Optimizing Air Scouring Energy for Sustainable Membrane Bioreactor Operation by Characterizing the Combination of Factors Leading to Threshold Limiting Conditions.

IF 3.3 4区 工程技术 Q2 CHEMISTRY, PHYSICAL Membranes Pub Date : 2024-02-23 DOI:10.3390/membranes14030058
Changyoon Jun, Kimia Aghasadeghi, Glen T Daigger
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Abstract

Key operating variables to predict the necessary scour air flowrate in full-scale Membrane Bioreactor (MBR) systems are identified, aiming to optimize energy consumption while avoiding the limiting condition (i.e., rapid increasing total resistance). The resulting metric, referred to here as the K value, was derived by balancing hydrodynamic conditions between the particle deposit rate imposed by permeate flux normalized by fouling condition and its removal by shear stress induced from air scouring. The metric includes air scouring flow, permeate flow, Mixed Liquor Suspended Solids (MLSS) concentration, Mixed Liquor (ML) viscosity, membrane packing density, and total resistance. Long-term (year-long) data from two full-scale MBR plants were analyzed. The value of K corresponding to limiting operational operation and referred to as the limiting K value, KLim, is estimated by detecting the occurrence of threshold limiting flux from the data stream and calculating the resulting value for K. Then, using KLim, the minimum required specific air demand per permeate (SADp,Crit) is calculated, indicating a potential reduction of over half the air scouring energy in typical operational conditions. The results from this data driven analysis suggest the feasibility of employing KLim to predict the adequate scour air flowrate in terms of dynamically varying operational conditions. This approach will lead to the development of energy-efficient algorithms, significantly reducing scour air energy consumption in the full-scale MBR system.

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通过确定导致阈值限制条件的因素组合,优化空气冲刷能量,实现膜生物反应器的可持续运行。
确定了预测全规模膜生物反应器(MBR)系统中必要冲刷空气流速的关键操作变量,旨在优化能耗,同时避免出现限制条件(即总阻力快速增加)。由此得出的指标(在此称为 K 值)是通过平衡水动力条件得出的,即按污垢条件归一化的渗透通量施加的颗粒沉积率与空气冲刷引起的剪切应力消除的颗粒沉积率之间的关系。该指标包括空气冲刷流量、渗透流量、混合液悬浮固体(MLSS)浓度、混合液(ML)粘度、膜填料密度和总阻力。对两个全规模 MBR 工厂的长期(一年)数据进行了分析。通过检测数据流中出现的阈值限制通量,并计算由此得出的 K 值,估算出与限制运行操作相对应的 K 值,称为限制 K 值 KLim。数据驱动分析的结果表明,采用 KLim 预测动态变化运行条件下的适当冲刷空气流量是可行的。这种方法将有助于开发节能算法,大幅降低全规模 MBR 系统的冲刷空气能耗。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Membranes
Membranes Chemical Engineering-Filtration and Separation
CiteScore
6.10
自引率
16.70%
发文量
1071
审稿时长
11 weeks
期刊介绍: Membranes (ISSN 2077-0375) is an international, peer-reviewed open access journal of separation science and technology. It publishes reviews, research articles, communications and technical notes. Our aim is to encourage scientists to publish their experimental and theoretical results in as much detail as possible. There is no restriction on the length of the papers. Full experimental and/or methodical details must be provided.
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