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.

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.

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.

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.

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.

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.