Innovative Projects Realized

Modeling recruitment in the Acadian Forest Region of North America using tree-list models

Predicting future wood supply is critical for stakeholders in the forest product sector to sustainably manage their activities. Such predictions are subject to various bio-physical factors. Several NB forest companies have made a priority to focus on the management of and adaptation to two of these environmental factors: climate change and, to a lesser extent, browsing by herbivores. The general objective of the project is to develop modeling tools to predict the regeneration of commercial hardwood species under environmental pressures. The project will produce deliverables targeted for forest stakeholders in New Brunswick and Canada. These deliverables will contain specific recommendations that forest stakeholders can use to sustainably conduct their sylvicultural activities in hardwood and mixed-wood stands. This project will foster economic growth of the forest industry in New Brunswick by providing solutions for sustainable and profitable operations in the context of a changing climate and environmental conditions.

Characterizing the concentration and makeup of microplastics in wastewater effluent and stormwater overflows to the Ottawa and Rideau Rivers and evaluating microplastic removal in wastewater streams with a newly developed mesh sock.

The research aims to examine the amount and type of microplastics in wastewater streams entering the Ottawa River. As wastewater treatment has been identified as one of the main conduits of microplastics to freshwater environments, the research will sample both wastewater effluent and combined sewer overflows to get a better understanding on how many, and what types of microplastics enter the Ottawa River via these pathways. By investigating the amount and make up of microplastics in wastewater streams, the research can provide valuable information to RESTco, so the company can further develop and test tools for effective micro and nano-plastic removal from wastewater streams and existing pollution in wild waters.

Improved transductive regression using interconnected data

The explosion of data from personal phones, apps, and sensors have enabled powerful machine learning algorithms to help computers identify, categorize, and evaluate information without the help of humans. However, teaching computers how to identify, categorize, and evaluate information usually requires feeding the computers a lot of data pre-labelled by humans. The pre-labelling process is costly and time consuming. The goal of this project is to develop new algorithms to teach computers to identify, categorize, and evaluate information with less pre-labelled data. These new algorithms will use hidden relationships within the information itself, and will also be able to integrate other related data in a way that is easier for the computer use. If successful, these algorithms will be able to learn more from data, while reducing the burden of producing pre-labelled data.

Robust project scheduling policies for naval refit operations at Thales Group

In large-scale construction projects such as naval refits or aircraft overhauls, project execution is subject to considerable uncertainty and a baseline schedule quickly becomes unachievable. For naval environments, high variability in work scope and duration occur at every stage. Furthermore, tools and equipment can fail or not be on-site when needed. Human resources are drawn from a pool of workers coming from a mix of fixed-capacity-unionized workers and contractors. To limit the effect of unexpected but inevitable schedule disruptions, resource (equipment and workers) buffers are used to absorb the changes and protect schedule quality. This project will explore the recent developments in critical chain project management (CCPM) and propose mathematical models to evaluate the effectiveness of time and resource buffers in improving schedule stability, and ways these buffers can be implemented in navy refit optimization to provide the best overall schedule adherence. The models will incorporate time-quality, capacity-cost, cost-risk trade-offs.

Air Quality Assessment for a chemical manufacturing plant.

Pollutants from various anthropogenic sources contaminate the environment which in tum

affects the ambient air quality. When general population gets exposed to these contaminant

through contaminated air they would have adverse health effects. The objective of the project is

to perform air quality assessment for a chemical manufacturing plant, located in Alberta (exact

location is confidential). This assessment predicts how the pollutants get dispersed in the

atmosphere. In order to perform this assessment the information regarding the source, site,

meteorological data, and receptor information will be collected. Using these data the Emission

characterization and air dispersion modeling will be carried out. The output from the model

Phase de transfert de la recherche sur de développement de la Relation de coopération au sein d’établissement d’enseignement au niveau des collèges privés non-subventionnés du Québec. Modalités de mise en place d’un dispositif relationnel de coopération au collégial.

Ce projet recherche porte sur la mise en place d’un nouveau dispositif relationnel de coopération pour favoriser une gestion de classe efficace au collégial. Ce projet de recherche propose comme premier objectif de décrire le processus de mise en place et de maintien du dispositif relationnel de coopération de St-Germain (2016) pour favoriser une gestion de classe efficace et comme deuxième objectif d’identifier les limites de sa mise en place. Ce groupe de recherche s’intéresse aux approches de la gestion de classe auprès des étudiants adultes et plus précisément au développement des savoir-être qui favorisent le partenariat entre l’enseignant et son groupe classe.

