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5 Conclusions 5.1 Accomplished goals A breakthrough model, using the multilayer Langmuir-Freundlich isotherm, was validated in the course of the present work, providing good predictions for the breakthrough time. However, for higher pressures the deviation between the simulation and experimental data increases, leading to the consideration that š¯‘˛š¯‘’š¯‘˛ might be over-estimated. Although the shape of the curves obtained through gPROMSĀ® simulation have some deviation compared to the experimental data, it was assumed that the validation of the considered model was accomplished. Considering that the physical properties present in Multiflash are provided with the purpose of being employed in a wide range of industrial processes can affect the prediction of the breakthrough profiles. This fact could explain the differences between experimental and simulation results, when binary mixtures were employed as feed. The employment of the multilayer Langmuir-Freundlich isotherm in other situations present in the literature showed that good predictions are obtained when only one layer of activated carbon is used. Satisfactory predictions are obtained for a process with two layers of adsorbent, activated carbon and zeolite, for a feed pressure of 6.5 bar. However, a considerable deviation between experimental and simulation results takes place when the feed pressure is increased to 8 bar. A Multisite Langmuir isotherm was successfully added to the gML libraries and a validation of the temperature profile through the entire bed was accomplished. The comparison between the literature and simulation loading profiles for methane showed that an over prediction of š¯‘˛š¯‘’š¯‘˛ also takes place when using this isotherm model. The Parameter Estimation tool present in gPROMSĀ® was employed with the purpose of estimating the LDF coefficients in the process concerning the validation of the Langmuir- Freundlich isotherm and the isotherm parameters of the Multisite Langmuir model. Two different variance models were applied in these estimations: constant variance and relative constant variance. However, results showed that for the process being considered the use of the relative constant variance model did not provide good approximations between the measured and predicted values. In the simulations using the constant variance, variances of 0.05 and 0.01 were applied. The results provided by gPROMSĀ® show that, in the situations considered for the parameter Pressure Swing Adsorption for Hydrogen Purification Conclusions 47PDF Image | PRESSURE SWING ADSORPTION FOR THE PURIFICATION OF HYDROGEN
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