Research Initiatives

Building Tall aims to establish a focus for research, teaching, and industrial collaboration. Faculty associated with the Centre will have the opportunity to highlight their research, state-of-the-art knowledge, and technologies in the area of tall buildings.

Current Projects:

Site Logistics Optimization for Construction of Tall Buildings

This research aims to improve site productivity by creating a site planning program. The first phase of this research was to gather information through interviews, site observations, and reviewing the literature regarding factors that impact decisions of choosing, locating, and creating operation plans for the crane, hoist, and concrete pumps. In the second phase of this research, a tool is being developed to determine the best locations for a crane on a site, and evaluate the productivity of the crane with and without the use of a concrete pump. Once completed, this tool will aid project managers in decision making at the start of a project.

Publication: Ali, H., McCabe, B., Shahi, A., Lyall, R., Francavilla, J. “Challenges of Site Logistics for Tall Building Construction.” Canadian Society of Civil Engineering Conference, London, Ontario, June 1-4, 2016.

Hiba Ali
MASc Candidate
Department of Civil Engineering
University of Toronto
Email:hib.ali@mail.utoronto.ca

Building Cladding Assemblies for Tall Buildings

As one of the core projects of Building Tall, building cladding assemblies used in tall building construction in the City of Toronto are being investigated. The first phase of this research was an objective comparison between Window Wall and Curtain Wall assemblies, as they relate to the construction, operation, and maintenance of tall residential towers. The results of this part of the research have been summarized in a conference paper, which is presented at CSCE 2017 conference. The second phase of this research is also well underway, and is investigating the way window/wall ratio is being calculated in the residential sector. The second paper from this research, will introduce a new paradigm, called ‘the effective window-wall ratio’, which suggests that a unit-centric approach should be considered in evaluating the window/wall ratio in tall buildings. This second paper will also address some of the ways that the energy saving could be established, without necessarily reducing the window/ wall ratio in tall buildings.

Publication: Marquis, P., Ali, H., Mirhadi, F., McCabe, B.Y., Shahi, A., De Berardis, P., Lyall, R. “Window Wall and Curtain Wall: An objective review”. CSCE/CRC International Construction Specialty Conference. Vancouver, British Columbia, May 31 to June 3, 2017

Patrick Marquis
MASc Candidate
Department of Civil Engineering
University of Toronto
Email: patrick.marquis@mail.utoronto.ca

Evaluation and Benchmarking of Tall Building Construction Permitting Process in City of Toronto

The City of Toronto is one of the fastest growing municipalities in North America, attracting many developers to invest in its physical growth. This research focusses on the evaluation of the policies and regulations imposed on the permitting process and the construction of tall buildings. This project includes two distinct phases: 1) evaluation of the challenges in obtaining construction permits for tall buildings in the City of Toronto and 2) benchmarking of the permitting process for tall buildings in the City of Toronto against other Canadian and International cities. The first phase of this project has been completed, and its report has been submitted to CSCE 2017 conference in Vancouver. The second phase of this research, the international benchmarking, is currently underway with an expected completion in Fall 2017.

Publication: Shahi, K. McCabe, B.Y., Shahi, A., De Berardis, P., Lyall, R. “Evaluation of Tall Building Construction Permitting Process in Toronto”. CSCE/CRC International Construction Specialty Conference. Vancouver, British Columbia, May 31 to June 3, 2017

Kamellia Shahi
MASc Candidate
Department of Civil Engineering
University of Toronto
Email: k.shahi@mail.utoronto.ca

Stack Effect Management in Tall Buildings

Air movement within and across residential buildings can have critical influence on smoke and cross-contamination resilience, building serviceability performance, and total energy consumption. For high-rise residential buildings, stack effect acts as the dominant driving force and constantly affects the direction and magnitude of airflows. This research aims to investigate the ways to mitigate stack effect induced airflows and pressures in residential towers, as part of a comprehensive energy performance program. The first phase of this research examines the potential solutions that can reduce negative impacts of stack effect. One of the promising methods is compartmentalizing of the different areas of the building. The second phase focuses on the effectiveness of compartmentalization strategy in counteracting the stack effect in tall residential towers. A simulation program named CONTAM will be utilized to establish the relationship between the level of building airtightness and the resulted stack induced pressures and airflows.

