Seismic performance of helical pile groups and their cost efficiency as alternative to driven piles

A new seismic hazard model of Canada will be incorporated in the NBCC2020, which will increase the seismic hazard by 50-100%. Meanwhile, helical piles are a reliable and cost-effective alternative to conventional driven piles because of their fast installation, lower cost and lower labour risk. They are suitable for retrofitting existing deficient foundations because they […]

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Paving the way to concrete 3D printing for sustainable housing in cold regions

These two first units are sub-projects of a larger feasibility study that looks to solve the challenges that prevent the construction of housing in remote northern areas of Canada despite overwhelming need. Using 3D printing to accomplish quality housing projects in remote climates requires further research prior to being deployed. The larger context pf this […]

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Nano-engineered concrete and composites with advanced graphene-based 2D nanomaterials

The development of high performance and durable concrete material is extensively required in the present world to build resilient and sustainable infrastructure. This project will open the prospects for developing a high performing advanced concrete composite engineered with graphene-based nanomaterials. Graphene is a nanomaterial typically produces from graphite, with extraordinary strength and chemical properties. The […]

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Climate Change Adaption for Masonry Material, Construction and Design

Climate change is having an affect all aspects of everyday life. In some regions, climate change could also have a negative impact on buildings. To help cope with these expected issues, we will be reviewing the Canadian masonry design standards in order to identify specific aspects of masonry construction that need special attention in their […]

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Spinning Multi-Beam LiDAR (VLP-16) new mapping scheme and the effect on the generated 3D point cloud : Point density and Thin features extraction in a Mobile mode of operation

Maps are vital in our life. Three-dimensional (3D) maps are essential in traditional and new applications, such as smart cities, autonomous vehicles and augmented reality. The number of end-users who require 3D maps has expanded exponentially in recent years and is anticipated to expand even more in the future. LiDAR scanners are the main sensors […]

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Complete destruction of perfluoroalkyl and polyfluoroalkyl substances (PFAS) in water and by-products minimization via a novel Boron-Doped-Diamond anodes electrochemical oxidation

Perfluoroalkyl and Polyfluoroalkyl substances (PFAS) are anthropogenic compounds with unique properties and wide applications. The consequence of using such persistent chemicals is widespread contamination reported for groundwater, soil, sediment, and wastewater, especially in industrialized countries such as Canada. The endocrine-disrupting and likely carcinogenic nature of PFAS have resulted in strict regulations on PFAS in drinking […]

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Network-wide bicycle monitoring

Bicycle and pedestrian counts are important data for the planning and design of safe roads. However, these data need to be inspected for quality, a time-consuming task. Part of this project is to make this project simpler, quicker and more accurate. Installing pedestrian and bicycle counters across an entire city road network is not financially […]

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Monitoring System for “Flushable” Consumer Products in Urban Wastewater Collection Systems

This research project explores the application of an artificial intelligence-based monitoring system comprised of image-based sensors and processing algorithms to detect, identify, and monitor the incoming presence of wet wipes and nonwovens in urban drainage systems in near real-time to pre-empt the effects of the damages caused by users’ disposal of these products in toilets. […]

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Improving Resource Estimation with Machine Learning

The proposed project aims to improve the prediction of mineral resources for better decision making throughout a mining project, that is, to decide whether to reject or to process extracted material using machine learning algorithms. This will help maximize profit for mining companies while minimizing environmental impact as the correct material will be processed more […]

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