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.

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.

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.

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.

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.

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.

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.

With the advent of e-commerce and logistics industry, numerous goods are delivered every day. Sorting systems play a pivotal role in orders delivery practices. Advanced sorting systems are required nowadays because e-commerce retailers are usually confronted with different orders, each consisting of various items. Integrated sorting systems typically consist of a mix of conveyors tied together which are controlled by the Warehouse Management System (WMS). Traditional objects sorting lines rely on human operators to locate and pick each product by hand.

The PDF will start by validating the use of the open-source Stanford University Unstructured (SU2) RANS-based CFD solver for rotorcraft design. This includes generating a mesh and configuration file with SU2 and performing a grid convergence study to validate SU2 and the chosen turbulence models against the reference experimental data. Following this, PDF will generate a mesh and configuration file for the reference rotor geometry provided by the partner organization, Limosa Inc.

The goal of this project is to develop safe, long-lifetime batteries for light electric vehicles such as E-bikes. The commercialization of such long-lifetime batteries would benefit Zen Electric Bikes to bring a disruptive product to the market, reduce GHG emissions and reach revenue targets.