Simulation And Optimisation Of A Drying Model For A Forced Convection Grain Dryer

ABSTRACT

Forced convection grain dryers are more efficient and achieve greater drying rates than natural convection dryers. However, it is necessary to provide an appropriate solar air heater in order to achieve the required drying air temperature. Well sized fan and drying cabinet, as well as an optimal combination of air velocity, temperature and grain layer thickness are also essential for improved performance of such a dryer. In order to predict variation of moisture content with time during the drying process, it is necessary to have an appropriate drying model. In this study carried out at Njoro, Nakuru County in Kenya, an experimental grain dryer was sized, fabricated and its performance investigated under different drying conditions. Simulation of air flow within an initial model of the dryer was done and the results used to size the fan and drying cabinet. The effect of air velocity, grain layer thickness, number of trays and temperature on drying efficiency (ratio of energy used in removing moisture to sum of energy lost by drying air and that used for running fan) and moisture removal rate (ratio of mass of moisture removed to mass of wet grain per unit time) was investigated. The Taguchi approach was used to determine the optimal combination of drying air velocity, temperature and grain layer thickness that could be used to ensure greatest drying efficiency and Moisture Removal Rate (MRR). Analysis of Variance (ANOVA) and Least Square Differences (LSD) tests were used to determine whether change of air velocity and grain layer thicknesses significantly affected drying efficiency as well as MRR. The best fitting drying model for drying maize grain was selected and subsequently used to develop a computer simulation model for predicting drying time. On the basis of simulation results, number of trays and mass of grain to be dried per batch, the experimental grain dryer developed was of dimensions 0.5 m x 0.5 m x 1.0 m and was equipped with a 0.039 kW centrifugal fan. MRR was found to decrease with increase in grain layer thickness as long as air velocity was kept constant. For example, at 0.41 m/s air velocity, as grain layer thickness increased from 0.02 to 0.08 m, MRR decreased from 0.061 to 0.022 kg moisture / (kg wet grain. hour). Drying efficiency decreased with increase in drying air temperature where-as MRR increased with rise in air temperature as long as air velocity and layer thickness remained constant. For an air velocity of 0.41 m/s and 0.04 m grain layer thickness, drying efficiency was 23.5% at 40 °C and reduced to 10.1 % at 55 °C. On the other hand, MRR increased from 0.045 to 0.058 kg moisture / (kg wet grain. hour) over the same temperature range. It was found that when drying a given grain layer thickness, use of two trays did not significantly improve MRR as compared to the use of one. As a result of the optimisation process, it was also determined that when drying was done under laboratory conditions, a combination of 0.41 m/s air velocity, 45 °C air temperature and 0.02m layer thickness resulted in greatest MRR and drying efficiency. The drying model that best describes the drying curve was found to be the Midilli model. The optimal drying parameters, if applied by the user of the dryer, will result in optimal drying rate and drying efficiency, and this in turn will lead to reduced post-harvest grain loss. The computer simulation model developed will enable the farmer to plan drying schedules. Application of simulation to size the fan and dryer cabinet should be emulated by those who seek to size dryers. It is recommended that further study be carried out to determine the effect of grain porosity on dryer performance. Investigations should also be done to find ways of utilizing the warm exhaust air from the dryer.