Davide Fittipaldi
Prediction of the laminar combustion velocity in methane-air mixtures by means of deep learning algorithms.
Rel. Daniela Anna Misul, Mirko Baratta. Politecnico di Torino, Corso di laurea magistrale in Ingegneria Meccanica (Mechanical Engineering), 2021
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Abstract
The need to reduce environmental pollution has led to a search for alternative, low-emission fuels. In fact, internal combustion engines, are one of the main source of pollution in the urban environment. Methane is one of the best alternatives to the main and most common fossil fuels, because it is one of the fuels with the lowest CO2 and hydrocarbon emissions. In addition to being one of the cleanest fuels, it has remarkable chemical and physical properties, such as high anti-knocking, which would allow high efficiency in monovalent methane-fuelled heat engines with an high compression ratio. However, compared to petrol, methane burns slowly, which leads to a variation in efficiency and not complete stability cycle by cycle, reducing power and increasing fuel consumption.
Low flame front propagation speed and poor burning capacity in poor mixture conditions can be improved by the addition of hydrogen, due to its higher burning speed
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