E. Farrokh - Department of Mining and Metallurgy Engineering, Amirkabir University of technology, Tehran, Iran

In every tunnel boring machine (TBM) tunneling project, there is an initial low production phase so-called the Learning Phase Period (LPP), in which low utilization is experienced and the operational parameters are adjusted to match the working conditions. LPP can be crucial in scheduling and evaluating the final project time and cost, especially for short tunnels for which it may constitute a major percentage of the total project completion time. The contractors are required to have a better understanding of the initial phase of a project to provide better estimates in the bidding documents. While evaluating and shortening of this phase of low production is important for increasing the productivity and daily advance rate of the machine, there has been limited a direct study and assessment of this period. In this work, we discuss the parameters impacting LPP, and introduce a new methodology for its evaluation. In this regard, an algorithm is introduced for estimation of the approximate extent of LPP based on some TBM tunneling case histories. On the basis of many statistical analyses conducted on the actual data and application of two different shapes of linear and polynomial for the description of LPP, a linear function is proposed for estimation of the learning phase parameters. The major parameters of this function are the learning conditions’ rating and the proportion of LPP to tunnel diameter (X۱/D). Analysis of the correlation between these two parameters show a very good coefficient of determination (R۲ = ۹۲%). This function can be used for the evaluation of TBM advance rates in LPP and for adjusting the TBM utilization factor in the initial stages of a TBM tunneling project. The learning phase can affect the overall utilization rate and completion time of the tunnels, especially when their lengths are around a couple of kilometers. A true understanding of the LPP characteristics can help the contractors to come up with a more accurate bidding time and cost evaluation, and may also benefit the clients to arrange a better schedule for the final project delivery to the public.

TBM, Advance rate, Learning phase, Normal phase, time evaluation