Geologic Prediction Model for Tunneling
Geologic uncertainty in underground construction often leads to design and construction conservatism and hence to inflated costs. This paper presents a general model for the probabilistic prediction of tunnel geology, as a basis for developing more effective tunnel design and construction decision support systems. The geologic conditions along the tunnel alignment are modeled by a set of geologic parameters (such as rock type, joint density, degree of weathering, etc.), each following a continuous-space, discrete-state Markov process. The state probabilities for each geologic parameter are initially based on general geologic information and are later updated to reflect the outcomes and reliability of the location-specific, non-deterministic observations provided by exploration programs. The resulting posterior geologic parameter profiles are aggregated into a single probabilistic ground class profile that can be used for determining optimal tunnel design and construction strategies. The model is illustrated by an example application.
Photios G. Ioannou
Civil & Environmental Engineering Department
University of Michigan
Ann Arbor, Michigan 48109-2125, U.S.A.
Tunneling, subsurface exploration, geologic exploration, geologic prediction models, probabilistic geologic modeling, Markov process.