Géométrie 3D du socle rocheux de l’ile de Montréal – développement d’outils de corrélation stratigraphique et d’analyse structurale basés sur les strates de K-bentonite

Le socle rocheux de l’île de Montréal est constitué de calcaires déposés sur la marge continentale de Laurentia, il y a 450 millions d’années, qui bordait alors un océan où existait une intense activité volcanique. La stratigraphie de ces formations rocheuses est bien documentée, mais il est encore difficile de déterminer précisément la position stratigraphique du roc à un endroit donné du territoire. Les importantes éruptions volcaniques contemporaines de la formation des calcaires sont soulignées par des dépôts de cendres volcaniques au sein des calcaires. Ces dépôts forment ce que l’on appelle des K-bentonites et représentent d’excellents horizons-repères.
Le projet de recherche vise à corréler et caractériser ces horizons-repères au niveau géochimique, physique, tectonique et géochronologique pour intégrer ces informations dans les travaux d’ingénierie urbaine. TO BE CONT’D

Fostering Learning and Professional Development for Users of Feature-Rich Design Software

Feature-rich design software is of critical importance to many industries, including manufacturing, architecture, and construction. A common feature of this software is that, to be used effectively, the user must possess technical competency and an understanding of the specific workflows and practices for using the software within their organizations. In the past, users could get by with an initial period of dedicated training on the software they would use in their careers, but the rate of change in design software is accelerating, making social and on-the-job learning of software skills much more important. The intern will investigate the practices that professionals use to develop their software skills over time on the job. The results of this study will be important for Autodesk, which makes 3D design software for the manufacturing, architecture, and construction industries, and is actively involved in developing tools to foster the professional development of Autodesk users.

Canada’s electricity system decarbonization pathways: a multi-model and multi-jurisdiction approach

Meeting Canada’s commitment to the Paris Agreement will require a fundamental shift in our energy system: increased generation from renewable sources, electrification of the transport and building sectors, and planning harmonization across jurisdictional scales. A new United Nations climate science report estimates that the world will invest an average of $3 trillion dollars per year over the next three years to transform the energy system and limit temperature rise to 1.5 degrees Celsius above pre-industrial times (IPCC, 2018). In Canada, the federal Government plans to invest over $180 billion between 2016 and 2028 in infrastructure, much of which is intended to improve resilience and transition to a clean economy (Government of Canada, 2017). In this project, we will develop the first suite of comprehensive and credible pathways for achieving pan-Canadian Paris commitments. TO BE CONT’D

New algal bioreactor design for clean food production with inland aquaculture

With increasing demand for fish and seafood products globally, inland aquaculture is becoming an important source of global food production. This is primarily because food can be produced in proximity to large and densely populated areas, cutting down on transportation costs and emissions. It also allows the use of a more diverse set of species as the risk of local species introductions is significantly reduced. Finally, inland aquaculture is less prone to natural disasters (hurricanes, typhoons, blooms, water contamination etc.). We are developing a photo-bioreactor for the removal of nutrients from recirculating aquaculture systems (RAS), making inland seafood production more sustainable and cost effective. In contrast to bacterial systems commonly used in the industry, our bioreactors will remove nitrogen, phosphate and CO2 at the same time and produce algae for commercialization. This leads to significant reductions in operating costs and can create an opportunity for inland aquaculture to increase profitability.

Improving reproductive performance and fur quality traits in Nova Scotia mink industry using genomics

Genomics is a field of science exploring the structure and function of DNA sequences. Genomic tools have provided new opportunities to accurately select animals for the traits of interest in livestock production. This project will explore the genome regions in American mink using the information from a large number of DNA sequences. The main idea of this exercise is to develop the appropriate tools for genomic selection in American mink. In this project, a wide range of economically important traits including reproductive performance and fur quality traits will be measured in collaboration with Nova Scotia Mink Breeders Association. The project will aim to create a big dataset of DNA information and phenotypic measurements to develop novel approaches in mink breeding. This research will implement the latest methods to improve the competitiveness of the Nova Scotia mink industry.

Application of the Five Capitals Framework to the Mineral Resources Sectorof Mongolia to Support Sustainable Development

The overall goal of the proposed program is the co-development of education programs and academic research with opportunities to apply this understanding in context of SEF/industry activities. The outcomes will benefit SEF’s business activities in Mongolia and other developing countries with significant mineral resource potential. The program will also support investment and business opportunities for Canadian companies that are working in Mongolia. The research undertaken by each intern will provide the recommendations necessary to feed back into training of Mongolian academics and the roadmap to be used when discussing transforming Mongolian universities’ mineral resource programs.