Evaluation of mechanical performance and in-situ health monitoring using destructive and non-destructive testing of cellulosic fiber reinforced cement composites

Today, construction activities have resulted in the depletion of vast amounts of non-renewable resources that cause climate change which is one of the most pressing environmental challenges of our day. The construction industry is a major source of greenhouse gas emissions globally. Sustainable construction is now mainstream, necessitating the investigation of environmentally friendly construction materials like cellulosic fibers. One of the potential applications of cellulose fibers is in development of cement-based composites.

Developing a novel medical robotic device for treatment of lower back pain employing a non-invasive human-robot interaction method

NeoSpina Health Care Inc intends to contribute to unprecedented treatment techniques for LBP by developing a novel medical device and investigating acquired data from treatment procedures. Accordingly, the main objective of this project is to develop a non-invasive robotic device to treat a wide array of spinal conditions while reducing the treatment duration compared to conventional methods. The device will be equipped with motor actuators and force sensors, permitting interaction with the patient’s lumbar spine and data acquisition in real-time, which entails an appropriate design.

Comparison of two Approximate Stochastic Dynamic Programming Schemes for Mid-term Hydropower System Management

The Energy potential of water has been successfully harnessed to produce electricity since the late 19th century. In 2018, hydropower production accounts for approximately 61 % of the total electricity produced in Canada. To exploit this source of energy, water is stored in dams and is strategically used based on hydrological cycles. Over the years, researchers around the globed have devised sophisticated mathematical tools to efficiently manage hydropower systems thanks to advancement in both Mathematics and Computer Science.

Exploring the relationship that short-interval intracortical inhibition has with muscle fatigue, and whether induced short interval intracortical inhibition can be used to mitigate muscle fatigue during extended submaximal output

This project will look at if and how transcranial magnetic stimulation can be used to influence or delay either observed or perceived muscle fatigue in either continuous or non continuous exhaustive physical activity. The project also will conclude whether or not it would make financial senes, based on observed performance gains, to include transcranial magnetic stimulation devices to pair with with any future brain-machine-interfaces that are developed.

Coupled thermal-electrochemical modelling and characterization of novel lithium-ion cell architectures for electric vehicle batteries

Significant advances in lithium-ion batteries (LIBs) are driving the automotive industry’s transition to electrification. Canada’s expansive ecosystem of leading automakers, part manufacturers, research institutions, and skilled workforce are collectively well-positioned to further advance LIB technologies and overcome critical barriers that continue impacting electric vehicle (EV) adoption, including vehicle driving range, and battery lifespan and safety.

Realizing a photovoltaic mosaic of interconnected solar cells

Square Solar Inc., a lower mainland British Columbia-based company, envisages a solar module that is comprised of a mosaic of, ideally at least, scalable solar cells that will tile any given surface that is exposed to the Sun’s rays. The intern on this project will develop a means simulating the electrical performance of such a mosaic, the goal being the development of a standard testing protocol for such a device. A number of proposed designs will be critically assessed within the context of this protocol.

Automotive Modular Real-time Edge Computing on Embedded Hardware

As vehicle systems become more advanced, accurate information about vehicle states, parameters, and surrounding operating conditions becomes paramount for vehicle health monitoring and driver control systems. This information is vital for the production, cost, and efficiency of the vehicles, as well as a key to improving passenger safety. In commercial vehicles, not all parameters of interest are directly measurable using sensors, because of sensor costs or design constraints.

Design and Development of a re-configurable Wheeled Robot and an on-board Laser-Optic-based Inspection unit for Identification, Classification, and Measurements of Pipe Surface Defects

This research project focuses on the design and development of a robotic system and an inspection unit carried by it for doing Identification, Classification, and Measurement (ICM) of defects in pipes. Images/videos of the defects will be collected by a pipe inspection system to be developed in this project. Furthermore, wewill investigate how economically beneficial the technology and its implementation would be. Automated digitalreporting on defects will be conducted in this project in a lab environment by using machine-learning-basedtechniques. Defects such as dent, cracks, pitting, etc.

Fabrication of Smart Clothing: From Machine Learning Approach to Fashion Design Concepts

Nowadays, wearable devices attract a lot of attention, especially in the healthcare field. But translating all devices to wearable devices always comes with challenges. Some of the challenges are lack of knowledge about the application of different materials in smart textiles, limitation of developed smart textiles in practical application, no significant dedication in designing clothing by considering the limits, etc. So, this proposal is trying to address those gaps.

Novel Graphene Systems for Battery Anodes Design and Thermal Management Systems in Electric Vehicles (EVs)

This proposed research utilizes novel graphene materials using Universal Matter’s “Flash Joule Heating” process in applications supporting the Electric Vehicle (EV) market. These graphene materials have disoriented stacking of its graphene layers, which helps incorporate metal ions and dopants into the graphene matrix, thereby creating exciting new opportunities across many electrical applications. The current research will investigate the efficacy of two new types of graphene materials for use in battery anode and thermal management system applications.