Freezing Time Prediction of Biologic Formulated Drug Substance Using the Plank Model

Nakach, Mostafa; Bahloul, Firas; Greco, Stéphanie; Authelin, Jean‐René; Klingler, Otmar; Bernhardt, Cathrin

doi:10.5731/pdajpst.2019.011247

Cited by 4 publications

(1 citation statement)

References 17 publications

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“…In order to forecast when chestnuts would freeze, researchers also made efforts (Lee and Kim 2008). The use of the Plank model to forecast the freezing durations of biological medicinal compounds was investigated by in the past (Nakach et al 2021). Furthermore, research has been done to forecast the freezing time of fresh corn using neural networks (Zhao et al 2015).…”

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confidence: 99%

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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confidence: 99%