Toward probabilistic ground models for time and cost estimation of tunnel projects

Abstract

The construction time and cost of a rock tunnel project are highly dependent on the rock mass quality and encountered ground behaviour. In most rock tunnel projects, the knowledge about the ground conditions along the tunnel is limited, making it difficult to predict accurately the construction time and cost. The KTH model takes a probabilistic approach to address this problem; however, it does not account for the spatial variability of the ground conditions. This paper investigates an alternative probabilistic ground model to be used within the KTH model that enables accounting for the spatial variability through Markov random field theory. The new ground model employs a parametric approach to describe the properties of the Markov field, hence, enabling the simulation of the ground conditions with limited data, but does not consider the epistemic uncertainty in the model parameters. This will be the addressed in future research.

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