Characterising mixing and soot production using a Lagrangian Statistical Method

This PhD thesis uses a Lagrangian Statistical Method (LSM) to investigate the time histories of mixing hence and soot development for massless particles tracked within an LES calculation. This provides the advantage of investigating soot development using an inexpensive post-processing technique. The method comprises tracking massless particles through the flow and recording the local temperature and composition at the particle location, as well as the age of the particle. This can be used to give statistical information about various aspects of mixing and soot production, such as distributions of mixture fraction or residence times. The history for each particle can then be used in a post-processing step to predict the soot development in time for that particle path. This has been used to compare Large Eddy Simulations (LES) of reacting flows in both a laboratory combustor and a geometry representative of an annular sector from an aircraft engine combustor. The Lagrangian Statistical Method proved to be a cost effective and efficient low-order method to characterise the reacting flow mixing, provide soot estimates based on unsteady histories of particle properties and reveal new knowledge in combustor regions, such as the primary zone, where measurements of long duration sooting flames are challenging. LSM provides also a convenient, preliminary design tool, a decoupled post-processing method and a rapid test bed on which soot models can be tested/assessed with realistic time histories of gas phase conditions without needing to run the full CFD simulation.