Sensitivity of freezing time estimation methods to heat transfer coefficient error

Fricke, Brian; Becker, Bryan R.

doi:10.1016/j.applthermaleng.2005.07.005

Cited by 11 publications

(3 citation statements)

References 20 publications

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“…The common practice to construct a mathematical diffusion model has been based on the solution of the energy and mass equations with a third-kind boundary condition on the surface. Spatial and time variations of the local convective heat transfer coefficients caused errors in the range of 5-15% compared to analytical models and with respect to the experimental data [50][51][52]. In industrial practice a simplified fast predictive method is preferred and the development of simple and available software is desired [53].…”

Section: Nonconjugated Casesmentioning

confidence: 99%

Computational Simulation and Developments Applied to Food Thermal Processing

2011

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New challenges to improve food processing have created an incentive in the potential use of computeraided engineering for simulating thermal processes in foods as a viable technique to provide effective and efficient design solutions. Mathematical conjugated and nonconjugated models used along suitable numerical methods such as finite differences, finite elements, and finite volumes in predicting food freezing, dehydration, and sterilization are discussed in this review. The application of computational simulation should be used in combination with conventional techniques such as physical experiments and analytical solutions in order to enhance the knowledge of fluid mechanics, heat and mass transfer in foods.

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Section: Nonconjugated Casesmentioning

confidence: 99%

Computational Simulation and Developments Applied to Food Thermal Processing

2011

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“…The minimum value of RMSE was 1.7 ± 0.3 C for the center point. Although h depends on many factors and is a difficult parameter to calculate directly (Fricke & Becker, 2006), it is necessary to achieve a good prediction in the simulation. Like the thermophysical properties, these parameters are tedious and complex to determinate directly from foods in the freezing temperature range (Cornejo, Cornejo, Ramírez, Almonacid, & Simpson, 2016).…”

Section: Mathematical Model Validationmentioning

confidence: 99%

Three‐dimensional modeling of heat transfer during freezing of suspended and in‐contact‐with‐a‐surface yellow potatoes and ullucus

Salas‐Valerio

Solano‐Cornejo

Zelada‐Bazán

et al. 2019

J Food Process Engineering

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The aim of this research was to model the heat transfer during the freezing process of cubed yellow potatoes (Solanum tuberosum L.) and ullucus (Ullucus tuberosus Caldas). A mathematical model was developed using the three‐dimensional (3D) finite difference scheme to simulate the freezing process of suspended and in‐contact‐with‐a‐surface cubic particles. The thermophysical properties were predicted using the proximal composition and the convective heat transfer coefficient (h) was obtained by optimizing the root mean square error (RMSE) value. A pseudo h was included to simulate the heat transfer of cubic particles in‐contact‐with‐a‐surface. Low values of h were found for suspended frozen cubes (17–27 W/m2°C) and high values of pseudo h (295–371 W/m2°C) were determined for frozen cubes in‐contact‐with‐a‐surface. An excellent agreement was observed between experimental and predicted temperatures histories (RMSE: 0.6–1.7°C) at different thermocouples positions. In conclusion, the developed model simulated correctly the freezing profile of potato and ullucu in cubic shape. With this model, the possible effects of h and external temperature on freezing times of these vegetables under different positions were evaluated and were represented by polynomial equations that could be used in the industry. Practical Applications In this research, a simple and easy‐to‐implement mathematical model was developed to simulate the heat transfer during freezing process of yellow potatoes and ullucus in cubes. The 3D finite difference scheme developed can be used to simulate the freezing of suspended cubed food, as is the case of fluidized bed freezers, or that are in contact with a metal surface, as in plate freezers. In addition, this study presented polynomial equations that allow the quick and precise calculation of the freezing times of cubed yellow potatoes and ullucus.

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“…Spatial and time variations of the local convective heat transfer coefficients cause errors in the range of 5 to 15% compared to analytical models and with respect to the experimental data. Fricke & Becker (2006) performed a sensitivity analysis on various estimation methods of freezing time to determine the impact of errors in the heat transfer coefficient. Various methods have been developed to determine the freezing time, which also has been modified by others authors.…”

Section: Introductionmentioning

confidence: 99%

Numerical Simulation of Experimental Freezing Process of Ground Meat Cylinders

Moraga¹,

Vega‐Gálvez²,

Lemus‐Mondaca³

2012

International Journal of Food Engineering

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The efficient prediction of freezing processes is important for the frozen food industry with the purpose of preserving food quality. A comparison is made between the finite difference and finite volume methods to predict the unsteady 2D temperature distribution for the freezing of three different ground meat cylinders, with variable convective boundary conditions. Experiments were carried out to measure the local heat transfer coefficients as a function of freezing time and location. Time-dependent air temperature conditions caused by thermostat action were included in the analysis. The meat thermophysical properties as density, specific heat, and thermal conductivity are assumed to vary non-linearly with temperature. The experimentally measured time-temperature data were compared with the simulation results obtained by both numerical methods. According to statistical test results (RE %), the finite volume method gave the best fit quality. The finite volume method is more accurate for simulating the freezing process, as well as estimating the freezing time of this product

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Sensitivity of freezing time estimation methods to heat transfer coefficient error

Cited by 11 publications

References 20 publications

Computational Simulation and Developments Applied to Food Thermal Processing

Computational Simulation and Developments Applied to Food Thermal Processing

Three‐dimensional modeling of heat transfer during freezing of suspended and in‐contact‐with‐a‐surface yellow potatoes and ullucus

Numerical Simulation of Experimental Freezing Process of Ground Meat Cylinders

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