Modeling of frying predicts key quality parameters.

Fundamental-based modeling of food processes that involve rapid evaporation, such as frying and baking, remains a major challenge. Modeling software developed in other engineering disciplines cannot readily accommodate the physics involved in these processes.

Using available software to solve processing problems that may arise would be a tremendous benefit to the design of food products and processes. Such software would make the power of simulation available for design.

To achieve this without sacrificing the fundamental physics behind the process, significant reformulations are needed that require mathematical as well as physical insight into a process. Scientists at Cornell University have demonstrated this by modeling the industrially important process of deep frying.

A multiphase porous media model involving heat and mass transfer with strong evaporation has been developed and solved numerically. Researchers studied two different formulations of evaporation: equilibrium and non-equilibrium. At temperatures below boiling, evaporation dominates. At boiling temperature, the limiting mechanism is the rate of heat transfer to the evaporation zone. This combined evaporation and boiling makes it possible to calculate more precisely high evaporation rates than was possible with previous models.

Initially, pressure and evaporation rates increase sharply but become constant once boiling starts. Incoming heat limits the phase changes. The temperature and moisture profiles clearly show crust and core regions separated by a sharp interface. There is negligible oil pickup during heating due to the high pressure inside the food that impedes oil inflow. During cooling, there is oil inflow due to the pressure drop created from the condensation of vapor.

The model is able to predict accurately important industrial food quality parameters, such as crust thickness and oil pickup. Since no physics have been sacrificed, and researchers are able to implement it in commercial software, scientists in process design and optimization could use this simulation more extensively and precisely.

Further information. Ashim Datta, Department of Biological and Environmental Engineering, Cornell University, 208 Riley-Robb Hall, Ithaca, NY 14853; phone: [phone]; fax: [phone]; email: [e-mail].