UNS Collaborative Research: Optimizing Microfilter Productivity During Water Treatment: Modeling and Experimental Verification

UNS 合作研究：优化水处理过程中微过滤器的生产率：建模和实验验证

• 批准号: 1619745
• 负责人: Shankar Chellam
• 金额: $ 17.94万
• 依托单位: Texas A&M University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-08-15 至 2016-04-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1619745&HistoricalAwards=false
• 关键词: UNS; Collaborative; Research; Optimizing; Microfilter

1510743 Cogan 1510526 Chellam This collaborative project results from the excellent filtered water quality of microfiltration membranes which are increasingly implemented for environmental and industrial water/wastewater separations. Tremendous effort has been spent studying fouling mechanisms during microfiltration; however, membrane fouling control by backwashing and air scouring remain largely unexplored topics. This work builds upon the PIs significant past collaborations to develop models of membrane processes. The proposed research will yield a rigorous mathematical framework along with systematic experimental validation to maximize microfiltration water productivity by maintaining high flux with periodic regeneration and electrocoagulation/flocculation pretreatment. This project provides a unique perspective to train students at all levels in multidisciplinary studies and broadening participation in science and engineering. The proposed research represents a synergistic collaboration between an experimentalist with expertise in membrane filtration and a mathematician with long-term expertise in modeling, fluid dynamics, and optimal control to make potentially transformative contributions to fouling control. The PIs tackle the problem of maximizing the cumulative volume of surface water filtered by hollow-fiber microfiltration incorporating periodic regeneration using optimal control theory. This study also includes sensitivity analysis and data assimilation, complementary mathematical processes used to quantify aspects of variability that arise in both theoretical and experimental studies due to underlying stochastic processes, uncertainty in measurements, or errors in approximations. Complementary laboratory measurements are aimed at generating necessary data for model validation as well as novel interfacial chemical characterization, to discern the sequence of mechanisms that lead to (ir)reversible fouling. Additionally, experiments and modeling will encompass Lake Houston water pretreated using an innovative electrochemical process, namely electrocoagulation with sacrificial aluminum electrodes. The underlying mathematical approach requires specific experimental measurements to determine sensitivity rankings for parameters (and hence physical quantities), statistical likelihood estimates for parameter distributions, and advanced optimal control analysis. Similarly, the experimental approach requires predictions such as key parameter regimes to explore, specific areas of uncertainty that can be reduced, and validation experiments to consolidate the real-world behavior with the mathematical predictions. This is facilitated by seamless collaboration, established over the past seven years or so, that brings together substantial experience on experimental and theoretical aspects to the project. Input will also be obtained from external stakeholders including a membrane manufacturer (Pall Corporation) and a water purveyor (Orange County Water District) who will provide hollow fibers as well as operational data from their long-term pilot-studies. They will also evaluate our methods and results to attempt to increase the productivity during low-pressure membrane filtration.

1510743 Cogan 1510526 Chellam这个合作项目源于微滤膜的优良过滤水质，微滤膜越来越多地用于环境和工业水/废水分离。微滤过程中膜污染机理的研究已经取得了巨大的进展，但是通过反冲洗和空气冲刷来控制膜污染仍然是一个未被探索的课题。这项工作建立在PI过去的重要合作，以开发膜过程的模型。拟议的研究将产生一个严格的数学框架沿着系统的实验验证，以最大限度地提高微滤水的生产力，保持高通量与定期再生和电凝聚/絮凝预处理。该项目提供了一个独特的视角，以培养学生在多学科研究和扩大参与科学和工程各级。拟议的研究代表了具有膜过滤专业知识的实验学家和具有建模，流体动力学和最优控制长期专业知识的数学家之间的协同合作，为污垢控制做出潜在的变革性贡献。PI解决了使用最优控制理论最大化通过中空纤维微滤过滤的地表水累积体积并定期再生的问题。本研究还包括敏感性分析和数据同化，用于量化由于潜在的随机过程，测量的不确定性或近似误差而在理论和实验研究中出现的变异性方面的补充数学过程。补充实验室测量的目的是产生必要的数据，模型验证以及新的界面化学表征，辨别的顺序的机制，导致（IR）可逆污垢。此外，实验和建模将包括使用创新的电化学过程，即牺牲铝电极电凝聚预处理的休斯顿湖水。基本的数学方法需要特定的实验测量来确定参数（以及物理量）的灵敏度排名，参数分布的统计似然估计，以及高级最优控制分析。类似地，实验方法需要预测，例如要探索的关键参数机制，可以减少的特定不确定性区域，以及验证实验，以巩固现实世界的行为与数学预测。这是由无缝协作，建立在过去七年左右，汇集了大量的经验，实验和理论方面的项目。还将从外部利益相关者处获得投入，包括膜制造商（Pall Corporation）和供水商（橙子县水务区），他们将提供中空纤维以及长期试点研究的运营数据。他们还将评估我们的方法和结果，以尝试提高低压膜过滤过程中的生产率。