Theses and Dissertations

ORCID

https://orcid.org/0000-0002-2921-151X

Issuing Body

Mississippi State University

Advisor

Knizley, Alta

Committee Member

Cho, Heejin

Committee Member

Bhushan, Shanti

Committee Member

Singh, Prashant

Committee Member

Hwang, Joonsik

Date of Degree

12-8-2023

Original embargo terms

Campus Access Only 1 Year

Document Type

Dissertation - Campus Access Only

Major

Mechanical Engineering

Degree Name

Doctor of Philosophy (Ph.D)

College

James Worth Bagley College of Engineering

Department

Department of Mechanical Engineering

Abstract

Fibrous air filters are commonly used to capture airborne particles due to their potential for a relatively high capture efficiency and low airflow resistance. Their performance characteristics make them ideal candidates in many instances, spanning a wide range from residential to sensitive industrial applications. However, as more particles are captured, the performance of the filter will evolve. This evolution of performance typically manifests as a higher capture efficiency and higher airflow resistance resulting from the additional particulate deposits. The prediction of fibrous filter performance has been the focus of research for many decades, resulting in numerous analytical, numerical, and empirical models. This work seeks to improve upon the state of aerosol filtration by investigating the process through which these models are developed and validated. To meet this objective, three major efforts are implemented: 1) a comprehensive literature review, 2) an aerosol and media measurement analysis focusing on instrumentation and Scanning Electron Microscope (SEM) imagery, and 3) the creation of a process to analyze and develop fibrous air filter models. A conceptual foundation is provided by the literature review, establishing the current state of fibrous filtration modeling of solid particles and identifying candidate models for implementation. The influence of data collection and reduction methodology for particle mass loading experiments is explored with an emphasis on the resulting effects towards filtration model development. Furthermore, an automated methodology to measure the physical characteristics of high efficiency particulate air (HEPA) filtration media is investigated, completing the set of variables necessary to predict filtration performance. Finally, an algorithm is proposed to optimize and correlate model variables to collected empirical data, allowing for the improvement of model predictions by investigating model functionality and identifying limitations. Altogether, the three efforts provide a framework through which fibrous aerosol filtration models of solid particles may be developed, validated, and systematically analyzed.

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