Analysis and evaluation of excavation performance of EPB-TBM: Hadim-Afşar-Bağbaşı Water Supply Tunnel example

The rapid increase in the global population has led to a corresponding surge in migration to major cities, resulting in significant changes to urban structures. This demographic growth has caused surface-level space to become insufficient, thus increasing the utilization and demand for underground structures. Consequently, tunneling activities have become more prevalent due to the growing importance of underground infrastructure. Traditional methods in tunneling have been superseded by the adoption of modern technologies and methodologies, particularly the widespread use of mechanized excavation equipment and transportation tools. The efficiency of mechanized excavation, combined with its provision of safer working conditions and higher excavation speeds, has made it a preferred choice in tunneling projects. However, thorough preliminary studies are essential to fully harness the benefits of mechanized excavation. These studies involve identifying the geological and physico-mechanical characteristics of the excavation route, anticipating potential challenges, and selecting appropriate excavation equipment. Neglecting these preparatory measures may lead to significant economic and temporal losses. In addition to selecting the right excavation equipment, accurately predicting their performance is crucial for ensuring the successful execution of projects and conducting precise cost analyses. The objective of the thesis is to develop performance prediction models for full-face tunnel boring machines based on the physico-mechanical properties of the excavated formation. Predicting the performance of full-face tunnel boring machines aids in accurately estimating project duration during the planning phase and ensuring project control during implementation. Furthermore, it contributes to more precise cost estimations, making it an important preparatory endeavor. The study encompasses work on two distinct tunnel projects: the Hadim-Afşar-Bağbaşı Water Supply Tunnel project within Konya province and the Çekmeköy-Sancaktepe-Sultanbeyli Metro Line project within Istanbul province. Both projects utilized the same type of tunnel boring machine, namely the Earth Pressure Balance TBM. Regression analyses, conducted using the SPSS statistical program and the Python programming language, were employed to develop the performance prediction model. The advancement rate parameter was used as an output parameter in the performance prediction model, with the physico-mechanical properties of rocks selected as independent variables. Subsequent analyses yielded correlation coefficients of 0.51 and 0.42 for the performance prediction model based on the physico-mechanical properties of rocks.