The project objective is to understand and apply the metallurgical fundamentals for the heavy gauge steel product development. The major tasks can be divided into two groups: (A) the precipitate investigation through conventional and advanced characterization techniques such as transmission electron microscopy (TEM) and (B) the implementation of thermomechanical processing models for the rolling schedule […]

The proposed project aims at developing new catalytic processes and corresponding catalysts for heavy oil upgrading with the assistance of natural gas. Compared with traditional hydrotreating processes, these new processes provide alternative ways for heavy oil and natural gas utilization, which are economically and environmentally favorable in terms of higher profit margin, lower operating cost, […]

Static mixers are metal structures inserted into pipes to enhance the mixing of fluids flows. Different mixer designs cause different levels of mixing for a given energy loss. An ongoing and promising project is the invention of a new mixer geometry that is more efficient than anything on the market. Experimental testing uses the PLIF […]

Greenfield Global is developing a process to produce jet fuel from renewable materials, such as waste biomass and organic municipal waste. The renewable materials are first converted to a synthetic oil and then converted into jet fuel. This project deals with the final step in the process, namely, to convert the synthetic oil to jet […]

Greenfield Global is currently developing a conversion process to produce jet fuel from renewable feedstocks. Collection and densification of different biomass waste materials and municipal waste at satellite facilities to produce bio-oils, which are then processed at a central facility, is expected. The first processing step at the central facility is supercritical water gasification and […]

The proposed project aims at developing new catalytic processes and corresponding catalysts for heavy oil upgrading with the assistance of natural gas. Compared with traditional hydrotreating processes, these new processes provide alternative ways for heavy oil and natural gas utilization, which are economically and environmentally favorable in terms of higher profit margin, lower operating cost, […]

This project will study the corrosion of two nickel alloys commonly used in nuclear reactors: Monel 400 and Alloy 800. In the steam generator section of nuclear reactors, the chemistry is complex and may lead to the formation of ammoniacal species such as soluble ammonia (NH3). Ammonia may accelerate the corrosion of these alloys. The […]

This project will involve the development and validation of simulation models suitable for studying, designing and implementing a small-sized power system with reduced fuel expenditure and carbon (iv) oxide emissions, for oil and gas extraction activities. The successful implementation of the project will further Audacious Energy Corp.’s knowledge to launch and test a Minimum Viable […]

In general, when a more viscous fluid is displaced by a less viscous one, instabilities grow at the interface between them which are referred to as viscous fingering. Viscous fingering is of paramount importance in many applications including, but not limited to, contamination transport in underground waters, enhanced oil recovery, filtration, and chromatographic separation of […]

The overall aim of the research is to develop a decision support system to quickly estimate the oil outflow from a damaged tanker in a collision or grounding accident, in Arctic conditions. The work in this Mitacs project focuses on a part of this overall objective: modeling the dynamic oil outflow from a damaged tanker. […]

The overall aim of the research is to develop a decision support system to quickly estimate the oil outflow from a damaged tanker in a collision or grounding accident, in Arctic conditions. The work in this project focuses on modeling the accidental damage size for representative tankers operating in the Canadian Arctic, when these experience […]

This project will develop practical workflows, algorithms and programming codes for inferring unknown reservoir properties from distributed temperature and acoustic sensing data. In-situ pressure and flow conditions can be interpreted from downhole fiber signals gathered in real time, which are used to estimate unknown heterogeneous reservoir parameters continuously. Machine learning methods will be incorporated to […]