Innovative Projects Realized

Marine Icing Models and Sensors for Arctic Exploration Vessels

Marine icing problems pose significant risk to both marine vessel stability and human safety during harsh weather operations. The project will address a need for better physical understanding of marine icing phenomena and the development of appropriate sensors for detecting marine icing conditions. Current technologies have proven inadequate for marine conditions due to the complex nature of marine structures and the conditions leading to icing, as many are developed for fresh water environments or atmospheric icing conditions for aeronautical and/or land based structures. New technologies for better prediction of icing conditions and ice accretion levels will assist industry in developing both anti-icing and de-icing strategies.

Modélisation d’un arc électrique immergé nanoseconde dans le cadre de la synthèse de nanoparticules

L’objectif de ce projet est de mettre au point un modèle numérique permettant d’étudier la dynamique du milieu environnant un arc immergé nanoseconde. Le système est supposé à l’équilibre thermodynamique local.
En s’appuyant sur des mesures courant-tension réalisées au sein de l’équipe, le modèle doit permettre de résoudre le champ électrique et magnétique.
Lors d’une décharge dans un liquide, une bulle de cavitation est générée. La taille et la pression de cette bulle évoluent avec le temps et peuvent être modélisées à l’aide du modèle de Rayleigh-Plesset. L’interface liquide/vapeur, zone importante pour la synthèse de nanoparticules, doit également être prise en compte afin d’y obtenir la concentration des différentes espèces.
Une attention particulière sera portée sur les phénomènes aux électrodes liés au passage du courant. En effet, l’échauffement induit une vaporisation et/ou une fusion partielle de l’électrode dont il faut tenir compte afin d’obtenir l’évolution du mélange gazeux au cours du temps.

Co-operators : Création de plongements et représentations pour l’assurance commerciale

En assurance commerciale, il est important de pouvoir comprendre l’industrie dans laquelle opère une entreprise afin de bien identifier les risques auxquels l’entreprise est exposée. À cette fin, l’approche traditionnelle consiste à assigner à chaque entreprise un code d’industrie. Cependant, cette assignation est problématique car la plupart des classifications d’industrie comptent des centaines et souvent même des milliers de classes. Ceci rend la tâche très difficile pour un humain parce que : 1) retenir toutes les classes est presque impossible ; 2) les distinctions entre deux classes peuvent être extrêmement subtiles de telle sorte que deux agents pourraient ne pas s’entendre sur le bon choix de classe dans certaines situations. De plus, ces classes ne nous permettent pas facilement de mesurer à quel point deux industries sont similaires (ou différentes). Pour pallier à ces problèmes, nous proposons d’étudier la possibilité de créer des plongements denses à peu de dimensions (i.e. environ 20) pour représenter chacune de ces classes.

Development of a tool to assess the impacts of efficient technologies in residential districts

Today, the world faces climate change, uncoordinated depletion of natural resources and rapid urbanization. Buildings in cities account for about 25% of the global energy consumption and 15% of the energy-related greenhouse gas emissions. Likewise, in the province of Québec, buildings are responsible for a large share of the total energy use. A recent study shows that the building sector in Québec accounts for 31% of the total energy use, from which 18% is the share of residential buildings. Projections show that population growth, facilities concentration, and diverse economic activities in urban areas will intensify these figures unless valid energy practices are applied to the building stock. Towards the notion of net-zero energy communities, this project aims to develop a tool to assess the impact of adopting energy technologies in future residential neighbourhoods. This tool will contain various building and technology archetypes and help compare the baseline demand profile of different layouts. The novelty of this project is to use a gray-box approach for developing design-oriented building archetypes that facilitate energy assessment at the early design stage. For example, key design variables in these archetypes will be 1) total floor area, 2) total fenestration area, 3) building type, and 4) level of insulation. Primarily, this tool provides a platform for community designers and planners to make informed decisions and optimize the design; however, it can also be useful for retrofit applications in the existing neighbourhoods.

New Generation Membrane Electrode Assembly using Novel Nanoporous Carbon Scaffold

Hydrogen fuel cells (HFCs) are clean and efficient energy conversion devices that produce electricity from green hydrogen with zero carbon emissions. Currently, the catalyst layers in HFCs are composed of Pt-decorated carbon powders mixed with an ion conducting polymer (ionomer), leading to uncontrolled distribution of each phase and significant tortuosity due to the complex pores and pathways between particles.
The membrane electrode assembly (MEA) is the core component of a HFC that plays the most critical role in the HFC performance and lifetime. However, there are gaps in the MEA market involving high cost and inadequate performance. Momentum Materials Solutions Corp, an Alberta start-up, recruits a Mitacs M.Sc. student from the University of Calgary to develop a paradigm-shifting MEA technology using proprietary, novel, and ordered nanoporous carbon materials, with the goal being to fill the industry gaps and achieve high significantly improved performance and lifetime.

BusPas Inc – Internationalization opportunities of smart mobility technology.

BusPas is a dynamic development company committed to advancing today’s mobility and shaping tomorrow’s. Through cloud and mobile technologies, we are transforming the mobility experience for users and supporting transit agencies in the digitalization of the city.

