Innovative Projects Realized

Explore thousands of successful projects resulting from collaboration between organizations and post-secondary talent.

31133 Completed Projects

2940
AB
5159
BC
837
MB
685
NL
882
SK
9292
ON
9695
QC
97
PE
601
NB
1161
NS

Projects by Category

Optimisation de la diète et du procédé de transformation

NEXFID est une start-up de biotechnologie qui compte produire et commercialiser les protéines et acides gras de haute qualité provenant de l’élevage d’insectes tout en valorisant les déchets organiques. La farine et l’huile d’insecte sont des alternatives durables et écologiques au soja et à la farine de poisson. La production se situera dans une dynamique de symbiose industrielle où les déchets d’agroindustriels seront utilisés comme intrants dans la production des larves. La bioconvertibilité de ces déchets représente l’élement central de la production et c’est dans ce contexte que NEXFID compte rentrer en production pilote afin de valider et optimiser certains paramètres de production. L’objectif de la phase de recherche se situe trois niveaux.
• Évaluer et optimiser la bio-convertibilité des déchets organiques qui seront valoriser
• Optimiser le procédé de transformation
• Évaluer la qualité et la performance de notre farine et de notre engrais
Nous comptons également envoyer les échantillons de notre farine et engrais à nos clients potentiels afin d’évaluer leurs performances, leurs qualités et leurs adaptabilités à leurs équipements de production. Le but sera de signer des contrats de ventes avant de commencer la production industrielle

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Faculty Supervisor:

Marie-Hélène Deschamps

Student:

Partner:

NEXFID

Discipline:

Life Sciences

Sector:

Manufacturing

University:

Université Laval

Program:

Accelerate

Continuous flow chemistry synthesis of Vitamin C

Natural health products have become integral to many personal routines and the Canadian economy as a $9 billion industry. But recent problems within China and India, which currently have a stranglehold on raw materials, are endangering the health of this growing sector. Replacing foreign sources with traditional batch production means is foolish since domestic labor costs are not competitive. By utilizing the high-tech method of production of continuous flow chemistry, we can achieve a cost-effective and competitive production method. We chose to investigate the production vitamin C since it is the most-consumed nutraceutical ingredient by mass. If successful, we can open a new paradigm of vitamin C synthesis with potentially trivial achievement of pharmaceutical-grade purity, minimal labor input and near-zero environmental impact. Furthermore, this technology can be implemented into other key vitamins and even pharmaceuticals which not only has obvious commercial implications but can contribute significantly to establishing healthcare independence.

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Faculty Supervisor:

Kalindi D. Morgan;Andrea Gorrell

Student:

Partner:

EluciDx

Discipline:

Life Sciences

Sector:

Professional, scientific and technical services

University:

University of Northern British Columbia

Program:

Accelerate

A Finite Element Framework for Anisotropic Material Constitutive Modelling of Additive Manufactured Superalloy Parts

Additive Manufacturing is a rapidly growing technology in the gas turbine industry. Its numerous advantages allow for the design of complex shapes which have not been possible in the past, using conventional manufacturing method. The parts could be manufactured on demand, with reduce cost and lead time. Selective Laser Melting is the common method to additive manufacture metal super alloy parts for combustors and turbines. The anisotropic microstructure from the printing process pose a challenge to numerical simulation and conventional predictive models. To accurately predict the mechanical integrity of the part, an improved constitutive material model that could accurately predict the part non-linear deformation after yielding is crucial. It’s especially important to couple this non-linear deformation model with the thermo-mechanical loading where the temperature could be in phase or out of phase with the loading
This project aims to create an efficient and accurate non-linear deformation for predicting the mechanical deformation of the SLM parts, theirs associated stress and strain, in preparation for future mechanical integrity assessment model. Using mathematical model and empirical factors from material testing, an efficient predictive tool will be developed to extend the current capability within Abaqus finite element software.

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Faculty Supervisor:

Mathias Legrand

Student:

Partner:

Siemens Energy Canada

Discipline:

Engineering

Sector:

Information and cultural industries; Professional, scientific and technical services

University:

McGill University

Program:

Accelerate

Calibration of numerical model of the three-stage corrosion process of galvanized steel reinforcements in Mechanically Stabilized Earth

Bridge abutments are commonly built with a construction technology called Mechanically Stabilized Earth that provides structural soundness. The core element is a composite material that alternates layers of backfill soil with layers of galvanized steel reinforcements. Although the structural design has been well developed since its introduction in the construction practices, the degradation of the reinforcements due to corrosion has not been considered in detail and it is a major failure mechanism. A numerical model of the three-stage corrosion process of galvanized steel in Mechanically Stabilized Earth has been developed. The model considers variations in properties of the soil such as temperature, oxygen availability and salts content. However, field data from several bridges in British Columbia is about to be collected with the Ministry of Transportation and Infrastructure. The information gathered will be used to calibrate the model to its most realistic prediction capability so it gives reliable estimations that can be used for risk assessment of the structures.

