While most filters are made of pleated fibrous media, almost all existing theories of aerosol filtration are developed for flat media placed perpendicular to the air flow. Expressions developed for flat sheet media do not provide accurate information directly useful for designing a pleated filter, and therefore, most progress made in developing pleated filters is based on empiricism. This study is aimed at establishing an enabling knowledge that allows for a better design and optimization of pleated aerosol filters. This study is focused on developing a predictive simulation method that accounts for the influence of a filter’s micro-scale geometric parameters, such as fiber orientation, as well as its macro-scale features, like pleat shape, in predicting the transient pressure drop and collection efficiency with or without the effects of dust loading. The dual-scale simulation method developed in this work is believed to be the only feasible approach for design and optimization of pleated aerosol filters with the current academic-level computational power. Our study is divided into two major tasks of micro- and macro-scale modeling. Our micro-scale studies are comprised of a series of CFD simulations conducted in virtual 2-D or 3-D fibrous geometries that resemble the internal micro-structure of a fibrous medium. These simulations are intended to isolate the effects of each micro structural parameter and study its influence on the performance of the filter medium. In detail, it is intended to propose a method to predict the performance of micro-structures with fiber size distribution. Also, the effects of micro-structural fiber orientation were investigated. Moreover, we offered methodology to predict the performance of noncircular fibers using available analytical expressions for circular fibers. It is shown that the circumscribed circle for a trilobal shaped fiber gives the best prediction for collection efficiency. In macro-scale simulations, on the other hand, the filter medium is treated as a lumped porous material with its properties obtained via micro-scale simulations. Our results showed that more number of pleats helps better performance of pleated filters, however, if the pleat channel becomes blocked by dust cake then this effect is no longer valid.

This thesis examines the particle capture, fibre wetting and droplet flow processes within wet filters collecting solid and liquid aerosols and within filters collecting only liquid aerosols. The processes involved in this type of filtration were examined through a series of experiments and models developed to describe the behaviour of fibre/liquid systems. This work can be summarized in 4 categories: (1) The bounce and immediate re-entrainment of liquid and solid monodisperse aerosols under a stable filtration regime (pre cake formation) by wet and dry fibrous filters. In this work it was found that the solid particles generally exhibited a lower fractional filtration efficiency than liquid particles (of the same size), although this difference decreased in the smaller size fractions. However, for the wet filtration regime (each fibre of the filter was coated by a film of water), no significant difference in filtration efficiency was detectable between solid and liquid aerosols. Either the bounce effect of the particles is inhibited by the liquid film, or the filtration conditions in the wet filter are so different that the aerosol properties are less significant with respect to capture. (2) A microscopic study of the effect of fibre orientation on the fibre wetting process and flow of liquid droplets along filter fibres when subjected to airflow and gravity forces was conducted. The flow of the liquid collected by the fibres was observed and measured using a specially developed micro-cell, detailed in the thesis. The experimental results were compared to a theoretical model developed to describe the flow of droplets on fibres. The theory and experimental results showed a good agreement. A sensitivity analysis of the model was performed which showed the droplet radius to be the most significant parameter. The model has the potential to improve filter self-cleaning and minimise water use. (3) An experimental study of the capture of solid and liquid (oil) aerosols on fibrous filters wetted with water. Variable quantities of liquid irrigation were used, and the possibility for subsequent fibre regeneration after clogging or drying was also studied. It was found that self-cleaning (removal of solid aerosols by water) occurred even under heavily dust-laden conditions, and post evaporation of water. With the collection of oil aerosols on fibres wetted with water, a predominance of the barrel shaped droplet on the fibre was observed, with oil droplets displacing water droplets (if the oil and fibre combination created a barrel shaped droplet), creating various compound droplets of oil and water not previously reported in literature. (4) An extensive experimental investigation of the wetting processes of fibre/liquid systems during air filtration (when drag and gravitational forces are acting) has shown many important features, including droplet extension, oscillatory motion, and detachment from fibres as airflow velocity increases. The droplet oscillation is believed to be induced by the onset of the transition from laminar to turbulent flow as droplet size increases. To model such oscillation it was necessary to create a new conceptual model to account for the forces both inducing and preventing such oscillation. The agreement between the model and experimental results is satisfactory for both the radial and transverse oscillations.

Electrospinning has been the focus of countless studies for the past decades for applications, including but not limited to, filtration, tissue engineering, and catalysis. Electrospinning is a one-step process for producing nano- and/or micro-fibrous materials with diameters ranging typically from 50 to 5000 nm. The simulation algorithm presented here is based on a novel mass-spring-damper (MSD) approach devised to incorporate the mechanical properties of the fibers in predicting the formation and morphology of the electrospun fibers as they travel from the needle toward the collector, and as they deposit on the substrate. This work is the first to develop a physics-based (in contrast to the previously-developed geometry-based) computational model to generate 3-D virtual geometries that realistically resemble the microstructure of an electrospun fibrous material with embedded particles, and to report on the filtration performance of the resulting composite media. In addition, this work presents a detailed analysis on the effects of electrospinning conditions on the microstructural properties (i.e. fiber diameter, thickness, and porosity) of polystyrene and polycaprolactone fibrous materials. For instance, it was observed that porosity of a PS electrospun material increases with increasing the needle-to-collector distance, or reducing the concentration of PS solution. The computational tool developed in this work allows one to study the effects of electrospinning parameters such as voltage, needle-to-collector distance (NCD), or polymer concentration, on thickness and porosity of the resulting fibrous materials. Using our MSD formulations, a new approach is also developed to model formation and growth of dust-cakes comprised of non-overlapping non-spherical particles, for the first time. This new simulation approach can be used to study the morphology of a dust-cake and how it impacts, for instance, the filtration efficiency of a dust-loaded filter, among many other applications.

Clean air is a global health concern. Each year more than seven million people across the globe perish from breathing poor quality air. Development of high efficiency particulate air (HEPA) filters demonstrate an effort to mitigate dangerous aerosol hazards at the point of production. The nuclear power industry installs HEPA filters as a final line of containment of hazardous particles. Advancement air filtration technology is paramount to achieving global clean air. An exploration of analytical, experimental, computational, and machine learning models is presented in this dissertation to advance the science of air filtration technology. This dissertation studies, develops, and analyzes alternative air filtration materials and methods of analysis that optimize filtration efficiency and reduce resistance to air flow. Alternative nonwoven filter materials are considered for use in HEPA filtration. A detailed review of natural and synthetic fibers is presented to compare mechanical, thermal, and chemical properties of fibers to desirable characteristics for air filtration media. An experimental effort is undertaken to produce and evaluate new nanofibrous air filtration materials through electrospinning. Electrospun and stabilized nanofibrous media are visually analyzed through optical imaging and tested for filtration efficiency and air flow resistance. The single fiber efficiency (SFE) analytical model is applied to air filtration media for the prediction of filtration efficiency and air flow resistance. Digital twin replicas of nonwoven nanofibrous media are created using computer scripting and commercial digital geometry software. Digital twin filters are visually compared to melt-blown and electrospun filters. Scanning electron microscopy images are evaluated using a machine learning model. A convolutional neural network is presented as a method to analyze complex geometry. Digital replication of air filtration media enables coordination among experimental, analytical, machine learning, and computational air filtration models. The value of using synthetic data to train and evaluate computational and machine learning models is demonstrated through prediction of air filtration performance, and comparison to analytical results. This dissertation concludes with discussion on potential opportunities and future work needed in the continued effort to advance clean air technologies for the mitigation of a global health and safety challenge.