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Project

Simulation of gas transport during controlled atmosphere storage of pome fruit using computational fluid dynamics and discrete element modelling

Pear fruit is a major export product of Flanders. To preserve quality after harvest, pears are commonly stored in a controlled atmosphere (CA), in which the oxygen concentration is reduced and carbon dioxide concentration is elevated to minimize respiration. Too low oxygen concentrations, however, lead to fermentative decay. A recent innovation uses dynamic controlled atmosphere (DCA). In DCA the oxygen concentration is dynamically adapted to the optimal level, based on measurements of a biological stress response of the fruit to low oxygen levels. In comparison to CA, DCA leads to a strongly improved post-storage quality. The respiratory quotient (RQ) of the fruit has been proposed as a suitable measure of the stress. RQ-DCA is already implemented on pilot scale; however, it is not operating well on a larger scale due to limitations on measuring the RQ. Critical to the success of RQ-DCA is that the measured RQ signal must be representative for the whole cool store. However, to date there is no information about the spatial homogeneity of gas and hence, the RQ, in the cool store. Likewise, respiration strongly depends on temperature. So temperature gradients may cause gas concentration and RQ gradients. Therefore, the aim of this PhD is to identify the effect of the uniformity of gas and temperature inside the cool room on the RQ measurement, taking into account effects of fruit metabolism, size and shape, bin design and room configuration. At the end of the project, measures for successful implementation of RQ-DCA are derived.

The research is performed by using computational fluid dynamics. Because it would be extremely computationally demanding to immediately include the effect of individual pears in the model of the whole cool room, a multiscale modelling approach is used. First, a respiration-diffusion model of a single pear is constructed to study gas exchange and heat transfer inside the fruit in relation to development of hypoxia. The geometrical and physiological variation of the fruit will be taken into account by using statistical shape models and by performing respiration measurements, such that stochastic simulations can be performed. Apparent parameters are extracted and then inserted in a second CFD model, which consists of multiple pears inside a bin. These pears are stacked in a realistic, random filling pattern by using discrete element modelling. Finally, this model is homogenized to obtain a model for the entire cool room, which will be used to study the effect of different parameters on the distribution of gasses and temperature inside the room.

Date:1 Sep 2019 →  25 Feb 2022
Keywords:multiscale computational fluid dynamics, RQ-DCA, Postharvest technology
Disciplines:Post harvest technologies of plants, animals and fish (incl. transportation and storage)
Project type:PhD project