Advanced Mathematical Modeling and Parallel Simulation Algorithms for Analysis and Design of Electrical Power Systems and Smart Grid Technologies
Postdoctoral fellow: Dr. Natalie Nakhla, Electronics, Carleton University
Lead faculty member: Dr. Q. J. Zhang, Electronics, Carleton University
With today’s rapidly increasing energy demands and the emergence of smart grids and renewable energy resources, the current energy and power technologies need to be advanced to keep up with these changes. Simulation and modeling plays a vital role in understanding, designing and planning of electrical power systems. The proposed research aims at developing a new generation of advanced mathematical models and simulation tools for electrical power systems and smart grids.
Dr. Kim McAuley, Queen's University
Engineers use mathematical models to describe the production of plastics and other chemicals. The models contain unknown parameters that are estimated from plant data. In the past year, the research team analyzed several criteria that modelers use to decide how complex or how simplified their models should be. They showed that one popular model-selection criterion, the corrected Akaike Information Criterion, tends to select very simple models, and that another, the adjusted coefficient of determination, tends to select models with many parameters.
[url=mailto:firstname.lastname@example.org]Dr. Mads Kaern[/url] , University of Ottawa
The goal of the MITACS-funded research program on reverse-engineering cellular complexity is to develop new mathematical tools and algorithms for analyzing genetic switching networks. Many genes operate as switches and are turned on and off, like light bulbs, when needed. Understanding the regulatory circuits that control this switching behaviour would improve our ability to modulate gene activity, provide clues to fundamental biological design principles, and lead to better synthetic circuits for biotechnological applications.
[url=http://www.matrix-as.com/]Matrix Advanced Solutions Ltd.[/url]