ORCID Profile
0000-0002-5880-0233
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Chemical Engineering | Mechanical Engineering not elsewhere classified | Powder and Particle Technology
Publisher: Elsevier BV
Date: 09-2017
Publisher: Elsevier BV
Date: 09-2019
Publisher: Elsevier BV
Date: 2022
Publisher: MDPI AG
Date: 08-09-2021
DOI: 10.3390/MIN11090978
Abstract: Cross-stream cutters are widely used in the mining and resources industry to obtain representative s les of particulate flows. Discrete element modelling (DEM) and analysis can be used to investigate influences of operational parameters, s ler design and material physical properties in the generation of the Increment Extraction Error (IEE), which when present, results in a frequently biased, non-representative s le. The study investigates the practicality of the rules and recommendations proposed by Dr. Pierre Gy that were developed and established as principles for the correct extraction of s les in industrial s ling equipment. Results validate Pierre Gy’s s ling theory using DEM in a cross-stream cutter of a sulphide gold plant. Importantly, the outcomes indicate that careful consideration must be given to physical ore properties and, consequently, that s ling systems should be developed specifically to each application.
Publisher: Elsevier BV
Date: 12-2019
Publisher: MDPI AG
Date: 02-06-2023
DOI: 10.3390/PR11061698
Abstract: This study investigates pneumatic conveying of four different biomass materials, namely cottonseeds, wood pellets, wood chips, and wheat straw. The performance of a previously proposed model for predicting pressure drop is evaluated using biomass materials. Results indicate that the model can predict pressure with an error range of 30 percent. To minimize the number of trial tests required, an optimization algorithm is proposed. The findings show that with a combination of three trial tests, there is a 60 percent probability of selecting the right subset for accurately predicting pressure drop for the entire range of tests. Further investigation of different training subsets suggests that increasing the number of tests from 3 to 7 can improve the probability from 60% to 90%. Moreover, thorough analysis of all three-element subsets in the entire series of tests reveals that when considering air mass flow rate as the input, having air mass flow rates that are not only closer in value but also lower increases the likelihood of selecting the correct subset for predicting pressure drop across the entire range. This advancement can help industries to design and optimize pneumatic conveying systems more effectively, leading to significant energy savings and improved operational performance.
Publisher: Elsevier BV
Date: 12-2019
Publisher: Elsevier BV
Date: 09-2023
Publisher: Elsevier BV
Date: 02-2017
Publisher: MDPI AG
Date: 06-2023
DOI: 10.3390/PR11061697
Abstract: This study introduces a novel methodology to evaluate the behaviour of biomass material by examining the ratio of aeration and deaeration time constants. To this end, a series of tests were conducted on four different materials, namely, cottonseed, wood chips, wood pellets, and wheat straw, in order to investigate their aeration and deaeration behaviours. The study derives the aeration and deaeration pressure drop equations, and discusses the corresponding time constant expression. Subsequently, the four materials were conveyed in 12 m long batch-fed and continuous pneumatic conveying pipelines to examine their behaviour in longer pipelines. The results indicate that the aeration and deaeration time constants increased with an increase in air superficial velocity. However, the ratio of the aeration and deaeration time constants was identified as a unique number, where a value close to 1 indicates a higher likelihood of plug flow. On the basis of the results, cottonseed, with the lowest ratio of time constant, was more likely to form a stable plug flow in both batch-fed and continuous pneumatic conveying. Given the unique properties of biomass and the limited research on the pneumatic conveyance of biomass, this methodology represents a novel approach for predicting modes of flow in materials with complex properties.
Publisher: Elsevier BV
Date: 07-2018
Publisher: Wiley
Date: 25-01-2018
DOI: 10.1002/BBB.1851
Publisher: Springer International Publishing
Date: 2021
Publisher: Wiley
Date: 11-2007
Abstract: This paper presents a design, and a design method, sufficient to engineer a passive solution to the problem of discharge bias resulting from tonnage fluctuation with soft loading transfer chutes. This is achieved by considering the momentum change inherent in the bulk material stream through the hood section of a soft loading transfer point. This momentum change is utilised to move the hood in a predefined path to ensure the discharge centroid remains consistent. The majority of soft loading transfer points are between conveyor belts that include a plan view change in the material direction which immediately impacts on the design of the transfer point. This impact is, the designer must optimise the transfer for a narrow bandwidth of throughput to achieve optimal outcomes or else accept the potential for mis tracking on the receiving belt. This is due to variations in throughput tonnage altering the location of the discharged materials centroid from a fixed hood section, resulting in a tendency for the receiving belt to mistrack due to biased loading.
Publisher: Wiley
Date: 11-2007
Abstract: In belt conveying systems, bulk solid material immediately prior to discharge moves from a troughed profile on the last idler set to a flat profile at the head pulley. How the bulk solid material behaves in this zone is a function of the material properties of the bulk solid and the transition time, which in turn depends on the transition length and belt speed. The accurate determination of the discharge profile is essential for effective transfer chute design. This paper describes an experimental test rig which aims to simulate the motion of the bulk solid material on the conveyor belt during transportation and throughout the transition zone. Results are presented and compared to existing theoretical approximations.
Publisher: European Respiratory Society (ERS)
Date: 12-07-2022
DOI: 10.1183/16000617.0250-2021
Abstract: Workers in the mining and construction industries are at increased risk of respiratory and other diseases as a result of being exposed to harmful levels of airborne particulate matter (PM) for extended periods of time. While clear links have been established between PM exposure and the development of occupational lung disease, the mechanisms are still poorly understood. A greater understanding of how exposures to different levels and types of PM encountered in mining and construction workplaces affect pathophysiological processes in the airways and lungs and result in different forms of occupational lung disease is urgently required. Such information is needed to inform safe exposure limits and monitoring guidelines for different types of PM and development of biomarkers for earlier disease diagnosis. Suspended particles with a 50% cut-off aerodynamic diameter of 10 µm and 2.5 µm are considered biologically active owing to their ability to bypass the upper respiratory tract's defences and penetrate deep into the lung parenchyma, where they induce potentially irreversible damage, impair lung function and reduce the quality of life. Here we review the current understanding of occupational respiratory diseases, including coal worker pneumoconiosis and silicosis, and how PM exposure may affect pathophysiological responses in the airways and lungs. We also highlight the use of experimental models for better understanding these mechanisms of pathogenesis. We outline the urgency for revised dust control strategies, and the need for evidence-based identification of safe level exposures using clinical and experimental studies to better protect workers’ health.
Publisher: Elsevier BV
Date: 10-2018
Publisher: Elsevier BV
Date: 10-2020
Publisher: Elsevier BV
Date: 09-2019
Start Date: 2019
End Date: 2021
Funder: Australian Research Council
View Funded ActivityStart Date: 04-2019
End Date: 12-2022
Amount: $390,000.00
Funder: Australian Research Council
View Funded Activity