Projets novateurs réalisés

Analysis of the potential for carbon offsets in North American Tribal Lands

The research objectives for this proposed Mitacs project are to identify the forested

Tribal Lands in the US that hold the most promise for participating in the developing

regional US and Canadian offset markets. The partner organization is Offsetters Clean

Technology, a BC based company with expertise in carbon management and advisory

services in Canada. This project will ultimately result in the creation of a new line of

business for the company focused on First Nations and tribes outside of British

Columbia. The successful completion of this project will result in publishable research

outcomes for the company, in partnership with UBC, continuing a strong tradition of

knowledge translation.

Quantification of Intra-Host Diversity of Piscine orthoreovirus (PRV-1) Infecting Atlantic and Chinook Salmon in BC

The decline in many populations of wild Pacific salmon is of great concern given their critical importance to First Nations, the ecosystems of the Pacific Northwest, and wild and farmed fisheries. The conservation efforts of the Pacific Salmon Foundation (PSF) have provided opportunity for research into infectious diseases like Heart and Skeletal Muscle Inflammation (HSMI) and jaundice/anemia that may contribute to these declines. Piscine orthoreovirus (PRV) causes HSMI in Norwegian Atlantic salmon. Recently detected HSMI in BC farmed Atlantic salmon, links between PRV and disease in Pacific species, and healthy PRV-infected salmon, have called into question the threat PRV poses to BC salmon health. When a virus infects a salmon and begins copying, errors are made, which leads to a variety of genome sequences that can have different biological effects. This research investigates previously overlooked genetic diversity of viral populations to help PSF explain differences in HSMI symptoms among salmon populations to inform industry practices, future research, and governmental policy.

High Energy, Range extending battery for Electrical Vehicles (HERA-EV)

We can deal with the daunting challenges of depleting fossil fuels as-well-as the toxic and greenhouse gases emitted from the gasoline/diesel driven vehicles by replacing their internal combustion engine with rechargeable batteries. This project focuses on the development of an all-metal-free and biocompatible rechargeable battery system that will compete with the existing counterparts (Lithium-ion batteries, LIBs) in Electric Vehicles (EVs) currently under development. We herein propose to design and develop dendrite-free organic anode, porous air-cathode, and solid-biopolymer electrolyte based solid-state batteries, having high energy density, enhanced service-lifetime, lightweight, cheaper and much safer than LIBs. This new metal-free, low-cost and solid-state rechargeable battery system when equipped in Ford vehicles (Ford is the industrial partner in this project) will not only enhance their driving range between consecutive recharge but will also provide a sustainable and eco-friendly solution to deal with the environmental problems and rising energy demands in the automotive sector.

Development of an IoT-enabled Controlled-environment Indoor Plant Growth Prototype

The proposed project will establish an echo-system consisting of various environmental sensors and actuators and how they can be integrated to build a prototype indoor garden for demonstration purposes. Through utilizing IoT-enabled sensory data from image and environmental sensors, one can obtain relevant information about plant growth in real-time or use the data for a posteriori analysis. The large number of generated data will be used to create mathematical signatures that can be used for a variety of applications such as detecting anomalies in the growth process. The prototype will be used to investigate challenging problems in controlled environment agriculture such as resource optimization (electricity, water, and nutrients) in the area of intelligent ho

Geometallurgical Simulation and Multicriteria Risk Evaluation

The evaluation of mining projects depends on modern computational techniques. There is a demand for increasingly sophisticated techniques, due to environmental considerations and the drive toward increasingly complex ores. Without these techniques, projects may be wrongfully held back or abandoned, leading to severe socioeconomic consequences in the surrounding communities. Conversely, mining projects may be wrongfully approved, causing unfortunate environmental and socioeconomic consequences. Engineers, geologists and other experts may indeed be pressured to support ill-fated projects, despite their technical opinions; yet they rely on the rigour of their methods to defend their conclusions. The current proposal consolidates multidisciplinary perspectives within a new computational tool for mining project evaluation. It extends geostatistical techniques, by incorporating system dynamics (in the form of discrete event simulation) and the behaviour of financial decision-makers. Behavioural finance simulation is an innovative approach to integrate the technical, environmental and socioeconomic risks that are inherent to mining projects

La mise en art de la montagne comme facteur d’attractivité touristique

Si le ski et les activités de glisse ont longtemps été considérés comme les principaux produits touristiques des régions montagneuses, les changements climatiques autant que les changements démographiques et la transformation des pratiques sportives et touristiques amènent aujourd’hui les gestionnaires de stations et sites de montagne à revoir leur offre. Proposer des activités à longueur d’année, et des produits diversifiés, mettant en valeur la beauté de la nature et des paysages, l’animation culturelle, l’intégration des résidents locaux, deviennent des réflexions partagées et de plus en plus pressantes pour les gestionnaires de ces sites et des destinations touristiques qui les accueillent. Ce projet vise à étudier les formes de mises en art de la montagne comme élément d’attractivité touristique et à identifier les principaux facteurs de réussite pour assurer cette attractivité.

