Multiphysics modeling to understand microwave-food interactions in a multi-port solid-state microwave system.

Multiphysics modeling plays a crucial role in understanding the complexities of microwave-food interactions, especially in multi-port solid-state microwave systems where microwave parameters can be precisely and dynamically controlled. However, previous models using simplistic or manually measured oven geometries face challenges in accurately simulating the microwave heating process. This study first developed a robust 3-D scanning approach to capture precise geometric details of the oven cavity, incorporating them into multiphysics modeling for solid-state microwave heating. Furthermore, a quantitative validation approach was also developed to characterize modeling accuracy against experimental results. The results showed that multiphysics modeling with 3-D scanned geometry demonstrated improved prediction accuracy, with notably lower root mean square error (RMSE) values (ranging from 1.57 to 4.11 °C) compared to models using simple box geometry (ranging from 1.73 to 6.33 °C) and manually measured geometry (ranging from 1.48 to 4.66 °C) for various heating scenarios with various frequencies (2.40, 2.45, and 2.48 GHz) and waveguide port locations (Right, Back, and Left).

The study further focuses on utilizing the multi-port solid-state microwave heating processes and investigates the impact of differential phase between multiple sources on microwave-food interactions. To improve the modeling efficiency in simulating extensive scenarios of relative phase (0° to 360°), this study developed a simple analytical approach that extends the existing knowledge of plane wave interactions to encompass multi-mode standing wave interactions. By employing only four physics-based models, this analytical approach enables the prediction of microwave power densities at any arbitrary source phase difference ranging from 0° to 360°.To validate the performance of the developed analytical model, comparisons were made with results obtained from the physics-based models in terms of electric field and power dissipation densities. After validation, extensive predictions and characterizations of differential phase-dependent microwave power densities revealed wave-like patterns in the average, standard deviation, and coefficient of variations of the nodal power densities. This observation emphasizes the importance of selecting an appropriate differential phase to ensure uniform heating performance.

The developed 3-D scanning approach, improved multiphysics model, and simple analytical model provide useful tools to evaluate complicated microwave-food interactions for the development of solid-state microwave processing technology.