Prediction of RMR ahead excavation front in D&B tunnelling

Abstract

As known, geological conditions are a complex challenge in any civil engineering work, however this is not as relevant as in tunnelling where ground knowledge usually has many uncertainties at the beginning of the construction phase. The prediction of the ground quality of advancing tunnel face represents, itself, a key step during tunnelling, allowing to prepare and mobilize the most appropriate means to proceed with the works, with an adequate level of safety, quality and efficiency. The authors tested a quantitative methodology for prediction of rock mass quality during drill and blast excavation. The paper is based on the application of three mathematical prediction methods for the estimation of rock mass quality: linear regression, geostatistical kriging and neural networks algorithms. Additionally, a fourThempirical method was also applied, based on engineering geologist’s expertise, aiming to assess the deviation of the quality prediction. The methodology was tested using RMR information of several tunnels, dug in a granitic rock mass, integrating the power generation reinforcement of Picote dam, located in the northeast of Portugal. The obtained results revealed, for all cases, a significant correlation between the estimated RMR and the observed value, thus raising good expectations for the progress of the ongoing research works.