To meet the requirements of urbanization, tunneling projects are being undertaken to enlarge underground infrastructure systems. The success of a tunneling project not only depends on the performance of tunneling equipment, but also on the subjective actions and decisions taken by experienced personnel as well as a myriad of unforeseen factors and events associated with tunneling operations. The number and unpredictability of these factors results in considerable project uncertainty, making it difficult for practitioners to determine the most effective course of action following deviations from project baselines or an unanticipated event. Attempts to capture project information have resulted in the widespread implementation of data collection systems throughout the tunneling industry. Despite collecting vast amounts of data, however, practitioners continue to struggle with the transformation of these data into usable information for improved tunneling project performance. Indeed, without systems capable of automatically combining, analyzing, and transforming data into a format that is easily interpretable, decision-making will continue to rely primarily on the subjective
decisions of practitioners.
The proposed work will combine our research team's academic strength in simulation-based analytics and geotechnical engineering with the practical knowledge and experience of our industrial collaborator to develop a new, decision-support framework for tunnel construction that is capable of integrating project, equipment, ground, and behavioral data, in real-time, to effectively and rapidly redirect tunneling operations in response to project irregularities or deviations. In addition to enhancing tunneling operations, this work is expected to provide new insights into the modeling of operational behavior in the construction decision-support domain.