Computational modelling for decarbonised drying of agricultural products: Sustainable processes, energy efficiency, and quality improvement. (February 2023)

• Record Type: Journal Article
• Authors: Adnouni, M.; Jiang, L.; Zhang, X.J.; Zhang, L.Z.; Pathare, Pankaj B.; Roskilly, A.P.
• Is Part Of: Journal of food engineering. Volume 338(2023)
• Publication Date: 2023-02
• Subjects: CFD -- Energy modelling -- Sustainable drying -- Quality evaluation -- Decarbonisation; Food industry and trade -- Periodicals; Food -- Analysis -- Periodicals; Aliments -- Industrie et commerce -- Périodiques; Aliments -- Analyse -- Périodiques; Aliments -- Recherche -- Périodiques; 664.005
• DOI: 10.1016/j.jfoodeng.2022.111247
• Languages: English
• ISSNs: 0260-8774

Abstract

Abstract: Drying agricultural products consumes massive amounts of energy. The rapid depletion of non-renewable energy sources, along with rising environmental concerns, are opening up new opportunities for developing sustainable drying systems and reducing its carbon footprint. Drying modelling is a powerful tool for understanding the mechanism and predicting fluid flow hydrodynamics and heat and mass transfer during the drying process. The current review outlines the state-of-the-art of various modelling techniques for drying technologies, explores the unresolved bottlenecks in technology development, and provides new avenues for more innovative and sustainable drying technologies. First, the drying mechanism and novel drying technologies are explained. Then, various modelling methods are summarised. Finally, new insights into quality and energy modelling using CFD are discussed. Based on the research achievements, future challenges of CFD modelling and their contribution to improving the drying process in terms of high quality and low energy consumption and decarbonisation are addressed. Highlights: A comprehensive understanding of the drying mechanism is indispensable in CFD modelling. Energy and environmental concerns create new avenues for developing sustainable drying. CFD is conducive to heat and mass transfer prediction and drying parameter optimisation. Modelling the drying process should be geared towards integrating energy and quality aspects.