A prediction method of ground volume loss variation with depth induced by tunnel excavation

2021 ◽  
Author(s):  
Qingtao Lin ◽  
Yu Tian ◽  
Dechun Lu ◽  
Qiuming Gong ◽  
Xiuli Du ◽  
...  
2012 ◽  
Vol 446-449 ◽  
pp. 1432-1436
Author(s):  
Suo Wang

In order to predict tunnel surrounding rock pressure, this paper puts forward a series of dynamic numerical simulative model on the tunnel excavation. According to the change of rock damage in the construction program, it adjusts dynamically the mechanical material parameters of surrounding rock. So the model achieves the purpose which is controlling and simulating the process of tunnel progressive damage. In accordance with the numerical simulative results, it analyzes the relationship between the rock parameters with the plastic strain, radial displacement. Then this paper proposes a prediction method of tunnel surrounding rock pressure based on the theory of the progressive damage and method of characteristic curve. Finally, it compares the pressure on the numerical simulative models with on the site date, and it proves that the prediction method has practical engineering value.


Author(s):  
Hisashi HAYASHI ◽  
Daisuke SAKAI ◽  
Yasuyuki OKAZAKI ◽  
Shingo MORIMOTO ◽  
Masato SHINJI

2013 ◽  
Vol 2013 ◽  
pp. 1-9 ◽  
Author(s):  
Sun Shaorui ◽  
Liu Jiaming ◽  
Wei Jihong

Predicting overbreak blocks is a valid way to protect constructors, safeties in the process of tunnel excavation. In this paper, a prediction method of the overbreak blocks in tunnels is developed in the frame of the wavelet neural network of geological statistics models. Geometrical parameters of structural plane are first obtained by field survey. Then, a statistical model can be deduced from the measured geometrical parameters on the basis of the geological statistics theory. Furthermore, the volumes and distribution of the overbreak blocks are calculated by the theory of wavelet neural network. Finally, the valid support measurements can be designed according to the prediction results for all overbreak blocks appeared in tunnel excavation, and the amount of overbreak blocks can also be predicted. The code with respect to the method has been developed by the fortran language. The method proposed in this paper has been used in a tunnel construction. The results show that there exists an approximate 10%~30% difference between the prediction and the real volume of overbreak blocks. Therefore, the method can be well used to predict the volumes distribution and the overbreak blocks, and the accordingly support measurements can be also given according to the prediction results.


2018 ◽  
pp. 214-223
Author(s):  
AM Faria ◽  
MM Pimenta ◽  
JY Saab Jr. ◽  
S Rodriguez

Wind energy expansion is worldwide followed by various limitations, i.e. land availability, the NIMBY (not in my backyard) attitude, interference on birds migration routes and so on. This undeniable expansion is pushing wind farms near populated areas throughout the years, where noise regulation is more stringent. That demands solutions for the wind turbine (WT) industry, in order to produce quieter WT units. Focusing in the subject of airfoil noise prediction, it can help the assessment and design of quieter wind turbine blades. Considering the airfoil noise as a composition of many sound sources, and in light of the fact that the main noise production mechanisms are the airfoil self-noise and the turbulent inflow (TI) noise, this work is concentrated on the latter. TI noise is classified as an interaction noise, produced by the turbulent inflow, incident on the airfoil leading edge (LE). Theoretical and semi-empirical methods for the TI noise prediction are already available, based on Amiet’s broadband noise theory. Analysis of many TI noise prediction methods is provided by this work in the literature review, as well as the turbulence energy spectrum modeling. This is then followed by comparison of the most reliable TI noise methodologies, qualitatively and quantitatively, with the error estimation, compared to the Ffowcs Williams-Hawkings solution for computational aeroacoustics. Basis for integration of airfoil inflow noise prediction into a wind turbine noise prediction code is the final goal of this work.


2018 ◽  
Vol 138 (9) ◽  
pp. 1075-1081
Author(s):  
Yasuhide Kobayashi ◽  
Mitsuyuki Saito ◽  
Yuki Amimoto ◽  
Wataru Wakita

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