Projets novateurs réalisés

Heat dissipation characteristics and ampacity analysis of three-phase underground cables with detailed soil thermal conductivity modeling

To satisfy the growing demand of power transmission in urban regions especially from the renewables such as
solar and wind, the three-phase underground cable lines have become one of the most attractive solutions
which fit both the space and landscaping requirements. The heat generation and energy dissipation
characteristics of these underground cable assemblies directly determine the cable ampacity and operation
performance. This project will create and validate a thermal model for three-phase cable assemblies in a
metallic ventilated enclosure; both in free air and within a concrete box. This study will benefit the partner
organization by allowing the design engineers to model variable types of cable assemblies that are not covered
in standards or electrical codes.

Hierarchical graph kernels for classification of molecules

The central problem of pharmaceutical research is to understand the effect of a certain molecule on human or animal biology. Many machine learning models have been developed in recent years and show great efficiency and accuracy for this kind of predictions. However, a problem common to many of the best algorithms is that they require huge amounts of data to be sure the models are well trained and make accurate predictions. This is a serious issue when such data volume is not available. We propose to adapt a family of methods called hierarchically defined kernels we belive is well suited to tackle the problem of molecule classification for small datasets. This method works by decomposing the objects of interest in a tree-like structure of sub-objects (like a picture can be split up into sub-pictures, each sub-pictures be decomposed into smaller sub-pictures and so on) and constructing iteratively a similarity measure starting with a similarity on the smallest sub-objects.

Novel Perovskite Nanoparticle Water Quality Sensor

The proposed research aims to manufacture smart water sensors for real-time monitoring of Canadian watersheds’ quality. The need for clean water is constant for communities across Canada. With growing concerns related to organic pollutants entering the water supply, the treatment of drinking water and water systems, and their health effects a need has been sown. The requirement for rapid, high accuracy and low cost water quality sensors is as prevalent now as at any point in the past. One pollutant source comes in the form of organic molecules, often hydrocarbon wastes from manufacturing, or hormones given off from animal excrement. Tracking the dissipation and sequestration of organic molecules in a water body is critical to watershed health. In cities, these systems help identify and treat some of the symptoms of urban stream syndrome. The research will increase Canada’s scientific and engineering capabilities in water quality monitoring. As a result, Canada will benefit of high-skilled interns to the workforce in the addition of its ability to compete in the global water marketplace.

Characterizing the sensory attributes of red and white wheat, their bransand whole grain products made using red or white wheats.

Red wheat is the most predominant wheat grown in Ontario. However, red wheats impart an

off-flavor to products when used in whole wheat formulations. The food industry is moving

towards developing a whole portfolio of whole wheat products in order to provide a healthier

alternative to consumers. However, issues related to the sensory characteristics of these

products have to be addressed first. There is a paucity of research on the subject of the

sensory attributes of red wheats compared to white wheats; what is the nature of off-taste,

what are the reasons for these; is the sensory attribute different based on the particle size of

the bran, etc. This collaborative project is the first step to establish clearly the nature of the

sensory attributes and its perception by consumers. The knowledge gained hereby will lead

to developing strategies to formulate whole grain products with improved sensory and textural

attributes.

Groundless MEMS DC Voltage Sensors for Electric Power Utilities

This research project will develop dc electric field sensors for the monitoring of electric power utility infrastructure and for non-contact voltage probing and monitoring. MEMS sensors are the focus, as they offer small size, low cost, and low power operation. These properties make them ideal for hand held operation, and for deployment in remote locations far from urban centres, a requirement needed by utilities to monitor their 1000’s of km of transmission infrastructure. Developed sensors would also be valuable to other industries requiring electric field or static charge monitoring. Two main categories of sensors will be developed. First, sensors for measuring high dc electric fields (100 V/m – 1 MV/m) and ionic flux will be explored. These would be suitable for monitoring HVDC infrastructure. Second, sensors for low fields (1 – 10,000+ V/m) and close proximity measurements will be investigated. Included in these efforts, will be the development of optimized sensor enclosures to maximize sensor sensitivity.

Accelerating eVTOL Research Outcomes (AeRO)

Electric Vertical Take-off and Landing (eVTOL) vehicles represent the new frontier of transportation electrification. Since the dawn of aviation, enthusiasts have dreamed of “flying cars” that can reduce trips that take hours on the ground to minutes in the air, improving productivity and quality of life. What was previously the realm of science fiction is rapidly becoming a viable commercial reality. However, significant performance and efficiency improvements, at both individual component and overall system levels, must be made in order to bring eVTOL from the proof-of-concept stage to a viable product. This project will research and develop models, prototypes, and tools to support the development of power electronics components, controls and architectures for an eVTOL application under developed by our industry partner. In so doing, this project will enable the development of eVTOL aircraft that will: reduce emissions; meet stringent safety requirements; comply with aerospace standards; address an emerging global market opportunity; and provide engineering postgrads with a unique opportunity to gain hands-on experience in an emerging sector with excellent career prospects.

