Predictive Chemical and Statistical Modeling of Particulate Matter Formation in Turbulent Combustion with Application to Aircraft Engines
Abstract
Soot formation in gas turbine engines is a major concern in the design of modern aircraft propulsion systems. Accurate modeling of soot formation is extremely di cult due to the complex underlying chemical and physical processes. A set of critical modeling requirements for soot prediction were identi ed and investigated under a comprehensive program covering three di erent research areas{chemical modeling, statistical modeling, and soot modeling in turbulent combustion. The chemical modeling aspect of the project includes further improvements of the gas-phase kinetics and the heterogeneous reactions on the particle surface leading to further soot mass growth or oxidation. In this project, we developed a new method for statistical modeling of the particle size distribution based on particle volume and surface area. The chemical and statistical methods were incorporated into turbulent combustion models for large-eddy simulation. In addition, the complex interactions of molecular and turbulent transport with the ame chemistry and particle formation and oxidation was studied in direct numerical simulations.
Document Details
- Document Type
- Technical Report
- Publication Date
- Mar 01, 2012
- Accession Number
- ADA569679
Entities
People
- Heinz Pitsch
- Michael Frenklach
- Venkat Raman
Organizations
- Stanford University