Characterization of the Galactic White Dwarf Population in the Next Generation Virgo Cluster Survey

Halo white dwarfs remain one of the least studied stellar populations in the Milky Way because of their faint luminosities. Recent work has uncovered a population of hot white dwarfs which are thought to be remnants of low-mass Population II stars. This thesis uses optical data from the Next Generation Virgo Cluster Survey (NGVS) and ultravoilet data from the GALEX Ultraviolet Virgo Cluster Survey (GUViCS) to select candidates which may belong to this population of recently formed halo white dwarfs. A colour selection was used to separate white dwarfs from QSOs and main-sequence stars. Photometric distances are calculated using model colour-absolute magnitude relations. Proper motions are calculated by using the difference in positions between objects from the Sloan Digital Sky Survey and the NGVS. The proper motions are combined with the calculated photometric distances to calculate tangential velocities, as well as approximate Galactic space velocities. White dwarf candidates are characterized as belonging to either the disk or the halo using a variety of methods, including calculated scale heights (z> 1 kpc), tangential velocities (vt >200 km/s), and their location in (V,U) space. The 20 halo white dwarf candidates which were selected using Galactic space velocities are analyzed, and their colours and temperatures suggest that these objects represent some of the youngest white dwarfs in the Galactic halo.

Development of An Enhanced Oil Sands Fluid Tailings Generation Model

Bitumen extraction from surface-mined oil sands results in the production of large volumes of Fluid Fine Tailings (FFT). Through Directive 085, the Province of Alberta has signaled that oil sands operators must improve and accelerate the methods by which they deal with FFT production, storage and treatment. This thesis aims to develop an enhanced method to forecast FFT production based on specific ore characteristics. A mass relationship and mathematical model to modify the Forecasting Tailings Model (FTM) by using fines and clay boundaries, as the two main indicators in FFT accumulation, has been developed. The modified FTM has been applied on representative block model data from an operating oil sands mining venture. An attempt has been made to identify order-of-magnitude associated tailings treatment costs, and to improve financial performance by not processing materials that have ultimate ore processing and tailings storage and treatment costs in excess of the value of bitumen they produce. The results on the real case study show that there is a 53% reduction in total tailings accumulations over the mine life by selectively processing only lower tailings generating materials through eliminating 15% of total mined ore materials with higher potential of fluid fines inventory. This significant result will assess the impact of Directive 082 on mining project economic and environmental performance towards the sustainable development of mining projects.