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This thesis explores the development of a digital twin for a real-life tunnel facility in Revinge, Skåne, using fire simulations and machine learning. The study aimed to identify preferred machine learning algorithms and compare fire simulation tools in terms of efficiency and performance. A literature review highlighted Long Short Term Memory (LSTM) networks as a suitable choice. Fire simulations
