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Grant: Discovery Grants Program - Individual

Ryerson University

$46,000.00

Understanding Soot Formation from Combustion with Numerical Modelling

FY 2019-20

Summary
Atmospheric pollution and the associated climate change are responsible for a myriad of detrimental environmental, ecological, health, and socio-economic effects. One particularly hazardous pollutant, particulate matter emitted from combustion (commonly referred to as soot' or black carbon') is a key contributor to climate change and leads to adverse respiratory health conditions. This research program seeks to address atmospheric soot emissions through detailed computational modelling of combustion systems, fundamental studies of soot formation, and the development of new algorithms to predict engine emissions. ******Whereas larger soot particles absorb solar radiation either while in the air or once they have settled on the Earth's surface, smaller particles are respired and absorbed through the lungs into the bloodstream. To comply with anticipated emissions regulations pertaining to particle size, fundamental understanding in this area needs to advance. Therefore, this research will focus on improving the state-of-the-art in soot formation modelling from the current benchmarks of semi-empirical inception models and quantitative concentration prediction. Research initiatives will seek to accurately model the particle nucleation phase, and predict size and shape. This research will proceed by analyzing and processing experimental trends to develop new fundamental models. It will also consider elevated pressures and transportation fuels. ******Another research thrust will focus on developing computational tools to predict soot emissions from engines. Engine modelling pushes the limits of computational capability and existing soot models are either inaccurate or too cumbersome for reliable use. Canadian industry currently suffers from a lack of accurate predictive capability in the prototype design or modification processes. Such a capability could reduce the need for expensive prototype fabrication and testing and help facilitate cleaner engine design. This research will seek to leverage our understanding of soot particle physics to devise innovative methods to inexpensively estimate concentrations, and later, more detailed particle characteristics such as size and shape. This research has a dramatic potential impact on industry as it will lead to a priori emissions predictions from new designs.******This research program will continue to generate new knowledge for academia and industry on the mechanisms of particle formation, and distribute the newly developed high-performance computing tools to other researchers for expanded use. Advancements in soot particle emissions understanding and predictive capability will lead to improved public health and reduced environmental impact. This research will continue to strengthen our industry, knowledge base, and Canada's role in a cleaner energy future.*****
Program
Discovery Grants Program - Individual
Location
Ontario, Canada
Recipient Type
Academia
Type
Grant
Source
NSERC's Awards Data

As published

Application id
RGPIN-2019-04628
Name nom
Dworkin, Seth
Department département
Mechanical and Industrial Engineering
Organization id
43
Institution établissement
Ryerson University
Province en
Ontario
Province fr
Ontario
Country en
CANADA
Country fr
CANADA
Fiscal year exercice financier
2019
Competition year année de concours
2019
Award amount
46000
Program id
RGPIN
Program name en
Discovery Grants Program - Individual
Program name fr
Programme de subventions à la découverte - individuelles
Group en
DISCOVERY RESEARCH
Group fr
RECHERCHE AXÉE SUR LA DÉCOUVERTE
Committee code
1512
Committee name en
Mechanical Engineering
Committee name fr
Génie mécanique
Area of application code
1200
Area of application group en
Advancement of knowledge
Area of application group fr
Avancement des connaissances
Area of application en
Advancement of knowledge
Area of application fr
Avancement des connaissances
Research subject code
2110
Research subject group en
Mechanical engineering
Research subject group fr
Génie mécanique
Research subject en
Combustion
Research subject fr
Combustion
Installment
inst:1 - 5
Partie
1
Nb partie
5
Application title
Understanding Soot Formation from Combustion with Numerical Modelling
Keyword
NSERC
Application summary
Atmospheric pollution and the associated climate change are responsible for a myriad of detrimental environmental, ecological, health, and socio-economic effects. One particularly hazardous pollutant, particulate matter emitted from combustion (commonly referred to as soot' or black carbon') is a key contributor to climate change and leads to adverse respiratory health conditions. This research program seeks to address atmospheric soot emissions through detailed computational modelling of combustion systems, fundamental studies of soot formation, and the development of new algorithms to predict engine emissions. ******Whereas larger soot particles absorb solar radiation either while in the air or once they have settled on the Earth's surface, smaller particles are respired and absorbed through the lungs into the bloodstream. To comply with anticipated emissions regulations pertaining to particle size, fundamental understanding in this area needs to advance. Therefore, this research will focus on improving the state-of-the-art in soot formation modelling from the current benchmarks of semi-empirical inception models and quantitative concentration prediction. Research initiatives will seek to accurately model the particle nucleation phase, and predict size and shape. This research will proceed by analyzing and processing experimental trends to develop new fundamental models. It will also consider elevated pressures and transportation fuels. ******Another research thrust will focus on developing computational tools to predict soot emissions from engines. Engine modelling pushes the limits of computational capability and existing soot models are either inaccurate or too cumbersome for reliable use. Canadian industry currently suffers from a lack of accurate predictive capability in the prototype design or modification processes. Such a capability could reduce the need for expensive prototype fabrication and testing and help facilitate cleaner engine design. This research will seek to leverage our understanding of soot particle physics to devise innovative methods to inexpensively estimate concentrations, and later, more detailed particle characteristics such as size and shape. This research has a dramatic potential impact on industry as it will lead to a priori emissions predictions from new designs.******This research program will continue to generate new knowledge for academia and industry on the mechanisms of particle formation, and distribute the newly developed high-performance computing tools to other researchers for expanded use. Advancements in soot particle emissions understanding and predictive capability will lead to improved public health and reduced environmental impact. This research will continue to strengthen our industry, knowledge base, and Canada's role in a cleaner energy future.*****