A Multiscale Approach Towards Prediction of Stress-Cracking in Corn Kernels
Food grains such as corn often develop cracks during various stages of processing. Cracked grains are generally considered of inferior quality and are more prone to insect and microbial damage. The phenomenon causes millions of dollars worth of losses to food grains in the US. In the proposed research we will use hybrid mixture theory of porous media to develop an engineering model for predicting crack initiation in corn kernels. The model will aid improved design and optimization of unit operations such as heating, drying and sorption. The model predictions will be validated by conducting experiments. The model will be made general so that it could also be applied to other types of food materials. The objectives of the study are to develop a mathematical model for predicting stress-crack initiation, solve the model using finite-element method
and validate the predictions by conducting experiments.