Numerical and Experimental Analysis of Industrial Oven Heat Distribution and its Effect on Food Quality

Thermal uniformity in industrial forced convection ovens is critical for ensuring consistent food quality and process efficiency. This study presents a comprehensive numerical and experimental investigation of an industrial forced convection oven. The experimental data were acquired from a multi-channel digital data logger and thermocouples arranged in a 24-point grid across ten tray levels. The numerical study employed Computational Fluid Dynamics (CFD) using a pressure-based transient solver for buoyant, turbulent flow of compressible fluids. To accurately capture the complex physics within the oven, turbulence was modeled using the Shear Stress Transport (SST) k - ω framework to resolve boundary layer effects, while radiative heat transfer was accounted for using the Discrete Ordinates (DO) method. The results demonstrate a strong correlation between the experimental and numerical data. Under the specified working conditions, the numerical model accurately predicted the temperature distribution, with observed deviations remaining within an acceptable margin of error. These findings suggest that the proposed computational framework serves as a reliable tool for assessing and optimizing thermal performance in industrial baking applications.