Air losses in compressed air tunneling : a prediction model

Data (measurements) from a tunnel in Munich, Germany was used to develop and validate a model to predict air loss volumes in the process of compressed air tunnelling. In the implemented case study, compressed air was used as a measure to control the groundwater followed by placing a shotcrete lining as temporary support. Evolutionary polynomial regression was used for modelling. EPR is a data-driven method based on evolutionary computing aiming to search for an explicit and structured polynomial model representing air losses. Comparisons made between the actual measurements and the model predictions represented robustness of the suggested model in learning and predicting the behaviour of the system. A sensitivity analysis was also performed on the developed model which revealed the reliability of the model by correctly presenting the expected effect from air permeability of the soil despites in non-homogeneous and layered nature of the geo-materials involved in this case study