Freezing time-temperature behavior and parametric study of cylindrical shaped tylose gel samples: A numerical and experimental study

Deep, Charan; Pratihar, A.K.; Sharma, Manoj Kumar

doi:10.1016/j.tsep.2021.100933

Cited by 5 publications

(2 citation statements)

References 25 publications

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“…This illustrates the predictive power of the Cleland et al model for freezing periods under a range of convective heat transfer conditions: 5 W/m 2 K showed the least favourable performance, while 12.5 W/m 2 K yielded a better result. This model also showed good results when it was used for prediction of freezing time of minced fish and gels (Cuesta et al 2021;Deep et al 2021).…”

Section: Residual Analysis Of Cleland Et Al Modelmentioning

confidence: 83%

Framework for Accurate Estimation of Freezing Time and Convective Heat Transfer Coefficient for Freezing of Food product in Domestic Refrigerator: A Numerical and Simulation Modeling approach

Ray,

Minz,

Sinha

2024

Preprint

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Freezing time estimation is essential for quality assurance, process optimization, and innovation in a variety of industries. The total freezing time is greatly influenced by the heat transfer parameters like convective heat transfer coefficient (CHTC), which in turn affects the product's quality characteristics. The correct calculation of CHTC, especially in domestic freezers, remains largely unexplored despite the development of several mathematical models for freezing time prediction. To fill this gap, this research presents a framework-driven analysis of CHTC for estimating the freezing time of frozen sweetened yoghurt in a domestic refrigerator. This research not only compares the performance of several freezing time prediction models, but also seeks to determine the optimal CHTC range for accurate freezing time forecasts, determining the most accurate freezing time prediction model and to replicate the freezing process by simulation accurately for this specific scenario. The results showed great accuracy for the determined CHTC range (RMSE = 27.24, CV = 0.16, MSE = 741.85, MAE = 22.4, MAPE = 12.24 and MBE = 8.14) and lowest average residual (3.95 min) for the fitted prediction for the freezing time calculation of frozen yoghurt. The simulation analysis further backed the results by showcasing marginal temperature difference between the simulated and actual temperature (0.232℃ to 0.684℃) of the frozen yoghurt by using the determined CHTC range. This showed the developed framework’s reliability in freezing time prediction and CHTC range determination, which will eventually help in modeling the freezing process of different food products with high accuracy.

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Section: Residual Analysis Of Cleland Et Al Modelmentioning

confidence: 83%

Framework for Accurate Estimation of Freezing Time and Convective Heat Transfer Coefficient for Freezing of Food product in Domestic Refrigerator: A Numerical and Simulation Modeling approach

Ray,

Minz,

Sinha

2024

Preprint

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“…Derivatives of methyl cellulose, known by the trade name tylose, have already been used as a model food product both to study microwave-assisted heating [35,39] and to study freezing [40,41]. Thus, the material is ideally suited for an investigation of MFD.…”

Section: Model Productmentioning

confidence: 99%

Microwave-Assisted Freeze-Drying with Frequency-Based Control Concepts via Solid-State Generators: A Simulative and Experimental Study

et al. 2023

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Freeze-drying is a common process to extend the shelf life of food and bioactive substances. Its main drawback is the long drying time and associated high production costs. Microwaves can be applied to significantly shorten the process. This study investigates the effects of modulating the electromagnetic field in microwave-assisted freeze-drying (MFD). Control concepts based on microwave frequency are evaluated using electromagnetic simulations. The concepts are then applied to the first part of primary drying in a laboratory-scale system with solid-state generators. Targeted frequency modulation in the electromagnetic simulations enabled an increase in energy efficiency or heating homogeneity throughout MFD while having negligible effects on the power dissipation ratio between frozen and dried product areas. The simulations predicted the qualitative effects observed in the experimental proof of concept regarding energy efficiency and drying homogeneity. Additionally, shortened drying times were observed in the experiments with a targeted application of energy-efficient frequencies. However, differences occurred in the quantitative validation of the electromagnetic models for energy efficiency in dependence on frequency. Nevertheless, the models can be used for a time-efficient investigation of the qualitative effects of the control concepts. Therefore, frequency-based control of MFD represents a promising approach for process control and intensification.

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Framework for accurate estimation of freezing time and convective heat transfer coefficient for freezing of a food product in domestic refrigerator: a numerical and simulation modeling approach

Ray,

Minz,

Sinha

2024

Multiscale and Multidiscip. Model. Exp. and Des.

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Freezing time-temperature behavior and parametric study of cylindrical shaped tylose gel samples: A numerical and experimental study

Cited by 5 publications

References 25 publications

Framework for Accurate Estimation of Freezing Time and Convective Heat Transfer Coefficient for Freezing of Food product in Domestic Refrigerator: A Numerical and Simulation Modeling approach

Framework for Accurate Estimation of Freezing Time and Convective Heat Transfer Coefficient for Freezing of Food product in Domestic Refrigerator: A Numerical and Simulation Modeling approach

Microwave-Assisted Freeze-Drying with Frequency-Based Control Concepts via Solid-State Generators: A Simulative and Experimental Study

Framework for accurate estimation of freezing time and convective heat transfer coefficient for freezing of a food product in domestic refrigerator: a numerical and simulation modeling approach

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