Turbulence-driven flow control for efficient passive and active battery cooling in electric vehicles

This project aims to develop advanced hybrid cooling strategies for electric vehicle (EV) battery systems by integrating turbulence-enhanced flow control with passive air and active liquid cooling methods. Using an unsteady Reynolds-averaged Navier-Stokes k-omega model, the research will investigate the role of turbulence in improving heat dissipation, temperature uniformity, and overall thermal performance. By combining […]

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Anisotropie de l’aluminium suivant les chemins de déformation et taux de recristallisation

Afin de contrôler les propriétés mécaniques des pièces en aluminium, il est nécessaire de mieux comprendre l’effet de la déformation et de la recristallisation dans le processus de fabrication. Le présent projet documentera l’anisotropie de l’aluminium suivant différents chemins de déformation et taux de recristallisation. Le stagiaire pourra ainsi être initié à différentes techniques de […]

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Caractérisation des déformations hétérogènes en compression : Analyse des simulations numériques

L’objectif du stage de recherche proposé est de poursuivre un travail de thèse portant sur la caractérisation des déformations d’un matériau testé en compression. Pour exploiter des essais de compression et en déduite les propriétés mécaniques d’un matériau, l’hypothèse de la déformation homogène du matériau est faite. Or, la déformation est hétérogène à cause de […]

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L2M QC Spring 2025 | Electric axles for semi-trailers

Greenhouse gas (GHG) emissions from road freight in Canada have doubled since 1990, now making up a third of transport-related emissions. However, fleet managers hesitate to switch to electric trucks due to high costs, technical limitations, and uncertain government subsidies. This project introduces a motorized electric axle that replaces a traditional axle on a semi-trailer. […]

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Caractérisation de l’anisotropie d’alliages d’aluminium

L’aluminium, utilisé dans les secteurs des transports pour ses caractéristiques de légèreté et de robustesse, se trouve souvent sous forme d’extrusions comme les poutres de châssis et de carrosserie. Toutefois, les propriétés des pièces extrudées varient fortement en fonction des conditions de fabrication, telles que la température et la vitesse de déformation, ce qui entraîne […]

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Data collection and cross-domain representation models for trajectory analysis

Due to the vast amount of available tracking sensors in recent years, high-frequency and high-volume streams of data are generated every day. Such tracking sensors include but are not limited to vessel, airplane or vehicle tracking data, drones, smartwatches and smart bands as well as cameras and earth observation sensors. Despite the overabundance of data […]

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Comprendre les accidents de la route : une modélisation micro

Ce projet de recherche, dirigé par une chercheuse en sciences économiques dans le cadre du programme Mitacs Globalink, vise à analyser les accidents de la route en Tunisie en utilisant des méthodes avancées d’analyse spatiale pour identifier les zones à haut risque, ou “zones noires”. Avec une base de données de 30 000 accidents couvrant […]

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L2M – Optimizing Energy Efficiency in Sea Transportation Using Machine Learning

Our project tackles the critical challenge of optimizing energy efficiency in electric boats, a vital issue in the growing market of sustainable marine transportation. The primary problem lies in the inefficient energy consumption of electric motors used in electric boats when navigating varying wave conditions, leading to reduced range and increased operational costs. This research […]

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L2M – Deep Learning-Based Detection and Classification of Biofouling on Marine Surfaces

The maritime industry faces significant challenges from biofouling—the buildup of marine organisms on vessel hulls—which leads to higher fuel costs, increased carbon emissions, and frequent maintenance. Traditionally, biofouling inspections are manual, costly, and time-consuming, offering limited real-time insights. Our project seeks to address these inefficiencies by developing an AI-powered model to automate the detection and […]

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L2M – Chainfare

The seafaring industry, responsible for transporting over 90% of the world’s goods, faces critical issues with organized money laundering and human trafficking. The International Labor Organization estimates that 24.9 million people are victims of human trafficking, many of whom are trafficked via maritime routes. Additionally, the UN Office on Drugs and Crime (UNODC) reports that […]

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L2M – Using Wave Energy to Charge Electric Boats Without a Traditional Charger.

Recently, there has been a massive transition from internal combustion engine-based boats to electric boats that do not depend on fossil fuels. However, there are some factors hindering the fast pace of this transition. These factors include the bulky charging system, the unavailability of reliable power sources, and the increased operational cost of electric boats. […]

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L2M – ARMIS: Autonomous Real-time Mapping and Imaging System

The ARMIS (Autonomous Real-time Mapping and Imaging System) project aims to develop an advanced indoor mapping solution utilizing cutting-edge robotics, AI, and image processing technologies to create detailed, real-time indoor maps. This system will autonomously navigate complex environments such as universities, hospitals, corporate campuses, and transportation hubs, capturing 360-degree images and processing them to blur […]

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