03/19/2025
By Danielle Fretwell
The Francis College of Engineering, Department of Biomedical Engineering, invites you to attend a Doctoral Dissertation defense by Kian Barari on, "Mask-Wearing Thermoregulation and Speech Flows: Analyzing Respiratory Flows with Computational Modeling, Sensor Techniques, and Schlieren Imaging."
Date: Wednesday, April 2, 2025
Time: 11 a.m. - 1 p.m.
Location: ETIC 445
Committee:
Advisor: Jinxiang Xi, Associate Professor, Biomedical Engineering, UMass Lowell
Co-Advisor: Rozhin Hajian, Assistant Professor, Mechanical and Industrial Engineering, UMass Lowell
Committee Members*
1. Rozhin Hajian, Assistant Professor, Mechanical and Industrial Engineering, UMass Lowell Lowell
2. Jay Hoon Park, Assistant Professor, Plastics Engineering, UMass Lowell Lowell
Abstract:
This thesis investigates the thermoregulation, respiratory dynamics and leakage effects of face masks, addressing their impact on wearer comfort, protection efficiency and speech transmission. Wearing a mask increases facial temperature and can cause thermal discomfort, which affects mask compliance and often leads to improper fit, reducing protection efficacy. Through computational modeling, we analyze temperature variations at different facial points under varying mask fits, revealing significant microclimate changes. Additionally, leakage flows are quantified using sensor technologies, demonstrating how even small gaps significantly compromise filtration efficiency.
To further explore mask-wearing dynamics, Schlieren imaging is employed to visualize phonetic airflow patterns and exhaled respiratory jets, providing high-resolution insights into speech articulation. Combined with neural network analysis, this approach enhances speech recognition capabilities, offering promising applications in automatic speech recognition and therapy.
Furthermore, the study examines the fogging of safety glasses caused by exhaled moisture in masked and unmasked conditions. Simulations and experiments were conducted under various breathing rates, environmental conditions (13°C and 21°C at 27% RH), and mask fit scenarios, including fully sealed masks, top-gap masks and no-mask conditions. The results demonstrate that airflow patterns and humidity distribution significantly affect condensation on the safety glass. By comparing these conditions, the study provides a detailed understanding of how mask fit, breathing patterns and environmental factors contribute to fogging, guiding the development of improved mask and safety glass configurations to enhance visibility and comfort. These findings highlight the interplay between mask design, thermoregulation, speech articulation and safety glass fogging, offering a comprehensive framework for improving mask efficacy, comfort and usability in real-world scenarios.