Projets novateurs réalisés

User Interface with analytics for Mini-substation monitoring

The project entails the creation of a web based application that will monitor sensors on substations. The application will graph data from the sensors with warning thresholds. It will notify specific users via text and email when thresholds have been met. The app will also store sensor data and look for trends using machine learning. For example if the substation goes down when the humidity and temperature are at a certain level.

Développement de modèles de détection d’anomalies pour les parcs éoliens et solaires

Power Factors offre une plateforme de suivi de performance de parcs éoliens et solaire. Cette plateforme collecte

les données opérationnelles des parcs, les archive, puis les traite (calcul d’indicateurs de performance) pour

ensuite les transmettre aux exploitants et propriétaires de ces parcs. Power Factors utilise déjà quelques modèles

de détection d’anomalies à travers sa plateforme d’analytiques avancées. Ces modèles ont pour but d’identifier

des anomalies et des tendances alarmantes telle que la détection précoce d’un bris ou d’une sous-performance

et par la suite, aider les exploitants de ces parcs dans leurs opérations de planification de la maintenance. L’objectif

du projet est de développer de nouveaux modèles de détection d’anomalie pour les parcs éoliens et solaires, ce

qui permettrait à Power Factors de garder un avantage concurentiel considérable.

Catalytic oxidative desulfurization of tire pyrolysis oil, fuel oils and their distillates

Thermochemical conversion of waste tires to useful energy resources is attractive to obtain pyrolysis oils with potential economic value. However, the high sulfur and nitrogen contents prevents its direct application as a drop-in fuel in refineries. Though, catalytic hydrotreatment can reduce these heteroatoms, the prohibitive costs of high pressure equipments and harsh reaction conditions necessitates other options including oxidative desulfurization to be explored. This work package with AirScience Technologies proposes to: 1) develop a protocol to fractionate the virgin pyrolytic and fuel oils; 2) develop catalysts for the upgradation of the various cuts via oxidative desulfurization; 3) develop adsorbents for the removal of oxidized heteroatoms; 4) perform regeneration study of optimized catalyst and adsorbent; and 5) scale-up the process from 100 mL to 2 L batch using the optimized catalyst and adsorbent. The proposed project will be beneficial to our industrial partners and Canadian Waste Recycling Industries.

Validation d’un modèle de la connectivité écologique

La connectivité écologique est un des attributs les plus importants pour le maintien de la qualité de l’habitat et de la bioiversité présents sur le territoire. La mission de la compagnie Eco2Urb est d’assister les grands propriétaires d’écosystèmes et d’infrastructures naturelles pour augmenter la résilience de leur réseau écologique au bénéfice de la biodiversité ainsi que le bien-être et la santé des citoyens. Ainsi, la compagnie développe une plateforme informatique visant à calculer la diversité et la connectivité d’un territoire en se basant sur les modèles développés récemment par l’équipe du Dr. Andrew Gonsalez. Afin de paramétriser la plateforme à l’aide de données de terrain, la compagnie souhaite incorporer les données d’utilisation du territoire par la faune, recueillie sur le territoire de la MRC Papineau. Plus précisément, ce modèle sera utilisé au sein d’un contrat de recherche pour la MRC de Papineau au Québec, pour paramétriser le modèle à l’aide de l’utilisation réelle du territoire par les espèces fauniques, d’identifier les infrastructures naturelles les plus utilisées par la faune, et de raffiner la portée du modèle.

Data-Driven and Anthropometric Local Editing of Facial Polygon Meshes

Editing the faces of 3D avatars is a difficult and important task. We will develop an approach that enables users

to perform local edits of faces through means of adjusting the values of anthropometric measurements. Such

measurements are derived from well-established research about the shape and proportion of faces. Based on a

data set of 3D scans of faces, our approach will understand trends among the measurements and the shape of

faces. With our approach, editing the face will be easier and more predictable. Furthermore, editing a specific

region of the face, for example the nose, will not have unexpected side effects elsewhere on the face, as is

common with current methods. Our new tool will enable artists to create faces that match their intent.

Microelectromechanical Low-power Strain Sensor for structural health monitoring applications

Structural health monitoring (SHM) of airplanes requires very compact and low-power stain sensors. Therefore,

IPR wants to investigate how a commercial micro-fabrication process can be used to implement its MEMS sensor

design, particularly using the electro-conductive properties of doped silicon vs. metal-coated crystalline silicon or

polysilicon. The project will consist 0f e conceptual study of the current design provided by IPR and the design

and evaluation through simulations of that design implemented in different technology. Moreover, design variants

of different geometries will be investigated.

This project aims at the design of an adapted sensor for the PiezoMUMPS and PoIyMUMPS offered by the

MEMSCAP fou ndry and the investigation of several design variants to improve yield and performance. Moreover,

it will also provide a custom process flow that could be implemented as an alternate approach to fabrication at the

C2MI.

