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8 Summary and final conclusions 83 measurement method is inordinately unrepresentable in relation to standard operating conditions of the PSA system. The adsorbent bed would need to be fully regenerated and pressurised with helium; then, the synthetic air stream could be directed into the column. Although, in the PSA applications, the CMS surface is always occupied with oxygen and nitrogen molecules, since their adsorption takes place at atmospheric pressure; whereby the column pressurisation is accomplished with the compressed air stream itself. Apart from that, since the classical approach of breakthrough curve fitting is based on the assumption of the flow pattern corresponding to axially dispersed plug-flow; the occurrence of inevitable effects such as gas channeling within the column, as well as back-mixing in the tube transporting the effluent to the detector, makes this method somewhat unreliable [107]. Notwithstanding the presented explanations, it could still be beneficial to analyse the breakthrough curve in terms of its potential asymmetries, which could ultimately confirm the diffusional resistance occurring mainly in micropores mouths [108]. Without those results, the considerations presented in this work are purely theoretical. Furthermore, detailed experimental data regarding measurements of pure-component adsorption isotherms, exposing the amount adsorbed in the function of time at intermediate pressure steps, were not available. In this work, the only accessible insight into mass transfer kinetics concerns the adsorption of synthetic air mixture, as presented in Fig. 3.5- 2. Based on those data, however, the evaluation of a suitable kinetic model was not feasible. Therefore, an enhanced focus should be placed on the experimental study of the mass transfer rate. Apart from that, the estimation of mass dispersion along the adsorber column could also be improved by performing experimental research. In this work, the axial dispersion coefficient is calculated according to empirical equation presented in Eq. 3.1-4, which does not account for any gas channelling effect, either in the core of the packed bed or alongside the adsorber wall. However, the presence of those effects was concluded based on PSA performance results, as well as experimentally confirmed in the measurement of pressure drop caused by uncontrolled flow resistances in the piping system, as presented in Appendix 10.5. Therefore, the correction of axial dispersion coefficient should be considered, since both effects of mass dispersion and mass transfer kinetics are influencing the progress of mass transfer zone; thus the correct prediction of PSA dynamics. 8.3 Outlook In this work, the performance of a twin-bed PSA pilot plant for the production of high-purity nitrogen was tested under many different process conditions, cycle organisation strategies, and design parameters; however, the research can be extended to investigate some unusual energy- reduction techniques or some distinct issues occurring during the industrial operation of those systems. Some of the activities considered are described below. (1) Execution of multi-parameter analysis in order to forecast straightforwardly the PSA performance indicators based on results at miscellaneous operating situations and customer requirements. Therefore, it is advantageous to perform a classical multivariate regression analysis or to implement machine learning techniques to study the PSA system behaviour based on the probability analysis. In particular, artificial neural networks can be used to derive the output of the PSA system [109]. By means of this strategy, the optimum PSA performance could be established.PDF Image | Modelling and Simulation of Twin-Bed Pressure Swing Adsorption Plants
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