A Dimensionless Empirical Model to Predict Heat Transfer Coefficients for Cooling High-Moisture Meat Analog with...

Area of Science:

• Food Engineering
• Heat Transfer
• Materials Science

Background:

• Optimizing cooling rates is critical for achieving desired texture and fibrous quality in whole-cut meat analogs.
• Accurate heat transfer estimations are essential for designing efficient cooling dies in continuous food processing.

Purpose of the Study:

• To develop an empirical dimensionless relationship for estimating heat transfer coefficients during the continuous cooling of high moisture meat analogs (HMMA).
• To provide a tool for designing improved cooling dies and scaling up HMMA production processes.

Main Methods:

• Extrusion of wheat-based HMMA under varied cooling media temperatures, product mass flow rates, and die aspect ratios.
• Continuous in situ measurement of product and cooling media temperatures and mass flow rates.
• Dimensional analysis and nonlinear regression fitting to a dimensionless heat transfer model.

Main Results:

• A dimensionless model correlating Nusselt number, Graetz number, and die aspect ratio was established: $\overline{\mathrm{Nu}}$ = A∙(Gz^-1)^B∙(C+D∙[1-a*]^E).
• The model demonstrated a high degree of accuracy (RMSE = $\overline{\mathrm{Nu}}$ ± 4.9, p < 0.0001) and was logically bound within theoretical limits.
• The model quantifies the impact of cooling die geometry and heat exchanger length on heat transfer coefficients.

Conclusions:

• The developed empirical model provides a reliable method for estimating heat transfer coefficients in HMMA cooling dies.
• This research offers practical applications for engineers and scientists aiming to optimize meat analog production for improved quality and cost-effectiveness.
• The findings facilitate the scale-up of HMMA processes by providing insights into cooling die design and operational parameters.