| 项目编号: | 1636104
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| 项目名称: | UNS Collaborative Research: Optimizing Microfilter Productivity During Water Treatment: Modeling and Experimental Verification |
| 作者: | Shankar Chellam
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| 承担单位: | Texas A&M Engineering Experiment Station
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| 批准年: | 2014
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| 开始日期: | 2015-08-15
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| 结束日期: | 2018-07-31
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| 资助金额: | USD195401
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| 资助来源: | US-NSF
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| 项目类别: | Standard Grant
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| 国家: | US
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| 语种: | 英语
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| 特色学科分类: | Engineering - Chemical, Bioengineering, Environmental, and Transport Systems
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| 英文关键词: | modeling
; research
; surface water
; orange county water district
; industrial water/wastewater separation
; lake houston water
; water purveyor
; collaborative project
; electrocoagulation/flocculation pretreatment
; excellent filtered water quality
; microfiltration water productivity
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| 英文摘要: | 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. |
| 资源类型: | 项目
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| 标识符: | http://119.78.100.158/handle/2HF3EXSE/93727
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| Appears in Collections: | 影响、适应和脆弱性
气候减缓与适应
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| Recommended Citation: | |
Shankar Chellam. UNS Collaborative Research: Optimizing Microfilter Productivity During Water Treatment: Modeling and Experimental Verification. 2014-01-01.
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