Modelling fire occurrences in heavy goods vehicles in Norwegian road tunnels
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This master thesis project has been organized to scrutinize current incident data on near fires and fully developed fires in Norwegian road tunnels longer than 500 meter. This length is chosen because it is assumed that this length could threaten humans in case of fires. There has been a huge e ort in collecting data and transfer them into formats that has enabled mathematical modelling. The major issue of this thesis have been to resolve; What are the major contributing tunnel infrastructure factors leading to heavy goods vehicles fires in Norwegian tunnels? By using Poisson regression modelling several models are developed showing good fit with the observations. All models revealed that slope, length, annual average daily tra c of heavy goods vehicles, and whether a tunnel is subsea, are the significant factors. The most important factor is the subsea factor. This interacts with certain other factors revealing that subsea tunnels with excessive attributes are really exposed to HGV fires. The thesis discusses weaknesses in the data material, as well as there are a number of other interesting factors, for example related to the state of HGVs and driver behavior that are currently missing. The research potential is huge in order to improve the models and the understanding of HGV fires in tunnels.
Master's thesis in Mathematics and physics