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Faculty Supervisor:

Akram Alfantazi

Student:

Partner:

Transportation and Infrastructure BC;Atlantic Industries Limited (NB)

Discipline:

Engineering

Sector:

Construction; Transportation (excluding aerospace)

University:

The University of British Columbia

Program:

Accelerate

Optimization of Isolation and Purification of the Microbe-to-Plant Signal Bacillin 20 from Bacillus thuringiensis

Plants are always associated with a well-coordinated and beneficial community of microbes – the phytomicrobiome; this plus the associated plant forms the holobiont, the entity that provides crop yield. There is considerable communication between the phytomicrobiome and the plant, often through signal compounds. Bacillin 20 is a small protein (a peptide) produced by a Bacillus thuringiensis strain and discovered by the Smith laboratory. It improves plant ability to tolerate stress when applied at very low concentrations. One plant response to stress is accelerated flowering, leaving longer time for grain production. The proposed work will evaluate the potential for bacillin 20. This work focuses on bacillin 20 mature and widely used technology (both relatively inexpensive and environmentally friendly) for the production of a wide range of agricultural crops (extending all the way from soybean to cannabis). This work will make Canada a global leader in the area of microbe-based biostimulants. Technologies that assist crops in dealing with stress will play a key role in the longer-term development of climate change resilient agriculture.

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Faculty Supervisor:

Donald Smith

Student:

Partner:

CXC

Discipline:

Life Sciences

Sector:

Agriculture; Professional, scientific and technical services

University:

McGill University

Program:

Accelerate

System-on-Chip-based Sensor Interfaces With Thermal Management for Aerospace Applications

Nowadays, aircrafts use computer-regulated flight control systems that replace mechanical controls with electronic interfaces. These sensor interfaces convert physical movements or quantities (temperature or pressure for instance) to electronic signals between flight control computers (FCCs) and actuators and sensors. A large number of sensor interfaces are used in an aircraft to allow FCCs communicating with electromagnetic-based actuators and sensors. Their cost, size, weight, and power (CoSWaP) should be optimized. Moreover, these interfaces are connected to different loads and sensors in the aircraft that typically have their own requirements. Therefore, sensor interfaces should be adjusted for different needs. Redundancy and lack of versatility/flexibility motivate interfaces’ manufacturers to look for ways to reduce CoSWaP by shrinking the size of components and making sensor systems more flexible. This helps to ease maintenance and gain economic benefits.
This project aims at leveraging advanced system-on-chip (SoC) integration technologies to implement senor interfaces for aerospace applications. In this technology, low and high-voltage electronic modules are integrated in a single microelectronic chip, which reduces CoSWaP. Means of programming and configuring these interfaces will be developed to allow adjusting SoCs to specific target uses of the proposed sensor interfaces.

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Faculty Supervisor:

Yvon Savaria;Ahmed Lakhssassi;Ahmad Hassan;Yvon Savaria;Benoit Gosselin;Ahmad Hassan

Student:

Partner:

Thales Canada Inc;Mitacs - Vancouver

Discipline:

Engineering

Sector:

Manufacturing; Professional, scientific and technical services

University:

Polytechnique Montréal; Université du Québec en Outaouais

Program:

Accelerate

Analyse et amélioration de modèles NLU dans le domaine de l’assurance

Koïos Intelligence est à la source de l’agent conversationnel Olivo qui vise à offrir une expérience interactive, guidant l’utilisateur au travers des processus de prévente, de vente et d’après-vente pour tous les types d’assurances. Bien que l’outil soit dans un état avancé tant au niveau de la conversation écrite qu’orale, et ce aussi bien en français qu’en anglais, son amélioration se heurte aux exigences computationnelles lourdes pour l’entraînement des modèles d’apprentissage automatique sous-jacent. De plus, les outils de discussions inte-ractifs sont souvent imprécis dans leur développement et mise en œuvre dans le cadre d’un champ d’application particulier. C’est en particulier le cas en finance, pour les outils de conseils en matière bancaire et assurance. Il est nécessaire pour les rendre plus pertinents d’améliorer leur entraînement en utilisant des bases lexicales spécialisées, dont dispose en interne Koïos Intelligence.

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Faculty Supervisor:

Michel Desmarais

Student:

Partner:

Koïos Intelligence Inc

Discipline:

Computer science

Sector:

Professional, scientific and technical services; Retail trade

University:

Polytechnique Montréal

Program:

Accelerate

Humpback whale prey consumption in British Columbia and the effects of a growing population on the food web in the Strait of Georgia

Since the end of whaling, the population of humpback whales feeding in the Canadian Pacific waters has
been steadily increasing. As generalist feeders, these large cetaceans aggregate near the coast of British
Columbia to feed on krill, Pacific herring, and other schooling fish. Yet, the consumption of prey by humpback
whales in Canadian Pacific waters has not been estimated. The aim of this research is to quantify how much of
each prey population the humpback whale population consumes from the Strait of Georgia. This project will also
predict the effects of a growing population of humpback whales on the food web. This study will help inform both
conservation and fisheries management strategies as it focuses on economically and culturally valuable species.

