Modelling valid population estimates using non-probability samples

This project undertakes an experimental approach to improving the accuracy of public opinion surveys conducted online. By leveraging unique datasets from the partner organization, the project team will endeavour to develop a model that produces more reliable estimates of public opinion than conventional polling methods. This model will be applied in the first instance to the forecasting of elections as a proof of concept and then extended to the measurement of public opinion more generally.

Micro Geothermal Power Generation in Depleted Wells

Engineers use the earth's heat to create heat pumps, to store energy, and to generate power. As the world moves away from carbon fuels, geothermal resources are increasingly attractive, promising sustainable, reliable sources of energy. Fortunately, the oil industry has already provided infrastructure to access this resource—depleted horizontal oil and gas wells drilled to a minimal depth of 1500 m, where a supply a steady heat can be sourced at a minimum of about 60 °C.

CCREST: Cold Cracking by Resonance Energy for Sustainable Technologies – Phase 2

Did you know that Partial Upgrading of bitumen and heavy oil can boost Alberta and Canada’s economy? The most cost effective high volume mode for transporting crude oil over land is by pipeline and most Alberta bitumen moves on the existing pipeline network. Viscosity maxima and API gravity minima are specified by pipeline companies to ensure efficient operations and maximize movement of heavy oil from Alberta. To satisfy these specifications, Alberta bitumen and heavy oil must be diluted by diluent, which reports as a cost to the bitumen producer.

Investigation of enhanced superplastic forming behaviour of Ti-6Al-4V alloy sheets for aerospace applications

Titanium alloys are used to manufacture aerospace components that require high strength at high operating temperatures such fan blades, heat shields and jet engine exhaust cones. Parts that have complex geometries are commonly formed at high temperature (around 900°C) so as to achieve maximum ductility during the forming process. By applying a small oscillating load during the forming process, the titanium alloy is expected to deform more uniformly and to a greater extent than during conventional superplastic forming.

Proof of Concept Electrical and Colorimetric Detection of Bacteria and Bacteriophages using Molecularly Imprinted Polymers in Microfluidic Sensors

The COVID-19 pandemic has affected the whole world by the spread of a new respiratory virus (SARS-CoV-2), posing a significant burden on the society and the health system. Rapid and selective detection of pathogens, like SARS-CoV-2 virus, in clinical samples, food, water and the environment at large is crucial in diagnosis and breakout prevention. Conventional lab-based biodetection methods lack sensitivity and are expensive, time-consuming, and non-specific in comparison to the newly developed portable biosensors.

A new automated approach for Engineering Design and Manufacturing Specification generation

RPS Composites Inc. designs and manufactures a wide range of corrosion-resistant (fibre reinforced plastic/polymer) FRP and Dual Laminate equipment from piping systems to ducts, stacks, hoods, covers, cells, and other miscellaneous custom equipment. Their engineering team has used different design methods provided in the codes and standards. The current process of designing and generating the manufacturing specifications is observed to be very time-consuming.

Additive Manufacturing of Functionally Graded Materials and Shape Memory Alloys with Biomedical Applications

Functionally graded materials (FGM) offer a better alternative than the conventional coating techniques since it eliminates the sudden change in composition between different materials. This project proposes to print FGM biomedical implants using a combination of titanium (Ti) powder and hydroxyapatite (HA) powder. Titanium will offer the required mechanical strength for load-bearing implants, while HA will enhance the biological properties of the implant surface to enhance bone cell attachment. The project will follow a comprehensive approach to cover the gaps in the literature.

Comprehensive Spray Characterization of Commercial and New Vaping Devices

Aerosol sprays from commercial and newly developed vaping devices will be characterized (size and concentration distributions) using a traditional low flow cascade impactor, in addition to PSD (Particle Size Distribution) analyser and PDA (Phase Doppler Anemometry). Localized regional aerosol deposition in the mouth as well as numerical simulations of aerosol dispersion will also be performed by the intern. The “know-how” and research data to be obtained in this project will be used by the company in the continuous improvement and development of new vaping devices.

Improving power production by better recognizing power quality issue events with machine learning

Solar energy offers a green energy future both for Canada and the world. To best collect this energy, solar farms, collections of solar panels, are often distributed to ensure efficient local collection. Weather is often a challenge for production; however, the failure of components can also adversely affect this as well. These failures can be difficult to track and predict; in this project, we propose to develop tools to help operators expect events that could lead to power losses and improve solar energy harvesting using both standard analytical tools and machine learning.

Evaluation of smart microcarriers for high-density culture and enzymefree harvesting of primary dermal sheath cells and fibroblasts

RepliCel is a regenerative medicine company that develops autologous cell therapies to treat chronic tendinosis, UV-damaged or aged skin, and pattern baldness. The cells in this technology are isolated from skin biopsies obtained from patients. However, because of limited available tissue samples, RepliCel seeks novel technologies to improve their cell culture process, which is currently time-consuming, labor-intensive, and low throughput.