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accurate models to predict dynamic behavior of pressure swing adsorption processes. Currently, research efforts are aimed at improvements in multicomponent mixture isotherms, and better understanding of mass transfer phenomena, axial dispersion and fluid transport within packed beds [169, 206]. We also discussed operation strategies for two-bed as well as multi-bed PSA processes, and mentioned that industrial PSA systems carry out high purity separations with the help of so- phisticated cycles involving complex sequences of operating steps. Designing such complicated sequences and PSA processes is generally non-intuitive, and thus a systematic methodology is desired which can ameliorate the arduous task of synthesizing PSA cycles. In the next few chapters, we present a novel optimization-based framework to design optimal PSA cycles, and illustrate it with the help of examples motivated from the application of PSA for carbon capture. Finally, we showed that bed model for PSA processes is defined by hyperbolic partial differ- ential and algebraic equations (PDAEs) with high nonlinearities arising from non-isothermal effects and nonlinear adsorption isotherms, and with solution profiles represented by steep ad- sorption fronts. Optimization of such systems presents a significant computational challenge to current algorithms. To address this, we present in subsequent chapters a novel optimization algorithm based on reduced-order modeling. 2.6 Concluding Remarks Chapter 2. Pressure Swing Adsorption 34PDF Image | Design and Operation of Pressure Swing Adsorption Processes
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