Optimization of Ash and Energy Yields from the Combustion of Flamboyant Pod, Groundnut Shell and Additive (Kaolin) Composite
Ebenezer O. Dada
Department of Chemical Engineering, Ladoke Akintola University of Technology, P.M.B. 4000, Ogbomoso, Nigeria and Bioenvironmental, Water and Engineering Research Group, (BWERG), Ladoke Akintola University of Technology, P.M.B. 4000, Ogbomoso, Nigeria.
Blessing A. Adebayo
Department of Chemical Engineering, Ladoke Akintola University of Technology, P.M.B. 4000, Ogbomoso, Nigeria and Bioenvironmental, Water and Engineering Research Group, (BWERG), Ladoke Akintola University of Technology, P.M.B. 4000, Ogbomoso, Nigeria.
Abass O. Alade *
Department of Chemical Engineering, Ladoke Akintola University of Technology, P.M.B. 4000, Ogbomoso, Nigeria, Bioenvironmental, Water and Engineering Research Group, (BWERG), Ladoke Akintola University of Technology, P.M.B. 4000, Ogbomoso, Nigeria and Science and Engineering Research Group, (SEARG), Ladoke Akintola University of Technology, P.M.B. 4000, Ogbomoso, Nigeria.
Kamoru O. Oladosu
Science and Engineering Research Group, (SEARG), Ladoke Akintola University of Technology, P.M.B. 4000, Ogbomoso, Nigeria and Department of Mechanical Engineering, Kwara State University, Malete, Nigeria.
*Author to whom correspondence should be addressed.
Abstract
Aim: I-optimal design via the Combined Methodology of the design expert software was used to optimize the ash yield from the combustion of a biocomposite mixture of Flamboyant Pod and Groundnut Shell with additive (Kaolin) in a grate furnace.
Study Design: Analysis of Variance, and Artificial Neural Network were used to predict the ash yield from the data generated from the design process, while the coefficient of determination between variables was determined using the Principal Coefficient Analysis. The resulting ash yield was characterized for ash composition using a Scanning Electron microscope.
Place and Duration of Study: Biochemical Engineering Laboratory, Department of Chemical Engineering, Ladoke Akintola University of Technology, Ogbomoso. September-December 2020.
Methodology: Proximate analysis was used to determine Moisture Content, Fixed Carbon Content, and Volatile Matter values used to determine the Higher Heating Value of the composite.
Results: The sample with 53wt. % Flamboyant Pod, 37wt. % Groundnut Shell, and 10wt. % kaolin mixture at 825 °C gave the lowest ash yield of 5wt. %. The correlation coefficient (R2) of the model equation developed for ash yield (0.9992) validated the model due to its closeness to 1. The deviation between the experiment and prediction for ash yield indicated 3wt. %. The Higher Heating Value calculated shows that the lowest ash yield composition has a higher heating value of 15.14 and the highest yield mixture has a lower Higher Heating Value of 12.26.
Conclusion: The reduction of ash yield from 56 to 5wt. % (as observed in previous studies shows a greater improvement in ash reduction during the combustion process.
Keywords: Ash, biomass, solid fuel, renewable energy