Year: 2024
Type: dissertation
Abstract: The rapid spread of SARS-CoV-2 has created challenges for societies, healthcare settings, business and institutions. To curb virus transmission appropriate personal protective equipment (PPE) including face masks have been recommended given their role in preventing direct transmission of the virus. In the first project government distributed face masks and respirators during the COVID-19 have been tested following ASTM standards. Suggestions were made based on the results obtained. R95 respirator has the highest filtration performance followed by N95 respirator and face masks. N95 has the highest air permeability and filtration performance near R95 and thus may act an effective barrier. Face mask could be an alternative since they have comparable filtration performance and air permeability. The second project discussed about the effects of cold plasma on meltblown polypropylene 3PLY face mask. Three different plasma conditions; low, medium, and high; and nine different runs were made on meltblown polypropylene for three exposure periods; 5, 10 and 15 minutes. Results showed that medium plasma condition for 15 minutes gives the highest increase of filtration performance indicating the potential plasma condition on enhancing filtration performance of polypropylene meltlbown mask. The third project compared the filtration performances of after-market automotive cabin air filters (ACAFs) against ultrafine particles. Both charcoal and standard cabin filter were tested against ultrafine size particles. Charcoal filters were performed better than standard filters. Filters with meltblown layer have superior filtration performances as well. Filter characteristics of cabin filters like GSM, Thickness, and Number of filter layers were positively related to each other and influence the filtration performances of cabin filters.
Author: Rahman, Md Faizur
Language: English
Subfield: Electrical and Electronic Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W7000646529
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