Analysis of the liquefied soil effect on single pile under seismic action

It has many advantages to treat liquefied soil foundation with pipe vibrosinking compacted gravel pile.

The evaluation of liquefaction hazard and the seismic design for the pile foundation built in the liquefiable soil is potentially significant.

By analyzing the mechanism of sand and water spewing of the liquefiable foundation soil with nonliquefiable soil layer above under the effect of foundation,the author of this article advances a method to judge if the foundation soil,which is determined to be liquefiable soil according to code for seismic design of buildings,can be used as the bearing stratum directly.

Moreover,the change rules of the relative displacement between the underground structures and liquefiable soils,dynamic earth pressures acting on the sidewall of RC structures,shear stress and excess pore wat.

The underground pipeline in liquefaction soil under seismic force was simplified as a simple beam with elastic supports on two ends.

Aseismic reliability of traversing pipelines based on soil liquefaction analysis;

The tests made before and after the construction show that this technology has a good effect on reinforcing the foundation and eliminating the soil liquefaction.

Finally, by means of this model, the process and phenomena of the soil liquefaction is exp.

Evaluation on soil liquefaction occurred at Taliao Main Depot of Kaohsiung MRT systems in Taiwan;

In this paper,the state-of-the-art of studies on the liquefaction of saturated soils are reviewed,including the mechanism of the soil liquefaction,the influential factors of the seismically induced soil liquefaction,the approach of estimating and analyzing the seismic hazard of the soil liquefaction,and the characters of the post-liquefaction soils.

Study on the saturated sand liquefaction judgment method in Guangzhou district;

Seismic settlement estimation of sand liquefaction based on RBF neural network model;

Probabilistic estimation of sand liquefaction based on neural network model of radial basis function;