Modelling and optimization of manufacturing calcium carbonate-based aluminum foam

Abstract

Recently, closed-cell aluminum foam gained increasing attention in many industrial applications due to its high stiffness compared with its very low density. Enhance the properties of aluminum foam by developing its manufacturing process is very important for both industrial and scientific purposes. In this work, an attempt has been made to enhance the essential characteristics of aluminum foam, i.e., compressive strength and porosity level by optimizing the manufacturing process parameters using statistical techniques. The aluminum foam samples were prepared under various conditions of calcium carbonate content, alumina content, foaming temperature and stirring time based on Screening experimental design. Analysis of variances was performed to evaluate the roles of each factor in influencing on the foam properties and identify their optimum values. In addition, mathematical models based on quadratic regression model were developed to predict the responses. The results revealed that all studied parameters have a significant effect on the properties of the produced foams, however, calcium carbonate content is found to be the most effective factor in the process. The optimization results showed the ability to produce high quality aluminum foams with 2.86 MPa compressive strength and 80.4% porosity level by using the optimized fabrication parameters and these results have a permissible error percentage compared with the experimental results.