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Mask-Wearing Thermoregulation and Sp...

Barari, Kian,

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Mask-Wearing Thermoregulation and Speech Flows: Analyzing Respiratory Flows With Computational Modeling, Sensor Techniques, and Schlieren Imaging /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Mask-Wearing Thermoregulation and Speech Flows: Analyzing Respiratory Flows With Computational Modeling, Sensor Techniques, and Schlieren Imaging // Kian Barari.
Author:	Barari, Kian,
Description:	1 electronic resource (210 pages)
Notes:	Source: Dissertations Abstracts International, Volume: 86-12, Section: B.
Contained By:	Dissertations Abstracts International86-12B.
Subject:	Biomedical engineering. -
Online resource:	https://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=31847488
ISBN:	9798280724105

Mask-Wearing Thermoregulation and Speech Flows: Analyzing Respiratory Flows With Computational Modeling, Sensor Techniques, and Schlieren Imaging /
Barari, Kian,

Mask-Wearing Thermoregulation and Speech Flows: Analyzing Respiratory Flows With Computational Modeling, Sensor Techniques, and Schlieren Imaging /Kian Barari. - 1 electronic resource (210 pages)

Source: Dissertations Abstracts International, Volume: 86-12, Section: B.

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.

English

ISBN: 9798280724105Subjects--Topical Terms:

535387
Biomedical engineering.
Subjects--Index Terms:

Face masks

Mask-Wearing Thermoregulation and Speech Flows: Analyzing Respiratory Flows With Computational Modeling, Sensor Techniques, and Schlieren Imaging /
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520 $a 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.
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653 $a Face masks
653 $a Respiratory dynamics
653 $a Safety glasses
653 $a Schlieren imaging
653 $a Thermoregulation
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