Nutrient removal using a solid state glass adsorbent for treating agricultural waste, waters, and public effluents

Agricultural waste and public effluents often contain elevated levels of phosphorous and nitrogen that limit its ability to be directly repurposed as crop fertilizer or irrigation spray. Removal of soluble nutrients from waste water is difficult. Current treatment options have high investment costs and are often not well suited for smaller farm sizes common in Canada. This research intends to characterize the utility of a solid state absorbent material engineered by NPower Clean Tech Corporation that shows promise for removing anionic forms of phosphorous and nitrogen. If the product economically recovers these nutrients, then this research may directly benefit Canadian farmers, public sewer utilities, and waste generating industries by offering an additional means of controlling their waste stream profiles.

Developpement d’une strategie de cartographie de la neige a partir des donnees deteledetection a I’aide de I’estimation d’ensemble

Au Quebec, la fonte du couvert nival est Ie mecanisme responsable de la majorite des crues

printanieres. Par consequent, I’evaluation de I’etendue du couvert nival en temps reel

interesse au plus haut point les autorites responsables de la gestion des ressources

hydriques, en particulier Hydro-Quebec. L’objectif de ce projet de recherche est Ie

developpement d’une strategie de cartographie en temps quasi-reel de I’etendue du couvert

nival a partir des donnees de teledetection a I’aide d’une estimation d’ensemble. Pour

I’atteinte de cet objectif, trois etapes sont necessaires : (1) Ie developpement d’un algorithme

de cartographie du couvert nival ada pte aux conditions d’automne du Quebec a partir des

images journalieres du capteur optique NOAA-AVHRR; (2) la realisation d’une analyse

comparative des divers algorithmes de cartographie du couvert nival actuellement

disponibles pour differents capteurs, incluant ceux developpes par I’INRS et Hydro-Quebec

pour I’automne et Ie printemps;

Developing a reliable model of biochar behaviour in northern forest soils

Understanding the fate of biochar in boreal soils is critical in order to develop appropriate

application rates and carbon credits. Accurate models of biochar stability and carbon density

are required for proper carbon accounting. The intent of this study is to model the long term

stability of charcoal in northern forest soils. We will utilize a combination of existing and new

trials to develop Boreal specific turnover rates and an existing 200 year post-fire

chronosequence of forest stands to calibrate and validate the model outcomes. Development

of the model will form the basis of early carbon credit estimates for our partners and aid in the

development of a carbon sequestration market.

Knowledge Translation and Simulation: the Viability of Teaching Financial Literacy through Gameful Design

The project seeks to make online management of credit card usage easier by developing new design methods for making information easier to understand in digital platforms. Through rhetorical accommodation, or the process of translating complex information into simpler forms, the project will improve TD’s web-based (EasyWeb) and mobile (TD App) platforms so that credit card usage and payment will be easy to understand. This research is important because it studies the ways financial service providers like TD can improve customer satisfaction. The project will establish new methods of gameful design which could include visualizations, for example, to inform TD’s customers on credit card habits in an informative, subtle, and respectful way. The guidelines would aid consumers making educated decisions and obtain more financial freedom as they better understand the product and services available to them. This could result in adoption of more TD products and increase in consumer spending habits.

Ecological engineering in Sphagnum cultivation: From establishment and production of moss biomass to water management and greenhouse gas monitoring

This project proposes to develop appropriate engineering tools to optimize the operation and tracing of a Sphagnum cultivation site. The project has three major stages: 1) literature review of main indicators of water stress based on the WTD, 2) construction of a database and indexes to represent fluctuations of seasonal water table that allows the estimation of biomass accumulation in Sphagnum cultivation, and 3) construction of a cost-effective and efficient prototype for continuous monitoring of greenhouse gases in Sphagnum cultivation sites. It is expected that the results of this research be useful to extrapolate these experiments in a large-scale Sphagnum cultivation project.

Automated Change Detection of Serial MR Images Using Compressed Sensing

We aim to develop a new algorithm to detect changes in serial MR examinations.

Computer-based change detection system is an important tool to automatically

process abundant information produced by imaging systems and assist physicians to

identify clinically important changes in the images. Many existing methods are

computationally costly. The emerging mathematical theory of compressed sensing

(CS) allows exact reconstruction of a sparse signal from fewer samples. Generally, a

medical image does not have a noticeable quality change by discarding certain

information) and changes of the same patient over time are spatially sparse. We thus

utilize the CS techniques to develop novel change detection algorithms that reduce

computational cost and extract clinical-relevant information robust to the presence

of noise. Our algorithm is expected to assist radiologists to make early diagnosis and

be used as a training tool for young practitioners as well as to advance the

development of change detection technology in geological and other applications.