This PhD thesis experimentally studies the volumetric efficiency of gerotor pumps in aero-engine gas turbine oil systems. This efficiency is the ratio of the effective measured flow rate and the theoretical flow rate computed based on pump displacement. In case of low inlet pressure and high rotational speed, which is often the case in aeronautical applications, the pump performance is severely affected by cavitation. This phase change from liquid to vapour causes a large portion of the flow to be occupied by gas, reducing the volume available for the liquid and reducing the overall mass flow rate. Due to its nature, the lubrication oil used in gas turbine engines is subjected to aeration which is the dissolution of air in oil. The air is dissolved in the liquid at high ambient pressure and released at lower pressure causing more air to occupy the cavities inside the pump. The change in liquid aeration is a relatively slower phenomenon causing the variation of aeration to be delayed with respect to the actual pressure and therefore varying also accordingly to the previous oil condition.The essential part of the work presented in this thesis is based on experimental research realised at the ATM department. This was conducted on a dedicated oil system test rig. This rig is build to reproduce the complete set of operating conditions encountered in a flying embedded oil system. This test rig was modified and equipped with several specific measurement systems to acquire data on pump performance and oil aeration. Precisely, a series of single-phase performance characterisations and transients have been recorded. The oil aeration was measured with two density-based instruments. The pump outlet pressure was recorded with a high-frequency pressure transducer. A new set-up of the test rig was also developed to allow the testing of pumps in two-phase flows conditions. Two-phase flows performance characterisations and transients have then also been studied.The data processing provided information necessary to build empirical models and to understand pump and cavitation behaviours. The focus is on pump performance in cavitation. This justify the extensive use of the cavitation number indicating the tendency of a flow to experience cavitation in given conditions. The base models can be used to determine if a given condition leads to cavitation or not, and predict the pump efficiency in both cases. The high-frequency pressure measurements provided an efficient tool to detect cavitation. / Doctorat en Sciences de l'ingénieur et technologie / info:eu-repo/semantics/nonPublished

The present research seeks to advance the understanding and application of Principal Component Analysis (PCA)-based combustion modelling for practical systems application. This work is a consistent extension to the standard PC-transport model, and integrates the use of Gaussian Process Regression (GPR) in order to increase the accuracy and the potential of size reduction offered by PCA. This new model, labelled PC-GPR, is successively applied and validated in a priori and a posteriori studies.In the first part of this dissertation, the PC-GPR model is validated in an a priori study based on steady and unsteady perfectly stirred reactor (PSR) calculations. The model showed its great accuracy in the predictions for methane and propane, using large kinetic mechanisms. In particular, for methane, the use of GPR allowed to model accurately the system with only 2 principal components (PCs) instead of the 34 variables in the original GRI-3.0 kinetic mechanism. For propane, the model was applied to two different mechanisms consisting of 50 species and 162 species respectively. The PC-GPR model was able to achieve a very significant reduction, and the thermo-chemical state-space was accurately predicted using only 2 PCs for both mechanisms.The second part of this work is dedicated to the application of the PC-GPR model in the framework of non-premixed turbulent combustion in a fully three-dimensional Large Eddy Simulation (LES). To this end, an a posteriori validation is performed on the Sandia flames D, E and F. The PC-GPR model showed very good accuracy in the predictions of the three flames when compared with experimental data using only 2 PCs, instead of the 35 species originally present in the GRI 3.0 mechanism. Moreover, the PC-GPR model was also able to handle the extinction and re-ignition phenomena in flames E and F, thanks to the unsteady data in the training manifold. A comparison with the FPV model showed that the combination of the unsteady data set and the best controlling variables for the system defined by PCA provide an alternative to the use of steady flamelets parameterized by user-defined variables and combined with a PDF approach.The last part of this research focuses on the application of the PC-GPR model in a more challenging case, a lifted methane/air flame. Several key features of the model are investigated: the sensitivty to the training data set, the influence of the scaling methods, the issue of data sampling and the potential of a subgrid scale (SGS) closure. In particular, it is shown that the training data set must contain the effects of diffusion in order to accurately predict the different properties of the lifted flame. Moreover, the kernel density weighting method, used to address the issue of non-homogenous data density usually found in numerical data sets, allowed to improve the predictions of the PC-GPR model. Finally, the integration of subgrid scale closure to the PC-GPR model allowed to significantly improve the simulations results using a presumed PDF closure. A qualitative comparison with the FPV model showed that the results provided by the PC-GPR model are overall very comparable to the FPV results, with a reduced numerical cost as PC-GPR requires a 4D lookup table, instead of a 5D in the case of FPV. / Le double défi de l'énergie et du changement climatique mettent en avant lanécessité de développer des nouvelles technologies de combustion, étantdonné que les projections les plus réalistes montrent que la plus grandeaugmentation de l'offre d'énergie pour les décennies à venir se fera à partirde combustibles fossiles. Ceci représente donc une forte motivation pour larecherche sur l'efficacité énergétique et les technologies propres. Parmicelles-ci, la combustion sans flamme est un concept nouvellementdéveloppé qui permet d'obtenir des rendements thermiques élevés avecdes économies de carburant tout en maintenant les émissions polluantes àun niveau très bas. L'intérêt croissant pour cette technologie est égalementmotivé par sa grande flexibilité de carburant, ce qui représente uneprécieuse opportunité pour les carburants à faible valeur calorifique, lesdéchets industriels à haute valeur calorifique et les combustibles à based'hydrogène. Etant donné que cette technologie est plutôt récente, elle estde ce fait encore mal comprise. Les solutions d'une application industriellesont très difficiles à transposer à d'autres. Pour améliorer les connaissancesdans le domaine de la combustion sans flamme, il est nécessaire de menerdes études fondamentales sur ce nouveau procédé de combustion afin defavoriser son développement. En particulier, il y a deux différencesmajeures par rapport aux flammes classiques :d’une part, les niveaux deturbulence rencontrés dans la combustion sans flamme sont rehaussés, enraison des gaz de recirculation, réduisant ainsi les échelles de mélange.D'autre part, les échelles chimiques sont augmentées, en raison de ladilution des réactifs. Par conséquent, les échelles turbulentes et chimiquessont du même ordre de grandeur, ce qui conduit à un couplage très fort.Après un examen approfondi de l'état de l'art sur la modélisation de lacombustion sans flamme, le coeur du projet représentera le développementd'une nouvelle approche pour le traitement de l'interaction turbulence /chimie pour les systèmes sans flamme dans le contexte des simulationsaux grandes échelles (Large Eddy Simulations, LES). Cette approche serafondée sur la méthode PCA (Principal Component Analysis) afin d'identifierles échelles chimiques de premier plan du processus d'oxydation. Cetteprocédure permettra de ne suivre sur la grille LES qu'un nombre réduit descalaires non conservés, ceux contrôlant l'évolution du système. Destechniques de régression non-linéaires seront couplées avec PCA afind’augmenter la précision et la réductibilité du modèle. Après avoir été validégrâce à des données expérimentales de problèmes simplifiés, le modèlesera mis à l'échelle afin de gérer des applications plus grandes, pertinentespour la combustion sans flamme. Les données expérimentales etnumériques seront validées en utilisant des indicateurs de validationappropriés pour évaluer les incertitudes expérimentales et numériques. / Doctorat en Sciences de l'ingénieur et technologie / info:eu-repo/semantics/nonPublished