The New Jersey Institute of Technology's
Electronic Theses & Dissertations Project

Title:	Modeling and design optimization for membrane filters
Author:	Sun, YiXuan
View Online:	njit-etd2021-049 (xvi, 132 pages ~ 7.2 MB pdf)
Department:	Department of Mathematical Sciences
Degree:	Doctor of Philosophy
Program:	Mathematical Sciences
Document Type:	Dissertation
Advisory Committee:	Cummings, Linda Jane (Committee co-chair) Kondic, Lou (Committee co-chair) Shirokoff, David (Committee member) Oza, Anand Uttam (Committee member) Griffiths, Ian (Committee member)
Date:	2021-08
Keywords:	Complex fluid Design optimization Mathematical modeling Membrane filtration Multi-stage and multi-species filtration Porous media
Availability:	Unrestricted
Abstract:	Membrane filtration is widely used in many applications, ranging from industrial processes to everyday living activities. With growing interest from both industrial and academic sectors in understanding the various types of filtration processes in use, and in improving filter performance, the past few decades have seen significant research activity in this area. Experimental studies can be very valuable, but are expensive and time-consuming, therefore theoretical studies offer potential as a cost-effective and predictive way to improve on current filter designs. In this work, mathematical models, derived from first principles and simplified using asymptotic analysis, are proposed for: (1) pleated membrane filters, where the macroscale flow problem of Darcy flow through a pleated porous medium is coupled to the microscale fouling problem of particle transport and deposition within individual pores of the membrane; (2) dead-end membrane filtration with feed containing multiple species of physicochemically-distinct particles, which interact with the membrane differently; and (3) filtration with reactive particle removal using porous media composed of chemically active granular materials. Asymptotically-simplified models are used to describe and evaluate the membrane performance numerically and filter design optimization problems are formulated and solved for a number of industrially-relevant scenarios. This study demonstrates the potential of such modeling to guide industrial membrane filter design for a range of applications involving purification and separation.