Process modeling of compression moulding with sheet moulding compound (SMC) for automotive hollow parts

To reduce the weidht of cars in order to reduce greenhouse gas emissions, the automotive industry has recently been turning to the extensive use of composite materials for structural applications. Magna Exteriors Inc (MEI), a world leader tier 1 automotive supplier and a division of Magna International Inc, is seeking ways to develop a new high-volume manufacturing process for hollow parts using sheet moulding compound (SMC).

Thermal Performance Study of Switch Module Redesign

Thermal analysis is performed on a proposed design change on electronic assembly to ensure that it meets customer requirements (temperature ranges) and is a more cost-effective design. Such design change should be cost efficient. The important aspect, in addition to the design, is interacting with different engineers at different positions in the company. Working with mechanical engineers and suppliers in achieving such targets and ensuring the work done is viable and on track.

Techno-Economic Feasibility of Wastewater Heat Recovery for Cold Climates like Canada

Wastewater is an abundant and severely underutilized energy source in North America. Sewers experience predictable flow profiles and nearly constant temperatures between 18 ?C and 20 ?C year-round. When wastewater is used in conjunction with heat pumps, it can serve as an energy source and sink to provide both heating and cooling to buildings. Therefore, there exists the potential to extract significant amounts of thermal energy from the wastewater using heat exchangers, resulting in substantial economic and environmental benefits.

Sensitivity Analysis of Gas and Particulate Matter Emissions from Future Power Generation in the Province of Alberta

The Province of Alberta (AB) has decided to phase out coal power generation by 2030 and increase renewable electricity production to 30% of total power generation, also by 2030 with the remaining 70% of the power generation being dependent on natural gas. It has been conjectured that part of generation portfolio could be diversified to include nuclear power generation.

Optimization of a calibration procedure for Mecademic’s Meca500 robot arm

Mecademic manufactures the smallest and most precise six-axis robot arm. The repeatability of this robot is better than 0.005 mm, but like any industrial robot, the robot’s accuracy is far worse. The only practical way of improving the robot’s accuracy is to calibrate each individual robot.

CardiAI Point-of-Care Device for High-Caliber and Rapid Diagnosis of Biomarkers from Blood of Patients for Early Heart Failure Detection

The aim of this research and development project is to design and develop a bedside point-of-care device to be equipped with the CardiAI’s machine learning technology for heart failure management. Our POC system will include disposable cardiac biomarker strips and an electronic reader.

Application of advanced analytics in PEM fuel cell development and engineering

This project is a collaboration between Triptech Engineering and Software Services LTD and Laboratory for Alternative Energy Conversion (LAEC) at SFU to develop data analytics solutions for PEM fuel cell industry. The fuel cell industry is suffering from component/system failure and coping with analysis of tremendous amounts of data. Knowledge extraction from this complex data is necessary to predict key factors of component/system failure and enhance the reliability and lifetime of fuel cells.

Emissions control and reduction for natural gas engines

The use of natural gas as a fuel for on-road commercial vehicles offers significant benefits, including lower greenhouse gas emissions. Methane, the main component of natural gas, has many virtues as a fuel. One of these benefits is that it is a very stable molecule. This stability does introduce a challenge: it is hard to remove from the exhaust stream any methane that isn’t consumed in the engine. This internship will help to address this factor, focusing on using a catalytic reactor in the exhaust of an engine.

Artificial Intelligence (AI) Powered Adaptive Flight Controller for Novel Unmanned Aerial Vehicle (UAV) with Commercial and Humanitarian Applications

The project entails research into machine learning techniques to control unmanned aerial vehicles (UAVs) with complex flight characteristics for surveillance and cargo transportation applications. In addition, it advances networked UAV fleet control and optimization methodologies to improve the potential of UAV fleets to perform coordinated tasks efficiently and reliably.

3D Printable conductive nanocomposite sensors for CRFID moisture, strain, and temperature sensing in composite pipes

Transportation of oil and gas through pipeline networks remain a crucial infrastructure for sustainable economic growth in Canada. Pipeline wear and damage will remain a major concern as it can lead to catastrophic failures causing environmental and economic damage if undetected. For easier detection of damage on a large network of pipelines, an array of wireless radio frequency identification tags was developed for steel pipes. However, the material used for the tags were not suitable for pipes made with polymer composites as the stiffness of the copper could damage it.

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