There is an increasing interest in applications of machine learning to solve mining and geotechnical problems; this is made easier thanks to user-friendly and open source machine learning codes and improved computational power. The benefit of incorporating machine learning in rock engineering design are apparent, including the reduction in the time required to sort and characterize field data and the capability to find mathematical correlations between complex sets of input data. However, there are challenges to be investigated, including the use of qualitative data.
With ever-increasing societal demands for mineral and energy resources, mining and civil tunnelling projects are developing deeper and more complex underground excavations. Experiences are showing that the response of rock at these depths is significantly different and much more hazardous than that previously encountered at shallower depths for which many of our current engineering design tools were developed.
Perfluoroalkyl and Polyfluoroalkyl substances (PFAS) are anthropogenic compounds with unique properties and wide applications. The consequence of using such persistent chemicals is widespread contamination reported for groundwater, soil, sediment, and wastewater, especially in industrialized countries such as Canada. The endocrine-disrupting and likely carcinogenic nature of PFAS have resulted in strict regulations on PFAS in drinking water.
Golder Associates Inc. is the Technical Lead Consultant on the Environmental Assessment for the expansion of the W12A landfill of the City of London. One key aspect of this project is landfill design alternatives and the impact on air quality and, specifically, odour issues. The proposed project aims at providing critically valuable information regarding local air and odour monitoring at the W12A landfill site, regional air and odour monitoring in the South London area, as well as an assessment of the industry best practices not currently employed that may be applicable.
Golder Associates Ltd., teaming with the Seyem’ Qwantlen Business Group (Kwantlen First Nation), was retained by the Township of Langley to develop a model to predict the location of unrecorded archaeological sites on a 10,000 year-old landscape located in the Fraser River Valley, British Columbia. Conventional predictive modelling techniques are common practice however with the increased availability of more powerful computers and software there is a growing potential for using machine learning algorithms to predict a wider variety of archaeological site types with greater accuracy.
A coal mine operating on the Snuneymuxw First Nation reserve lands between 1913 and 1939 has left mine waste that has contaminated the soil, sediment, groundwater and surface water with metals and polycyclic aromatic hydrocarbons (PAHs). Human health and ecological assessments are being conducted in the area to determine how best to deal with the contamination in the area.
This project will review water source alternatives for the Husky Lloydminster Upgrader Complex. These alternatives will be evaluating in terms of their relative economic, technical, social and environmental risks. The framework developed will provide a basis for conducting similar water risk assessments for other operations. The interns will research alternatives, risks, and develop the assessment framework.
The long-term research goal of the research group is to contribute to the fundamental state-of-knowledge on gas hydrates by improving methodologies and techniques for characterization, assessment, and development of natural gas hydrate accumulations. The short-term goal and main objective of the present proposal is to characterize and assess submarine geohazards evolving from gas hydrate instability.
Soil vapour transport and intrusion into buildings has emerged as a highly relevant issue at contaminated sites with volatile contamination. Advanced modeling tools for vapour transport are relatively limited. Further, there has only been limited in-depth evalution of important factors such as hydrocarbon vapour biodegradation and seasonal influences on site conditions and their impact on vapour intrusion. The interaction between building and subsurface conditions is also not well understood.
A 150m high mine slope has been subject to movement, requiring the mine to reduce the slope steepness while extensive investigation and analysis is undertaken. This reduction in ore production has major implications for the economical viability of the mine.
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