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  • 标题:Determination of the Uncertainty Bounds of a Continuous Distillation Code: Effect of Input Variability and Model Uncertainty
  • 本地全文:下载
  • 作者:J.M. Gozalvez-Zafrilla ; J.M. Gozalvez-Zafrilla ; J. Carlos García-Díaz
  • 期刊名称:Procedia - Social and Behavioral Sciences
  • 印刷版ISSN:1877-0428
  • 出版年度:2010
  • 卷号:2
  • 期号:6
  • 页码:7668-7669
  • DOI:10.1016/j.sbspro.2010.05.170
  • 语种:English
  • 出版社:Elsevier
  • 摘要:AbstractIn this work, the effect of input variability and model uncertainty on the distillate composition of a continuous distillation tower is studied. To do that, we developed a stationary distillation code by combining mass and energy balance equations with a liquid-vapor equilibrium model and tray efficiency correlations. Feed and model uncertainties were modeled by using normal and uniform distributions respectively. A Monte Carlo propagation method was used to determine the upper and lower uncertainty margins of the distillate composition. The results of the application to a methanol-water distillation showed that the model uncertainty is as high as that of the feed variability. The information can be useful for the robust design of distillation towers.
  • 关键词:Uncertainty analysis;Monte Carlo method;Continuous distillation
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