Modelling variability in initial parameters for the simulation of rough rice drying using the covariance decomposition algorithm

Fumihiko Tanaka, Kazuo Morita, Hiroyuki Sekiya, Naoya Izumi, Toshitaka Uchino, Daisuke Hamanaka, Griffiths Gregory Atungulu

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

The drying of rough rice kernels was studied using Monte Carlo modelling of batch behaviour at a constant low air temperature and relative humidity. In order to determine the effects of air temperature and initial moisture content on the drying constant and equilibrium moisture content, the tests were performed in a laboratory-scale drying system at various temperatures (15, 20, 25 and 30 °C) at a constant air velocity of 0.5 m s-1 and a relative humidity of 35±2%. The drying model to describe the batch behaviour was developed by coupling drying kinetics with a Monte Carlo method based on a covariance decomposition algorithm. It was concluded that the proposed drying model could successfully describe the batch drying of rough rice under the range of conditions studied.

Original languageEnglish
Pages (from-to)53-57
Number of pages5
JournalBiosystems Engineering
Volume100
Issue number1
DOIs
Publication statusPublished - May 1 2008

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Food Science
  • Animal Science and Zoology
  • Agronomy and Crop Science
  • Soil Science

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