Thermophysical properties of carbohydrate solutions: Correlation between thermal and transport properties
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Sugar solutions such as sucrose, glucose and fructose are often used in osmotic dehydration processes. Thus, the experimental determination of their thermophysical properties is a must for designing purposes. Density, specific heat and thermal conductivity were determined in a wide range of solute concentration (10–60 °Brix) and temperature (273.15–358.15 K). Empirical equations were considered to fit the experimental data and to evaluate the data behavior. An assessment based on the Prandtl number was considered to correlate thermal and rheological data. Higher density and lower specific heat and thermal conductivity values were observed when temperature decreased and solute concentration increased. Prandtl number behaved similarly as density, indicating that momentum transfer is favored in comparison with heat transfer in more concentrated solutions at lower temperatures. A versatile polynomial model concerning the significant variables could predict the experimental values for all solutions with good accuracy (R2 >.9863 and MRE < 1.20%). Reported data and equations showed to be essential for engineering aspects and transport phenomena analysis. Practical Applications: Sucrose, glucose and fructose solutions are commonly used in osmotic dehydration processes to promote solute incorporation, increasing shelf-life and quality of food products. The availability of thermophysical properties in a wide range of solute concentration and temperature covers the most of conventional and nonconventional conditions for designing osmotic dehydration and many other food processes. Among the unit operations, it could be found pumping, mixing/stirring, pasteurization, sterilization, evaporation and so on. These data are useful to understand how properties change when the conditions are altered during the processes. They also provide important information about momentum and heat transfer through the fluid. By analyzing dimensionless parameters, as Prandtl number, one phenomenon or other can be favored under specific conditions. The presence of accurate mathematical models results in greater agility and reliability in the execution of processes, especially for those operating in wide ranges of temperature and solute concentration.