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Fixed Bed Adsorption of Water Contaminants: A Cautionary Guide to Simple Analytical Models and Modeling Misconceptions
Separation and Purification Reviews ( IF 5.4 ) Pub Date : 2022-04-27 , DOI: 10.1080/15422119.2022.2039196
Khim Hoong Chu 1
Affiliation  

ABSTRACT

This contribution is intended as a specific review of the modeling approaches used to describe breakthrough curves of water contaminants and as a cautionary guide to some common and persistent modeling misconceptions. Its intended audience is early career researchers working in the area of adsorptive water remediation. First, typical data- and mechanism-driven models are discussed. A brief description of numerical fixed bed models with multiple curve broadening mechanisms (axial dispersion; intraparticle diffusion; film mass transfer; reaction kinetics) is presented. Particular attention is paid to analytical fixed bed models constructed for linear and nonlinear trace systems. Because these models assume that a single curve broadening mechanism is operative, their functional forms are relatively simple. Examples of spreadsheet calculations with these models are provided. A summary describing several egregious misconceptions associated with the use of two phenomenological models based on reaction kinetics (Bohart–Adams and Thomas) and one empirical model (Yoon–Nelson) to fit breakthrough curves is presented. In many previous studies, the three models have been used blindly, resulting in meaningless findings. The author hopes that this article will help the early career researcher avoid repeating the same mistakes.



中文翻译:

水污染物的固定床吸附:简单分析模型和建模误解的警示指南

摘要

本文旨在对用于描述水污染物突破曲线的建模方法进行具体审查,并作为一些常见和持久的建模误解的警示指南。它的目标读者是在吸附水修复领域工作的早期职业研究人员。首先,讨论了典型的数据和机制驱动模型。简要描述了具有多种曲线展宽机制(轴向分散;颗粒内扩散;薄膜传质;反应动力学)的固定床数值模型。特别注意为线性和非线性跟踪系统构建的分析固定床模型。因为这些模型假设单一的曲线加宽机制是有效的,所以它们的函数形式相对简单。提供了使用这些模型进行电子表格计算的示例。摘要描述了与使用基于反应动力学的两个现象学模型(Bohart-Adams 和 Thomas)和一个经验模型(Yoon-Nelson)拟合突破曲线相关的几个严重误解。在以往的许多研究中,这三种模型都被盲目使用,导致了无意义的发现。作者希望本文能帮助刚起步的研究人员避免重蹈覆辙。导致无意义的发现。作者希望本文能帮助刚起步的研究人员避免重蹈覆辙。导致无意义的发现。作者希望本文能帮助刚起步的研究人员避免重蹈覆辙。

更新日期:2022-04-27
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