Jae-Woong Han

Physical Properties of Rapeseed (II)

Some physical properties of rapeseed were measured at five moisture levels of 10.03, 14.91, 20.07, 25.06 and 30.12% (w.b.), which include frictional properties (coefficient of static friction, emptying and filling angle of repose) and aerodynamic properties (terminal velocity and drag coefficient). The physical properties of rapeseed were evaluated as a function of seed moisture content. In the moisture content range, the coefficients of static friction, emptying and filling angle of repose increased linearly with increase of moisture content. The maximum values of coefficients of static friction were on the acrylic surface, varied from 0.34 to 0.43; the next is on the galvanized steel, varied from 0.30 to 0.38; and the minimum were on stainless steel surface, varied from 0.27 to 0.35. Emptying and filling angle of repose varied from 26.12 to 29.62 and 23.83 to 27.05 degrees, respectively. Terminal velocity increased linearly from 3.47 to 3.91 m/s with increase of moisture content. Drag coefficient varied from 1.84 to 1.64 as the moisture content increased. The relationship between drag coefficient and moisture content were expressed by non-linear equation.

Circulating Concurrent-flow Drying Simulation of Rapeseed

In this study, computer simulations were conducted to assess the use of a circulating concurrent-flow dryer for rapeseed drying and to determined the effect of this drying method on the germination ratio of rapeseed after the drying process was complete. The simultaneous heat and mass transfer between air and rapeseed in a concurrent-flow dryer was examined by simulation. The drying simulation was based on several parameters with sequent time series. Equations concerning air psychrometrics, physical properties, thermal properties, equilibrium moisture content, thin layer drying of rapeseed, etc. were all combined to solve the simulation models. Based on energy and mass transfer in the concurrent-flow drying model, a simulation program for the circulating concurrent-flow rapeseed dryer was built along with a detailed description of the mathematical solution to the model. A pilot scale circulating concurrent-flow dryer(200 kg/batch) was used to verify the fitness of the simulation program. A comparison between the experimental data and the model predicted results was presented and discussed. The drying parameters and germination ratio were analyzed and the accuracy of the simulation program was evaluated. The simulation program proved to be reliable and was shown to be a convenient tool for predicting rapeseed drying and germination ratio of rapeseed in a concurrent-flow dryer.

Low Temperature Drying Simulation of Rough Rice

This study was conducted to verify the simulation model through the drying test, and investigate effect of factors, such as temperature of drying air, airflow rate, and velocity of the airflow, on the drying. The low temperature drying simulation model was developed based on the circulation dry simulation model presented by Keum et al. (1987), and by modifying low temperature thin layer drying model, equilibrium moisture content model, latent heat of vaporization model, and crack ratio prediction model. The heat pump and experimental dryer with a capacity of 150kg were used for the test. The RMSE between the predicted and measured value was 0.27% (drying temperature), 0.15% (crack ratio), and 2.08% (relative humidity), so the relevance of the model was verified. In addition, the effect of drying temperature, airflow rate, and velocity of the airflow on the drying was examined. The experimental results showed that the crack ratio at drying temperature of was allowable. Moreover, at below , variation of the crack ratio was slight, but drying time was delayed. Given these results, the drying temperature of over was effective. As the airflow rate increased, required energy dramatically increased. Whereas drying rate slowly increased, so loss of drying efficiency was caused. Considering these results, the dryer needed to be designed and adjusted to lower than . As velocity of the airflow increased, required drying energy increased when the velocity of the airflow was over /hr, while crack ratio and drying rate showed little variation.

Thin Layer Drying Model of Sorghum

Hong-Sik Kim, Oui-Woung Kim, Hoon Kim, Hyo-Jai Lee, Jae-Woong Han* Research Group of Smart Food distribution system, Korea Food Research Institute, Sungnam 13539 Korea Division of Bio-Industry Engineering, Koungju National University, Yesan, 32439 Korea Received: August 31st, 2016; Revised: September 26th, 2016; Accepted: November 5th, 2016 Purpose: This study was performed to define the drying characteristics of sorghum by developing thin layer drying equations and evaluating various grain drying equations. Thin layer drying equations lay the foundation characteristics to establish the thick layer drying equations, which can be adopted to determine the design conditions for an agricultural dryer. Methods: The drying rate of sorghum was measured under three levels of drying temperature (40°C, 50°C, and 60°C) and relative humidity (30%, 40%, and 50%) to analyze the drying process and investigate the drying conditions. The drying experiment was performed until the weight of sorghum became constant. The experimental constants of four thin layer drying models were determined by developing a non-linear regression model along with the drying experiment results. Result: The half response time (moisture ratio = 0.5) of drying, which is an index of the drying rate, was increased as the drying temperature was high and relative humidity was low. When the drying temperature was 40°C at a relative humidity (RH) of 50%, the maximum half response time of drying was 2.8 h. Contrastingly, the maximum half response time of drying was 1.2 h when the drying temperature was 60°C at 30% RH. The coefficient of determination for the Lewis model, simplified diffusion model, Page model, and Thompson model was respectively 0.9976, 0.9977, 0.9340, and 0.9783. The Lewis model and the simplified diffusion model satisfied the drying conditions by showing the average coefficient of determination of the experimental constants and predicted values of the model as 0.9976 and Root Mean Square Error (RMSE) of 0.0236. Conclusion: The simplified diffusion model was the most suitable for every drying condition of drying temperature and relative humidity, and the model for the thin layer drying is expected to be useful to develop the thick layer drying model.

Simulation of Wheat Circulating Cross-flow Dryer

Purpose: In Korea, wheat is dried using circulating cross-flow grain dryers. However, there is no research on wheat drying which can be utilized for the dryers. Therefore, this study developed and evaluated a simulation of the circulating cross-flow dryer, and examined the effects of various factors on drying performance. Methods: The simulation program was developed using drying models and was evaluated against wheat-drying experiments with a dryer having a 30-ton capacity. The influence of drying temperature, air volume, and grain falling rate on drying performance were examined through the simulation. Results: The experimental results validated the simulation program by showing the same root mean square error (RMSE) for moisture content (0.286%) and drying rate (0.056%/h) in both the experimental data and the simulation values. The appropriate wheat-drying parameter values, considering drying conditions, were determined to be 50°C for drying temperature, 500 m 3 /min for air volume, and a grain falling rate of 36.0 m 3 /h. Conclusions: The developed simulation program for circulating cross-flow dryers analyzed the influences of performance factors such as drying temperature, air volume, and falling rate on drying performance.

Combine Harvest Scheduling Program for Rough Rice using Max-coverage Algorithm

Purpose: This study was conducted to develop an optimal combine scheduling program using Max-Coverage algorithm which derives the maximum efficiency for a specific location in harvest seasons. Methods: The combine scheduling program was operated with information about combine specification and farmland. Four operating types (Max-Coverage algorithm type, Boustrophedon path type, max quality value type, and max area type) were selected to compare quality and working capacity. Result: The working time of Max-Coverage algorithm type was shorter than others, and the total quality value of Max-Coverage algorithm and max quality value type were higher than others. Conclusion: The developed combine scheduling program using Max-Coverage algorithm will provide optimal operation and maximum quality in a limited area and time.