Impact of Mixing on the Signature of Combustor Defects

Abstract

AbstractDefects in the combustion chamber can negatively influence the performance of an aircraft engine and increase component stress in the turbine. One aim of the Collaborative Research Center 871 is to provide early prediction about the condition of the engine by analysing the signature of the exhaust gas jet. This includes the usage of machine learning techniques and helps to optimise maintenance times and to reduce costs. This topic is linked to the question, how defects in the combustion chamber affect the flow field and how the defect signature is mixed out in the hot gas path. Examples are shown for a simplified ring burning chamber, where several experimental and numerical studies have been done. Additionally, one failure case is described in detail here, where the methodology is applied to a real size gas turbine burning chamber and its subsequent turbine. Furthermore the diffusion theory is generalized to situations with complex geometrical boundary conditions, for instance from the turbine passage channel geometry. This approach is applied on the investigated example case and shows complex thermal diffusion coefficients, being in the order of 10,000–100,000 times larger than the molecular diffusion coefficient. Even these large values allow the determination of burning chamber defects from the exhaust flow pattern.