High‐purity Nitrogen by pressure‐swing adsorption

Shirley, Arthur I.; Lemcoff, N.O.

doi:10.1002/aic.690430215

Cited by 23 publications

(12 citation statements)

References 15 publications

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“…The main reason for this finding is probably the different flow velocity in the adsorber columns at different purities and its effect on the mass transfer and diffusion conditions (Shirley and Lemcoff 1997). Thus, the selection of the cycle time is strongly related to the desired product purity level in order to improve the overall system performance.…”

Section: Resultsmentioning

confidence: 99%

Performance determination of high-purity N2-PSA-plants

2020

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The global demand on highly purified gases provided by energy-efficient separation processes grows steadily since decades. An example of particular industrial relevance is nitrogen generated by pressure swing adsorption from compressed air. A kinetically based separation of oxygen from nitrogen is possible by means of carbon molecular sieves (CMS) since oxygen adsorbs remarkably faster in CMS than nitrogen. Even high product purities (5-1000 ppm O 2) are easily achievable in commercial generators. However, only a few studies present experimental findings in this purity range. That comes as no surprise, since experimental conditions are not standardised and the determination of N 2-PSA performance indicators still creates an experimental challenge. Moreover, the design of the setup remarkably influences the experimental results. Thus it is the motivation of this study to develop a multi-step strategy, comprising the definition of a reference process, the derivation of explicit and implicit performance indicators based on either flow meter readings or macroscopic material balances, a verification strategy for experimentally obtained data, and an error consideration, which advices accuracy requirements for analysers and flow meters. The effect of cycle time and operating temperature on the performance indicators is exemplarily studied at high purities by means of the proposed strategy.

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Section: Resultsmentioning

confidence: 99%

Performance determination of high-purity N2-PSA-plants

2020

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“…The proper determination of the cycle time in the PSA process is a relevant factor while aiming for a performance improvement, especially in the case of kinetically-controlled separations. Because the shape of the mass transfer zone (MTZ) is sensitive to the adsorption duration at high product purities [13], the influence of the half-cycle time on PSA performance indicators is investigated in the range of 40-60 s while other process conditions follow the reference state. The results are presented in Tables 10 and 11; Fig.…”

Section: Effect Of the Half-cycle Timementioning

confidence: 99%

“…However, the N 2 -PSA process simulations involving LDF models present the results almost exclusively at low product purity levels (< 99% N 2 ) [7][8][9][10][11][12]. Solely, Shirley and Lemcoff published predicted and experimental data in the range of higher nitrogen purity (> 99.9% N 2 ), describing the mass transfer kinetics through the Langmuir adsorption rate expression as an approximation of the slit-potential-rate model introduced by LaCava [13][14][15]. While the influence of cycle time on the PSA process performance was investigated and confirmed by the model qualitatively, the accuracy values were completely omitted.…”

Section: Introductionmentioning

confidence: 99%

Dynamic simulation of high-purity twin-bed N2-PSA plants

Marcinek

Möller²,

Guderian

et al. 2021

Adsorption

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At present, nitrogen production from air by pressure swing adsorption (PSA) is simulated almost exclusively at low product purity levels (< 99% N2). However, with increasing global demand for highly purified gases provided by energy-efficient separation processes the requirement for either extensive experimental research in the high-purity range or predictive computer simulations arises. This paper presents a mathematical model of a twin-bed PSA plant equipped with a carbon molecular sieve (Shirasagi MSC CT-350) for the generation of high-purity nitrogen (99.9–99.999% N2). The model is implemented in the process simulator Aspen Adsorption™. The influence of operating conditions as well as the cycle organisation on the process performance is validated, especially the influence of pressure, temperature, half-cycle time, purge flow rate, and cutting time. The precision of the performance prediction by numerical simulations is critically discussed. Based on the new insights efficiency improvement strategies with a focus on reduced energy consumption are introduced and discussed by means of radar charts.

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“…Recently, several theoretical and experimental studies of a kinetically controlled PSA separation have been reported, see LaCava et al [2,3], Farooq and Ruthven [4], Lemcoff and LaCava [5], Lemcoff et al [6], Shirley and LaCava [7], Ng et al [8], Schork et al . [9], and Shirley and Lemcoff [10].…”

Section: Introductionmentioning

confidence: 97%

Use of Neural Networks in the Simulation and Optimization of Pressure Swing Adsorption Processes

Lewandowski¹,

Lemcoff²,

Palosaari

1998

Chem. Eng. Technol.

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In this work a method for the simulation and optimization of a pressure swing adsorption process for the separation of nitrogen from air by using neural networks was developed. The model is used to obtain a prediction for the process performance, namely, the specific product and yield, over a wide range of operating conditions. These results are compared with the predictions from a mass tranfer model, and a very good agreement is found. The network developed is also used to minimize a cost objective function, and it is shown that it can easily be used in process optimization and/or control.

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High‐purity Nitrogen by pressure‐swing adsorption

Cited by 23 publications

References 15 publications

Performance determination of high-purity N2-PSA-plants

Performance determination of high-purity N2-PSA-plants

Dynamic simulation of high-purity twin-bed N2-PSA plants

Use of Neural Networks in the Simulation and Optimization of Pressure Swing Adsorption Processes

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