Topology validation, Error detection, and Correction of rooftops 3D models from LiDAR point clouds and Photogrammetry

The last few years have seen a tremendous increase of the collection and use of LiDAR (Light Detection and Ranging) data for 3D modeling of cities, forest surveys and autonomous driving. In the context of 3D cities, buildings are reconstructed separately, sometimes with the help of aerial images. The accuracy assessment of these 3D models is not straightforward. However, end-point users need to know how reliable the models are for using them for tasks such as roofing quotes and solar installations design.

Development of an Industrial Design Workflow to Incorporate 3D Scanning for Manufacturing Tooling Processes – Phase II

Today's modern industries aim at supplying premium quality products that can offer added performance value, lower weight, less environmental impact, decreased manufacturing and maintenance costs, increased durability and safety, and eventually higher customer satisfaction and market competitiveness. To achieve these goals, new-engineered materials such as glass fiber reinforced polymers (GFRPs) are rapidly replacing traditional single materials such as steel and aluminum.

Greenhouse gas and volatile organic compound reduction using the SmogStop® coating

Sound barriers can be seen beside highways across Ontario and are designed to protect residents from the noise produced by traffic. However, these barriers do little in the way of protecting residents from the pollution produced by nearby vehicles. This project will help determine the ability of the SmogStop® barrier to reduce the level of exposure to GHGs and VOCs for those living close the major urban roadways. The partner organization is an R&D firm that would greatly benefit from the access to equipment and HQP that they would gain from a partnership with the University of Guelph.

Data-driven Adaptive Model Predictive Control of Heat produced by Resistive Heating Elements in Enhanced Oil Recovery

NEXEN has proposed a novel and advanced thermal EOR technique for oil sands recovery, which is both economically efficient and environmentally sustainable as compared to current thermal oil recovery method (SAGD). The focus of this research project is to investigate, analyze, improve, and design heat transfer modeling and control strategies for proposed enhanced oil sands recovery so that it could be commercialized in future. Rate of heat transfer in proposed technique is low as compared to SAGD, which is directly proportional to rate of oil recovery.

Development of a Novel Marine Icing Prediction Model

All shipping and marine activity is subject to risks, such as flooding and capsize in extreme seas. Shipping in cold winter conditions is subject to additional risks, such as ice accretion on the topsides, which in extreme cases can cause capsize. The catastrophic capsize of smaller vessels due to icing is still taking place, with the subsequent loss of life (Arctic Operations Handbook 2013). The consequences of a capsize in a remote area has a large financial and regulatory impact as well as subsequent environmental damage to the ice prone areas.

Innovative Designs in Methane Sourcing

The purpose of this project is to change the way piplelines are sourced for potential leaks. Currently, gas sniffers that detect gas near the pipeline monitor subsea pipelines. However, these sniffers do not differentiate between gas types and are unable to determine the source of the detected gas. Therefore, sniffers are unable to confirm if the detected gas is thermogenic methane leaking from the pipeline or an alternative nearby gas. This can lead to costly false positives that make the process inefficient.

Numerical Simulation and Experimental Validation of a Large Scale Industrial Biochar plant

Slow pyrolysis is a process to convert biomass residues to valuable biochar products, which are used in agricultural, wastewater treatment, animal feed, carbon sequestration etc. IRSI focused on identifying optimal pathways for converting biomass into high quality biochar with maximum energy efficiency and minimal environmental degradation. This project focusses on modelling and simulation of a large-scale biochar reactor in order to enhance the efficiency of pyrolysis processes and increase the reliability of biochar products for the global market place.

Advanced Analysis Setup of Next Generation XRT Algorithms

The research project will include a study using dual energy X-ray transmission (DE-XRT) technology to investigate how to improve the current DE-XRT analysis. To conduct the research, large amounts of samples will be taken from different types of deposits and operations. The research will evaluate various data mining methods to generate algorithms using the data from DE-XRT technology and hence improving the sorter efficiency. The findings from research can help benefit SDE by providing solutions to improve algorithm generation using DE-XRT technology and benefit the mining industry.

Data Analytics for Social Network Marketing

Influencer marketing is a new and innovative way for brands to target their customers on social media in a highly accurate and trusted way. Brand partners work with hundreds of influencers over a period of time, which is called a campaign, to create marketing material. This marketing material is shared by both the brand and influencer to the audience of the influencers, who are followers on social networking platforms such blogs, YouTube, Instagram, and Facebook. A key challenge in influencer marketing is to identify influencers with the greatest social networking reach.

Understanding DETA in the Strathcona Tailings Area

Glencore is considering the use of DETA (diethylenetriamine), a mineral processing reagent, to improve process performance in Strathcona Mill, located near Sudbury, Ontario. DETA forms soluble complexes with nickel and copper ions, and can cause the concentration of these metal ions to exceed the value permitted in the final effluent.