Abstract
Soot emissions from combustion devices are known to have harmful effects on the environment and human health. This project leverages existing knowledge in soot modelling and soot formation fundamentals to develop a stand-alone, computationally inexpensive soot concentration estimator to be linked to CFD simulations as a post-processor. The estimator consists of a library generated using the hystereses of soot-containing fluid parcels, which relates soot concentration to the aggregated gas-phase environment histories to which a fluid parcel has been exposed. The estimator can be used to relate soot concentration to computed parcel hystereses through interpolation techniques. The estimator shows the potential ability to produce accurate predictions with very low computational cost in laminar coflow diffusion flames. Results also show that as flame data representing a broader set of conditions is added to the library, the estimator becomes applicable to a wider range of flames.
Highlights
Results show that the stochastic algorithm employed by Patterson et al, [56] produced results within a factor of 2 to those generated by the established Method of Moments with Interpolative Closure (MOMIC) technique
Turbulent Combustion Soot Modelling Overview The primary focus of this thesis is the development of a soot concentration estimator for industrial combustion applications
Preliminary Testing of Soot Estimator It is important to emphasize that the strategy of the estimator is to predict soot concentration, not on local conditions, as it is clear from residence time disparities that local conditions neither determine soot concentrations, nor correlate to them, but rather based on the cumulative soot-particle-containing fluid parcel history
Summary
In the design of industrial combustion devices, such as engines, detailed numerical modelling and Computational Fluid Dynamics (CFD) simulations have become commonplace. The inclusion of soot formation within these simulations is challenging, and if it is to be reliably accurate, it incurs an intractably high computational cost It is a major objective of the combustion industry and research community to develop novel numerical techniques to model, predict, or estimate soot concentrations. This thesis does not propose a new model for soot formation and oxidation, rather it seeks to develop a system of library generation that can be used to estimate soot properties using correlations and interpolation The goal of this technique is to produce reasonably accurate predictions of soot concentration with low computational cost and without modelling the physical processes and phenomena.
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