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5 Validation of the mathematical model 72 determined productivity and air demand values. For instance, if simulating the PSA process at fixed productivity, the highest relative errors obtained at product purity of 10 ppm O2 would correspond to an absolute error of merely 12.09 ppm O2 in purity prediction, and 0.238 m3n/h air / m3n/h N2 in air demand prediction; both of which do not amount to much in an absolute scale. This issue would be unlikely to occur while using CMS adsorbents of improved separation efficiency, especially in the high-purity range; since they exhibit less pronounced gradients of productivity and air demand in the function of nitrogen purity. Therefore, these materials would probably be represented better by the PSA mathematical model rather than the originally selected Shirasagi MSC CT-350 grade in this work. However, a few general conclusions can be stated. At almost every investigated process condition, the developed model underestimates the productivity and consequently overestimates the air demand at a product purity level of 10 ppm O2. The possible explanations of this effect include minor inaccuracies originating both in PSA experimental set-up and in the mathematical description of the process, e.g. • underestimation of the adsorbent equilibrium loading by the IAST approach as presented in Fig. 3.3-3, most likely due to coarse IAST theory assumptions as neglecting adsorbate- adsorbate and adsorbate-surface interactions as well as omitting heterogeneous surface of CMS; • lack of experimental equilibrium data of pure oxygen adsorption at very low pressure (< 0.01 bar abs) as presented in Fig. 3.3-1a, as well as deviations in the amount adsorbed prediction by Sips isotherm model at low pressures; • inaccuracies in the estimation of oxygen mass transfer rate according to Darken approach due to inexact calculation of the slope of isotherm at very low pressure; • inhomogeneous gas distribution along the adsorber column in the pilot-plant and therefore channelling effects; • adsorption/desorption of other air components, especially carbon dioxide and moisture, which most likely cause superimposing effects on the gas temperature along the adsorber column, as presented in Fig. 5.4-1; or • imprecise evaluation of the multi-component diffusion process in the pore system of the CMS adsorbent. It is highly possible that different inaccuracies are overlapping, therefore increasing the simulation error of the performance indicators. It is most likely, that – in combination with a modified IAST approach – the biggest improvement of the model is possible by introducing an additional gaseous key component combining the effects of moisture and carbon dioxide adsorption for a better simulation of their thermal influences. However, the measurement of pure oxygen isotherm at very low pressure (1 × 10-5 bar abs) could also bring a certain improvement in simulation accuracy.PDF Image | Modelling and Simulation of Twin-Bed Pressure Swing Adsorption Plants
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