Design and Operation of Pressure Swing Adsorption Processes

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Design and Operation of Pressure Swing Adsorption Processes ( design-and-operation-pressure-swing-adsorption-processes )

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Performance variables H2 purity H2 recovery CH4 purity CH4 recovery Rigorous model 0.9987 0.1095 0.9421 0.2091 ROM 0.9987 0.1094 0.9425 0.2094 6.5 Case Study - Hydrogen PSA From MATLAB after integration From AMPL after solving algebraic equations 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 00 0 400 0.5 20 40 Bed length 1 0 Time 0.5 Bed length 1 0 20 Time Figure 6.6: Comparison of methane mole fraction profile for adsorption step obtained after integrating in MATLAB and solving simultaneously in AMPL Table 6.7: Comparison of rigorous model and ROM based on the performance variables are quite steep in the spatial dimension, especially for the adsorption and depressurization steps, and ROM effectively captures such steep behavior, besides adequately capturing system’s behavior in the temporal dimension. To check for the accuracy of the temporal discretization in AMPL, we integrate the DAE system of the ROM in MATLAB as well as solve it in AMPL without the CSS conditions. Figure 6.6 compares the gas-phase methane mole fraction profile for the adsorption step for both approaches. Clearly, the profiles compare very well and show that the additional errors introduced by a pre-determined temporal discretization in AMPL are negligible for this system of equations. Table 6.7 compares the purity and recovery of hydrogen and methane obtained from the rigorous model as well as the reduced-order model at CSS. This can be seen as another basis Chapter 6. Reduced-order Modeling for Optimization 123

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