| Summary: | The snow galleries along the Iron ore railway line in northern Sweden have had major problems in recent years due to increasingly large snow loads. Despite great efforts reducing the loads by shoveling off the snow, several of the galleries have been damaged. Due to these incidents, the Swedish Transport Administration (TRA) has asked Luleå University of Technology (LTU) to make an evaluation of galleries 4, 9 and 13A in the neighborhood of Vassijauri. TRA has asked for a way to monitor the load on these galleries with a trigger system that gives a warning message when the galleries are exposed to a critical load. Measurement systems have been installed in galleries 9 and 13A during the autumn of 2021 such that the snow load in one mainframe per gallery could be monitored. In this thesis, work has been performed by assessing how much snow load each gallery can handle before it collapses. The restrictions for the project are set based on the drawings that is available from the TRA's information database, BaTMan. A literature study is performed on snow load, how it was changing over the years, both back and forth, how snow load is calculated according to today’s regulations and how the density of the snow affects the intensity of the snow load. The distribution of the snow on the galleries has been performed based on the Eurocodes and National Standards. Models of the galleries in two- dimensional have been created for all frames in all the galleries to find the weakest frame in order to compute the critical load. Some of the frames are not stable when they are analyzed as individual members, therefore the decision was made to also construct 3D models to see how the cobweb effect influenced the galleries' capacity. Before the main frames have reached their full capacity, the secondary construction elements (roof beams) have been damaged and therefore has no major collapse taken place. From the 3D model, it is clear that the secondary construction that lacks capacity. The critical frames are completely different ...
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