A comprehensive investigation of loading variance influence on fuel consumption and gas emissions in mine haulage operation

Soofastaei, Ali; Aminossadati, Saiied M.; Kizil, Mehmet S.; Knights, Peter

doi:10.1016/j.ijmst.2016.09.006

Cited by 24 publications

(12 citation statements)

References 6 publications

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“…The mine area road gradient has a great impact on the energy consumption of transportation vehicles [8]. Field surveys have calculated the proportions of heavy load uphill, heavy load downhill and peaceful road driving in the total operating mileage, as shown in Figure 4.…”

Section: Energy Consumption Analysis Based On Field Surveymentioning

confidence: 99%

Study on energy conservation and emission reduction of pure electric non-road mining dump truck

Zhang

Ma²,

Yang

et al. 2021

E3S Web Conf.

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Non-road mobile machinery emits a large amount of pollutants, which has attracted wide attention. As one of the effective means of air pollution control, the application of new energy technology in the field of non-road mobile machinery is slightly inadequate. Mine dump trucks play an important role in the transportation of open-pit mining areas, but they have high power, high level of activity, and difficult to control pollutant emissions. In this study, field experiments were carried out in several open pit mines in China. By comparing with similar diesel engine powered vehicles, the potential of energy consumption and emission reduction was evaluated. Research shows that pure electric mine dump truck can effectively reduce energy consumption and emissions.

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Section: Energy Consumption Analysis Based On Field Surveymentioning

confidence: 99%

Study on energy conservation and emission reduction of pure electric non-road mining dump truck

Zhang

Ma²,

Yang

et al. 2021

E3S Web Conf.

View full text Add to dashboard Cite

show abstract

“…Table 3 shows the values of carbon dioxide emission from a wide range of refined products. Also, the fuel used in transport equipment is diesel oil, therefore the value used for the calculation of emission values will be 0.00268 t per liter of diesel fuel saved [13][14][15].…”

Section: Emission Of Greenhouse Gasesmentioning

confidence: 99%

Environmental and Operational Benefits through Implementing a Fleet Management System in Mining Industry

Felsch

2020

IJESNR

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Mining fleet management is fundamental to the transportation infrastructure in a mining nowadays. Several factors influence the success of a new system adoption, such as changes in the project design, operational maturity, direct leadership engagement, and senior management participation. To start with, the main objective of this study is to present the results obtained with the implementation of the Fleet Management System in a mining company located in the Southeast region of Brazil. In this study, the chronology of the implementation of the technology was presented, comparing the operational factors and environmental impacts to the operation results. As a result, there was a 23% increase in the transportation fleet performance, which led to a monthly potential reduction in the emission of 136 tons of greenhouse gases in the atmosphere because of the reduction of the transportation fleet required for ore movement. Furthermore, these gains may be enhanced over the years, expanding its possibilities with the use of new techniques and research.

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“…In this study, he shows the impact of load density variation based on the blasting procedures on fuel consumption by haul trucks. Soofastaei et al completed many different projects in the field of haul truck energy efficiency in surface and underground mines [9][10][11][12][13][14][15][16][17].…”

Section: Introductionmentioning

confidence: 99%

The Application of Artificial Intelligence to Reduce Greenhouse Gas Emissions in the Mining Industry

Soofastaei¹

2019

Green Technologies to Improve the Environment on Earth

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Mining industry consumes a significant amount of energy and makes greenhouse gas emissions in various operations such as exploration, extraction, transportation and processing. A considerable amount of this energy and gas emissions can be reduced by better managing the operations. The mining method and equipment used mainly determine the type of energy source in any mining operation. In surface mining operations, mobile machines use diesel as a source of energy. These machines are haul trucks excavators, diggers and loaders, according to the production capacity and site layout and they use a considerable amount of fuel in surface mining operation; hence, the mining industry is encouraged to conduct some research projects on the energy efficiency of mobile equipment. Classical analytics methods that commonly used to improve energy efficiency and reduce gas emissions are not sufficient enough. The application of artificial intelligence and deep learning models are growing fast in different industries, and this is a new revolution in the mining industry. In this chapter, the application of artificial intelligence methods to reduce the gas emission in surface mines with some case studies will be explained.

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A comprehensive investigation of loading variance influence on fuel consumption and gas emissions in mine haulage operation

Cited by 24 publications

References 6 publications

Study on energy conservation and emission reduction of pure electric non-road mining dump truck

Study on energy conservation and emission reduction of pure electric non-road mining dump truck

Environmental and Operational Benefits through Implementing a Fleet Management System in Mining Industry

The Application of Artificial Intelligence to Reduce Greenhouse Gas Emissions in the Mining Industry

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