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• W2768451316 startingPage "234" @default.
• W2768451316 abstract "Process simulators depend on models for estimating basic thermodynamic properties. The parameters of these models are subject to uncertainties due to measurement errors in the experimental data and the uncertainties are typically assumed to be insignificant in process simulation. This work shows the effect of model parameter uncertainty in the process simulation of extractive distillation for the separation of a diisopropyl ether – isopropyl alcohol minimum boiling azeotrope with entrainer 2-methoxyethanol. This is achieved by extending the application of the uncertainty quantification framework used by Hajipour and Satyro to an extractive distillation process. The approach used was to obtain the best fit of experimentally available literature data and then perform uncertainty quantification based on the combined experimental and model uncertainties using a Monte Carlo simulation for the uncertainty propagation and Aspen Plus® for process simulation. This systematic analysis of model uncertainty provides quantitative insight into the propagation of thermodynamic model errors to the various unit operations. It was found that while the propagated model parameters are able to predict the phase behaviour with a 95% certainty, significant deviations may occur for the process simulation. The approach can be used to improve the confidence with which appropriate safe design margins are assigned to columns and identify the risk areas in the design." @default.
• W2768451316 created "2017-12-04" @default.
• W2768451316 creator A5059734735 @default.
• W2768451316 creator A5061549731 @default.
• W2768451316 date "2018-02-01" @default.
• W2768451316 modified "2023-10-17" @default.
• W2768451316 title "Sensitivity of process design to phase equilibrium uncertainty: Study of the isopropanol + DIPE + 2-methoxyethanol system" @default.
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• W2768451316 doi "https://doi.org/10.1016/j.fluid.2017.11.027" @default.
• W2768451316 hasPublicationYear "2018" @default.
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