Doctoral Dissertations

Keywords and Phrases

Air quality; coal dust; computational fluid dynamics; dust; low-cost pm sensors; underground mine

Abstract

"Overexposure to respirable coal mine dust has been linked to causing serious health problems including coal workers pneumoconiosis (CWP) and chronic massive fibrosis. The prevalence of these health problems has been on the increase since the 2000s due to increased exposure levels with roof bolter operators having the highest exposure levels. The currently used PDM3700 is too expensive, heavy and bulky which limits their use only for regulatory monitoring failing to measure miners’ personal exposure levels. Also, since roof bolter operators are more prone to elevated coal dust levels, the canopy air curtain (CAC) was developed to protect then high coal dust concentrations. However, the current generation CAC only provides a 46% coal dust reduction efficiency leaving room for improvement. Insufficient coal dust monitors in mines make it challenging to effectively evaluate the performance of these CACs.

The objectives of this research are therefore, to develop a small, lightweight, low-cost coal dust monitor using a low-cost PM sensor for personal coal dust monitoring in underground coal mines; to develop statistical and machine learning calibration models for low-cost PM sensors to accurately measure coal dust concentrations; and to optimize the design of the CAC using computational fluid dynamics for improved coal dust protection. This study has led to the development and calibration of a low-cost coal dust monitor which will potentially reduce monitoring cost by ~$15,000 per unit while achieving 95% the accuracy of the PDM3700. The CAC design was optimized using CFD simulations improving the uniformity of the CAC. Further, the low-cost sensors present an opportunity to effectively measure the dust control efficiency of the CACs"-- Abstract, p. iv

Advisor(s)

Xu, Guang

Committee Member(s)

Awuah-Offei, Kwame, 1975-
Wang, Yang
Sherizadeh, Taghi
Cauda, Emanuele

Department(s)

Mining Engineering

Degree Name

Ph. D. in Mining Engineering

Publisher

Missouri University of Science and Technology

Publication Date

Spring 2024

Pagination

xiv, 171 pages

Note about bibliography

Includes_bibliographical_references_(pages 52, 95, 133, 161 and 166-170)

Rights

© 2023 Nana Kobina Amoako Amoah, All rights reserved

Document Type

Dissertation - Open Access

File Type

text

Language

English

Thesis Number

T 12329

Electronic OCLC #

1426865667

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