Projets novateurs réalisés

The synthesis and characterization of new boron subphthalocyanine derivatives for organic solar cells

Small molecules with conducting electronic properties resembling those of metals have been used in next generation electronic devices such as organic solar cells. These organic or carbon-based molecules are paving a new road towards environmentally-friendly, flexible and cheaper solar cells. Boron subphthalocyanines (BsubPcs) are an example of small organic molecules that have been used to achieve impressive power conversion efficiencies in these devices. BsubPcs have robust, industrially relevant chemistry and can be chemically modified to predictably tune their physical and electronic properties. In order to assess the structure-property relationships of newly functionalized BsubPcs as well as their impact on solar cell performance, we have expanded the matrix of potential BsubPcs with various halogens (for example, fluorine atoms) in the periphery and carbon-based groups bonded to the central boron atom of the BsubPc. TO BE CONT’D

Real-Time HIL Simulation of a Battery Energy Storage System

Batteries are becoming popular options for storage of energy at large scales for application in power systems. A battery energy storage system may be developed using batteries of different chemistries and also batteries that are not necessarily at the same state of health. The capabilities of a battery energy storage system are affected by the characteristics of the batteries that form it. Therefore, it is essential that a storage systems be developed and operated with a full understanding of how these differences affect its performance. This research aims to (i) develop an experimental storage system and investigate how these factors affect the system, and (ii) provide guidelines for operation and controller design for battery storage systems for enhanced operation.

Multifunctional piezoelectric sensors using two-dimensional layered materials

The project envisages the development of multifunctional piezoelectric sensors using two-dimensional (2-D) layered materials. Piezoelectricity is defined as the electrical response of the materials with respect to the mechanical actuation. This property persists in the materials that have non-centrosymmetry in their internal structure.In particular, the 2-D materials with the non-centrosymmetric structure a great potential lies in the field of electromechanical and electronic device applications owing to a large area coverage. One such class are transition metal dichalcogenides (TMDCs) . TMDCs contain one metal and two chalcogen atoms thus providing non-centrosymmetry in the monolayer . Our target is to explore monolayer of TMDCs by sandwiching it in between two graphene conductive electrodes to obtain a semiconductor device that is capable of sensing strain , actuation applications and energy generation using piezoelectric phenomena.

Next-Generation Thermal Energy Storage Systems for Smart Thermal Grids

Proposed Work- Design Assessment of Latent Heat Storage Systems (LHSS) Integrated with Smart Thermal Grids
Latent heat storage is a coherent technique having a potential of integration with real-time applications. The energy is stored in the form of latent heat during melting of phase change material’s (PCM’s). This energy can be utilized during the peak demand period.
Motivation –
Canada utilizes 19% of its total domestic energy consumption in water heating. Therefore, there is a need to explore technologies like energy storage to meet the surplus demands.
Objectives
• Estimation of thermal load/actual demand through data collection.
• Feasibility of utilizing waste heat sources.
• PCM selection for desired application.
• Developing a thermal model of LHSS of suitable capacity (roughly 13.3 kWh daily consumption per house in Canada) for domestic hot water system.
• Design and investigation using numerical analysis. TO BE CONT’D

KickStarter

Social networks like maps with real-time traffic are good examples of streaming graphs. These streaming graphs are processed and analyzed to answer the queries in real time. Conventional iterative graph processing algorithms estimate the results by approximating the intermediate values. Upon receiving a query, the computation is performed on these intermediate values. This setting gives proper results when the intermediate values are closer to actual values than the initial values, which is the case with monotonic graphs. A monotone function between the ordered sets preserves or reverses the given order. However, when an edge in deleted in such a graph, the monotonic structure get disrupted. And therefore these algorithms output incorrect results. The KickStarter, which is proposed, is expected to handle the problem of processing graphs correctly and efficiently even while the edge deletions are present. TO BE CONT’D

Efficient Computational tools for Magnetic Reconstruction and Image Decomposition

TerraNotes Ltd is a geoscience company based in Edmonton, Alberta. TerraNotes has

developed or improved 75 proprietary geophysical techniques to extract important information

from geophysical datasets. With the current advanced techniques in making use of airborne

surveys, the exploration industry can rapidly and effectively obtain magnetic data which cover

very large regions and remote areas. In the present project, efficient computational tools will

be developed to reconstruct geophysical parameters utilizing the airborne magnetic data, and

new image decomposition software using wavelet-based techniques will be implemented.

The developed numerical programs will enhance TerraNotes’ technologies integrating

geophysical and geological data to extract important information and features which are of

practical applications to the exploration industry in Canada.

