New statistical machine learning methods applied to high dimensional sensory input data from chemistry

Machine learning is the concept where a computer can be trained to recognize data and predict future outcomes based on the trends that exist in the data. This method of analysis has not been used on engine data, specifically in-line oil. Oil is an engine’s lifeblood and a lot of data can be collected and engine health can be predicted based on these measurements. This project aims to deploy machine learning concepts in the area of engine failure prediction.

Behavioral Analysis of H1 Reconstruction in New Software Environments

The precise prediction of fluid behavior is required in many fields of engineering. Fluid flows are governed by a complex system of continuous partial differential equations (PDEs) which rarely have an exact analytical solution. Computational Fluid Dynamics (CFD) has emerged as a leading method of analyzing fluid flows, by numerically solving the respective PDEs. Current methods in finite volume schemes of CFD on unstructured meshes have two major sources of errors: noise in the reconstructed gradients and lack of cancellation during flux integration.

Enhanced Mechanical Properties and Lower Gas Permeability for Liner Polyethylene in Fiber Reinforced Pipes (FRPs) - Year two

Permeation of CO2 gas through the inner layer in multi-layer fiber reinforced pipes (FRPs) destructively reduces pipe
durability. FRPs generally consist of three or more layers of polymer and reinforcing fibers. Gas permeation thorough
the polymer layer and its accumulation in reinforcing layer leads to pipe failure during depressurizing cycles. Using clay
nano-platelet can lead to decrease gas permeability in polymer layers. Good dispersion and good adhesion between
clay nano-layers and polymer are key features for optimization of gas permeability.

Production of Renewable Drop-In Fuel from Syngas Derived from an Ethanol Industry

The fuel-grade ethanol obtained from corn-based feedstocks, utilizes about 33% of the total carbon present in corn based feedstocks. The remaining fraction is converted into dry distillers’ grains (DDG) and carbon dioxide, which is then converted to syngas (CO+H2). In this research the syngas from ethanol plant will be converted to transportation fuel and derived chemicals using our patented Fischer- Tropsch (FTS) catalyst. The catalysts will be pelletized and tested in 5 cc micro-reactor. The process parameters such as, temperature, pressure will be evaluated to obtain optimal yields.

Modelling, simulation, field evaluation and feasibility study of gas heat pumps (GHPs) in cold climate–Canada

Despite the abundance of natural gas resources and relatively lower price of gas per unit energy compared to electricity gas-fired heat pumps (GHPs) have not been widely used in Canada. This project will study the feasibility of two types of (GHPs), i.e., gas engine-driven heat pump (GEHP) and gas-fired absorption heat pump (GAHP) for buildings located in Canada. The project will include making theoretical models for prediction of performance and energy savings, which would be verified by comparison with actual performance data.

Direct Contact Steam Generator Flue Gas Subsurface Modeling and Application

Direct Contact Steam Generators (DCSGs) for use in Steam Assisted Gravity Drainage generate flue gas containing steam and C02 which can be injected into reservoirs to aid bitumen recovery with part of the C02 remaining underground. The objectives of this project are to understand mechanisms of C02-stearn bitumen rate enhancement and determine the amount of C02 stored during the recovery process. Reservoir simulation modeling of C02 and steam injection will be done in parallel to Suncor's steam-C02 co-injection field pilot.

Emulsion Injection for Enhancing the Fast-and-Uniform SAGD Start-up Process

Steam-Assisted Gravity Drainage is the most commonly used in-situ thermal method for recovering bitumen from oil sands formations in western Canada. In this process, two parallel horizontal wells, about 5 m apart vertically, are drilled near the bottom of the formation. Before production, the bitumen between the two wells has to be heated, to become mobile, by circulating steam through the wells for several months. A new technology has been developed to make the inter-well bitumen flow in only a week, in which water is forced into the sands to dilate the pores, followed by steam injection.

Monitoring and Control System Design for Catalyst Manufac!uring Unit

As one of the novel element of a new technology for enhanced recovery and upgrading directly in the reservoir of bitumen and heavy oils, the unit for the online and on-field manufacturing and delivery of nanocatalysts into the reservoir will be constructed during 2015. The specialized and uniquely designed compact device, currently referred to as CATSKID, is currently in the patenting process.

Development and Characterization of All-in-OneEthanol Based Diesel Fuel Additive

The main objective of this research project is to obtain an additive helps to increase the cetane number as well
as reducing fuel consumption in diesel engines. In the proposed study, we will perform the characterization of
available petroleum diesel and analyze their properties. The ethanol based additive later will be added in several
different ratios into the diesel fuel to see their effect on fuel properties (CN, lubricity, emission and distillation
T90).

Organic sorbent and nanotechnology-assisted bioremediation of industrial effluents

Highly toxic organic and inorganic chemicals result from various industrial operations have been identified in surface and ground waters in very small concentrations, making their removal difficult. In partnership with Lorax Systems Inc., the objective of this research is to
develop a novel, biologically-based material for the treatment of industrially relevant wastewater streams, exploring not only the water treatment aspects but also the post-processing of the biomaterial for recycling within other processes.

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