• Journal of Biosystems Engineering
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• v.42 no.3
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• pp.190-198
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• 2017

Purpose: A thin-layer drying equation was developed to analyze the drying processes of soybeans (white and black beans) and investigate drying conditions by verifying the suitability of existing grain drying equations. Methods: The drying rates of domestic soybeans were measured in a drying experiment using air at a constant temperature and humidity. The drying rate of soybeans was measured at two temperatures, 50 and $60^{\circ}C$, and three relative humidities, 30, 40 and 50%. Experimental constants were determined for the selected thin layer drying models (Lewis, Page, Thompson, and moisture diffusion models), which are widely used for predicting the moisture contents of grains, and the suitability of these models was compared. The suitability of each of the four drying equations was verified using their predicted values for white beans as well as the determination coefficient ($R^2$) and the root mean square error (RMSE) of the experiment results. Results: It was found that the Thompson model was the most suitable for white beans with a $R^2$ of 0.97 or greater and RMSE of 0.0508 or less. The Thompson model was also found to be the most suitable for black beans, with a $R^2$ of 0.97 or greater and an RMSE of 0.0308 or less. Conclusions: The Thompson model was the most appropriate prediction drying model for white and black beans. Empirical constants for the Thompson model were developed in accordance with the conditions of drying temperature and relative humidity.

• Journal of Biosystems Engineering
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• v.20 no.3
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• pp.275-287
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• 1995

The rice processing complex(RPC) consisted of the rice handling, drying, storage, and milling processes. It has been established at 83 locations domestically by April 1994, and 200 of RPC will be built more throughout the country. Therefore, this study has been performed to achieve two objectives as the followings : 1) Development of mathematical models which can assess the requirement of electricity, fuel, and labor for four model systems of rice processing complex. 2) Development of a computer simulation model which produce the improved designs of RPC by the evaluation results of energy requirements of four RPC models. The results from this study are summarized as follows : 1) Mathematical models were developed on the basis of result of mass balance analysis and required power of machines for each process. 2) A computer simulation model was developed, which can produce the improved designs of RPC by the evaluation results of energy requirements. The computer simulation model language was BORLAND $C^{++}$. 3) The results of simulation showed that total energy requirements were ranged from 75.94㎾h/t to 124.30㎾h/t. 4) From the results of computer analysis of energy requirement classified by drying type, it was found that energy requirement of the drying type A{paddy rice (PR) for storage-natural air drying(15%), PR for milling-heated air drying(16%)} were less than that of the drying type B{1 step-natural air drying(PR for storage : 18%, PR for milling : 20%), 2 step-heated air drying(PR for storage : 15%, PR for milling : 16%)}. 5) The energy efficient drying method is that all the incoming rough rice to RPC should be dried by national air drying systems. If it is more than the capacity of national air drying system, the amount of surplus rough rice is recommended to be dried by the heated air drying method.

• Journal of Biosystems Engineering
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• v.27 no.1
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• pp.45-50
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• 2002

This study was performed to develop thin layer drying equations fur short grain rough rice using far-infrared ray. Thin layer drying tests was conducted at four far-infrared ray temperature levels of 30, 40, 50, 60$^{\circ}C$ and two initial moisture content levels of 20.7, 26.2%(w.b.). The measured moisture ratios were fitted to Lewis and Page drying models by stepwise multiple regression analysis. Half response time of drying was affected by both drying temperature and initial moisture content at drying temperature of below 40$^{\circ}C$, but at above 40$^{\circ}C$ was mainly affected by drying temperature. Experimental constant(k) in Lewis model was a function of drying temperature, but K and N in Page model were function of drying temperature and initial moisture content. Moisture ratios predicted by two drying models agreed well with experimental values. But in the actual range of drying temperature above 30$^{\circ}C$ Page model was more suitable for predicting of drying rates.

• Journal of Biosystems Engineering
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• v.32 no.5
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• pp.309-315
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• 2007

This study was performed to develop a simulation model of circulating concurrent-flow rice dryer. The simulation model consists of drying model, tempering model and crack prediction model. The drying and tempering models were developed based on mathematical analysis, and the crack prediction model was developed by thin layer drying tests. Rice drying tests were done with three replications by use of a pilot scale dryer of holding capacity of 700 kg. Experimental values for moisture content, rice temperature, rice crack, and drying energy were compared with predicted values by simulation model. The RMSEs of predicted moisture contents were ranged from 0.5807% (d.b.) to 1.1951% (d.b.). and the coefficients of determination were 0.9688 to 0.9812. The RMSEs of predicted rice temperatures at the exit of the drying chamber were 1.83 to $3.81^{\circ}C$ and the coefficients of determination were 0.8834 to 0.9482. The results for moisture contents and rice temperatures showed very good relationships between predicted values and experimental values. The RMSEs of predicted value of crack ratio were 0.4082 to 0.7967% and the coefficients of determination were 0.8742 to 0.9547.

• Journal of Biosystems Engineering
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• v.37 no.5
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• pp.327-334
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• 2012

Purpose: The color changes in red pepper during far infrared drying were studied in order to establish a color change model. Methods: The far infrared drying experiments of red pepper were conducted at two temperature levels of 60, $70^{\circ}C$ and two air velocity levels of 0.6 and 0.8 m/s. The results were compared with the hot-air drying method. The surface color changes parameters of red pepper were measured qualitatively based on L (lightness), a (redness), b (yellowness) and total color changes (${\Delta}E$). The goodness of fit of model was estimated using the coefficient of determination ($R^2$), the root mean square error (RMSE), the mean relative percent error (P) and the reduced chi-square (${\chi}^2$). Results: The results show that an increase in drying temperature and air velocity resulted in a decrease in drying time, the values of L (lightness) and a (redness) decreased with drying time during far infrared drying. The developed model showed higher $R^2$ values and lower RMSE, P and ${\chi}^2$ values. Conclusions: The model in this study could be beneficial to describe the color changes of red pepper by far infrared drying.