Junting (Eric) Li
MASc Candidate
Department of Civil Engineering
University of Toronto
Email: juntingeric.li@mail.utoronto.ca

Smart Disaster Management System in Tall Buildings

Tall buildings and their occupants are highly sensitive to emergencies. High volume of population residing in these types of dwellings, complexity of the emergency management strategies, significance of quick response in these cases and unknown reactions of occupants under stress highly complicate the decision-making in this area. This research tries to develop a Smart Emergency Management System (SEMS), which would be capable of performing a fully automated process of detecting the hazard, communicating with the involved entities, allocating the resources and executing the planned strategies, with the lowest intervention of manual operators. The first phase of this project focuses on real-time monitoring of the building and its occupants through advanced technologies of indoor positioning, building information modeling and smartphone-based applications. The second phase will focus on development of a thinking core, able to simulate the occupants’ behaviour and evaluate hypothetical emergency strategies. The last phase is the design of an occupant/rescuer guidance system, which makes a communication link between the thinking core and occupants/rescuers to guide them through the developed emergency plans. Once completed, this research will produce a smart emergency management system, which will be less restricted by human factors and more efficient in saving lives and property of the occupants.

Publication: Mirahadi, F., McCabe, B.Y., Shahi, A. “Smart Diaster Management System for Tall Buildings”. CSCE/CRC International Construction Specialty Conference. Vancouver, British Columbia, May 31 to June 3, 2017.

Farid Mirahadi
PhD Candidate
Department of Civil Engineering
University of Toronto
Email: f.mirahadi@mail.utoronto.ca

Knowledge Representation and Artificial Intelligence in Management of Megaprojects

The project is aimed at capturing the probabilistic dependencies of project variables by creating an intelligent decision making model, and a knowledge base that contains expert inputs and historic data. Therefore, the project is incorporating several topics including “Knowledge Representation”, “Graph Data Structures”, and “Artificial Intelligence”, and “Probabilistic Graphical Models” all in the context of application in management and forecasting of industrial megaprojects. This research is primarily focused on mining and energy sectors; with the potential future integration with infrastructures.

Publication: Zangeneh, P., McCabe, B.Y., Pearson, A., and Mason, N. “Representation and management of project’s knowledge – a linked data approach”. CSCE/CRC International Construction Specialty Conference. Vancouver, British Columbia, May 31 to June 3, 2017.

Pouya Zanganeh
PhD Candidate
Department of Civil Engineering
University of Toronto
Email: p.zangeneh@mail.utoronto.ca

Construction Worker Safety and Resilience

A safety plateau in construction safety performance has been observed in many countries or regions. In order to continuously improve safety performance, the key is to identifying factors that affect safety performance. In this research, four factors that may contribute to explaining safety outcomes are examined: safety climate, individual resilience (IR), interpersonal conflicts at work (ICW), and organizational resilience (OR). A self-administered survey was used. From 2013 to 2016, 1281 surveys were collected from 180 construction sites which covered 18 cities of Ontario, Canada. So far, the major findings of this research are:

  • Safety climate not only affects physical safety outcomes but also employees’ job stress level.
  • ICW is a risk factor for safety performance.
  • IR has the potential to mitigate post-trauma job stress and interpersonal conflicts of construction workers.

Publications:

  • Chen, Y., Alderman, E., McCabe, B., and Hyatt, D. “Data Collection Framework for Construction Safety.” ICSC15 – The Canadian Society for Civil Engineering’s 5th International/11th Construction Specialty Conference, Vancouver, Canada, 2015.
  • Chen, Y., McCabe, B., and Hyatt, D. “Impact of individual resilience and safety climate on safety performance and psychological stress of construction workers: A case study of the Ontario construction industry.” Journal of Safety Research, 61, 167–176, 2017.
  • Chen, Y., McCabe, B., and Hyatt, D. “Relationship between individual resilience, interpersonal conflicts at work, safety performance and stresses of construction workers.” Journal of Construction Engineering and Management, 04017042-1, 2017.
  • Chen, Y., McCabe, B., and Hyatt, D. “A belief network model to predict safety performance of construction workers-from the perspective of organizational resilience”. CSCE/CRC International Construction Specialty Conference. Vancouver, British Columbia, May 31 to June 3, 2017.

