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Einfache und praxistaugliche Voraussage von TBM‐Leistungen
Author(s) -
Tarkoy Peter J.
Publication year - 2009
Publication title -
geomechanics and tunnelling
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.317
H-Index - 18
eISSN - 1865-7389
pISSN - 1865-7362
DOI - 10.1002/geot.200900017
Subject(s) - performance prediction , function (biology) , tunnel boring machine , computer science , thrust , variable (mathematics) , simple (philosophy) , torque , predictive modelling , fuel efficiency , industrial engineering , engineering , operations research , machine learning , simulation , mechanical engineering , automotive engineering , mathematical analysis , philosophy , physics , thermodynamics , mathematics , epistemology , evolutionary biology , biology
The prediction of excavation rates for tunnel boring was originally developed for rock boring machines. One of the earliest working methods for predicting TBM performance was developed at the University of Illinois. The method was simple, reliable, inexpensive, and the data available to the public. Since then, various methods, more sophisticated, more time consuming and more expensive have been developed by various researchers. Some of them were quite exacting in the prediction despite a limited knowledge of anticipated conditions. Others were ever changing and unavailable for public use. Predictions of penetration rates and disc cutter consumption were tied to rock properties and machine variables while the prediction of TBM utilization was ignored even though in many cases it was the most variable element having the greatest impact. Prediction of TBM utilization was substantially more difficult since it was a function of time and length dependent downtimes, project conditions, TBM design features, work force, construction management, and site limitations. Many of these influences were simply a function of the impact of the human element and therefore tenuous to predict. The development of machines designed to negotiate soil, rock, and a combination of both inherently imposed additional influences on the productivity. An increase in the use of electronic technology in tunnel boring, both for control functions and recording of instantaneous machine variables have allowed the imposition of additional constraints, such as thrust & torque limitations. How do we take all of these additional variables into account in the forecasting of TBM performance?