This project makes an existing Autonomous Truck Mounted Attenuator (ATMA) system fully operational for Canadian harsh weather conditions and develops an augmented perception framework to enhance motion planning of the control system. The primarily focus of ATMA is ensuring the safety of highway workers and transportation infrastructure in work zones. On successfully understanding the existing control system, perception module will be augmented visual and radar information for reliable decision making and control in various environmental and highway driving conditions.
Le projet de recherche proposé sera effectué en collaboration avec Hydro-Québec et a pour objectif une meilleure compréhension des mécanismes à l’origine de l’instabilité des parois rocheuses par une analyse de quelques cas répertoriés dans le cadre du projet hydroélectrique de La Romaine.
Le conducteur est un élément critique d’une ligne de transport d’électricité. Il est sujet à la corrosion affectant significativement sa durée de vie. Hydro-Quebec surveille avec un vif interet l'etat de corrosion de ses 34 000 km de lignes haute tension et voudrait estimer dynamiquement l’état de cet actif majeur pour optimiser sa valeur d’un point de vue fiabiliste. En premier lieu, le projet consiste à effectuer une revue du phénomène de corrosion des conducteurs, ainsi que des données disponibles sur les essais accélérés de corrosion.
Effective wastewater treatment is essential to the health of the environment. When operating wastewater treatment plants, utilities must ensure that the treated water meets environmental regulations, while balancing competing needs to minimize the cost of running the plant against the maximizing resource recovery. Additionally, most wastewater treatment plants include a combination of physical, chemical, and biological processes, all of which are complex and which can change rapidly in response to changing conditions.
This research study proposed a unique platform that can provide information on location of the seniors inside the home, the type of activities they are performing, the intensity level of their activities and their progress in performing exercises that have been assigned by their therapists, remotely. This platform will combine different types of data
to increase the accuracy of the algorithms and to reduce the false alarms. Different data fusion techniques will be evaluated to provide different packages for the users according to their health status and privacy concerns.
Basement walls are traditionally built with reinforced concrete in Canada. However, concrete may not perform adequately in the long term and concrete has a huge carbon footprint – more than 8% of global man-made CO2 emission comes from the cement industry. The research project is aimed at timber panel walls, a sustainable material, to replace traditional concrete in the basement construction. The research will primarily be carried out on an existing large-scale experimental timber basement wall on the university campus.
The main focus of this project is to maintain energy-efficient components and assets in existing buildings. Artificial Intelligence (AI) will be applied first to predict the building's components' future energy consumption and health conditions. Then, by having these data, a novel maintenance management and energy management optimization model will be created to perform the correct maintenance tasks and activities at the right time to reduce the maintenance costs and energy consumption.
To contribute to society’s decarbonization goals, the Architecture, Engineering, and Construction (AEC) industry must rapidly transition to low-carbon buildings. Low carbon construction materials and other building technologies are contributing to this decarbonization, but the rate of change for this transition remains low.
This research will focus on direct-formed square and rectangular hollow sections (collectively referred to as RHS hereinafter) under combined compression and bending. The effects of the novel direct-forming approach on the beam-column behaviour of RHS will be quantified via experimental testing. The beam-column testing program will include RHS with material nominal yield strengths of 350 and 690 MPa. A finite element (FE) study will be performed with models developed using the measured residual stresses, strength properties and geometric imperfections in direct-formed RHS.
Combining design and digital workflows, pre-fabrication, and automated assembly provides a rare opportunity for the AEC industry to unite three critical construction items that have traditionally been at odds with one another: Time, Cost and Quality.