir casting techniques at constant cutting speed of 1000 rpm, three (3) different feed rates at various aluminum weight ratio. Response surface methodology was adopted to formulate a surface roughness model in terms of metal matrix constituents such as aluminum, barite and zircon under three (3) different feed rate. The model adequacy was verified using analysis of variance. Also, the approach was used to optimize the effect of reinforced materials on surface roughness of the matrix composites. The increase in weight ratio of aluminum matrix reduces the surface roughness and vice versa. However, increase in barite, zircon weight ratios and feed rate increase the surface roughness. The optimum matrix chemical composition ratios of 0.9310, 0.0296, and 0.0394 for aluminum, barite, and zircon respectively with optimal desirability index of 0.903 shows the validity of the design. The F-values obtained at 95% confidence interval revealed that the selected model adequately represent the data for the matrix composites. Therefore, the study confirm the effectiveness of Response Surface Methodology as a tool in predicting surface roughness and provide materials with enhanced mechanical properties.
Jimoh Olugbenga Hamed,
Ganiyu Ishola Agbaje,
Abdullahi Ikani Bakwo,
Bisola Abigail Olaniyi,
Ismail Olusegun Lawal,
Adekunle Benjamin Falade,
Estimation of Surface Roughness of Aluminum Reinforced Metal Matrix Composites, Applied Engineering.
Vol. 4, No. 1,
2020, pp. 7-13.
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