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膜生物反应器运行过程中有效减轻膜污染的建模与模拟辅助策略

Modeling and simulation-assisted strategies for effective membrane-fouling mitigation during membrane bioreactor operation.

作者信息

Homayoonfal Maryam, Hajhashemi Zohre, Hajheidari Maryam, Rezaei Fateme, Nadali Mohammad Saber

机构信息

Department of Chemical Engineering, College of Engineering, University of Isfahan, P.O. Box 81746-73441, Isfahan, Iran.

出版信息

Heliyon. 2024 Oct 4;10(20):e38953. doi: 10.1016/j.heliyon.2024.e38953. eCollection 2024 Oct 30.

DOI:10.1016/j.heliyon.2024.e38953
PMID:39492913
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11531625/
Abstract

This research principally aimed to present a suitable strategy for membrane-fouling mitigation in membrane-bioreactors (MBRs). The current strategies for membrane-fouling mitigation before initiating the process in many cases, are unmodifiable for a specific MBR system along the operations. Thus, membrane-fouling strategies during filtration should be applied. To select the best and most economical method for controlling fouling during the operations, the quality (site and mechanism) as well as quantity (thickness, mass, and porosity of the cake layer, and pore resistances) of fouling should be predicted. Accordingly, in this research, two powerful tools, i.e. modeling and simulation, have been used for predicting the quality and quantity of fouling, respectively. Through modeling, the best model describing the site and mechanism of fouling was chosen. Through simulation, the thickness, mass and porosity of the cake layer, along with resistance of cake and pores were calculated. In addition, the match between the results of modeling, simulation, and experimental results confirmed the accuracy of the performed predictions. Ultimately, to achieve the minimum membrane-fouling during filtration, based on the modeling results, the general solution of washing (physical or chemical), and based on the simulation results, its intensity (low, medium, and high) were proposed.

摘要

本研究的主要目的是提出一种适用于膜生物反应器(MBR)中减轻膜污染的策略。在许多情况下,当前在启动该过程之前减轻膜污染的策略,对于特定的MBR系统在运行过程中是不可修改的。因此,应采用过滤过程中的膜污染控制策略。为了选择运行过程中控制污染的最佳且最经济的方法,应预测污染的质量(位置和机制)以及数量(滤饼层的厚度、质量和孔隙率,以及孔阻力)。因此,在本研究中,分别使用了两种强大的工具,即建模和模拟,来预测污染的质量和数量。通过建模,选择了描述污染位置和机制的最佳模型。通过模拟,计算了滤饼层的厚度、质量和孔隙率,以及滤饼和孔的阻力。此外,建模、模拟和实验结果之间的匹配证实了所做预测的准确性。最终,为了在过滤过程中实现最小的膜污染,基于建模结果,提出了清洗(物理或化学)的通用解决方案,并基于模拟结果,提出了清洗强度(低、中、高)。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f84b/11531625/3eeea4594f13/gr6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f84b/11531625/44047e481d50/ga1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f84b/11531625/8d5b00736d51/gr1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f84b/11531625/328442caffdc/gr2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f84b/11531625/a8a315b9d72a/gr3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f84b/11531625/871c47a284d9/gr4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f84b/11531625/47c00877f724/gr5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f84b/11531625/3eeea4594f13/gr6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f84b/11531625/44047e481d50/ga1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f84b/11531625/8d5b00736d51/gr1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f84b/11531625/328442caffdc/gr2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f84b/11531625/a8a315b9d72a/gr3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f84b/11531625/871c47a284d9/gr4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f84b/11531625/47c00877f724/gr5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f84b/11531625/3eeea4594f13/gr6.jpg

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