• Journal of Ginseng Research
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• v.16 no.2
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• pp.111-123
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• 1992

Drying characteristic data for peeled ginseng were obtained to determine dominant drying factors and fitted with five selected drying models and an empirical model. Among air temperature, relative humidity and diameter of ginseng root, drying air temperature was found to be the most influencing factor on drying rate. Drying velocity appeared faster as the drying temperature increased but its effect was less at high temperature than at low temperature. Quality change during the drying process did not occur except when relative humidity was 75fb. At high relative humidity, skin color of ginseng was turned to light brown. Approximate-Diffusion and the Empirical model for drying were in a good agreement with experimental data. The models are as follows; $.$ Approximate-Diffusion model MR = A$.$exe(-k$.$1) A = 1.72 + 0.407 In(D) - 0.0000963T3 - 0.358 In(RH) + 0.0000945 RH2 B= 1.01 + 0.0195RH - 0.O0518D2 + 0.0708 In(T) - 0.492 In(RHI-D.0000933RH2$.$Empirical model MR= Cl + Cs$.$In(t) Cl= 1.14+0.382 In(D)-0.00008477a-0.139 In(RH)+0.0000664RH2 Cs=0.440-0.0224 In(D)-0.193 In(T)+0.0000464T2-0.00000771RH2

• Transactions of the Korean Society of Mechanical Engineers
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• v.17 no.8
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• pp.2088-2098
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• 1993

A mathematical model of freeze drying by sublimation was suggested and used to estimate the drying time. Under the various conditions, the drying time of pure water and carrot was numerically calculated for the suggested model. Optimal policies of freeze drying were investigated experimentally in a laboratory freeze dryer. It was found that the shortest drying times could be obtained when the chamber pressure and condenser temperature were kept at their lowest values and the best method of heat transfer for sublimation was the conduction involving radiation. The sublimation drying period was finished when the bottom temperature of material could be reached at near $0^{\circ}C$ from frozen temperature.

• Proceedings of the Korea Technical Association of the Pulp and Paper Industry Conference
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• 2006.06a
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• pp.19-29
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• 2006

Drying is the least developed of all unit operations of paper and board manufacture. While groundbreaking developments were Introduced during the several past decades in forming, pressing and calendering, no radical changes occurred in drying. The cylinder-drying technology is now more than 200 years old and, while it was subject to many incremental improvements, many of its inherent problems persist. We believe that conventional drying is now approaching the end of its life and the industry is ready for a major breakthrough in drying. Indeed several innovative technologies already exist at various stages of development or commercialization. In general, the novel drying technologies are striving to increase the drying rate, improve the product quality and boost the energy efficiency of drying. A novel, drying method, $Papridry^{TM}$, which combines conductive and convective heat transfer to obtain very high drying rates, is at an advanced stage of development at Paprican. The results obtained when drying printing paper ana board on a self-standing pilot $Papridry^{TM}$ machine and on the pilot paper machine equipped with a tandem of two $Papridry^{TM}$ units demonstrate both, the high drying rate and improved product quality achieved by using this drying method. A mathematical model of this operation has been developed and the software compiled with this model was used to calculate the effect of installing a $Papridry^{TM}$ unit into an existing dryer section. The model also allows to calculate the z-direction distribution of moisture and temperature at various points of the dryer section.

• Journal of Biosystems Engineering
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• v.31 no.5 s.118
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• pp.410-415
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• 2006

This study was performed to develop thin layer drying equations for green rice. Thin layer drying tests of green rice were conducted at three temperature levels of 30, 40, $50^{\circ}C$ and two relative humidity levels of 30, 50% respectively. The measured moisture ratio were fitted to the selected four drying models (Page, Thompson, Simplified diffusion and Lewis model) using stepwise multiple regression analysis. The overall drying rate increased as the drying air temperature and as relative humidity was increased, but the effect of temperature increase was dominant. Half response time (Moisture ratio=0.5) of drying was affected by both drying temperature and relative humidity Drying rate was mainly affected by relative humidity at drying temperature of $50^{\circ}C$. The results of comparing coefficients of determination and root mean square error of moisture ratio for four drying models showed the Page model was found to ft adequately to all drying test data.

• Journal of Biosystems Engineering
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• v.29 no.6 s.107
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• pp.495-500
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• 2004

This study was performed to develop thin layer drying equations for low temperature. Thin layer drying tests of short grain rough rice were conducted at three low temperature levels of 15, 25, $35^{\circ}C$ and two relative humidity levels of 30, $50\%$, respectively. The measured moisture ratios were fitted to the selected four drying models (Page, Thompson, Simplified diffusion and Lewis model) using stepwise multiple regression analysis. The overall drying rate increased as the drying air temperature was increased and as relative humidity was decreased, but the effect of temperature increase was dominant. Half response time (Moisture ratio=0.5) of drying was affected by both drying temperature and relative humidity at drying temperature of below $25^{\circ}C$, but at $35^{\circ}C$ was mainly affected by drying temperature. The results of comparing coefficients of determination and root mean square error of moisture ratio for low drying models showed that Page model was found to fit adequately to all drying test data.