Simulation and verification of ohmic heating in static heater using MRI temperature mapping

Abstract

Mathematical modeling of ohmic heating of liquid–particulate mixtures allows insight into the heating behavior, but model verification that uses only a selected number of points in an ohmic heating system is inadequate because of the unknown temperature distribution within the heated food materials, including the locations of hot and cold spots. In this study, ohmic heating of liquid–particulate mixtures was simulated using the finite-element analysis with the commercial software FEMLAB, and the model predictions were verified against temperature maps obtained using magnetic resonance imaging (MRI). A factor ignored by the previous modeling works, the electricity-to-heat conversion efficiency, was considered in the model, resulting in an improved model performance. The electrical conductivity and its temperature dependence for all the materials used in the simulation were determined under consistent electric field strength as the simulated ohmic heating processes. Other factors/parameters affecting model prediction, such as the boundary conditions and heat transfer coefficients, were also determined in situ for an accurate parametric input. The model predictions yielded good agreement with the MRI temperature maps. Results showed that the electrical conductivity of the materials is the most critical factor causing heating rate variations between the particulate phase and the liquid phase. The heating rate variations could be overcome by adjusting the electrical conductivity of the food materials before ohmic heating. This modeling procedure can be used for designing and controlling ohmic heating processes to ensure thermal sterilization and safety of ohmically heated food products.