Benchmarking Thermodynamic Models for Optimization of PSA Oxygen Generators
Michael L. Carty and
Stephane Bilodeau ()
Additional contact information
Michael L. Carty: Smart Phases Inc., Plattsburgh, NY 12903, USA
Stephane Bilodeau: Smart Phases Inc., Plattsburgh, NY 12903, USA
J, 2023, vol. 6, issue 2, 1-24
Abstract:
In this review, the authors conducted benchmarks for three thermodynamic models to analyze PSA-based medical oxygen concentrator (MOC) systems to allow for optimization and operational flexibility. PSA oxygen generator plants are good medical-grade oxygen sources, a crucial tool in healthcare from the primary to the tertiary level. However, they must be designed accordingly and properly operated, considering key design goals such as improving adsorbent productivity, improving oxygen recovery, and innovating to reduce unit size and weight. The importance of mapping the performance of various design and operating requirements or designs themselves on outlet product specifications and production effectiveness is outlined. Emphasizing optimal PSA design and operation, the authors suggest considering simulation-based optimization frameworks or high-fidelity modeling for the optimal layout and operation conditions of adsorption-based MOC systems. Notwithstanding, a simplified first-principles-based model with additional assumptions and simplifications generates a large volume of scenarios faster. Therefore, it represents a good approach for a feasibility study dealing with many options and designs or even the real-time monitoring of PSA operating conditions. All this paved the way for efficient translation into machine learning models and even deep learning networks that might be better suited to simulate the complex PSA process. The conclusion outlines that PSA-based plants can be flexible and effective units using any of the three models when properly optimized.
Keywords: oxygen generator; pressure swing adsorption; medical oxygen; COVID-19; PSA; thermodynamic; NAPDE; exergy (search for similar items in EconPapers)
JEL-codes: I1 I10 I12 I13 I14 I18 I19 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations:
Downloads: (external link)
https://www.mdpi.com/2571-8800/6/2/23/pdf (application/pdf)
https://www.mdpi.com/2571-8800/6/2/23/ (text/html)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:gam:jjopen:v:6:y:2023:i:2:p:23-341:d:1162903
Access Statistics for this article
J is currently edited by Ms. Angelia Su
More articles in J from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().