Projets novateurs réalisés

Explorez des milliers de projets réussis issus de la collaboration entre organisations et talents postsecondaires.

30156 projets achevés

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Projets par catégorie

Investigation and development of an air-core dry-type reactor noise prediction model

Air-core dry-type electrical reactors are integrated into power system infrastructures to limit current and regulate voltage in transmission lines. These reactors, are designed and built to facilitate customer specific requirements using an elementary noise prediction model, which was developed almost 30 years ago. With increasingly stricter noise emission guidelines set by the environmental regulatory bodies, the need to better predict and meet specific noise requirements has become more important to the design and manufacturing of the reactors. The objective of the research is to identify the fundamental structural and electrical mechanisms of noise generation for the reactors and to use this information to develop a more advanced noise prediction model. Having the ability to accurately predict noise emissions at the early design stage will not only allow Trench to meet the specific noise requirements for their customers, but also give them an important competitive advantage over other manufacturers.

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Superviseur du corps professoral :

Colin Novak

Étudiant :

Partenaire :

Trench Canada;University of Windsor

Discipline :

Engineering

Secteur :

Manufacturing

Université :

University of Windsor

Programme :

Accelerate

Net ecosystem exchange of carbon dioxide over agricultural fields near Lacombe, Alberta: data management and processing

Agriculture/ Agri-Food Canada (AAFC) and Campbell Scientific Canada (CSC) have been operating an “eddy covariance” (EC) meteorological tower near Lacombe, Alberta that measures the flux of carbon dioxide (CO2) between agricultural fields and the atmosphere. This tower provides data that is used to assess plant growth and decomposition across fields which is critical for understanding crop viability and the role of Canadian agriculture in the global carbon cycle. Several years of EC data have accumulated from the Lacombe tower, however AAFC/CSC do not have resources to verify these data. Using several software packages, I will correct several years of CO2 flux data from the AAFC/CSC tower. I will statistically compare flux calculations between each program and choose the most suitable software for AAFC/CSC to use for future data processing. I will then develop a software use manual to guide data processors to consistently calculate EC flux data for this station.

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Superviseur du corps professoral :

Vincent St Louis

Étudiant :

Partenaire :

Discipline :

Sociology

Secteur :

Information and cultural industries

Université :

University of Alberta

Programme :

Accelerate

Advanced cluster and predictive analysis tool development for corporate real estate energy usage

The objective of this project is to develop an analytics tool for REALPAC to use to better classify buildings using the “20 x ‘15” dataset collected by REALPAC since 2009. Preliminary analysis has been conducted of this data in past years, but this has been limited to a simple retrospective analysis. The tool that will be developed will incorporate “big data” techniques such as machine learning, which will allow the classification of buildings as “likely strong performers”, “likely poor performers”, “high probability for significant energy conservation”, and “low probability for significant energy conservation”. The intern will undertake data cleaning and classification tasks, as well as the development and testing of the predictive models and associated algorithms that will make up this tool. This tool, in turn, will provide REALPAC with a depth of insight previously unavailable to inform both public policy as well as corporate sustainability strategies of its member organizations. TO BE CONT.

Voir la description complète du projet
Superviseur du corps professoral :

Jenn McArthur

Étudiant :

Partenaire :

Real Property Association of Canada

Discipline :

Engineering

Secteur :

Other services (except public administration); Professional, scientific and technical services

Université :

Toronto Metropolitan University

Programme :

Accelerate

Information Quality (IQ) assurance and control for the BIM lifecycle data

Managing complex, fragmented, and high volume portfolios of data that are generated during the lifecycle of buildings poses major challenges for the Architecture, Engineering, Construction, and Operations (AECO) industry. Required information during the operation and maintenance phase of a building’s lifecycle is usually lost (or not transferred) at information handover stages, and extensive rework should be done to revive them. This projects aims to identify lifecycle information requirements for the operation and maintenance of buildings. Additionally, an information quality management solution will be proposed to ensure the availability and the accuracy of the required data items throughout the lifecycle. The project outcomes will be used by the industry to improve processes related to asset management and the operation and maintenance of buildings. Additionally, newly devised processes help practitioners to ensure the quality of lifecycle data, to reduce the operation costs, and improve the functionality of buildings.

