Giovanni Nalin
Safety distances estimation for hydrogen blended natural gas jet fires using neural network methods.
Rel. Micaela Demichela. Politecnico di Torino, Corso di laurea magistrale in Ingegneria Chimica E Dei Processi Sostenibili, 2025
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Abstract
The global trend towards hydrogen as a key low-carbon energy vector is rapidly increasing worldwide, due to its high gravimetric energy density. Following this current, there were analysed different ways to produce it, overall, the ones powered by renewable energy sources (green H2), which represents a bridge between today and a zero-emission future. All the types of H2 could be transported with several strategies and in different forms, for example in trucks through liquid or compressed gas state. However, these last two methods need sophisticated structures and elevated costs. At the same time, existing natural gas (NG) transmission and distribution pipelines represent a vast infrastructure that could carry hydrogen blended natural gas (HBNG) over long distances more economically than pure hydrogen pipelines too.
Indeed, blending hydrogen into NG networks avoids massive costs for new infrastructures, but raises questions about mixing behaviour, energy transmission, compressor work and material integrity, particularly due to hydrogen embrittlement (HE) of steels under high pressure
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