Title of article :
Extent of mixing in a two-component batch system measured using MRI Original Research Article
Author/Authors :
Y. Lee، نويسنده , , M.J. McCarthy، نويسنده , , K.L. McCarthy، نويسنده ,
Issue Information :
روزنامه با شماره پیاپی سال 2001
Pages :
8
From page :
167
To page :
174
Abstract :
This work addresses the characterization of the degree of mixing to improve quality and efficiency. The objective was to establish a new method to evaluate the extent of mixing using a binary component batch system. Batch mixing was studied in a two-component system of Newtonian oil with a viscosity of 3.5 Pa s and suspended particles with a mean diameter of 200 μm. The experiments were performed with three particle loadings: 10%, 20%, and 30% by weight. Mixing was monitored as a function of number of revolutions using magnetic resonance imaging (MRI). Images were acquired from initially segregated material to fully uniform material. They were analyzed statistically in terms of center and spread characteristics, coefficient of variation, length scale, and mixing intensity. As mixing proceeded, the signal intensity distributions changed dramatically at approximately 500 revolutions for all three particle concentrations. The length scales decreased as mixing proceeded by factors of approximately 1.5, 3.6, and 6.3 for 10%, 20%, and 30%, respectively. Mixing intensities decreased from 1 to less than 0.05. Mixing intensity (I) versus log(no. of revolutions) showed a linear relationship with coefficient of determination values (R2) greater than 0.93 and slope values in a relatively narrow range.
Keywords :
partial least squares , Artificial neural networks , Quality control , Process modelling , Inferential estimation
Journal title :
Journal of Food Engineering
Serial Year :
2001
Journal title :
Journal of Food Engineering
Record number :
1165176
Link To Document :
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