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Superviseur du corps professoral :

Daniel Forgues

Étudiant :

Partenaire :

Pomerleau

Discipline :

Engineering

Secteur :

Construction and infrastructure

Université :

École de technologie supérieure

Programme :

Accelerate

10 Channel Prototype to 16 Channel Medical Grade EEG Headset

Epilepsy affects an estimated 50 million people worldwide. These people can experience unexpected seizures that makes it risky for them to engage in everyday activities like driving and walking. A portable wireless neuromonitoring headset prototype that is worn on the head has been developed by Avertus Inc. to address this issue. The headset is designed to read brain waves, and, through a wireless connection to a cell phone, warn the wearer that the device has measured brain activity characteristic with an oncoming seizure. Improvements to the robustness and comfort of the headset are required to make it easier for epilepsy patients to wear and to help improve its accuracy of seizure prediction. TO BE CONT’D

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Superviseur du corps professoral :

Julie Audet;Martín Del Campo

Étudiant :

Partenaire :

Avertus Inc;University of Toronto

Discipline :

Engineering

Secteur :

Manufacturing; Professional, scientific and technical services

Université :

University of Toronto

Programme :

Accelerate

Indigenous Rights and Environmental Assessment in Canada

Environmental assessment (EA) – the federal, provincial and territorial policy planning tool for deciding on industrial developments – is contentious and under review. Despite increased consideration of Indigenous rights and title as part of the EA process, articulation of concerns with decision-making and significance determination is not evident. In the absence of alternatives, EA is coming to better reflect Indigenous governance and decision-making. Our proposal builds on Firelight’s expertise working for First Nations to assert rights and title in EA processes. An examination of Indigenous based EA is timely given an ongoing federal review of the Canadian Environmental Assessment Act. Under Firelight’s direction, Dr. Hoogeveen will examine innovative EA managed and implemented by Indigenous Governments. She will do this through an examination of Indigenous controlled models of EA through the analysis of four case studies. TO BE CONT’D

Voir la description complète du projet
Superviseur du corps professoral :

Terre Satterfield

Étudiant :

Partenaire :

The Firelight Group

Discipline :

Sociology

Secteur :

Professional, scientific and technical services

Université :

The University of British Columbia

Programme :

Elevate

Balancing costs and benefits of invasive species management for endangered wetland reptiles

Invasive species can have major effects on the landscape, but sometimes their effects are assumed to be negative before they are scientifically tested. The common reed is an extremely tall and robust grass that is moving rapidly into wetlands across Canada. Common reed is believed to threaten some reptiles by reducing their access to suitable habitats, but this has not been tested. In this project, we use state-of-the-art tracking equipment to directly test whether endangered turtles and snakes are forced to change their habitat use in areas impacted by the common reed. We also test the impact of current control measures for common reed (application of the herbicide glyphosate) by assessing chemical loads in our study wetland. Our research fills critical knowledge gaps that will allow managers to make informed decisions, balancing the benefits of controlling this invasive plant against the potential costs of chemical control.

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Superviseur du corps professoral :

Christina Davy;Joanna Freeland

Étudiant :

Partenaire :

Wildlife Preservation Canada

Discipline :

Life Sciences

Secteur :

Professional, scientific and technical services

Université :

Trent University

Programme :

Accelerate

Vision-Based Welding Control and Quality Assurance – Year two

Manual welding is a highly demanding task which requires extensive expertise for certain applications such as pipe welding. To facilitate the welding process, increase productivity, and decrease welder’s required level of skill, Novarc Technologies has designed and manufactured a collaborative Spool Welding Robot (SWR) equipped with a laser assistant weld path tracking. Our proposed research takes into account the fact that currently, welders rely on their eyes and the limited view of the weld pool through the helmet to control the welding process. This is a very arduous task which requires training and experience. Therefore, machine vision and AI can effectively take over the task of visual inspection and detection. Our goals in this industrial research are to use weld image for weld path tracking and torch distance control. We also aim to extract information about weld quality using computer vision and machine learning techniques.

