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Previously, a new concept of indexing methodology has been proposed for quantitative assessment of tunnel collapse hazard level at each tunnel face with respect to the given geological data, design condition and the corresponding construction activity (Shin et al, 2009a). In this paper, `linear` model, in which weights of influence factors are invariable, and `non-linear` model, in which weights of influence factors are variable, are taken into account with some examples. Then, the `non-linear` model is validated by using 100 tunnel collapse cases. It appears that `non-linear` model allows us to have adapted weight values of influence factors to characteristics of given tunnel site. In order to make a better understanding and help for an effective use of the system, a series of operating processes of the system are built up. Then, by following the processes, the system is applied to a real-life tunnel project in very weak and varying ground conditions. Through this approach, it would be quite apparent that the tunnel collapse hazard indices are determined by well interlinked consideration of face mapping data as well as design/construction data. The calculated indices seem to be in good agreement with available electric resistivity distribution and design/construction status. In addition, This approach could enhance effective usage of face mapping data and lead timely and well corresponding field reactions to situation of weak tunnel faces.

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Quantitative evaluation of collapse hazard levels of tunnel faces by interlinked consideration of face mapping, design and construction data: focused on adaptive weights