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Faculty Supervisor:

Villy Christensen

Student:

Partner:

Marine Education and Research Society (MERS)

Discipline:

Life Sciences

Sector:

Professional, scientific and technical services

University:

The University of British Columbia

Program:

Accelerate

EXFO : Utilisation des réseaux neuronaux pour l’identification et la classification d’anomalies dans les fibres optiques

Ce projet proposé par EXFO vise à améliorer la performance des Optical Time-Domain Reflectometer (OTDR) pour l’évaluation de la qualité d’un lien de fibre optique utilisé pour la télécommunication. L’objectif principal est d’améliorer l’identification des événements et leur classification en utilisant des réseaux neuronaux.
Les méthodes actuelles peinent à identifier des événements successifs rapprochés, particulièrement lorsqu’ils sont loin de l’extrémité de la fibre optique où l’OTDR est branché. L’opération de moyennage des signaux, nécessaire à la réduction de dimensionnalité pour l’analyse classique, réduit l’information pouvant contribuer à identifier les événements. En utilisant les réseaux neuronaux, il devient possible d’utiliser les signaux bruts pour augmenter la résolution de l’analyse.

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Faculty Supervisor:

Christian Gagné;Leslie Rusch

Student:

Partner:

EXFO

Discipline:

Computer science

Sector:

Information and cultural industries

University:

Université Laval

Program:

Accelerate

Evaluating extended-release injectable buprenorphine in a Canadian setting

Canada is in the midst of an opioid epidemic. Although oral opioid agonist therapies (OAT) are effective for the treatment of opioid use disorder (OUD), a number of barriers pose a significant challenge to treatment initiation and retention. In 2018, Health Canada approved a new medication for OUD, a once-monthly injection, which may be able to address challenges related to medication adherence. The current project aims to support a larger observational study that assess the feasibility, efficacy, and safety of this new treatment option. The current project will ensure greater transparency in the research process and generate awareness of the study. Overall, this will support knowledge generation that will inform clinical practice and may contribute to improved health outcomes for individuals with OUD, a population of emphasis at Providence Health Care (the partner organization).

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Faculty Supervisor:

M. Eugenia Socias;Nadia Fairbairn

Student:

Partner:

Providence Health Care

Discipline:

Life Sciences

Sector:

Health and Related Sciences & Technology; Professional, scientific and technical services

University:

The University of British Columbia

Program:

Accelerate

Continuous molecular recognition technology for selective rare earth elements (REE) separation from leaching solutions

Global society trend in sustainable technologies and environmentally friendly solutions demand the energy-intensive rare earth elements (REEs) separation methods to be more sustainable and possibly adhere to the green chemistry principles. This project tackles molecular recognition technology (MRT) as a method to selectively separate REEs. MRTs is still in its infancy and literature lacks data. Specifically, we aim at selectively separating (+98% purity) target REEs from pregnant leaching solutions (PLS) from monazite ore. At the same time, we aim at establishing fundamental knowledge on MRT, which includes the identification of MRT chelating agents to separate specific REEs, the sequence of MRT steps, and ranges of operating variables. The research also includes the scale up of the laboratory-scale MRT system that will be conceived, from 5 mL to 4 L MRT units. We will as well design a pilot plant with MRT units of 60 L.

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Faculty Supervisor:

Daria Camilla Boffito

Student:

Partner:

Auxico;Central America Nickel

Discipline:

Engineering

Sector:

Mining

University:

Polytechnique Montréal

Program:

Accelerate

Jumine : Détection et prédiction des anomalies en flottation minière

Jumine propose, à l’aide d’un jumeau numérique, de développer l’intelligence nécessaire à la détection d’anomalies dans le procédé de flottation, une partie importante du procédé de traitement du minerai. Jumine doit créer un jeu de données pour concevoir un modèle de détection, qui permettra de signaler en temps réel les anomalies présentes dans le procédé et permettre d’obtenir un concentré de haute qualité et un taux de récupération plus élevé. Comme les projets miniers sont de plus en plus difficiles à exploiter, dû aux faibles concentrations présentes, cette innovation technologique en intelligence artificielle permettra aux opérateurs et aux gestionnaires d’être avisés des anomalies et ainsi, utiliser cet outil comme aide à la décision. En second temps, afin d’intégrer encore plus d’intelligence opérationnelle à leur produit, Jumine créera un modèle de prédiction des anomalies pour prévenir celles-ci. Cette façon novatrice d’opérer et de gérer une mine met en valeur toutes les données disponibles pour optimiser les opérations.

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Faculty Supervisor:

Christian Gagné;Philippe Giguère

Student:

Partner:

Jumine Inc

Discipline:

Computer science

Sector:

Mining; Professional, scientific and technical services

University:

Université Laval

Program:

Accelerate

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Mitacs — Return on Innovation

Mitacs is funded by the Government of Canada, the Government of Alberta, the Government of British Columbia, Research Manitoba, the Government of New Brunswick, the Government of Newfoundland and Labrador, the Government of Nova Scotia, the Government of Ontario, Innovation PEI, the Government of Quebec, the Government of Saskatchewan, and the Government of Yukon.