Computational Combustion Laboratory (CCL)


Ongoing Research


Computational Combustion Modeling | Combustion-generated Pollutants | Atmospheric Soot | High-performance Computing



Multiscale modeling of soot

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The exact process of soot formation is still yet to be understood. This is partly because of experimental uncertainty, partly because of the complex physico-chemical processes spanning multiple scales leading to soot formation. Understanding the physics and chemistry of soot formation will require understanding the soot nucleation from an atomistic standpoint as well as exploring the evolution of soot from an aerosol-dynamics viewpoint.

The transition from gaseous combustion products to a solid particulate phase starts via formation of large aromatic molecules aka polycyclic aromatic hydrocarbons (PAHs). They interact with one another and with other small species, and at one point they — by processes that are still not understood — form what can be termed as the first soot particle. Its diameter is close to a nanometer.

The incipient soot particles then grow and evolve due to physical interactions (e.g., Brownian collision) and chemical reactions (e.g. surface reactions) as they travel through the combustion gases. The exact nature of these physico-chemical processes — another poorly understood phenomena — controls how the shape, size, and properties of the final soot particles are going to be as they escape the combustion domain.

Recent CCL Publications
  • An Investigation of Soot Evolution in High-pressure Spray Combustion. Mukut, K., M.; and Roy, S. In 11th US National Combustion Meeting, 2019.
  • A Systematic Comparison of Detailed Soot Models and Gas-phase Chemical Mechanisms in Laminar Premixed Flames. Roy, S., P.; and Haworth, D., C. Combustion Science and Technology, 188(7): 1021-1053. 2016.
  • Dynamics of flow-soot interaction in wrinkled non-premixed ethylene-air flames. Arias, P., G.; Lecoustre, V., R.; Roy, S.; Luo, Z.; Haworth, D., C.; Lu, T.; Trouve, A.; and Im, H., G. Combustion Theory and Modelling, 19(5): 568-586. 9 2015.
Researchers
  • Khaled Mosharraf Mukut

Supporting organizations

Marquette XSEDE