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is 0.01. However, the estimation of the hydrogen LDF coefficients is the one with the higher level of uncertainty. When comparing the estimated values per layer of adsorbent, the data obtained from the estimation shows that predictions with a higher level of certainty are obtained for the zeolite layer. The final values obtained are now going to be used as initial guess for a new simulation with the aim to investigate if the results are again the same as it happened with the simulation for a constant variance of 0.05 or if better estimations are being obtained. The use of the final values from the simulation present in Figure 4.19 as initial guesses for a new parameter estimation showed that the values obtained were not the optimal values, as happened for the constant variance of 0.05. gPROMS® performed 7 major iterations and the process was interrupted due to a numeric error. With the aim of avoiding this error the bounds of molar and mass fraction as well as the bounds of velocity were changed. The valves coefficients were also increased considering that gPROMS® provided information related with problems in maintaining the desired pressure inside the adsorption bed. Six major iterations were again required to obtained new values which lead us to conclude that the final results from the first simulation with a constant variance of 0.01 were not the optimal ones. The results obtained for the previously mentioned parameter estimation shows that gPROMS® provides estimations with high levels of uncertainty. The LDF coefficients of hydrogen are the ones with the higher level of uncertainty, which could be related with the fact that this is the less strongly adsorbed, and therefore, the effect of the LDF coefficient of this component in the control variable is weaker when compared with the other components. Due to this reason, it is harder to gPROMS® to provide a better estimation. From all the estimations above the parameter estimated with a higher level of certainty was the LDF coefficient for carbon dioxide in the zeolite when considering a constant variance of 0.01. This component is the one which adsorbs more strongly in the considered adsorbent which could explain the fact of this being the better estimation obtained, due to the fact that a slightly change in the parameter being estimated affects strongly the control variable. 4.4.2 Multisite Langmuir parameters estimation With the aim of having more information about the model developed for the Multisite Langmuir isotherm, the model employing this isotherm is going to be used for parameter estimation. For this purpose, breakthrough data obtained in previous simulations presented in this work (see Figure 4.14) are going to be subjected to some treatment with Microsoft Excel, Pressure Swing Adsorption for Hydrogen Purification Modelling and Simulation 44PDF Image | PRESSURE SWING ADSORPTION FOR THE PURIFICATION OF HYDROGEN
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