A tool for predicting heating uniformity in industrial radio frequency processing - Ferrari-John, R.S.; Katrib, Juliano; Palade, Paula; Batchelor, A.R.; Dodds, Chris; Kingman, S.W. (Springer Verlag, 2016)
Radio frequency energy is utilised for heating in a wide range of applications, particularly in the food industry. A major challenge of RF processing is non-uniform heating in loads of variable and angular geometry, leading to reduced quality and product damage. In the study, the specific effects of geometry on the heating profiles of a range of geometrically variable loads in an industrial scale RF system are analysed, and the understanding used to derive a general tool to predict heating uniformity. Potato was selected as a test material for experimental work; dielectric properties were measured using a 44mm coaxial probe. Analysis of simulated and experimental surface temperature profiles and simulated power uniformity indices indicates that the presence of vertices and edges on angular particles, and their proximity to faces perpendicular to the RF electrodes increases localised heating; faces parallel to the electrodes heated less than those faces perpendicular to them. Comparison of the same geometrical shape in different orientations indicates that overall power absorption uniformity can be better even when localised heating of edges is greater. It is suggested, for the first time, that the rotation of angular shapes within a parallel plate electric field can improve heating uniformity, and that this can be achieved through the design of bespoke electrode systems. A Euler characteristic based shape factor is proposed, again for the first time, that can predict heating uniformity for solid, dielectrically homogenous shapes. This provides industry with a tool to quickly determine the feasibility for uniform RF heating of different three dimensional shapes based on geometry alone. This provides a screening method for food technologists developing new products, allowing rapid assessment of potential heating uniformity and reducing the need for early stage specialist computational modelling.