The goals of minimizing emissions and lowering operating costs by monitoring and controlling fuel efficiency have been a growing concern in the mining and construction industries. The largest single contributor of energy consumption in an open pit mining operation is haul trucks. At Goldstrike Mine, haul trucks accounted for approximately 67% of fuel used in 2010. By examining haul trucks in their operating environment, strategic changes in critical parts of the truck cycles can result in fuel savings. This project was a subproject of the Mine Traffic Optimization (MTO) project and is funded by MITACS and Barrick Gold Corporation. One objective of the MTO project was to examine how mine traffic affects fuel efficiency. Certain components of the haulage profile result in inefficient use of fuel, which results in increased operating costs and a larger environmental footprint. Monitoring the trucks in real time allows for the examination of various ways to modify truck’s behaviours in order to improve fuel efficiency. One critical component of the haulage cycle is intersections. An analysis was performed to gain a better understanding of efficient intersection layouts and travel speeds. Cycle time analysis was conducted to ensure that alterations to the haulage cycle would result in minimal impact to the overall productivity of the mine. Modifications to operating practices and simple coding changes to the dispatching program suggest possibilities for potential fuel savings, reduced mechanical degradation, and improved operation efficiency. / Thesis (Master, Mining Engineering) -- Queen's University, 2013-09-30 19:22:29.328

The purpose of this work was to examine vehicle fuel consumption in urban areas and provide a means by which consumption in various situations could be expressed. A review of previous work has been made, including details of the models used for overall consumption in urban areas. The models used are examined and compared with a simple model based on journey distance, journey time, and number of stops. The value of kinetic energy change as a predictive variable is also examined. An explanation of commercial vehicle consumption is provided, but there are difficulties in generalising this to include the whole vehicle fleet. Minimum estimates of consumption related to gross vehicle weight and functions of journey speed are therefore given for overall consumption and for urban conditions. The effect on fuel consumption of changing the area traffic signal control regime from TRANSYT to SCOOT is examined. The method used is to compare complete journeys of several kilometres rather than short lengths of road near each signal. Significant improvements are found for those routes which are mainly inside the control areas. Consumption at roundabouts, in queues, at simple curves and at part stops are considered in detail. The roundabout data and queueing data were collected on street, and the test track results for part stops and simple curves are compared with limited on street data. Predictive equations are given for the consumption of a 2. 2 litre car.

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Very little information is available on domestic fuel consumption in African villages in Southern Africa. And yet, it is a problem that concerns a large number of people, and which is contributing to environmental deterioration. At three villages, 'in Lesotho, Transkei and KwaZulu, the collection and consumption of wood, dung and par2ffin were recorded. The larges~ quantities of energy are consumed . .in KwaZulu with the least in the Transkei (only slightly belong Lesotho). the total consumption of energy largely depends on the availability tv of wood. wood becorr.es scarce, is burnt for heat and cooking. Paraffin is used for light, and for cooking by some women. Wood and dung are burnt at efficiencies of below 3%. The most obvious short term solution, to shortages of energy, is to raise the effi8iency with which fuel is burnt, In the long term, alternative energy sources must be developed.

This study outlines the development of an emissions modeling process in which tractive power based emissions functions are applied to microscopic traffic simulation data. The model enables transportation planners to evaluate the effects of transportation infrastructure projects on emissions and fuel consumption to aid in selecting the projects providing the greatest environmental return on investment. Using the developed model, the performance of a set of simplified macroscopic velocity profiles used in an existing emissions model has been evaluated. The profiles were found to under predict the vehicle emissions due to the low acceleration rates used. To illustrate the use of the model in evaluating transportation infrastructure projects, the benefits of two potential development scenarios in a major transportation corridor were evaluated. Weighing the benefits provided by each scenario against their associated costs revealed that greenhouse gas emissions would be reduced at a cost an order of magnitude greater than the value of a carbon credit suggesting that neither option is economical solely as a greenhouse gas emissions reduction tool.

Reducing fuel consumption and greenhouse gas emissions is becoming increasingly important in the United States, and new legislation can be expected in the near future that will affect trucks either directly or indirectly. This work is a qualitative examination of operational strategies for reducing fuel consumption from freight trucking, and also compares them with vehicular strategies. A focus is placed on who implements, benefits from, and pays for each strategy, and what type of trucking each strategy is applicable to. / text

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This thesis deals with the potential application of neural network technology to aviation fuel consumption estimation. This is achieved by developing neural networks representative jet aircraft. Fuel consumption information obtained directly from the pilot's flight manual was trained by the neural network. The trained network was able to accurately and efficiently estimate fuel consumption of an aircraft for a given mission. Statistical analysis was conducted to test the reliability of this model for all segments of flight. Since the neural network model does not require any wind tunnel testing nor extensive aircraft analysis, compared to existing models used in aviation simulation programs, this model shows good potential. The design of the model is described in depth, and the MATLAB source code are included in appendices. / Master of Science

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