Innovative Projects Realized

Marine Oil Spill Tacklers

A swarm of robots should be available on the board of a vessel or oil rig so they will be deployed when spill occurs. Based on our existing know-how knowledge and technology, the swarm of robots automatically detect the boundary of the oil, then they deploy inflatable booms to contain the oil. After they successfully contain the spill by detecting whether or not the booms achieve a close loop, the swarm continues to expand its searching area until it could not find any new spill.

Développement d’un véhicule autonome de descente guidée pour unenacelle stratosphérique

Lux est une entreprise de robotique spatiale spécialisée dans la conception, la fabrication et l’exploitation de satellites atmosphériques pour l’observation de la Terre. Les satellites atmosphériques de Lux sont constitués de ballons de haute altitude équipés d’une nacelle stratosphérique de matériel qui supporte un large éventail d’instruments scientifiques comme par exemple du matériel de télédétection. Le présent projet Mitacs se concentre sur la phase de récupération qui implique une descente et un atterrissage contrôlés afin de retrouver la nacelle et les données acquises. Le principal objectif de recherche sera axé sur la conception et le développement d’un véhicule autonome de descente guidée qui permettra de mieux contrôler la descente et l’atterrissage de la nacelle, et ce malgré les conditions atmosphériques. Il est alors possible d’assurer une récupération et une réutilisation sûres de la nacelle, et de privilégier une aire d’atterrissage en toute sécurité loin des centres habités et sur un terrain favorable.

Evaluation de l’impact de l’innovation technologique sur la productivité et la durabilité en construction

Le projet de recherche cherche à comprendre l’impact de l’innovation technologique sur la productivité et la durabilité en chantier. L’objectif principal du projet de recherche est donc d’investiguer et de documenter les différentes catégories d’innovation technologiques, notamment la construction industrialisée, dans une optique d’accroissement de la productivité et de la durabilité et d’encouragement de l’innovation au sein de l’industrie de la construction.
Le projet est divisé en deux volets :
– Le développement d’une cadre de référence portant sur les innovations technologiques en construction et un sondage investiguant le taux d’adoption de celles-ci au Québec
– Une investigation approfondie de la construction industrialisée et de son impact sur la productivité en chantier.
Les bénéfices escomptés du projet sont de développer des connaissances afin d’éduquer et formuler des pistes d’accompagnement en matière d’innovation technologique pour l’industrie. De plus, le projet jette les bases d’une étude plus large sur l’impact de l’innovation technologique en construction sur la productivité au Canada, notamment en offrant une mise à jour des connaissances sur l’impact de l’innovation technologique sur la productivité en construction, offrir des données empiriques sur celle-ci et d’informer les politiques en matière d’innovation technologique en construction au Canada.

3D Modelling and geophysical data integration: application to SudburyStructure, Ontario, Canada

3D geological models attempt to integrate all sources of geological and geophys ical data into a single

comprehensive model whose purpose is to help identify future poss ible mineral exploration targets. These

models are normally built based on sparse surface outcrops, a few boreholes and sometimes airborne

geophysical surveys to fill the gap. However, often the resulting geophysical models appear inadequate

because of a lack of phys ical property measurements, problems in contact definition and source depth

estimat ion caused by the interference of signals from overlapping sources, non-vertical geological contacts,

and the inherent non-uniqueness of unconstrained geophysical models. A combination of algorithms

involving edge mapping and strike and dip determination of geological contacts by means of using both

geophysical and topographic data represents a first step toward the construction of a set of constraints that

can be utilized for the actual 3D geologica l model. However all these algorithms and models need to be

tested on areas where we…TOBECONT’D…

Wind Powered Heat Generator

Imagine a freezingly cold winter day with the strong wind blowing outside your house somewhere in Newfoundland, and you are comfortably sitting in your room with heating and warm water – even during a power outage! This could be realized with a novel device that directly converts the wind energy to heat. This project aims to develop such a technology. The kinetic energy from the rotational motion of a small wind turbine is converted to thermal energy through fluid agitation and friction in a unique heat generator with specially designed rotating blades, baffles, and working fluid.

Saltmarsh and dykelands in Atlantic Canada: implications of biological and socio-economic change for conservation

Saltmarshes and coastal wetlands in Atlantic Canada are some of the habitats that have experienced the greatest decline in area over the past 400 years. Various organizations have monitored habitat change and bird use of these sites for decades, but no one has undertaken a comprehensive examination of changes in habitats or avian abundance, potential factors that influence those (including government policies), and the perspectives of local stakeholders on the successes and failures of conservation efforts in these region. This project seeks to remedy that through a collaborative examination of 40+ years of scientific data, as well as interviews with stakeholders and local landowners. The results will help direct future, multi-stakeholder land use activities and long-term planning for coastal wetlands in Atlantic Canada.

