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- W3081759973 abstract "Abstract Tunnel boring machines (TBMs) are considered to be the most efficient tunneling method for long tunnels because of their higher productivity, adaptability to a variety of subsurface conditions, and providing a safer work environment. The number of TBMs utilized over the past decade has escalated, testimony to their continuing success and flexibility for application on projects of different diameter, length, and ground conditions. There are various guidelines available for TBM selection and for developing a suitable specification for a machine for a given project. Proper application of these guidelines is an essential part of machine selection to assure optimal performance of these machines in a given project. However, available guidelines are very general in nature and based on past experiences: they cannot take into account the many intricacies of a specific upcoming project including site set up and geology. This paper discusses use of Discrete Event Simulation (DES) to model tunneling activities, and demonstrates the ability of simulation to capture the interrelationships between the TBM, back-up system, and geologic interactions. The simulations provide insight into expectations for utilization of individual components as well as overall TBM system utilization. The simulation model can be constructed to enable estimation of the machine utilization under various site set up and back-up arrangements, and thus paves the way to quantitative assessment of the value of adding different capabilities on the machine and back-up system. Case studies are used to demonstrate the impact of some common tunneling activities in different ground conditions. In particular, DES was used to study the effect of eight different tunneling activities on the overall performance of the TBM. Significant differences in productivity can be seen by varying the specification of the TBM and system components. The results show the importance of selecting the right components for the back-up and their impact on overall machine utilization, leading to the possibility of allowing more methodic and fact-based selection of system components for optimal TBM performance." @default.
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- W3081759973 date "2020-12-01" @default.
- W3081759973 modified "2023-09-26" @default.
- W3081759973 title "Investigating the impact of TBM downtimes on utilization factor based on sensitivity analysis" @default.
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- W3081759973 doi "https://doi.org/10.1016/j.tust.2020.103586" @default.
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