Video Quality-of-Experience Assessment Based on Advanced Machine Learning Technologies

The proposed MITACS cluster project aims to apply advanced artificial intelligence (AI) technologies to attack challenging video quality-of-experience (QoE) assessment and quality assurance problems that are critical in real-world large-scale video distribution systems. Six internship students will work closely with the technical staff members at SSIMWAVE INC, a deep-tech startup company based in Waterloo Ontario, to develop AI-based automated video QoE assessment and video anomaly detection algorithms and software prototypes. The research outcome is expected to help enhance SSIMWAVE’s current QoE solutions in terms of accuracy, efficiency, reliability and versatility. It will also accelerate the adoption of deep learning and AI in the video distribution industry, and strengthen Canada’s competence and global leadership in the field.

Computational Fluid Dynamics Study of High Energy Incidents Inside and Above Buried Underground Vaults

When a transmission cable joint in an underground vault undergoes an electrical failure this event can result in a high energy event and trigger a shock wave. Rapid and extreme pressure build up inside a manhole can cause a 200kg vault cover launching out as a dangerous projectile, which is referred as manhole incidents. The safety and reliability evaluation of the power cable joint in an underground vault has always been challenging with quite complex electromagnetic-thermal-mechanical coupling field. In this case, accurate representation of material properties is one of the most important issues in modeling the behavior of the cable joint-underground vault-vault cover system. Computational fluid dynamics (CFD) will be used to establish a 3-D parametric model considering the coupling field in this project. Based on the FE model, the pressure versus time curves in transmission vaults will be analyzed and computed considering different triggers and varying model geometry. Sensitivity analysis will be conducted to analyze the effect of parametric changes on the pressure versus time curves, such as ambient temperatures, number of vault covers, extent of venting, and input trigger energy and time profiles. The effects of the explosion of power cable joints on surrounding structures will be evaluated.

Analysis and optimization of a novel thermal storage system for ground-source heat pumps

Researchers at Ontario Tech University are collaborating with McClymont and Rak geotechnical engineers to develop a new sustainable thermal storage technology that addresses the main challenges that have prevented geothermal heating and cooling systems from being adopted in a meaningful way in Ontario. An innovative storage medium, based on a construction slurry, will be developed and used in the underground thermal storage, and coupled to a geothermal heat pump to provide high-efficiency and clean building heating and cooling. This new, inexpensive technology will be able to be effectively integrated with solar heating, making it more cost competitive with natural gas, and leading to increased adoption and considerable CO2 emissions reduction in the building sector.

Public Perception and Expectations of Paramedic Care in Saskatchewan

The proposed study is based on the premise that the public have valuable perspectives, insights, and ideas to offer regarding paramedic care. The study will use a qualitative descriptive research design to explore the publics’ perceptions and experiences related to paramedic care in Saskatchewan.
Interviews and focus groups will be conducted with participants from different communities including: Indigenous Peoples, seniors, new immigrants, residents of the inner-city, urban, rural, and northern areas of the province. The Saskatchewan College of Paramedics (SCoP), along with its research partners at the University of Regina (U of R) and Saskatchewan Polytechnic will use the data collected to inform future standards of practice, changes to scope of practice, program curriculum, and the effectiveness of the regulator in representing the public’s interests.

Portfolio management by reinforcement learning

This project is addressing the problem of portfolio optimization by using reinforcement learning, an area of machine learning that has recently attracted many researchers. Its advantages compared to the conventional models of portfolio optimization are coming from its ability in incorporating many features of the assets into the asset allocation problem without relying on the predicted returns outputted from another model. This model is able of considering risk measures and providing asset allocation strategies that are in line with the risk preferences of the investors. It also considers exogenous market constraints like the transaction costs, which are very important factors in the performance of the suggested strategies of the model.

Optimization of a Stochastic Heterogeneous Vehicle Routing Problem for the Trucking Industry

In the transportation industry customer satisfaction, driver retention and profitability are some of the most critical factors in company success. As regulatory environments change, and competition grows Contrans Corp., a flatbed freight company, is seeking to develop a user-friendly application that allows team members to rapidly and accurately determine an optimal dispatch schedule for the fleet. This tool takes in information, such as road conditions, order types, vehicle specifications, driver specifications and time windows and solves a vehicle routing problem to maximize company profits and driver satisfaction, all whilst ensuring customer demand is met. This tool will be implemented in a graphic user interface and will serve as a case study for how operations research can ensure sustainability in the trucking industry.