Processed Dataset for Energy Performance Analysis of EPB TBM Operations in Urban Underground Construction

This dataset contains processed operational and energy-related parameters derived from Earth Pressure Balance (EPB) Tunnel Boring Machine (TBM) operations in an urban underground infrastructure context. The dataset is designed to support reproducible research in energy performance modelling, physics-informed machine learning, and sustainable tunnelling systems. The dataset includes key operational variables such as thrust force, cutterhead torque, advance rate, and earth pressure, along with energy-related metrics including instantaneous power, specific energy, and energy intensity. Derived variables were computed based on physically grounded formulations to ensure consistency with excavation energy principles. All data have undergone systematic preprocessing, including noise filtering, outlier removal, normalization, and temporal alignment. The dataset preserves realistic correlations between operational parameters and energy consumption, enabling its use for machine learning model development, sensitivity analysis, and optimization studies. This dataset is associated with a research study on energy-oriented analytical frameworks for EPB TBM operations and is intended to facilitate transparency, reproducibility, and further methodological development in infrastructure energy modelling.