Determination of Particle‐Fluid Convective Heat Transfer Coefficient and Construction of Dimensionless Models for Different Cooking Methods

ABSTRACT The particle‐fluid convective heat transfer coefficient ( h fp ) is a critical parameter in cooking processes, determining heat and mass transfer rates between food particles and heating media, which has a significant impact on the final food quality. In this study, pork loin was used as the test sample. The particle‐fluid relative velocity was measured and a linear relationship was established between control conditions and particle‐fluid relative velocity during boiling, steaming, and stir‐frying processes. The h fp was determined by a hypothetical trial algorithm, which revealed its relationship with the cooking operating conditions. Additionally, the dimensional analysis method was employed to construct h fp dimensionless models during cooking processes. Our results demonstrated the existence of a linear relationship between the heating power during boiling and steaming, the stirring speed during stir‐frying, and the particle‐fluid relative velocity (Equations 11–13). The h fp values for boiling, steaming, and stir‐frying ranged from 544 to 1321, 211 to 404, and 410 to 1706 W/m 2 K, respectively. The h fp was influenced by various factors, including particle size, the particle‐fluid relative velocity, medium temperature, and thermophysical properties of the heat transfer medium. Specifically, smaller pork loin feature size, higher heating power during boiling and steaming, faster stirring speed, and higher oil temperature during stir‐frying resulted in a greater h fp . We constructed h fp dimensionless models during boiling, steaming, and stir‐frying based on dimensional analysis, where h fp was expressed as a function of the Nusselt number ( Nu ). The validation experiments showed that the average relative errors of h fp dimensionless models for boiling, steaming, and stir‐frying processes are 0.82%, 0.90%, and 1.89%, respectively, which confirmed the accuracy and reliability of h fp dimensionless models.