Moisture diffusion modeling of parboiled paddy accelerated tempering process with extended application to multi-pass drying simulation

被引:41
作者
Igathinathane, C. [1 ]
Chattopadhyay, P. K. [2 ]
Pordesimo, L. O. [1 ]
机构
[1] Mississippi State Univ, Dept Agr & Biol Engn, Mississippi State, MS 39762 USA
[2] Indian Inst Technol, Post Harvest Technol Ctr, Dept Agr & Food Engn, Kharagpur 721302, W Bengal, India
关键词
paddy; tempering; mathematical model; prolate spheroid; diffusion; drying; vacuum;
D O I
10.1016/j.jfoodeng.2008.02.014
中图分类号
TQ [化学工业];
学科分类号
0817 ;
摘要
Parboiled paddy grain tempering process, often employed in multi-pass drying for milling quality improvement, is theoretically modeled considering a multi-component prolate spheroid geometry in prolate spheroidal coordinate system. The finite difference formulation analyzed the moisture diffusion during tempering and established the effect of vacuum in tempering acceleration. Experimental procedure reported already is essentially a double-pass drying (90 and 75 degrees C) of parboiled paddy with tempering stage at a critical moisture content (20.48% d.b.), where the moisture equilibration is accelerated by the application of vacuum (0-700 mm of Hg vacuum gauge). Boundary conditions of previously developed drying model were appropriately modified to model the tempering process. A supplemental fixed boundary condition with the regular derivative boundary condition and incorporation of tempering diffusivity factor modeled the tempering process and explained the effect of vacuum in tempering acceleration. Analysis of moisture history of nodes indicated that starch component moisture moved towards husk through bran component and the moisture profiles clearly demonstrated the effect of vacuum in temperature acceleration. An exponential relationship (R-2 = 0.9813) adequately modeled the variation of diffusivity factor with the applied vacuum in accelerated tempering. The developed tempering model with drying model can simulate any multi-pass drying processes as well as help perform sensitivity analysis on factors, design equipment, and optimize operations. (C) 2008 Elsevier Ltd. All rights reserved.
引用
收藏
页码:239 / 253
页数:15
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