Validated numerical model of heat transfer in the forced air freezing of bulk packed whole chickensModèle numérique validé de transfert de chaleur dans la congélation par air forcé de poulets entiers emballés en vrac

https://doi.org/10.1016/j.ijrefrig.2020.06.015Get rights and content

Highlights

  • The first CFD freezing model using CT images to generate a realistic model geometry.

  • Temperature-dependent thermal properties of chicken meat were employed.

  • Mean error between measured and simulated average temperatures was less than 1.3 °C.

  • The effect of operating conditions on freezing time was modelled.

Abstract

This study presents a 3D computational fluid dynamics (CFD) model to predict the temperature profile of bulk-packed whole chickens during forced-air freezing based on 3D computed tomography (CT) images of the chicken. The model was validated against experimental cooling data. By using the temperature-dependent thermal properties of chicken meat, the mean differences between the predicted average drumstick temperatures with corresponding experimental results were less than 1.3 °C for all tested conditions. Based on the validated model, a correlation was proposed to estimate the effect of operating conditions on freezing time and that correlation may be used to optimise the design of the freezing tunnel for chicken products.

Introduction

Poultry is the most consumed meat globally, of which approximately 88 per cent is chicken (ThePoultrySite, 2014). The shelf life of chicken meat is relatively short (Jimenez et al., 1999), so it is necessary to freeze chicken to improve food safety and preserve product quality through the supply chain. Benefits of freezing include not only a long shelf life but also an excellent retention of nutrients, sensory qualities and complete absence of microbial growth (Pham, 2014). An efficient design of freezing equipment is required to maximise the economics. Therefore, it is important that the chicken freezing process be modelled accurately to allow for design optimisation.

On the industrial scale in New Zealand, chicken products are typically cooled within a plastic liner bag (polyliner), which has the effect of restricting air movement within the voids between the liner and the chicken and results in a large air void within the bag on top of the chicken. The polyliner increases resistance to heat transfer since it prevents air outside the bag from directly contacting the chicken; however, it serves to reduce moisture loss which is detrimental to product quality and appearance. Despite research to account for the effect of voids on heat transfer rates (Ambaw et al., 2017; Datta, 2007; James et al., 2006; North, 2000; O'Sullivan et al., 2016) a general approach for dealing with the problem has yet to be established. As such, accounting for voids within food packages remains a significant challenge for designers of industrial refrigeration equipment (Smitheram, 2018).

Mannapperuma et al. (1994) presented a finite difference numerical method based on enthalpy formulation to simulate the air blast freezing of plastic-wrapped whole chickens, packed trays of chicken parts and boxed chicken parts. Zilio et al. (2018) used the CFD software STAR-CCM + to model the liquid-solid phase change in the freezing of chicken breast. The above mentioned studies approximated the geometry of chicken by simple shapes and used average heat transfer coefficients to represent the boundary condition over the entire surface of the packaging. None of them accounted for the effect of air voids within the packaging on the freezing rate. Air voids of different shapes and sizes exist when chicken carcasses are packed in bulk, due to the irregular shapes of the products. A more rigorous model for the convective freezing of chicken would provide refrigeration equipment designers a greater ability to optimise this important industrial process.

This research focused on developing a CFD model for the forced-air freezing of bulk-packed whole chickens encased in a polyliner within a cardboard tray and validating the model against experimental data. The overall structure of the contents of the trays (bulk-packed chickens), air voids within the bulk-packed chickens, and the flow field around the products were included in the model. CT scanning was used to create a geometry that was similar to the empirical shape of bulk packed chickens. The model was then used to investigate the effect of operating conditions on the freezing time of a tray of whole chickens.

Section snippets

Experimental system

Experimental freezing trials were conducted in the Environmental Test Chamber (ETC) at AgResearch Ltd, Hamilton, New Zealand. The experimental system were designed to closely represent the industrial setting previously presented in Hoang et al. (2020). A polystyrene test tunnel (PTT) 2500 mm long x 720 mm height and 510 mm wide (Fig. 1) was used. The PTT consisted of a variable speed suction fan at the downstream end, a fine wire mesh at the upstream end (used to diffuse the airflow), and an

Numerical model validations

The numerical model was first validated by comparing the predicted temperatures with the experimental data for the average temperature history and the seven-eighths cooling time (SECT) of a tray of chickens. Subsequently, the measured temperature histories of specific positions within a tray were also compared with the numerical results to assess the accuracy of the numerical model in predicting the cooling behaviour at different locations within the tray.

The experimental average temperature of

Conclusions

This study presented a CFD model for the forced-air freezing of a tray of bulk-packed chickens that was validated against experimental data for a range of cooling air velocities. The geometry of the chickens and packaging was derived empirically via CT scan data, allowing for greater geometrical accuracy than previous models. The mean discrepancy between measured and simulated average temperature prediction was less than 1.3 °C, and the maximum difference between measured and simulated SECT was

Declaration of Competing Interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgement

The authors would like to acknowledge the assistance and support of Shane Leath and Robert Wieliczko at AgResearch Ltd, Robert Kemp of Robert Kemp Consulting Ltd, and Ross Clarke and Dave Smitheram both formerly at MilMeq. This work has received funding from Vietnamese government scholarship for Duy Hoang's PhD study.

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