Projets novateurs réalisés

DevOps of Descriptive and Predictive Analytics for Efficient Energy Supply and Work and Asset Management

NS Power is modernizing the electricity grid as a step closer to achieving a cleaner, more reliable, and affordable energy future for Nova Scotia. Smart meters are the standard in electrical meters. They are sophisticated, digital devices that record electricity use and send it to the company through a safe, secure wireless connection. These smart meters have now started providing a large amount of data streaming from every household in the province. While managing such a large amount of data is a challenge, the company is excited about the wealth of information that can be extracted from the dataset. The preliminary experimentation with the data helped us develop a proof of concept that consisted of various features such as stakeholder dashboards, power usage analytics, electricity consumption patterns, etc. The proof of concept is now in place and it has been tested with different datasets. This process helped us develop heuristics for data cleaning and creating configurations. However, this proof of concept now needs to be converted into a prototype that can be deployed and implemented as a full-fledged system at NS Power.

Non(Sleep)Social: Reclaiming the silent night

The project focuses on the benefits of wakefulness at night through listening, and listening collectively, in the context of public programs for exhibitions.

(NON)SLEEP SOCIAL challenges ideas around sleep and sleep ‘disorders’ such as insomnia as unwanted wakefulness during the night. The project focuses on the potential of all night cultural events within the context of the 24/7 city for an awareness of a diversity of life rhythms.

This application is the research phase of the project that will result in the curation of an overnight public program as part the Sociability of Sleep exhibition at the Agora Hydro Quebec in July 2023 involving McGill’s campus community radio CKUT.

Co-creation of a roadmap for data and information infrastructure for youth homelessness prevention

The research project aims to co-create a roadmap for data and knowledge infrastructure that contributes to youth homeless prevention in Canada. A roadmap will be created through collaboration between researchers, policymakers, service providers, and people with lived experience of youth homelessness. Based on the stakeholders’ concerns, priorities and needs identified in the initial phase, the intern will join the PolicyWise Team to lead environmental and jurisdictional scans of youth homelessness services and resources. The intern will also design and conduct stakeholder consultations to identify options that address needs and concerns related to youth homelessness in Canada. During the roadmap co-creation, the intern will design a strategy to access and consolidate a range of stakeholder input and feedback. The roadmap is expected to facilitate timely access to data insights for informed decision making and coordinated service delivery and research collaboration in the youth homelessness sector. PolicyWise can benefit from the intern’s expertise working with hard-to-reach populations applying the Equity, Diversity, and Inclusion approach.

Embedded FBG sensor system for cylindrical roller bearing condition monitoring

Rolling bearings are widely used in products and machinery with rotational motion due to their low rolling friction. Recently, integrating advanced sensor units in the bearings is in a rising demand due to the market requirements. In addition, the advent of the Internet of Things (IoT) has encouraged the real-time monitoring of connected equipment and machinery. However, there are still limitations for the current smart bearings, such as, lacking sensitivity considering the fault prediction, complicated structure, and so on. In order to meet the market demands, our project is going to develop a smart bearing by embedding the FBG optical fiber into the outer ring of the bearing, which can sensitively detect the strain data, thus realize high sensitivity for real-time fault diagnosis. Meanwhile, the structure of the embedded FBG bearing is simple and feasible for manufacturing. FBG optical fiber can collect information including temperature, rotation speed, strain/force, and so on of the bearings simultaneously. Currently, our smart bearing project is under lab test and simulation stage. The results meet our expectation so far. We plan to fulfill the embedded FBG optical fiber smart bearing design as a single unit and check the manufacturing feasibility for the next stage.

Evosep One LC optimization and absolute quantitation of proteins in human and mouse plasma using Multiple Reaction Monitoring and Parallel Reaction Monitoring-Mass Spectrometry

Proteins are sub-cellular molecules that provide important information of how well the body is functioning at a given time. Abnormal increase or decrease in the level of proteins can be indicative of the presence of a disease. Hence, developing tools to accurately measure protein levels in the human body is of utmost importance. Over the past few decades, a specialised instrument called the Mass Spectrometer (MS) has been used for this. The MS instrument can be used in a targeted and untargeted manner. In the untargeted mode, the instrument provides us information on what kind of protein is present in a sample, whereas in the targeted mode, scientists tell the instrument what it needs to look for. When used in the targeted mode, the MS can be used as a validation tool that re-confirms the presence of certain proteins in the sample. Additionally, it also provides information the exact amount of protein present
Although the targeted mode works very efficiently, it is time consuming and unreliable when the protein concentration is very low in the patient sample.

Developing and Implementing Testing Protocols for Large-Scale Hydrogen Storage in Lotsberg Salt Formation

This project will develop and implement laboratory protocols to evaluate the possibility of large-scale H2 storage in salt caverns in Canada. Proof of concept experiments will be conducted on core samples from the Lotsberg Salt Formation to identify and unlock challenges related to containment, contamination, and consumption of stored H2 in salt caverns. The laboratory protocol developed in this research will be used to analyze the core samples and to obtain the optimum design and operational parameters. Field-scale implementation of the developed protocols will facilitate transfer the knowledge to other companies to make the technology broadly used in other salt formation in Canada.

Application of a Novel 3D Centerline Extraction Algorithm for Automated Coronary Artery Mapping and Quantification

Clinical radiology and medical imaging research are beneficiated from the increased effectiveness of modern computer vision and image processing technologies. In order to automatically extract 3D centerlines from complex 3D images, our lab recently created a novel image processing technique. We will demonstrate its clinical utility using real-world medical imaging data. Therefore, the objectives of this project are to: 1) use an open-access algorithm evaluation framework to both quantify the accuracy and demonstrate the utility of our method using a real-world medical imaging benchmark; and 2) improve the computer code into an intuitive software suite to perform automated quantification of blood vessel diameter and cross-sectional area along the segmented coronary artery branches to highlight significant areas that need closer inspection.

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.