Waterloo researchers awarded for their work in asset and infrastructure management

Monday, July 16, 2018

Researchers from Waterloo Engineering were recognized with two awards from the Canadian Network of Asset Managers (CNAM), honouring their work to advance asset management across the country.

Mark Knight, associate professor in civil and environmental engineering and executive director of the Center for the Advancement of Trenchless Technologies (CATT), accepted the 2018 CNAM Pioneer Award.

Mark Knight accepting the CNAM Pioneer award

Mark Knight accepting the CNAM Pioneer award presented by Pious Maposa, CPA, CGA, MBA, Manager, Asset Planning Infrastructure Planning & Policy Public Works at Halton Region.

Knight accepted the award on behalf of his fellow researchers: Andre Unger, earth sciences professor; Carl Haas, environmental engineering professor; Neil Brisley, accounting and finance professor; and Rizwan Younis, CATT researcher. The award also recognizes CATT industry partners, including the City of Waterloo, City of London, Region of Waterloo, City of Niagara Falls and City of Cambridge. The research team also includes a number of graduate students.

“This award would not be possible without our amazing research team and industry partners, or our financial supporters” says Knight. Financial support was provided by industry partners, the Natural Science Engineering Research Council (NSERC) and the Centre for Advancement of Trenchless Technologies (CATT).

Innovative models create cost-saving utility plans

For 10 years, researchers created innovative water asset management tools that allow water utilities to develop long-term financial plans. The plans, spanning 30 years or more, use utility data from existing systems to determine inflation rates in water projects.

These water systems are complex with many feedback loops and non-linear interconnections that are difficult to model and understand – especially with current practices. The researchers developed dynamic models, allowing water utilities to better understand how their systems behave over time. These models are the first of their kind, and helped industry partners develop sustainable financial and infrastructure renovation plans.

“Our current research integrates machine learning, artificial intelligence, agent-based modelling and game theory to automate key processes for collecting and analyzing data from water utility systems,” explains Knight.

The tools developed by Knight’s team have already provided key information for industry partners, resulting in long-term cost savings and improved performance for utility systems. Key findings have already been made about water utility inflation rates and best practices for funding repairs.

“This is exciting research for water and other utilities in North America and around the globe,” says Knight. “Our tools help develop sustainable water rates and fees, improve network performance, and reduce infrastructure backlog and deficits. It’s a win for everyone – ratepayers, utilities, regulators and governments.”

The team’s latest industry partners are KPMG Australia and KPMG New Zealand. KPMG has recognized the team’s innovative tools, and their ability to support defensible five-year user rates and financial plans required by water and power regulators.

Waterloo student takes first place

Hamed Mohammed Fardi, a civil and environmental engineering doctoral candidate, was awarded first place for the 2018 CNAM Student Research Symposium. Fardi’s research adds sustainability assessments to the model developed by his supervisors, professors Mark Knight and Andre Unger. As a result, he developed a new decision-making tool that coordinates the asset management plans of linear and non-linear water and wastewater infrastructures. His work shows that the cost of building and operating wastewater treatment plants can be reduced with pipeline renovation programs that decrease inflow and infiltration to the pipe networks.

This article was originally featured on Engineering News.

  1. 2019 (2)
    1. July (1)
    2. March (1)
  2. 2018 (3)
    1. December (1)
    2. August (1)
    3. July (1)
  3. 2016 (2)