FORECASTING THE TBM PERFORMANCE USING GREY-STOHASTIC SIMULATIONS

АУТОР(И) / AUTHOR(S): Vladimir Krivošić, Luka Crnogorac , Rade Tokalić , Zoran Gligorić , Branko Gluščević 

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DOI:  10.46793/ACUUS2025.7.1.104

САЖЕТАК / ABSTRACT:

Tunnel boring machines (TBMs) are widely used in urban spaces tunneling projects because they provide safer working environment with higher efficiency compared to other underground construction methods. As for any project, good time management and cost control are of high importance. Tunneling in urban areas is challenging because of diverse geological conditions and other factors which affect the performance of TBM. From a mining engineer’s point of view, prediction of performance of TBM is of vital role for good organization of the work on tunnel construction. Good time management of all operations that are connected to the penetration rate of the machine (timely delivery and installation of support segments, installation of additional transport segments and all other auxiliary work) opens a possibility to plan construction costs and deadlines more appropriately. Penetration rate is the principal measure of TBM performance. For that reason, in this paper the focus was on developing a precise model based on grey-stochastic theory for TBM penetration rate prediction. Grey simulations models are widely used in forecasting in engineering and are scientifically proven. The stochastic grey model (GM 1,1) where stochastic parameter is described with Brownian motion is conceptualized to forecast five future data values based on the previously known twenty-five data values of penetration rate. Input data, penetration rate, can be expressed in millimeters per minute or any other unit considering the time resolution coefficient. Forecasted data accuracy of developed model is placed in a group of highly accurate models. Proposed model can successfully be used by mining and civil engineers on different underground construction projects in terms of better planning of the performance of tunneling machines, optimization of work organization, cost balancing as well as defining the deadlines more accurately.

КЉУЧНЕ РЕЧИ / KEYWORDS:

TBM, performance, forecasting, penetration rate, grey-stochastic simulations

ПРОЈЕКАТ / ACKNOWLEDGEMENT:

This research has been financially supported by the Ministry of Science, Technological Development and Innovation of the Republic of Serbia (Contract No: 451-03-136/2025-03/200126).

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