CFD Simulation of Deep-Bed Paddy Drying Process and Performance

TLDR

The study investigated deep‑bed paddy drying performance, focusing on how inlet air temperature and mass flow rate affect drying efficiency. A three‑dimensional CFD model in Fluent 6.3.26, augmented with a user‑defined function, was used to simulate drying behavior and energetic/exergetic performance, with results benchmarked against experimental data. The model predicted grain moisture, air temperature, and humidity with mean relative deviations below 6 %, 10 %, and 9 %, respectively, and showed that higher inlet temperatures combined with lower mass flow rates improve exergy efficiency.

Abstract

Computational Fluid Dynamics (CFD) was applied three-dimensionally to simulate the drying behavior of paddy in a deep-bed dryer. The commercial CFD software Fluent 6.3.26 was used. The deep-bed paddy drying process and performance were studied by incorporating user-defined function (UDF) in Fluent written in C language. The predicted drying parameters were compared with experimental data of deep-bed drying of paddy. The values of mean relative deviation (MRD), standard error of prediction (SEP), and maximum error of prediction (MEP) for prediction of grain moisture content, air temperature, and absolute humidity were less than 6, 10, and 9%; 0.33% (d.b), 1.24°C, and 0.06% (kg/kg of dry air); and 2.25% (d.b), 6.8°C, and 0.37% (kg/kg of dry air), respectively, which reflect reasonable accuracy. Moreover, the energetic and exergetic performance of deep-bed paddy drying were simulated and analyzed. The effects of inlet air temperature and mass flow rate on the performance parameters were investigated. It was shown that the application of higher levels of inlet air temperature and lower mass flow rates yielded higher exergy efficiencies of deep-bed paddy drying.