The influence of distributed chemical reaction groups in a multiphase coffee bean roasting model

The coffee industry relies on fundamental research to improve the techniques and processes related to its products. While recent theoretical and modelling work has focused on the heat and mass transfer processes within roasting coffee beans, modelling and analysis of chemical reactions in the contex...

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Bibliographic Details
Main Authors: Fadai, N, Akram, Z, Guilmineau, F, Melrose, J, Please, C, Van Gorder, R
Format: Journal article
Published: Oxford University Press 2018
Description
Summary:The coffee industry relies on fundamental research to improve the techniques and processes related to its products. While recent theoretical and modelling work has focused on the heat and mass transfer processes within roasting coffee beans, modelling and analysis of chemical reactions in the context of multiphase models of roasting beans has not been well-studied. In this paper, we incorporate modified evaporation rates and chemical reaction groups to improve existing mathematical models of roasting coffee beans. We model the phase change from liquid to vapour water within the bean during roasting using first-order Arrhenius-like global reactions, and for other components of the bean, we consider a threecomponent solid phase model which includes sucrose, reducing sugars, and other organic compounds, which allows for porosity of the solid matrix to vary during the roasting process. We non-dimensionalise and then solve the multiphase model numerically, comparing the simulations with data we have collected through full bean and chopped bean experiments. We demonstrate that numerical solutions of the enhanced multiphase model with global water reactions and three-component solid phase reactions agree with experimental data for the average moisture content in whole beans and small chunks of bean, but that the data allows for a range to possible parameter values. We discuss other experimental data that might be collected to more firmly determine the parameters and hence the behaviour more generally. The indeterminacy of the parameters ensures that the additional effects included in the model will enable better understanding the coffee bean roasting process.