scholarly journals LONG TERM PREDICTION OF VERTICAL EARTH PRESSURE LOADING ON A SHIELD TUNNEL IN SOFT CLAY GROUND

2017 ◽  
Vol 73 (3) ◽  
pp. I_75-I_84
Author(s):  
Shigeaki OKA ◽  
Yoshihiro ITO ◽  
Ayaka YOKOTA ◽  
Jin SAITO ◽  
Shunsuke KANEKO ◽  
...  
Keyword(s):  
Soft Clay ◽  
Earth Pressure ◽  
Shield Tunnel ◽  
Pressure Loading ◽  
Term Prediction ◽  
Clay Ground ◽  
Long Term Prediction ◽  
Vertical Earth Pressure

scholarly journals STUDY ON SIMULATION ANALYSES OF DEFORMED TUNNELS DUE TO EARTH PRESSURE BY GROUND STRENGTH REDUCTION MODEL AND IT'S APPLICABILITY TO LONG TERM PREDICTION

2009 ◽  
Vol 65 (1) ◽  
pp. 107-119 ◽  
Author(s):  
Kazuhide YASHIRO ◽  
Keisuke SHIMAMOTO ◽  
Yoshiyuki KOJIMA ◽  
Mikio TAKAHASHI ◽  
Takeshi MATSUNAGA ◽  
...  
Keyword(s):  
Earth Pressure ◽  
Strength Reduction ◽  
Reduction Model ◽  
Term Prediction ◽  
Long Term Prediction

scholarly journals Model Test on the Influence of Surcharge, Unloading and Excavation of Soft Clay Soils on Shield Tunnels

Symmetry ◽  
2021 ◽  
Vol 13 (11) ◽  
pp. 2020
Author(s):  
Pengfei Xiang ◽  
Gang Wei ◽  
Shuming Zhang ◽  
Yunliang Cui ◽  
Huifang Guo
Keyword(s):  
Model Test ◽  
Soft Clay ◽  
Earth Pressure ◽  
Confining Pressure ◽  
Surface Settlement ◽  
Clay Soils ◽  
Shield Tunnel ◽  
Weak Points ◽  
Radar Chart ◽  
Vertical Earth Pressure

In view of the influence of symmetrical surcharge, unloading and excavation of soft clay soils on shield tunnels, the surface settlement, tunnel settlement, vertical additional earth pressure and tunnel additional confining pressure are measured by an indoor model test. The changes of confining pressure, tunnel settlement, surface settlement and vertical earth pressure caused by surcharge, unloading and excavation are studied and analyzed. The results show that, in soft clay, surcharge will cause tunnel settlement, and unloading and excavation will generally cause tunnel uplift. There is hysteresis in surface settlement and tunnel settlement above the shield tunnel caused by surcharge and unloading; the change of additional confining pressure of the shield tunnel caused by surcharge is mainly concentrated in the three directions of 3, 5 and 7 of the radar chart. These points belong to weak points. Unloading and excavation can effectively reduce the additional confining pressure of the tunnel in these three directions; excavation will cause the increase of vertical cumulative additional earth pressure and tunnel confining pressure in local directions. The influence range of surcharge in soft clay is wider than that in sand, but the depth is relatively shallow.

scholarly journals Novel robust time series analysis for long-term and short-term prediction

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Hiroshi Okamura ◽  
Yutaka Osada ◽  
Shota Nishijima ◽  
Shinto Eguchi
Keyword(s):  
Robust Regression ◽  
Simulated Data ◽  
New Method ◽  
Short Term ◽  
Least Absolute Deviations ◽  
Term Prediction ◽  
Regression Approach ◽  
Short Term Prediction ◽  
Long Term Prediction

AbstractNonlinear phenomena are universal in ecology. However, their inference and prediction are generally difficult because of autocorrelation and outliers. A traditional least squares method for parameter estimation is capable of improving short-term prediction by estimating autocorrelation, whereas it has weakness to outliers and consequently worse long-term prediction. In contrast, a traditional robust regression approach, such as the least absolute deviations method, alleviates the influence of outliers and has potentially better long-term prediction, whereas it makes accurately estimating autocorrelation difficult and possibly leads to worse short-term prediction. We propose a new robust regression approach that estimates autocorrelation accurately and reduces the influence of outliers. We then compare the new method with the conventional least squares and least absolute deviations methods by using simulated data and real ecological data. Simulations and analysis of real data demonstrate that the new method generally has better long-term and short-term prediction ability for nonlinear estimation problems using spawner–recruitment data. The new method provides nearly unbiased autocorrelation even for highly contaminated simulated data with extreme outliers, whereas other methods fail to estimate autocorrelation accurately.

Long term prediction of forest resources

1985 ◽  
Vol 12 ◽  
pp. 176
Author(s):  
H Kurth ◽  
B Anders ◽  
G Lucas
Keyword(s):  
Forest Resources ◽  
Term Prediction ◽  
Long Term Prediction
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