Modeling and Validation of the Oil Control Ring Performance for a Orbiting Face-Sealing

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As ground transportation is slowly but surely being electrified, the air transportation industry is looking for solutions to reduce its carbon footprint. Unfortunately, batteries are too heavy to be viable for commercial flight and cheap, widely available bio-jet-fuel is still eluding. The best solution remains to increase engine efficiency to reduce fuel consumption as much as possible. Large gas turbines have reached impressive efficiency levels, but small gas turbines remains relatively inefficient due to limited combustion temperatures combined to high viscous and tip losses. In order to achieve radical reduction in fuel consumptions, manufacturers are forced to revisit alternative engine configurations with a new perspective. One of the prime candidates for cleaner propulsion are the non-reciprocating combustion engines types that combine high efficiencies of volumetric engines while being well-known for their high power density. Unfortunately, these type of engine are also well-known for their oil consumption that needs to be reduced before they are used for aerospace applications in order to meet customer perceptions, weight and forthcoming emission regulations. The leakage through the face-sealing Oil Control Rings (OCRs) can represent more than half of the oil consumption and is the first target to reduce total oil consumption as it can be drastically reduced from current values without a significant impact on engine durability. This proposed project aims at improving engine OCRs through detailed modeling and experimental validation. The UdeS and P&WC team will build upon previous OCR models by developing a novel numerical formulation of the hydrodynamic pressure generated tailored for the orbiting face-sealing OCR-housing interface required by this type of engines. The hydrodynamic pressure sub-model will then be integrated in a complete OCR simulation code that could be used to predict trends for oil leakage, friction and wear. In parallel, an experimental setup will be built to validate the model and OCR performance by measuring oil consumption and oil film thickness in a representative controlled environment.