Spatiotemporal travel behavior modeling and analysis for better public transport systems

The public transportation system is crucial in alleviating urban congestion. The widespread of smart card automated fare collection (AFC) system produces massive data recording passengers’ day-to-day transport dynamic, which provides unprecedented opportunities to researchers and practitioners to understand and improve transit services. This project aims to make full use of the transit operational data (mainly smart card data) to enhance transit services. The main body of the research project is spatiotemporal behavior patterns mining.

Electro-bioreactor (EBR) upgrading for high ammonium removal

The objective of this project is to build up an electro-biological system of high potential capacity for the removal of ammonium and phosphorus. Conventional biological treatment methods have limited capacity for removal of ammonia at higher concentrations. However, anammox bacteria have a high capacity to remove ammonium. The electro-biological treatment aims to enhance this capacity by electrically activating anammox bacteria on a fixed media.

Towards Automation of 3D Visualization & Analysis of Workspace Collisions on Construction Jobsites

Workspace Interferences/Collisions happen on construction jobsites when multiple resources (labor, equipment, material, etc.) don’t have enough space to coexist at the same time and will interfere with each other’s operations. These interferences affect performance, delaying the project, impacting cost, and may jeopardize the buildings’ integrity and people’s safety on site. Most of existing models simulate resources as being deterministic. However, the behavior of the crew interfering is more chaotic.

Compressed Air Energy Storage in Cased Wells

The project will adapt Compressed Air Energy Storage (CAES) to a cased well. CAES is a mature and proven energy storage technology, however it traditionally uses large salt caverns. By understanding the deformation of a wellbore due to pressure and hot air injection, one may be able to determine the operating range of the system. Cased wells are easy to deploy and decommission. They may be installed wherever is advantageous. They involve drilling a well and installing a high-grade steel casing into the wellbore. The depth of a single well can be anywhere from 500-1500 meters.

Automated Risk Identification in Modular and Offsite Construction

Modular and offsite construction, where a module of project or complete house is manufactured in a factory, requires a large upfront capital (working capital) investment in order to procure materials in advance of manufacturing and to deliver modules on time and on schedule. Thus, modular fabricators need to receive deposit and progress payment before the assembly process. In the eyes of a bank, a prefab house is “just materials”.

Productivity Tracking and Analysis of Earthmoving Operations

Monitoring and control earthmoving operations such as highways and dams construction; require the collection of large amounts of data. Collecting this data manually is time-consuming and it lacks accuracy, so there is a necessity for using automated data collection systems in such operations. Most of nowadays available data acquisition systems are costly back boxes, where the user can not use it based on his/her customised needs.

Utilization of Agile Management in Construction Projects

Usually, any construction project begins with the planning department preparing a construction schedule that is pushed onto the project team. The big up-front plan might cause delays in the construction process because it relies on predicting a lot in the future, so you need frequent updating of this plan throughout the execution. Agile is a project management approach that includes micro-planning tools to support construction contractors in the execution of projects.

Quality Improvement of BIM for Operation and Maintenance phase

The use of Building Information Modeling (BIM) processes and technologies is rapidly growing in the Architecture, Engineering and Construction (AEC) industry. It is being widely implemented during the design and construction phases. However, the building models created in these phases are not suitable for the Operation and Maintenance Phase (O&M). These models lack useful data for O&M or include unnecessary items which affect the usability of models. This project aims to develop tools to improve the quality of models used for O&M.

Material Point Method Modeling of Soil Liquefaction in Cyclic Loading

Large deformation problems represent a new issue in the current Canadian engineering practice since the current numerical methods cannot adequately address these problems. Material point method (MPM) is a modern numerical technique with many potentials for applications in large deformation problems in geotechnical engineering. The main benefit of addressing large deformation problems is the estimation of risk since as an example this methodology provides the opportunity to know the run-out distance in dam failures.

Accounting for uncertainties in dam safety assessment via machine learning techniques

When working with massive and complex structures such as dam-type structures it is required to generate a scale numerical model to simulate the real behaviour of the dam. The problem of this approach is that to be able to generate all possible hazard scenarios and system configuration, several computing hours are required. This represents a huge problem when the decision-making process need to be done in presence of natural disaster such as earthquakes.

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