Projets novateurs réalisés

Experimental and Numerical Study of Smart Blinds for Building Applications

Windows account for about 30% of the total heat lost from buildings. Fenestration products like blinds and shades can increase the thermal resistance of windows, causing a reduction in the heat loss from windows. In this study, the performance of Smart Blind, an automated blind that adjusts its position to reduce the cooling/heating energy consumption in buildings, will be assessed using a. numerical scheme (CFD) and a real time field study involving prototypes of the product. Specific focus will be laid on the insulating capacity of the stationary air between the window and the blind. The energy savings due to the implementation of the blinds will be determined by comparing the heating/cooling energy consumption for different configurations of the blind.

Quantitative Evaluation and Modeling of Action-Reaction Cycles in Interactive Human Driving Behaviors

This project aims to provide a framework to quantify the interactivity between human drivers in traffic, which could be used to design the decision-making policy for socially-compatible autonomous vehicles. Toward this end, we develop a conditional behavior prediction module based on Gaussian mixture models to jointly capture the dependency of one agent’s reactions on the other agent’s actions. We then implement an optimal transport theory to evaluate the interactiveness and dependency among traffic agents, resulting in a scalar value. Finally, we integrate the quantified dependency into an interaction-aware trajectory prediction model or controller to validate the performance in interactive traffic scenarios. This project would systematically and solidly bridge an enhanced understanding and characterization of human interaction-aware behaviors toward advances in autonomous car perception, decision-making, and control.

A study on additive manufacturing of a 304L stainless steel

Part distortion and residual stress development are two major issues that hinder the industry’s application of the Laser Powder Bed Fusion (LPBF) process. This research will study the formation of residual stress and the distribution of stress fields during the LPBF process using finite element method (FEM) modeling. A sequentially coupled thermo-mechanical FEM model will be developed using ABAQUS FEM software. This study will investigate the distribution of stress components (Sxx, Syy, and Szz) during the LPBF process. Also, the effect of laser power, laser speed, and preheating on the residual stress will be studied.

Identification expérimentale et sans contact du mistuning de blisks par excitation acoustique

Les turbines que l’on retrouve notamment dans les turboréacteurs sont soumises à de très grandes charges, dont de grandes vibrations. De plus, ces vibrations peuvent être amplifiées si de trop grandes imperfections sont présentes pour une turbine donnée. Il faut donc bien détecter ces imperfections pour déterminer si une turbine est sécuritaire avant de l’inclure dans un moteur d’avion. Ces imperfections proviennent de petits défauts d’usinage ou de l’usure en vol. Le partenaire industriel, GE Aviation, aura donc en mains, à la suite du stage, une procédure de test fiable et le plus simple d’utilisation possible lui permettant de bien détecter ces défauts.

Leveraging Third-Generation Sequencing to Facilitate Protein Engineering

Hyasynth Biologicals is a synthetic biology company based in Montreal. Hyasynth is focused on developing novel yeast-based production process for plant cannabinoids for the personal care market globally.

The MITACS projects at Hyasynth will further the goal of developing and optimizing a yeast-fermentation based production process. The optimization of the enzymes and metabolic pathways in yeast will enable greater efficiencies in production and allow Hyasynth to enter commercial production of its target molecules at an accelerated rate.

Improved and Expanded Strategic Marketing Plan for Royal Auto Group

Royal Auto Group needs to expand their market and create a new more diverse client base for their products and services. The intern, Randi will develop new marketing strategies and implement plans for media campaigns, ad buys and work with staff to market to clients in the region.

Hailey Logan – Ayrshire

Ayrshire is an investment management firm focused principally on real estate investing in Alberta. We own retail, office and residential properties in multiple markets. Recently we have seen a shift in investment demand associated with new acquisition and developments of multifamily apartment housing in Western Canada. Recently Ayrshire received federal funding through CHMC Rental Construction Financing Program to build affordable housing units for a project located in the Beverly community in Edmonton. Given it’s strong performance and impact investing nature, Ayrhsire has undergone research to raise capital for an Impact investing fund focused on core needs housing to service Canadian’s through affordable housing, seniors housing, student housing, accessible needs housing, etc. Given subsidy programs and available puclic private partnerships opportunities emerging in Western Canadian urban centres, there are strong tailwinds and an opportunistic time to be investing in multifamily developents that have measurable social impacts. We are needing an intern to help gather economic and financial data to help identify markets where Ayrshire’s investment thesis is supported. This research may be specific to some opportunities in our deal pipeline but will generally be focused on relative fundamentals important to real property markets.

Deneschuk Homes: Software installation and implementation

The intern will work with Deneschuk Homes and the academic supervisor to Implement new software for the business. This software will improve the work flow process in the contruction of custom build ready-to-move houses for customers and for the organization. The intern will also develop staff training and evaluation modules in the use of the new software to ensure that all employees in the organization are able to use the new software to the best of it’s capability.

Full body suit for ergonomic risk assessment

The cost of musculoskeletal disorders in Canada overpasses the $25 billion dollars every year, this amount can be significantly reduced by proving good quality ergonomic assessments and training. The main reason that not all companies invest on ergonomic assessments and/or training is due to the high costs that this entails. This project aims to reduce the cost of ergonomic assessments and trainings by completely automating the process. The research project is focused on designing and developing a computer software that can receive the signal from different inertial sensors and compute and display the body joint angles, and an ergonomic risk score (i.e., REBA) in an automatic way.

Wartime Policy Making and Governance: Ukraine and Canada Higher Education Alliance

Involving some of the smartest students in Ukraine, the research project and partnership will enrich the Master of Global Affairs and Master of Public Policy programs at the Munk School. KSE students will provide Munk community a window into the Ukrainian policymaking process as well as a more general understanding of governance during conflict, Simultaneously, student presentations to senior Canadian officials will offer the Canadian government an in-depth perspective into key policy questions facing Ukraine. This will improve Canadian government capacity to assist Ukraine.
The KSE-Munk students — will examine different models of policymaking in wartime and identity appropriate models for the Ukrainian context. For their final output students will make policy proposals and write up a 10-page policy brief.

Computational Optimal Transport

In the last 30 years, the theory of optimal transportation (OT) has emerged as a fertile field of inquiry, and a diverse tool for exploring applications within and beyond mathematics, in such diverse fields as economics, meteorology, geometry, fluid mechanics and engineering. More recently, thanks to many applications in finance, economics, quantum chemistry, machine learning and statistics, the OT theory for finitely many marginals has achieved important results and is growing considerably.

Despite the enormous amount of progress in the mathematical and scientific literature, computational and statistical challenges in the theory still prevent Optimal Transport to be the method of choices in scientific discovery. Unfortunately, several Multi-marginal OT problems of interest suffer from the so-called curse of dimensionality — their computational complexity scales exponentially in the number N of marginals and are NP-hard. In contrast to the N=2 marginals theory, many analytical and geometrical aspects of MOT problems are far from being fully understood.

Design and Optimization of Helical Coil Suspension Using ANSYS

Due to global trends changing from conventional vehicles(Gasoline) to electric vehicles. In electric vehicles every manufacture company want to reduce the mass of vehicles and my research is on Design Optimization of Helical Coil Suspension using ANSYS in this improving design of suspension system using advanced optimization techniques like response surface method and by using advanced lightweight materials i.e. metal matrix composites.At the end of research we can generate fix model for different vechiles like if commercial vechiles where carry load is more important than comfort or personal vechilces where comfort of vechiles is more important than load and this model we can easily sell to various automobile companies according to their need.