单 位：
华南农业大学南方农业机械与装备关键技术教育部重点实验室
关键词：
干燥;含水率;模型;稻谷;逆流循环干燥;瞬态模型;粮温;分布
摘 要：
为了解析稻谷逆流循环干燥过程,基于热质传递理论构建了瞬态解析模型,并采用一阶迎风有限差分格式数值求解,给出了整仓含水率、粮温、干燥段介质温度、含湿量的瞬态变化特征。模拟研究显示,当干燥条件恒定时,系统内含水率随时间和空间均呈现下降期、平台期交替的阶梯变化特征,稻谷温度沿粮流方向呈现下降期、上升期交替的锯齿状分布特征;含水率极大值点在第一干燥段内往复迁移,极小值点则始终处在第二干燥段出粮口处;整仓含水率变异系数随时间变化范围0.006～0.059,当干燥经历完整循环周期时,变异系数最小。不同干燥条件下的模拟发现,进气温度、初始含水率越大,平均干燥速率越大,但粮流速度的变化对平均干燥速率的影响较小。干燥试验显示,在动态干燥条件下,排粮含水率和温度解析值与实测值的变化趋势一致,含水率的解析均方根误差为0.99%,粮温的解析均方根误差为0.49℃,证实了循环干燥解析模型的有效性与可靠性。研究结果为循环干燥系统分析、状态跟踪与参数动态匹配提供了数学解析方法。
译 名：
Transient mathematical modeling of circulation counter-flow rice drying system
作 者：
Fang Zhuangdong;Li Changyou;Zhao Yikun;Key Laboratory of Key Technology on Agricultural Machine and Equipment Ministry,South China Agricultural University;
关键词：
drying;;moisture content;;models;;rice;;circulation counter-flow drying;;transient model;;grain temperature;;distribution
摘 要：
The circulation dryer consists of drying, tempering, preheating and discharging stages, is the main equipment for rice drying in southern China. During circulation drying process, grain flows from top to bottom and returns to the top by elevator; air passes through the drying stages after being heated and carries away the vapor form grain; high temperature gas from boiler transfers heat to the air through the heating exchanger, and the flue gas passes through the heating tube in the preheating stage. Drying system may behave unexpectedly because of fluctuations of heat supply, medium flow, material flow and environmental state. In order to achieve greater drying capacity, milling quality, and energy efficiency, matching drying parameters with the system states dynamically is necessary. Due to the complexity of drying process, it is difficult to measure the system states accurately and comprehensively by sensors, therefore, it is meaningful to propose a mathematical model to predict the behavior of drying system. In this study, a transient mathematical models of various stages were developed for circulation counter-flow rice drying system based on heat and mass balance. The models consists of partial differential equations involving moisture content, grain temperature, humidity and air temperature. As the coupling of variables, analytic solutions of the PDEs could not be obtained, it was solved by finite difference method with first order upwind difference scheme. A algorithm was programmed on MATLAB and the distribution of moisture content, grain temperature, humidity and air temperature throughout drying bed varied with time was presented. The numerical simulation results showed that in counter-flow drying stages, moisture content decreased and grain temperature rise along the grain-flow, humidity increased and air temperature decreased along the air-flow; high moisture grain versus low temperature air, low moisture grain versus high temperature air, which accorded with demand of drying energy. When the operation condition was constant, moisture content alternated between descent-phase and plateau-phase with position in drying bed and time; grain temperature alternated between descent-phase and ascent-phase with position in drying bed; the maximum moisture point moved periodically in the first drying stage, and the minimum one was at the outlet of second drying stage constantly. Coefficient of variation(c.v.) of moisture distribution can be used to measure the uniformity of dried products, statistical results showed the c.v. of moisture distribution changed with time periodically, ranging from 0.006 to 0.059, and was minimum when drying system went through compete cycling time. At different operation conditions, the higher the inlet air temperature and initial moisture content, the higher the average drying rate, however, the effect of grain flow velocity on average drying rate was not significant. The model was validated by performing experiments in a circulation counter-flow rice dryer(5 HP-20). The predictions of outlet moisture content and grain temperature vs. drying time were observed to be close to the measured values in the drying experiments, the root mean square error between predicted and measured values of moisture content and grain temperature were 0.99%d.b, and 0.49 ℃, respectively. The model can be applied to analyze and predict the circulation drying process.