Porous polymeric extraction devices for fast, convenient, and portable monitoring of organic contaminants in marine environments

Organic contaminants enter the marine environment through atmospheric transport, runoff into waterways, or directed disposal into the ocean. They are prone to long-range, bioaccumulation and can have adverse effects on human health and the environment. In this project, a simple and convenient extraction device developed for analysis of organic pollutants will be examined for various types of environmental monitoring such as active and passive sampling. Our proof-of-concept studies have shown the that these devices provide simple, high throughput, reliable and green analyses. However, there is a need to validate the devices for on-site purposes, which will be performed during this project.

Development of innovative approaches for the extraction and recovery of resources from gold-bearing materials

This project would address basic unanswered questions about how the application of environmentally benign process (i.e., biohydrometallurgy) on mine ores and tailings can leach and extract base and, precious that are essential for today’s “smarter” technologies. Bioprocessing methods for bio-extraction and bio-recovery of elements offer a new potential sustainable alternative compared to chemical conventional approaches. Rather than biohydrometallurgy, the proposed research program will also develop an economic process capable of recovering valuable metals directly from ores without the need for reprocessing. Therefore, this project will increase the flow-on benefit to the Quebec and Canada economy in a circular way. The results of this research will offer better management practices for tailing and reduced risks of environmental impacts and liabilities. Among HQP, 2 Ph.D.s and 1PDFs will be trained throughout the proposed research program. Such scientific and technological advances would significantly help for successful reclaiming mine tailings to address high-risk elements or effluents thereby reducing the overall volume of these waste in the long term.

Advance WAAM for hybrid manufacturing and additive repair purposes

Nowadays, the need for newer, more flexible, and efficient production methods is higher than ever. As a disruptive manufacturing technology, powder-based additive manufacturing (AM) systems are best suited for the fabrication of complex but small components. The limited enclosed working envelope of the powder-based AM processes, along with their low deposition rate, hinder their capabilities in the fabrication of large-scale parts. The mission of the proposed project is to realize the full potential of the state-of-the-art wire arc additive manufacturing (WAAM) technology for hybrid manufacturing and additive repair of metallic components. Owing to its significantly high deposition rate (3-8 kg/h), substantial reduction in the fabrication time, and an unlimited build envelope, WAAM technology has the potential to be one of the most significant manufacturing innovations in many industries. However, the industrial evolution and adoption of this technology are currently limited due to the current lack of a commercially available robotic WAAM platform. The proposed research program will contribute critical knowledge related to the advancement of the process in fabrication of dissimilar metal components from special grade of stainless steels.

Methodology development and implementation of a platform for non-destructive evaluation of both butt-fused and electrofused polyethylene pipe joints using ultrasound and deep learning

The infrastructure industry needs a way to non-destructively assess plastic pipe joints. We aim to research, design, and develop methodologies and a prototype device that allow automated inspection of these joints (made with the two most common joining methods) using ultrasound and artificial intelligence (AI). We propose a novel method that uses a two-element ultrasonic transducer (inexpensive but sensitive enough compared to previous methods). Ultrasonic signals produced by this transducer will be read by the AI, which will assess the joint (determine whether it contains a defect, and if so, characterize it in terms of type, size, and location), and display the results on a screen. Our proposed solution is inexpensive (so industry will adopt it), portable (as these joints are made usually in ditches as pipes are being inserted into the ground), and easy-to-use (hence, the AI component). The prototype will become a marketable product for our partner.

Empowerment et disempowerment dans les organisations de travail alternatives

L’objectif de ce projet de recherche est de mettre en pratique le concept central du mémoire de recherche de Samuel Dupuis : le « disempowerment », afin d’en comprendre les différentes utilisations pratiques et lacunes potentielles dans la réalité. Il s’agira d’observer en quoi le processus de responsabilisation et de développement, aussi personnel que collectif, nécessaire à une organisation de travail alternative, implique toujours déjà un travail de réflexion de la part des acteurs.trices. Ce volet pratique permettra à l’étudiant d’étoffer le volet théorique de son mémoire : le travail de conceptualisation du « disempowerment ». Puisque la méthode de recherche employée en sera une active, plusieurs changements sont à attendre dans l’organisation de travail. C’est d’abord et avant tout l’expérience personnelle et la volonté collective des employé.es de l’entreprise qui modèleront les changements organisationnels apportés.

Machine learning for real-time parameters estimation and control of robotic laser cleaning

Surface cleaning is a technology used in a wide variety of industries, from heavy manufacturing and the energy sector through to conservation and restoration. Historically, technologies such as sandblasting and pressure washing have been used which have significant environmental and waste challenges. More recently, laser ablation has been used for surface cleaning. This last technology has a much lower waste disposal requirement due to the lack of blast media along with other benefits. Currently, lasers are used in paint stripping, rust removal, radioactive surface removal as well as component resurfacing for further processing. The current market’s needs hold a lot of potential. Market adoption of laser cleaning is limited as the systems available today must be operated by highly skilled technicians with constant monitoring/control of the cleaning process. The main objective of this project is to integrate AI and machine learning capabilities with the laser cleaning technology to allow for faster, more accurate and autonomous cleaning of increasingly complex components. This is achieved through constant monitoring of the substrate surface using sensors. The data from these sensors will be used to compare against required surface conditions and the AI will be used to control the laser settings accordingly.