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结构化化学反应器中的熵产生分析:空气污染物催化燃烧的优化

Analysis of Entropy Production in Structured Chemical Reactors: Optimization for Catalytic Combustion of Air Pollutants.

作者信息

Korpyś Mateusz, Gancarczyk Anna, Iwaniszyn Marzena, Sindera Katarzyna, Jodłowski Przemysław J, Kołodziej Andrzej

机构信息

Institute of Chemical Engineering, Polish Academy of Sciences, Bałtycka 5, 44-100 Gliwice, Poland.

Faculty of Chemical Engineering and Technology, Cracow University of Technology, Warszawska 24, 31-155 Kraków, Poland.

出版信息

Entropy (Basel). 2020 Sep 11;22(9):1017. doi: 10.3390/e22091017.

DOI:10.3390/e22091017
PMID:33286786
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7597110/
Abstract

Optimization of structured reactors is not without some difficulties due to highly random economic issues. In this study, an entropic approach to optimization is proposed. The model of entropy production in a structured catalytic reactor is introduced and discussed. Entropy production due to flow friction, heat and mass transfer and chemical reaction is derived and referred to the process yield. The entropic optimization criterion is applied for the case of catalytic combustion of methane. Several variants of catalytic supports are considered including wire gauzes, classic (long-channel) and short-channel monoliths, packed bed and solid foam. The proposed entropic criterion may indicate technically rational solutions of a reactor process that is as close as possible to the equilibrium, taking into account all the process phenomena such as heat and mass transfer, flow friction and chemical reaction.

摘要

由于经济问题高度随机,结构化反应器的优化并非没有困难。在本研究中,提出了一种熵优化方法。介绍并讨论了结构化催化反应器中的熵产生模型。推导了由流动摩擦、传热传质和化学反应引起的熵产生,并将其与过程产率相关联。熵优化准则应用于甲烷催化燃烧的情况。考虑了几种催化载体变体,包括金属丝网、经典(长通道)和短通道整体式、填充床和固体泡沫。所提出的熵准则可以在考虑所有过程现象(如传热传质、流动摩擦和化学反应)的情况下,指出尽可能接近平衡的反应器过程的技术合理解决方案。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fbf7/7597110/36fb2057f42b/entropy-22-01017-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fbf7/7597110/2d7a1df6cbcd/entropy-22-01017-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fbf7/7597110/7def68db8ee0/entropy-22-01017-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fbf7/7597110/ca4f422debd1/entropy-22-01017-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fbf7/7597110/252f3ca0bfbe/entropy-22-01017-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fbf7/7597110/51d3bec10ff1/entropy-22-01017-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fbf7/7597110/5b3e8b325270/entropy-22-01017-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fbf7/7597110/1b097a95ab67/entropy-22-01017-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fbf7/7597110/37ccd126bdef/entropy-22-01017-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fbf7/7597110/36fb2057f42b/entropy-22-01017-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fbf7/7597110/2d7a1df6cbcd/entropy-22-01017-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fbf7/7597110/7def68db8ee0/entropy-22-01017-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fbf7/7597110/ca4f422debd1/entropy-22-01017-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fbf7/7597110/252f3ca0bfbe/entropy-22-01017-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fbf7/7597110/51d3bec10ff1/entropy-22-01017-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fbf7/7597110/5b3e8b325270/entropy-22-01017-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fbf7/7597110/1b097a95ab67/entropy-22-01017-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fbf7/7597110/37ccd126bdef/entropy-22-01017-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fbf7/7597110/36fb2057f42b/entropy-22-01017-g009.jpg

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