Dr. Yuting (Tina) Chen
Researcher
Department of Civil Engineering
University of Toronto
Email: yut.chen@mail.utoronto.ca

Automated Unmanned Aerial Vehicles (UAV)-Based Construction Progress Tracking Using Machine Intelligence and Building Information Modeling (BIM)

Construction Projects often run over budget and schedule; to ensure their timely completion, reducing reworks, and ensuring the quality of the constructed works, it is essential to regularly monitor the state of progress. Unfortunately, manual progress tracking is unreliable, costly, and time-consuming. This research project offers smart and automated progress tracking techniques using light-weight unmanned aerial vehicles (UAV). Prior to UAV-based data capture, the project’s building information models (BIM) are used to automatically design an optimal inspection plan which ensures full coverage of inspection targets while minimizing UAV resource use. The UAVs will perform automated image capture at construction sites, and the images are analyzed by a computer vision- and machine learning-based solution designed by our team. This results in the automated detection of constructed elements and their state of progress. Further, using a novel technique, the as-designed four-dimensional (4D) BIMs are automatically updated using the progress results. This updating process does not require any manual intervention, achieves 100% accuracy rates, and has a run time of 1-2 minutes for a full model update.

Other works associated with this project include: 1) an industry foundation classes (IFC)-based technique for automated model updates based on site observations during inspections; 2) IFC-based and automated development of navigational models supporting customized and real-time information retrieval at sites; 3) The application of swarm intelligence in coordination with multi-dimensional BIMs for optimized UAV inspections.

Publications:

  • Hamledari, B. McCabe, S. Davari, A. Shahi (2017), “Automated Schedule and Progress Updating of IFC-based 4D BIMs”, ASCE Journal of Computing in Civil Engineering, 31 (4)
  • Hamledari, B. McCabe, S. Davari (2017), “Automated Computer Vision-Based Detection of Components of Under-Construction Indoor Partitions, Automation in Construction, Volume 74, Pages 78-94
  • Hamledari, E. Azar, B. McCabe (2017), “Automated BIM Updating and in-BIM Inspection Documentation: IFC-based Solution for Smart Construction and Facility Inspection”, Under Review at ASCE Journal of Computing in Civil Engineering
  • Hamledari, S.O. Sajedi, B. McCabe, A. Shahi, P. Zangeneh (2017), “4D BIM- and IFC-based Automated Inspection Planning Support for Facility Management and Construction Applications”, Under Review at Advanced Engineering Informatics
  • Hamledari, B. McCabe, S. Davari, A. Shahi, E. Azar, F. Flager (2017), “Evaluation of Computer Vision- and 4D BIM-Based Construction Progress Monitoring on a UAV Platform”, CSCE/CRC International Construction Specialty Conference. Vancouver
  • McCabe, H. Hamledari, A. Shahi, P. Zangeneh, E. Azar (2017), “Roles, Benefit, and Challenges of Using UAVs for Smart Construction Applications”, ASCE International Workshop on Computing in Civil Engineering 2017, Seattle
  • Hamledari, B. McCabe (2016), “Automated Visual Recognition of Indoor Project-Related Objects: Challenges and Solutions”, Construction Research Congress 2016, pp 2573-2582, Puerto Rico
  • Hamledari (2016), “InPRO: Automated Indoor Construction Progress Monitoring Using Unmanned Aerial Vehicles”, Thesis, Master of Applied Science, University of Toronto, Toronto, Canada

hesam Hamledari
Department of Civil Engineering
MASc (University of Toronto, 2014-2016)
PhD Student (Stanford University, CIFE)
hesamh@stanford.edu