Land Speculation and Speculative Landscapes: Possible Architectures of Periurban Vacancy in Sweden

Major Swedish urban centres are facing a backlog of housing issues, and the recent influx of refugees has done little to lessen the pressure on the Swedish housing, rental and social housing markets. The Swedish government struggles to balance state-led housing and civic interests against the growing market for private speculation and development projects. One of the main public concerns is that new, private development will be at the sacrifice of current Swedish cultural values, namely in the periurban recreational landscapes that are primed with redevelopment potential. TO BE CONT’D

La réalité virtuelle : une façon novatrice de favoriser l’apprentissage socio-émotionnel chez les adolescents (deuxième partie)

Le présent projet vise à mettre sur pied un outil d’intervention utilisant la réalité virtuelle afin de favoriser le développement de saines habiletés sociales et affectives chez les adolescents. En collaboration avec la Fondation Jasmin Roy, le stagiaire sera ainsi appelé à participer à la création de scénarios sociaux qui seront projetés par le biais de la réalité virtuelle aux adolescents dans leur milieu scolaire, à l’élaboration d’un guide permettant aux enseignants de diriger la réflexion en lien avec ces projections ainsi qu’à l’évaluation de l’efficacité de l’outil d’intervention. Ce projet permettra à la Fondation Jasmin Roy de poursuivre son intervention visant à stimuler les saines habiletés socio-émotionnelles tout en documentant l’utilisation émergente de la réalité virtuelle en milieu éducatif.

Analyse de performance et potentiel des secteurs manufacturiers de l’Estrie

Le projet vise à identifier les secteurs porteurs pour l’économie estrienne. Ainsi, maximiser les retombées économiques d’investissements futurs dans la région sera facilité par la réalisation de ce projet. De plus, des composantes additionnelles permettront, d’abord, de quantifier les besoins de main-d’oeuvre régionaux ainsi que l’offre de main-d’oeuvre, ce qui permettra aux entreprises d’élaborer des stratégies de recrutement et de rétention de la main-d’oeuvre basées sur les estimations réalisées au cours de cette étude. Ensuite, la quantification de l’impact de l’université à l’innovation régionale offrira une mesure objective pouvant servir de point de comparaison avec d’autres villes universitaires de tailles similaires. Sur la base des indicateurs développés, il sera aussi possible de développer des stratégies visant à développer et à améliorer la synergie entre l’université et les entreprises de la région afin que ces dernières bénéficient de l’appui nécessaire pour innover dans leur domaine respectif.

Modeling atmospheric gas dispersion using computational fluid dynamics

Although rare, industrial facilities can suffer from minor to catastrophic failures, commonly referred to as loss of primary containment (LOPC), which can result in the release of hazardous gases and/or liquids. In order to protect the safety of the public, companies must provide a means of mitigating the potential damage to people and the environment. Since these measures are determined beforehand, the ability to develop and produce accurate modeling techniques is of the utmost importance.
The modeling of gas dispersion in the atmosphere following industrial releases (industrial stacks, containment breaches, etc.) relies on the ability to simulate accurate atmospheric flow close to the Earth’s surface. These flows are generally divided into three stability classes. Although neutral stability is well understood and applies to a number of real world scenarios, accurate prediction of dispersion under stable and unstable atmospheric flow would expand upon the current number of applicable cases. TO BE CONT’D

Constrained Kalman filtering for train position estimation

Just like for the automotive industry, there is growing interest in the development of fully autonomous trains. One of the key steps in the creation of a fully autonomous solution is optaining an accurate estimate of the train position and velocity. Accurate estimates are critical component of the train safety during operation and better estimates allow more trains to operate safely on the same track. The current project deals with trains operating in areas without GPS coverage, such as subways, and so accurate position measurements cannot be obtained as frequently. This means that the estimation algorithm used to calculate the position in between measurements must be as precise as possible to reduce any possible drift. The proposed method to improve the estimate is to ensure that the train states (position, velocity, train orientation) are explicitly constrained by the track the train is traveling on. TO BE CONT’D

Bridging Simulation-based Search and Model-based Reinforcement Learning with Entropy Regularization

Reinforcement learning (RL) provides a unified framework for sequential decision-making problem, where a computer agent interacts with an environment while trying to learn optimal decisions to maximize its long-term reward. This makes RL a suitable choice for many real-world applications, including finance. RL applications in finance have created a lot of in-depth innovation such as better execution of approving loans, managing investments, and most importantly measuring risk. The objective of this project is to advance RL approaches by combining them with powerful simulation-based search algorithms. In particular, we will investigate how simulation-based search can improve the sample efficiency of RL. The performance of our proposed algorithms will first be evaluated on well-known test domains, such as board and video games. We will then employ our algorithms in finance applications.