Estimation of Permeability of Green Sand Mould by Performing Sensitivity Analysis on Neural Networks Model

Abstract

Abstract Permeability is the ability of a material to transmit fluid/gases. It is an important material property and it depends on mouldparameters such as grain fineness number, clay, moisture, mulling time, and hardness. Modeling the relationships among thesevariable and interactions by mathematical models is complex. Hence a biologically inspired artificial neural-network technique witha back-propagation-learning algorithm was developed to estimate the permeability of green sand. The developed model was used toperform a sensitivity analysis to estimate permeability. The individual as well as the combined influence of mould parameters onpermeability were simulated. The model was able to describe the complex relationships in the system. The optimum processwindow for maximum permeability was obtained as 8.75-10.5% clay and 3.9-9.5% moisture. The developed model is very useful inunderstanding various interactions between inputs and their effects on permeability.Key words: Green sand mould, Permeability, Neural networks, Sensitivity analysis