Étude des paramètres physico-chimiques affectant le procédé de fabrication du fondant

La fabrication de produit issu de réactions chimiques pourra bénéficier des retombées de l’industrie 4.0. Cependant, pour arriver à un grand degré d’automatisation et le choix approprié des paramètres à contrôler par l’acquisition de données en temps réel, il est important de déterminer et de comprendre l’impact des variables sur la qualité du produit final. Dans le cadre de ce projet, les caractéristiques des réactifs impliqués dans la production de fondants seront étudiées. À l’aide d’outils d’analyse chimique, nous pourrons connaitre l’impact individuel et synergétiques de certains paramètres clés affectant les caractéristiques des produits de synthèse.

Development of a commercial preservation technology to minimize physiologicalinjury and assure quality attributes of apple fruit

The ripening of fleshy fruits such as apple, pears and tomatoes results in a coordinated

change in texture, nutritional characteristics, color, flavor and aroma, and initiates

senescence processes that reduce shelf life. Fresh market apples are often treated with 1-

methylcyclopropene and stored under controlled atmosphere conditions to delay ripening and

extend the supply period to consumers. However, there is always some degree of economic

loss due to external injury and flesh browning of the fruit. In this proposal, we intend to

investigate mechanisms responsible for these physiological disorders in two popular

Canadian apple cultivars (‘Empire’ and ‘McIntosh’). The fruit will be stored under various

conditions of temperature and carbon dioxide with or without 1-methylcyclopropene treatment

and fruit quality and biochemical and molecular parameters will be assessed. The overall goal

is to contribute to the development of a reliable commercial preservation technology to

minimize physiological injury and assure quality attributes of apple fruit.

Development of converter based electrochemical impedance spectroscopy, modeling and data processing tools for fuel cell stack diagnostics and servicing

Heavy-duty fuel cell vehicles as a clean energy transportation solution have attracted much interest over the last few years. However, they still suffer from various degradation and faults and a relatively short lifetime, hindering their wider market adoption. Better diagnostics tools are highly needed to obtain information from the fuel cell stacks of the industrial partner, Ballard Power Systems. Electrochemical impedance spectroscopy (EIS) has been established as an important technique for fuel cell diagnostics. Linear power amplifiers were used previously as an excitation source for EIS with limited power rating and efficiency, restricting their applications to only single cell or short stack testing. This project therefore aims to develop a converter based EIS tool with higher power capability for Ballard’s fuel cell diagnosis at the stack level. It also aims to develop new models and data processing techniques to augment and generate EIS data for hydrogen leak predictions.

Novel heavy oil separator design

Heavy oil reservoirs experience complex production problems when polymer gels are used to control water produced from the reservoir. Produced gels destroy facility equipment and can be a potential physical or environmental hazard. The current project will address this issue and propose mitigation measures that may include pre-treatment of the produced fluids prior to entering the water/oil separators, or alternative separator designs. One M.Sc. student will be trained alongside engineers of the industrial partner. The industrial partner will get a methodology and/or a design for a novel separator.

An automated system to identify and extract key structural components in academic written texts or genres

To streamline knowledge acquisition, indexing, dissemination, and synthesis—especially important to the future of libraries—a fundamental understanding of knowledge storage and communication is required. In a textual body of knowledge, relevant qualities include layout and structure; headings, chapters, sections, and paragraphs; figures, tables, lists, captions, and illustrations; authorship information and references; and, most importantly, the relationship between these semantic components. We propose research to develop a series of software model pipelines capable of producing a JSON file of an input document’s relevant semantic qualities. This inter-disciplinary project combines computer vision, natural language processing (NLP), and computational linguistics to research optical character recognition, document classification, document object detection and segmentation, document layout recognition and classification, and semantic labelling. Deep learning, statistical machine learning, and traditional computer vision-based methods for these topics will be researched and evaluated.

The real world of environmental pollutants: New approaches to identifying priority contaminants in the Endangered Southern Resident Killer Whale food web

The Southern Resident Killer Whales (SRKW, Orcinus orca) population is assessed at 73 individuals, and significant threats include high levels of endocrine disrupting contaminants, alongside other anthropogenic threats. Studies have painted a partial picture of the contaminants of concern in the SRKW food web. For example, preliminary studies of chinook salmon suggest that some resident populations are more contaminated than others which may be contributing to the high PCB burden in SRKW. This underscores the value of generating new information on contaminant concentrations and profiles in dominant prey species and / or stocks of this endangered whale population. This study presents a science-based evaluation of the contaminants found in their diet (food web) and habitat, the development, adaptation and/or application of new tools to prioritise (rank) the pollutants of concern, and the delivery of refined guidance to support of the wider conservation agenda for this (and other) at risk species