scholarly journals STIFFNESS DESIGN OF A SHEAR-BEAM STRUCTURE SUPPORTED BY A SHEAR-BEAM GROUND FOR SPECIFIED SEISMIC DEFORMATION

Author(s):  
Tsuneyoshi NAKAMURA ◽  
Izuru TAKEWAKI ◽  
Yasuhiko ASAOKA
2019 ◽  
Vol 13 (3) ◽  
pp. 148
Author(s):  
Rickey Pek Eek Ting ◽  
Intan Zaurah Mat Darus ◽  
Shafishuhaza Sahlan ◽  
Mat Hussin Ab Talib
Keyword(s):  

1992 ◽  
Author(s):  
MITSUNORI MIKI ◽  
YOSHISADA MUROTSU ◽  
NOBUHIKO MURAYAMA ◽  
TETSUO TANAKA

2019 ◽  
Vol 484 (1) ◽  
pp. 87-92
Author(s):  
T. M. Zlobina ◽  
V. A. Petrov ◽  
K. Yu. Murashov ◽  
A. A. Kotov

This study investigates the effect of mechanisms of paleode formations during the period of fluid inflow into the accumulation sphere of gold concentrations. Such mechanisms are believed to correspond to DC- and NDC- type seismic mechanisms, whose main influence on fluid migration lies on the formation of different, relative to fluid regime parameters, structural and hydrodynamic organizations of the ore-forming system, and fluid flow control within the area of the accumulation of ore concentrations.  


2021 ◽  
Vol 208 ◽  
pp. 1-15
Author(s):  
Liangliang Zou ◽  
Jin Yuan ◽  
Xuemei Liu ◽  
Jinguang Li ◽  
Ping Zhang ◽  
...  

2021 ◽  
pp. 147592172199847
Author(s):  
William Soo Lon Wah ◽  
Yining Xia

Damage detection methods developed in the literature are affected by the presence of outlier measurements. These measurements can prevent small levels of damage to be detected. Therefore, a method to eliminate the effects of outlier measurements is proposed in this article. The method uses the difference in fits to examine how deleting an observation affects the predicted value of a model. This allows the observations that have a large influence on the model created, to be identified. These observations are the outlier measurements and they are eliminated from the database before the application of damage detection methods. Eliminating the outliers before the application of damage detection methods allows the normal procedures to detect damage, to be implemented. A multiple-regression-based damage detection method, which uses the natural frequencies as both the independent and dependent variables, is also developed in this article. A beam structure model and an experimental wooden bridge structure are analysed using the multiple-regression-based damage detection method with and without the application of the method proposed to eliminate the effects of outliers. The results obtained demonstrate that smaller levels of damage can be detected when the effects of outlier measurements are eliminated using the method proposed in this article.


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