We have developed something new for transit operators and agencies. An innovative technology that will be deployed massively at bus stops in the coming years. We are a Montreal-based company and officially launched our product in November at the APTA 2021 Expo in Orlando. Our smart bus stop sign can help Transit Agencies to improve their customer experience, improve safety for their bus operators and users, and increase data availability for operational and planning purposes.

Today, we are seeking to internationalize our activities in order to further develop a new and high potential market in the transport industry for years to come.

We try to understand what is being done abroad, what solutions exist in major cities around the world. Therefore, in our international business intelligence, business development and marketing approach, we want to conduct international research to better understand the level of maturity of transit agencies around the world.

As well as having a rewarding work experience, Ashish will be able to put to good use the knowledge and skills developed in the courses at HEC Montreal. He will be mentored by our new Executive Director of Operations, Brad Cameron, and myself, having also been offered a Mitacs SSE with BusPas and HEC in 2020.

Enhancing a sales forecasting predictive model within the business rule engine using AI techniques

Flex Travel Solutions is preparing to launch its Machine Learning Module to enhance its BRE tool through predictive analysis. The objective of the project is to provide its clients a sales forecasting predictive model within the BRE to facilitate their business strategies and decisions.

Rapid control prototyping of adjustable speed drive systems for OPAL-RT coursewares with the OP8666 module

This project is focusing on the development of RCP coursewares for adjustable speed drive (ASD) systems with the OP8666 module. The OP8666 RCP module will be used to implement, test, and validate the control algorithms in real-time before being connected in the real-world ASD systems.
Two ASD courseware module families have been agreed for the development of RCP teaching laboratory. The first courseware module includes different electric motor drives such as PM, IM and DC machines, while the second one includes power electronic converter topologies such as DC-DC choppers, three-Phase Thyristor Bridge Rectifier, single-phase and three-phase 2-level inverter and finally three-phase 3-level NPC inverter.
With the developed RCP teaching laboratories, students and researchers in R&D centers or universities will learn and master adjustable speed drives with the OP866 module, which is fast enough to visualize electrical motor drives and power electronics phenomena that can be seen on more expensive and time-consuming analogue setups.

Performance and Robustness-Aware Deep Neural Network Compression for Next-Gen AI Accelerators

Deep Learning (DL) is seen by many as “the” framework to solve complex problems involved in numerous applications that influence people’s lives. It is widely used in safety and security-critical environments such as self-driving cars as well as drones and robotics. This makes it highly essential to secure DL algorithms and systems from malicious actors. To address this, recent work has focused on developing efficient and effective techniques to defend against such attacks on deep neural networks. One major challenge that state-of-the-art defense methods commonly face is that they often study large networks, even for simple tasks. This is impractical to deploy, especially in resource-constrained settings. This project evaluates and explores different methods to decrease the storage and computational costs of robust deep neural models by exploring the impact of model compression techniques such as quantization and pruning on network performance and adversarial robustness.

Tundra North Tours Sustainability Planning

The project being undertaken by the intern will be to develop a sustainability strategy/plan in the form of a report for the host organization’s Okpik Arctic Village. This report will be developed by the intern as they gain important and relevant information though consultations with related stakeholders, conducting environmental impact assessments (based on fuel consumption, water consumption, food consumption, and waste production), and observe all the activities that are undertaken at the village. This will benefit the intern as it will allow them to apply their learned knowledge from their recent education to a real world business. It will also provide the intern the ability to develop real world skills desired by employers. This opportunity will also benefit the host organization by subsidizing the fees associated with an intern that has a thorough understanding of sustainability and is able to utilize their education for the benefit of the business.

Automatic Segmentation of SCG Signal for Ischemic Patients

Research has shown that by monitoring the vibration of the heart using a simple sensor mounting on the human chest, the mechanical characteristics of heart can be measured. The purpose of this research is to design software that can automatically find some important points on the SCG signal. The software will be used to find hemodynamic parameters of the heart that will be used for diagnosis of ischemic heart patients. The outcome of this project is anticipated be extremely beneficial for both academia and the company. By successful completion of this project, multiple publications and patents will help improve the field of cardiac engineering.

Intact : Tarification par apprentissage par renforcement

La tarification en assurance de dommages est une des fonctions fondamentales et elle est traditionnellement entreprise par des actuaires. La tarification demande notamment d’estimer les coûts d’assurance (pertes attendues), les dépenses encourues ainsi que le profit attendu par la compagnie. En plus de ces éléments, la compagnie doit prendre en compte les forces du marché, les compétiteurs, les tendances et bien d’autres éléments qui peuvent affecter le prix du client. Les techniques de tarification sont en constante évolution et utilisent de plus en plus des méthodes d’apprentissage machine ou profond pour améliorer les capacités de segmentation des clients et aller chercher un avantage concurrentiel.
Intact cherche constamment à améliorer ses pratiques de tarification. Dans cette optique, l’utilisation de technique d’apprentissage profond par renforcement semble un filon intéressant à exploiter. En effet, l’intégration d’une politique de tarification qui serait capable de s’adapter aux tendances du marché, aux habitudes d’achat des clients et à l’évolution du risque de chaque assuré est un défi de taille que Intact aimerait relever.