Multi-physics modelica modeling of rotary dryer with fouling resistance effects

Rotary dryers are widely applied in the industrial drying field. During operation, the accumulation of fouling resistance (FR) seriously impairs heat transfer efficiency and material drying uniformity. This study utilizes the Modelica multi-domain modeling language to develop an equivalent fluid model with FR equations, enabling precise characterization of the non-uniform wall temperature field. Validated via simulations and experiments, the model not only accurately predicts wall temperature distributions and outlet moisture content variations under different combinations of fouling thicknesses and thermal conductivities, but also exhibits high precision—with relative errors of outlet material temperature, moisture content, and flow rate all below 1.0% under steady-state conditions. Sensitivity analysis further demonstrates that the thermal conductivity of the FR layer is a critical factor affecting drying efficiency. As the fouling thickness grew from 0 mm to 2 mm, the temperature difference in Model II reaches 20 °C, significantly exceeding the approximately 5 °C observed in Model I. Concurrently, the total heat change in Model II was approximately 4.5 times that of Model I, while the moisture content of the dried material increased by 0.92% to 4.13%. This indicates that the presence of a FR layer indeed reduces heat transfer efficiency during the drying process, rendering it a critical factor that must be carefully considered in system performance evaluation. The proposed model provides a quantitative basis for optimizing drying process parameters, which helps enhance the stability of drying process control, ensure processing quality, and offer strong data support for process optimization in actual production. The research also indicates that the accumulation of FR has a significant impact on process stability and energy efficiency. By quantifying the possible critical thresholds of FR thickness under two thermal conductivity conditions, the model lays a theoretical foundation for formulating intelligent cleaning strategies based on thermophysical parameters. Future research can further explore online monitoring methods to achieve real-time assessment of fouling status and intelligent regulation of process parameters.