Real-Time Updated Risk Assessment Model for the Large Deformation of the Soft Rock Tunnel
Publication: International Journal of Geomechanics
Volume 21, Issue 1
Abstract
Large deformation of the surrounding rock is a common geological hazard when excavating a new tunnel to be driven through soft rock, and this occurrence can severely interrupt the construction schedule and affect the safety of tunnel engineering. Therefore, it is important to study the risk level prediction for large deformation of the soft rock tunnel. Thus, this paper developed and examined a real-time (immediately) updated model. The model can parameterize for use in predicting levels of risk of large deformation of soft rock tunnel projects based on fuzzy multiattribute decision-making (FMADM). Two real field-based deformation indicators and 3 first-level evaluation indicators, including the 14 second-level indicators, were collected for data. Each indicator was quantitatively graded into four levels of risk of large deformation based upon the expert evaluation system for classification. Furthermore, a real-time updated comprehensive weight of each assessment indicator was presented from results using the analytic hierarchy process (AHP) and the entropy weight method (EWM). After that, a real-time updated risk assessment model was established by the use of the development of fuzzy membership functions. This risk assessment model was applied to five soft rock tunnel projects, and the corresponding model-based evaluated results were consistent with the real deformation degree based upon field measurement. This model could be used as new and well-defined sets of guidelines for improving the understanding of risk-based assessments of the potential for large deformation of the soft rock tunnel.
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Acknowledgments
Much of the work presented in this paper was supported by the National Natural Science Foundations of China (Grant Nos. 41877239, 51379112, 51422904, 40902084, and 41772298), Key Technology Research and Development Program of Shandong Province (Grant No. 2019GSF111028), the Fundamental Research Funds of Shandong University (Grant No. 2018JC044), and the Natural Science Foundation of Shandong Province (Grant No. JQ201513).
Notation
The following symbols are used in this paper:
- A1
- ratio of crown settlement to cavern height;
- A2
- ratio of peripheral convergence to cavern span;
- a
- effect of two indicators;
- D
- evaluation vector;
- e
- entropies;
- F1
- engineering construction factor;
- F2
- engineering geological condition;
- F3
- mechanical and physical properties of rock;
- fS1(x)
- membership function of the cavern span;
- J
- judgment matrix;
- M
- decision matrix;
- P
- fuzzy judgment matrix of the second-level indicator;
- p
- proportion;
- R
- fuzzy judgment matrix of the first-level indicator;
- S1
- cavern span (m);
- S2
- cavern height (m);
- S3
- support pattern;
- S4
- support close time (d);
- S5
- excavation method;
- S6
- excavation footage (m);
- S7
- tunnel depth (m);
- S8
- groundwater seepage condition;
- S9
- number of structural surfaces;
- S10
- weathering degree;
- S11
- uniaxial compressive strength (MPa);
- S12
- elasticity modulus (MPa);
- S13
- water content (%);
- S14
- strength-stress ratio;
- w
- comprehensive weight;
- wo
- objective-based weight;
- ws
- subjective-based weight;
- X
- original value;
- x
- normalized value;
- α
- subjective preference coefficient; and
- λmax
- maximum eigenvalue of the judgment matrix.
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Published In
International Journal of Geomechanics
Volume 21 • Issue 1 • January 2021
Copyright
© 2020 American Society of Civil Engineers.
History
Received: Jul 23, 2020
Accepted: Aug 12, 2020
Published online: Oct 23, 2020
Published in print: Jan 1, 2021
Discussion open until: Mar 23, 2021
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