New formulation of optimization‐based simulation of a pressure swing adsorption process: Hybrid dynamic optimization

Ayoub, Shahid; Tondeur, Daniel; Latifi, M.A.

doi:10.1002/aic.12344

Cited by 4 publications

(2 citation statements)

References 26 publications

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“…Moreover, experimental data are seldom available, which is especially the case for a grassroots PSA cycle design. Other studies considered linear − or exponential ,− pressure changes during the CnD step. Although these seem reasonable, it is not clear how well these functional approximations represent the actual relationship between the pressure and flow rate at the exit of the bed, especially for a VSA cycle where a vacuum pump is necessarily used.…”

Section: Introductionmentioning

confidence: 99%

Importance of Incorporating a Vacuum Pump Performance Curve in Dynamic Adsorption Process Simulation

Jiang

Ebner

Ritter

2019

Ind. Eng. Chem. Res.

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The importance of incorporating a vacuum pump performance curve into a mathematical model that describes the regeneration steps in a vacuum swing adsorption (VSA) cycle was assessed. This was accomplished by evaluating the relationship between the pressure and flow rate at the exit of a 13X zeolite bed, initially and uniformly saturated with 70 vol % CO2 in N2 at 333.15 K and 1 atm, which then underwent only countercurrent depressurization and light reflux (LR) steps, that is, the regeneration steps in a VSA cycle. Overall, this study revealed that it is imperative to use a realistic vacuum pump model in cyclic adsorption process simulation, especially for estimating the ideal isentropic energy consumed during the regeneration steps in a VSA cycle, and it revealed the possible inaccurate performance predictions that might result when using a valve equation alone to describe these steps. The study on the effect of valve size (c v) without the vacuum pump present to mimic the behavior of the vacuum pump performance curve showed that ideal isentropic energies from the valve equation can be overestimated significantly, in this case ranging from 1 to 6 kJ/mol CO2 removed. The study on the effect of LR flow rate only with the valve or only with the vacuum pump present showed marked differences in performance when using a valve equation to mimic a vacuum pump performance curve during the LR step. As secondary outcomes, the study on the effect of bed size when operating with a Pfeiffer ACP 40 vacuum pump alone showed that it was easier for it to regenerate beds of a smaller size; it showed a power consumption benefit during depressurization, a feature of VSA processes when the vacuum pump is not restricted by a valve; and it showed how to determine an approximate bed size. The study on the effect of valve size (c v) when placed before the suction side of the vacuum pump showed that a valve should never be placed there to avoid choking of the vacuum pump and expending more energy; it showed that if a valve is required for flow rate control, then its c v should be chosen carefully; and it showed how to determine an approximate valve size.

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Section: Introductionmentioning

confidence: 99%

Importance of Incorporating a Vacuum Pump Performance Curve in Dynamic Adsorption Process Simulation

Jiang

Ebner

Ritter

2019

Ind. Eng. Chem. Res.

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“…Other researchers have formulated CSS calculations as a dynamic optimization problem (Ayoub et al, 2011) or used (quasi)-Newton methods to accelerate convergence to CSS (Smith and Westerberg, 1992). Most PSA simulators use direct substitution (i.e., Picard iterations, fixed-point methods) to calculate CSS operating points.…”

mentioning

confidence: 99%

Pressure Swing Adsorption Optimization Strategies for CO2 Capture

Wang

Dowling

Krieft

et al. 2015

Computer Aided Chemical Engineering

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Multivariable model predictive control of a novel rapid pressure swing adsorption system

2017

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A multivariable model predictive control (MPC) algorithm is developed for the control and operation of a rapid pressure swing adsorption (RPSA)‐based medical oxygen concentrator. The novelty of the approach is the use of all four step durations in the RPSA cycle as independent manipulated variables in a truly multivariable context. The RPSA has a complex, cyclic, nonlinear multivariable operation that requires feedback control, and MPC provides a suitable framework for controlling such a multivariable system. The multivariable MPC presented here uses a quadratic optimization program with integral action and a linear model identified using subspace system identification techniques. The controller was designed and tested in simulation using a complex, highly coupled, nonlinear RPSA process model. The model was developed with the least restrictive assumptions compared to those reported in the literature, thereby providing a more realistic representation of the underlying physical phenomena. The resulting MPC effectively tracks set points, rejects realistic process disturbances and is shown to outperform conventional PID control. © 2017 American Institute of Chemical Engineers AIChE J, 64: 1234–1245, 2018

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New formulation of optimization‐based simulation of a pressure swing adsorption process: Hybrid dynamic optimization

Abstract: International audienc

Cited by 4 publications

References 26 publications

Importance of Incorporating a Vacuum Pump Performance Curve in Dynamic Adsorption Process Simulation

Importance of Incorporating a Vacuum Pump Performance Curve in Dynamic Adsorption Process Simulation

Pressure Swing Adsorption Optimization Strategies for CO2 Capture

Multivariable model predictive control of a novel rapid pressure swing adsorption system

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