Voir la description complète du projet
Superviseur du corps professoral :

Farrokh Sassani

Étudiant :

Partenaire :

Novarc Technologies

Discipline :

Engineering

Secteur :

Advanced Manufacturing; Technology; Automotive

Université :

The University of British Columbia

Programme :

Elevate

Vision-Based Welding Control and Quality Assurance

Manual welding is a highly demanding task which requires extensive expertise for certain applications such as pipe welding. To facilitate the welding process, increase productivity, and decrease welder’s required level of skill, Novarc Technologies has designed and manufactured a collaborative Spool Welding Robot (SWR) equipped with a laser assistant weld path tracking. Our proposed research takes into account the fact that currently, welders rely on their eyes and the limited view of the weld pool through the helmet to control the welding process. This is a very arduous task which requires training and experience. Therefore, machine vision and AI can effectively take over the task of visual inspection and detection. Our goals in this industrial research are to use weld image for weld path tracking and torch distance control. We also aim to extract information about weld quality using computer vision and machine learning techniques.

Voir la description complète du projet
Superviseur du corps professoral :

Farrokh Sassani

Étudiant :

Partenaire :

Novarc Technologies

Discipline :

Engineering

Secteur :

Advanced Manufacturing; Technology; Automotive

Université :

The University of British Columbia

Programme :

Elevate

Effects of Geomechanical Heterogeneity on Wormhole Development during Cold Heavy Oil Production – Phase 1

Canada possesses vast resources of heavy oil, which is oil that is too thick to flow through porous sandstone reservoirs and into production wells at economic rates when conventional operating practices are used. Since the mid 1980’s, heavy oil operators have demonstrated their ability to increase heavy oil production rates by encouraging the creation of porous and permeable zones (“wormholes”) within their reservoirs by allowing sand grains to detach from the reservoir rock and flow into the well (along with the oil). However, in order to improve the efficiency of these operations, a better understanding of the processes controlling wormhole growth is required. The proposed project will result in the design of a laboratory testing system that will lead to a better understanding of wormholes in heavy oil reservoirs.

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Superviseur du corps professoral :

Chris Hawkes;Peter Yongan Gu

Étudiant :

Partenaire :

Petroleum Technology Research Centre

Discipline :

Engineering

Secteur :

Mining; Professional, scientific and technical services

Université :

University of Saskatchewan

Programme :

Accelerate

Magnetic Field Modelling and Optimization in NMR Spectroscopy Device

Nuclear Magnetic Resonance Spectroscopy is the preeminent technique used to perform advanced quantification of chemical samples. Industries that rely on rigorous quality assurance can quickly take samples of their product and perform extremely detailed chemical analysis to guarantee reactions, and overall product quality. Currently, the spectroscopy devices used are incredibly large and expensive and do much more than fill the needs of the average consumer. A novel approach using a tabletop device has been proposed to fill the market however given the size and price constraints, it is extremely challenging to meet the requirements for magnetic field strength and uniformity. The computer modelling proposed in this project, will provide a detailed numerical representation of the magnet showing the deficiencies and strengths of current designs without having to build every piece and conduct full-scale experimentation.

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Superviseur du corps professoral :

Elise Fear

Étudiant :

Partenaire :

Discipline :

Engineering

Secteur :

Université :

University of Calgary

Programme :

Accelerate

Exploring the Impact of Housing-based Overdose Prevention Interventions on People who use Drugs in Vancouver – Year two

Canada is amid an opioid epidemic, with governments declaring overdose public health emergency. Drug-related overdose mortality in British Columbia reached a record high in 2017, with over 1400 deaths. In response, novel overdose prevention interventions (OPI) have been implemented, including: overdose prevention sites in which people can inject drugs under supervision; and, naloxone training and distribution (a medication that blocks the effects of opioids during an overdose). For the first time, these interventions are being implemented in emergency shelters and single room accommodations (SRA) housing, which provides shelter to more than 3000 people who use drugs (PWUD) in Vancouver’s Downtown Eastside. This study will explore social-, structural-, and physical-environmental influences on the implementation and effectiveness of overdose prevention interventions in SRA housing and emergency shelters. TO BE CONT’D

Voir la description complète du projet
Superviseur du corps professoral :

Thomas Kerr

Étudiant :

Partenaire :

Pivot Legal Society

Discipline :

Sociology

Secteur :

Other services (except public administration)

Université :

The University of British Columbia

Programme :

Elevate

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