Year

2022

Degree Name

Doctor of Philosophy

Department

School of Mechanical, Materials, Mechatronic and Biomedical Engineering

Abstract

Dust emissions in the industries that rely on bulk materials handling are very common, from mines and port terminals to processing and production plants and factories. They can affect production efficiency, cause material waste and threaten human health. Water spraying is one of the oldest and most popular methods for suppressing dust emissions and is still widely used today in many bulk material handling scenarios, such as crushing, transferring, dumping, and so on. However, reports from industry show that a large proportion of spraying systems do not work very well, and the most typical problem is that the actual dust suppression efficiency of the spraying system does not reach the design or desired value. To improve the design and performance of spraying dust suppression systems, researchers from the Bulk Materials Handling team at the University of Wollongong have applied modern technologies to investigate the characteristics of spraying nozzles and dust particles and also visualise and model the mist and dust streams using computational methods. The aim of this work was to provide engineers with a scientific method to design spraying dust suppression systems.

As an extension of the research at the University of Wollongong, this thesis aims to develop a novel laboratory test rig to evaluate the dust suppression efficiency of sprays and to predict the dust suppression efficiency of a spraying system using computational fluid dynamics (CFD) method. Using the new laboratory test rig, the efficiency of a mist curtain formed by nozzles for different working conditions can be evaluated, which is helpful for selecting the proper nozzle/s and suitable operating conditions for a given application. Once the nozzles are selected, the CFD method can be used to predict the efficiency of the spraying system by simulating the process and mechanisms of spraying dust suppression. This allows engineers to gain a better understanding of the performance of the designed system resulting in a higher system success rate.

FoR codes (2020)

4011 Environmental engineering, 4017 Mechanical engineering, 401905 Mining engineering

This thesis is unavailable until Wednesday, August 14, 2024

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Unless otherwise indicated, the views expressed in this thesis are those of the author and do not necessarily represent the views of the University of Wollongong.