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• Experimental approach (lab/field characterization)
• Multi-scale approach: micro (crystals, drops...); macro (properties, distribution, stacking...); pilot (reactor, furniture, pallet...), system (factory, warehouse, network...)
• Multi-physics: crystallization, phase change
• Deterministic, stochastic modeling
• Multi-criteria optimization

Development of rigorous methods for assessing the temperature, energy consumption of equipment, product quality and environmental impact of refrigeration processes. These methods will be applied to low-TRL problems (microtomography, controlled crystallization, slow or rapid phase change, etc.), but will also help to increase the TRL of certain applications, in some cases by integrating a territorial dimension (cold chain, demand-side management, etc.). 

Control kinetics and mass/thermal transfers in products, fluids, processes or machines, to define optimal configurations for innovative systems. The key is the coupling between the various phenomena that contribute to the efficiency of the cold process (food + energy) at different scales (impact of nucleation and mass and heat transfers on the quality and/or efficiency of energy fluids/machines and frozen/refrigerated food products/processes).

Characterization and enhancement of phase changes (crystals, droplets, fluids, phase-change materials) to intensify refrigeration processes and guarantee product quality during freezing (e.g.: use of PCMs in packaging to limit temperature fluctuations, a subject related to both teams, with Enerfri's expertise in PCMs and Metfri's expertise in the impact of temperature fluctuations on product quality, especially quick frozen/chilled).

Taking into account process safety and flexibility: implementation and sizing of processes based on phase-change materials (storage, thermopile, etc.), storage in different systems (product inertia, cryogenics, porous matrices, etc.).

Coupling predictive models and global approaches (degraded, simplification of complex physical models, learning models, etc.). For example, the fields of application are black-box modeling (requiring large data sets) versus white-box modeling (which can be used to produce these data sets, after experimental validation on pilots), and the coupling of hard sciences (energetics, thermics).

Fields of application: Food, refrigeration, climate control and pharmaceutical industries