The construction of tunnels beneath the water table presents significant challenges, particularly due to the presence of groundwater. These challenges range from safety concerns during excavation to potential damage to nearby structures and environmental consequences. This project aims to advance the science and engineering of tunneling by developing new design and analysis tools, informed by cutting-edge research, to address these water-induced challenges. The focus is on creating simple, yet accurate solutions, such as numerical models, design charts, and BIM-integrated monitoring techniques, to improve predictions and mitigate tunneling risks. The project will also explore the influence of tunnel drainage, the behavior of Tunnel Boring Machine (TBM) shields, and the impact of groundwater fluctuations, which are often overlooked in traditional design practices.

The research builds on the hypothesis that advanced numerical modeling, when calibrated with field and laboratory data, can improve predictions of excavation-induced deformations and inform better design practices, especially for underwater or deep subfluvial tunnels. The novelty of this approach lies in its incorporation of digital technologies, such as artificial intelligence and Bayesian methods, to enhance risk analysis and construction safety, particularly in challenging subterranean environments. This work is expected to make significant contributions to global tunneling practices, particularly in urban transport, high-speed rail, and critical infrastructure projects, by reducing risks associated with water table-induced failures. Additionally, the project aligns with key societal priorities, including energy efficiency, sustainable mobility, and environmental protection, thus providing solutions that are crucial for advancing modern infrastructure while minimizing negative impacts on the surrounding environment.