chemical

Combustion of fossil fuels is responsible for a major fraction of greenhouse gas emissions and the emission of pollutants such as nitrogen oxides (NOx), carbon monoxide (CO), soot, aerosols and other harmful chemical species. Reducing Canada’s dependence on fossil fuels is one of today’s major challenges. To design new pollutant-free combustion devices, improved mathematical models and computational tools for describing reactive flows are required. These models will enable a new understanding of combustion and lead to improved combustor designs and energy systems.

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.

This research project looks to develop computer programs which will enable the study of reactive flows and combustion processes in gas turbine engines. Combustion is inherently a multi-scale process that involves a wide range of complicated physical/chemical phenomena, as well as a wide range of spatial and temporal scales.

With the widespread deployment of networked sensors and cameras throughout cities, there is an incredible opportunity for improving safety and security. Surveillance networks incorporate cameras mounted on traffic lights and overpasses, mobile cameras attached to emergency vehicles, and chemical and biological sensors for detecting dangerous contaminants. Surveillance networks can comprise several thousand sensors and cameras throughout a city.