Abstract

Soot formation from complex solid fuels, such as coal or biomass, is an under-studied and little understood phenomena which has profound physical effects. Any time a solid fuel is combusted, from coal-burning power plants to wildland fires, soot formation within the flame can have a significant influence on combustion characteristics such as temperature, heat flux, and chemical profiles. If emitted from the flame, soot particles have long-last effects on human health and the environment. The work in this dissertation focuses on creating and implementing computational models to be used for predicting soot mechanisms in a combustion environment. Three models are discussed in this work; the first is a previously developed model designed to predict soot yield in coal systems. This model was implemented into a computational fluid dynamic software and results are presented. The second model is a detailed-physics based model developed here. Validation for this model is presented along with some results of its implementation into the same software. The third model is a simplified version of the detailed model and is presented with some comparison case studies implemented on a variety of platforms and scenarios. While the main focus of this work is the presentation of the three computational models and their implementations, a considerable bulk of this work will discuss some of the technical tools used to accomplish this work. Some of these tools include an introduction to Bayesian statistics used in parameter inference and the method of moments with methods to resolve the 'closure' problem.

Degree

PhD

College and Department

Ira A. Fulton College of Engineering and Technology; Chemical Engineering

Rights

http://lib.byu.edu/about/copyright/