Research Projects

The safety of nuclear power plants is crucial due to the potential consequences of nuclear accidents. The Passive Residual Heat Removal system (PRHR) is designed to extract heat from the reactor core in case of a loss of coolant, preventing damage to fuel rods and potentially catastrophic failure. The project proposal aims to increase boiling heat transfer on a circular vertical tube and its bundle by controlling vapour bubble generation and implementing machining learning techniques. A novel technique, bi-philic coating, will be applied to reduce vapour bubble coalescence at the top of the tube bundle. The proposed technique will also provide root-level knowledge about departure characteristics, such as initiation, growth, and merging. Variable machining learning techniques can provide more accurate and efficient process behavior predictions in two-phase heat transfer (nucleate boiling). By forming machine learning models on large experimental or simulation datasets, precise models can be developed to predict pool boiling parameters, optimize variables influencing boiling phenomena, increase heat transfer efficiency, and reduce the risk of overheating and other safety issues.