Search

Minimizing uncertainties is an important issue among the significant discussions pertaining to the project design and planning. Usually, the uncertainties in subsurface projects arise from the unknown ground conditions that may cause the designer to fail to consider all the potential issues prone to occur during the construction procedure. Total time and costs uncertainties can be considered as the most important uncertainties during the planning and excavation of a tunnel project that is directly connected with cognition of the subsurface conditions. This work presents an updating procedure and associated code, which allows one to refine predictions during construction. Updating does not only involve replacing the original prediction by actual data from the excavation but also includes a learning effect. The updating uses information from the actual excavation to arrive at an improved prediction for the unexcavated part. Updating the ground conditions and time-cost scatter-gram in tunnels during excavation is a tool, which helps the user refine input parameters by deriving relevant information from construction data and presenting it together with original input. In this paper, an example project shows that the updating result has a significant impact on the precision of the prediction and reduces the uncertainty about ground conditions and construction time and cost of the tunnel substantially. It facilitates both the owners and the contractors to be aware of the risk they should carry before construction of the unexcavated part, and it is useful for both tendering and bidding.